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Are GenAI Prompts Discoverable? Three Misunderstandings About This Emerging Data Type
Generative AI tools are creating new data types, such as prompts, outputs, and logs, that are quickly becoming relevant in investigations and litigation. This piece breaks down the top misunderstandings about GenAI discoverability and offers practical guidance for legal teams and attorneys preparing for what’s next.
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Untangling Complexity: How to Manage Multijurisdictional Matters in Modern Discovery
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M365 Academy: The Power of Sensitivity Labels in Microsoft 365
Summary: Read takeaways from our recent M365 Academy webinar on sensitivity labels, which covered how labels support governance across M365, from taxonomy design and classification to Copilot oversight, DLP, Insider Risk, and eDiscovery. Discover how to strengthen your own information protection strategy with these critical insights. Note: The information provided is based on available features as of the date of publication and is subject to change.Sensitivity labels cover the entire Microsoft 365 ecosystem, including Outlook, Teams, SharePoint, and OneDrive. They signal how information should be handled, enforce protections, and guide user behavior. In our recent M365 Academy webinar, M365 experts Marta Pucci and Noah Koerner shared practical guidance on building and sustaining a labeling program that supports Copilot adoption, strengthens compliance, and provides assurance in eDiscovery scenarios.Purpose and scope of labelsSensitivity labels are metadata tags that indicate the classification of information in emails, meeting notes, files, and containers (e.g., SharePoint sites, Teams, M365 Groups). They help you effectively govern information, reduce risk, and demonstrate compliance. You can apply visible content markers in the headers, footers, or watermarks to indicate access controls that enforce who can open, view, edit, print, or forward the document. Access controls are only enforced once you enable them. And, once they are activated, the protection travels with the item as it moves within and outside your organization. Protection controls in practiceOne of the primary uses of labels is to apply and enforce access controls (formerly called encryption), which provide granular control over how content can be used. You can assign roles, such as viewer, editor, or co-owner, set expiration periods that require re-authentication, or block actions such as copy/paste, screen capture, or printing. Purview provides built-in options for emails that match common restrictions: Do Not Forward and Encrypt-Only. You can target (scope) controls to required authentication for external collaboration or to limit internal access by department. These label features safeguard information and enforce your organization’s policies. Design and implement your taxonomyCollaboration across departments is key to designing an effective taxonomy. We most commonly see stakeholders from legal, compliance, security, and IT involved in these discussions. Labels should use easily understandable names and can be organized into groups or include subgroups to tailor access and usage for more specific use cases. Publishing policies determine which users see which labels, simplifying the choices for users. For instance, a “highly sensitive” label might only appear in the list for HR personnel. Adoption is key to an effective labeling program, so easily identifiable cues are important. Content markers in headers, footers, or watermarks, and features like color coding or a lock icon, help users recognize sensitivity. Restrictions also support adoption; you can require a label before saving or prompt users to justify sensitively level downgrades. A taxonomy that reflects how your organization actually categorizes and handles data, along with practical adoption measures, ensures that your labeling program delivers compliance.Classification and automationLabels are based on classifications that define the types of data your organization wants to identify and protect. Microsoft Purview provides several ways to detect that data: Sensitive Information Types (SITs) recognize common patterns such as credit card or Social Security numbers, Trainable Classifiers use machine learning to recognize categories of documents (e.g., legal or financial), and Exact Data Match (EDM) pinpoints specific values in structured data. Once records are categorized, labels can be applied manually or automatically. Client-side auto-labeling works while users are creating or editing content, either suggesting a label or applying it directly, while service-side labels apply to data at rest in SharePoint or OneDrive and to email in transit through Exchange. When a record fits into more than one category, label priorities ensure that the most restrictive label is applied, reducing ambiguity and strengthening protection. A well-designed classification and automation strategy ensures that sensitive data is labeled accurately and consistently, without relying solely on user judgment.Copilot governanceOversharing is one of the most common obstacles to M365 Copilot adoption. Copilot accesses information from across the enterprise, which means sensitive content may appear in responses if it is not properly governed. Sensitivity labels play a critical role here: By applying access controls, you can prevent Copilot from processing or exposing labeled data to unintended audiences. For example, content marked as “highly confidential” can be excluded from Copilot results altogether, or restricted so that only users with specific permissions can see it. Data Loss Prevention (DLP) policies extend this protection by blocking Copilot from drawing on content that meets certain sensitivity thresholds. Together, these controls allow your organization to take advantage of Copilot’s productivity benefits while minimizing the risk of accidentally exposing sensitive information.DLP and Insider RiskData Loss Prevention (DLP) policies help prevent sensitive information from leaving the organization through email, chat, or sharing. As noted above, they also govern Copilot by limiting oversharing. Insider Risk Management addresses a different but complementary challenge: risky behavior inside the organization. It can highlight patterns such as repeated label downgrades, attempts to bypass restrictions, or unusual spikes in data movement. Together, DLP and Insider Risk provide a dual layer of protection—blocking inappropriate sharing at the source and alerting you to behaviors that may signal intentional or unintentional misuse.Measure and iterateEffective labeling is not a one-time setup; it requires continuous evaluation. There are several tools within Purview to monitor how labels are being used across your enterprise. Information Protection reports show which and where labels are applied most often, offering a high-level view of adoption. Data and Content Explorer drills into specific items to confirm that sensitive content is being labeled correctly. For more recent activity, Activity Explorer provides up to 30 days of detail on user actions, including label changes and downgrade justifications. These insights help you identify trends, spot misuse, and refine your labeling strategy over time to keep pace with evolving business and regulatory needs.eDiscovery and downstream impactSensitivity labels don’t just affect how data is used day to day, they also influence how it behaves in downstream processes like eDiscovery and regulatory investigations. Label metadata typically persists when items are converted into formats like CSV or PDF. However, this practice can cause defensibility issues in eDiscovery. In some cases, you might choose to use DLP controls to manage information. Understanding how labels behave during export and planning accordingly ensures that your compliance and legal teams can rely on the data set.Moving forwardSensitivity labels are most effective when treated as part of a broader governance strategy rather than a standalone tool. Labels connect policy with practice across M365. They apply protections, support Copilot adoption, and integrate with DLP, Insider Risk, and eDiscovery. Their program’s success depends on thoughtful design that reflects how your organization handles data, the right controls to enforce policy, and ongoing monitoring so usage evolves with business and regulatory demands. Implemented thoughtfully, sensitivity labels provide both the guardrails and the assurance needed to protect information and support compliance at scale.Take the next step toward protecting your data and visit our data privacy and security page.
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Does It Actually Work? How to Measure the Efficacy of Modern AI
The first step to moving beyond the AI hype is also the most important. That’s when you ask: How can AI actually make my work better? It’s the great ROI question. Technology solutions are only as good as the benefits they provide. So it’s critical to consider an AI solution’s efficacy—its ability to deliver the benefits you expect of it—before bringing it onboard.To help you do that, let’s walk through what efficacy means in general, and then look at what it means for the two types of modern AI.Efficacy varies depending on the solutionYou can measure efficacy in whatever terms matter most to you. For simplicity’s sake, let’s focus on quality, speed, and cost.When you’re looking to improve efficacy in those ways, it’s important to remember that not all AI is the same. You need to choose technology suited for your task. The two types of AI that use large language models (LLMs) are predictive AI and generative AI (for a detailed breakdown, see our previous article on LLMs and the types of AI). Because they perform different functions, they impact quality, speed, and cost in different ways.Measuring the efficacy of predictive AIPredictive AI predicts things, such as the likelihood that a document is responsive, privileged, etc. Here’s how it works, using privilege as an example. Attorneys review and code a sample set of documents.Those docs are fed to the AI model to train it—essentially, teaching it what does and doesn’t count as privilege for this matter.Then, the classifier analyzes the rest of the dataset and assigns a percentage to each document: The higher the percentage, the more likely the document is to be privileged.The training period is a critical part of the efficacy equation. It requires an initial investment in eyes-on review, but it sets the AI up to help you reduce eyes-on review down the line. The value is clearest in large matters: Having attorneys review 4,000 documents during the training period is more than worth it when AI removes more than 100,000 from privilege review.With that in mind, here’s how you could measure the efficacy of a predictive AI priv classifier.Quality: Does AI make effective predictions? AI privilege classifiers can be very effective at identifying privilege, including catching documents that other methods miss. A client in one real-life matter used our classifier in combination with search terms—and our classifier found 1,600 privileged docs that weren’t caught by search terms. Without the classifier, the client would have faced painful disclosures and clawbacks.Speed: Does predictive AI help you move faster? AI can accelerate review in multiple ways. Some legal teams use the percentages assigned by their AI priv classifier to prioritize review, starting with the most likely docs and reviewing the rest in descending order. Some use the percentages to cull the review population, removing docs below a certain percentage and reviewing only those docs that meet a certain threshold of likelihood. One of our clients often does both. For 1L review, they prioritize docs that score in the middle. Docs with extremely high or low percentages are culled: The most likely docs go straight to 2L review, while the least likely docs go straight to production. By using this method during a high-stakes Second Request, the client was able to remove 200,000 documents from privilege review.Cost: Does predictive AI save you money? Improving speed and quality can also improve your bottom line. During the Second Request mentioned above, our client saved 8,000 hours of attorney time and more than $1M during privilege review.Measuring the efficacy of generative AIGenerative AI (or “gen AI”) generates content, such as responses to questions or summaries of source content. Use cases for gen AI in eDiscovery vary widely—and so does the efficacy.For our first gen AI solution, we picked a use case where efficacy is straightforward: privilege logs. In this case, we’re not giving gen AI open-ended questions or a sprawling canvas. We’re asking it to draft something very specific, for a specific purpose. That makes the quality and value of its output easy to measure.This is another case where AI’s performance is tied to a training period, which makes efficacy more significant in larger matters. After analysts train the AI on a few thousand priv logs, the model can generate tens of thousands on its own.Given all that, here’s how you might measure efficacy for gen AI.Quality: Does gen AI faithfully generate what you’re asking it to? This is often tricky, as discussed in an earlier blog post about AI and accuracy in eDiscovery. Depending on the prompt or situation, gen AI can do what you ask it to without sticking to the facts. So for gen AI to deliver on quality and defensibility, you need a use case that affords: Control—AI analytics experts should be deeply involved, writing prompts and setting boundaries for the AI-generated content to ensure it fits the problem you’re solving for. Control is critical to drive quality.Validation—Attorneys should review and be able to edit all content generated by AI. Validation is critical to measure quality.Our gen AI priv log solution meets these criteria. AI experts guide the AI as it generates content, and attorneys approve or edit every log the AI generates. As a result, the solution reliably hits the mark. In fact, outside counsel has rated our AI-generated log lines better than log lines by first-level contract attorneys.Speed: Does gen AI help you move faster? If someone (or something) writes content for you, it’s usually going to save you time. But as I said above, you shouldn’t accept whatever AI generates for you. Consider it a first draft—one that a person needs to review before calling it final. But reviewing content is a lot faster than drafting it, so our priv log solution and other gen AI models can definitely save you time.Cost: Does gen AI save you money?Giving AI credit for cost savings can be hard with many use cases. If you use gen AI as a conversational search engine or case-strategy collaborator, how do you calculate its value in dollars and cents?But with priv logs, the financial ROI is easy to track: What do you spend on priv logs with gen AI vs. without? Many clients have found that using our gen AI for the first draft is cheaper than using attorneys.Where can AI be effective for you?This post started with one question—How can AI make your work better?—but you can’t answer it without also asking where. Where are you thinking about applying AI? Where could your team benefit the most?So much about efficacy depends on the use case. It determines which type of AI can deliver what you need. It dictates what to expect in terms of quality, speed, and cost, including how easy it is to measure those benefits and whether you can expect much benefit at all.If you’re struggling to figure out what benefits matter most to you and how AI might deliver on them, sign up to receive our simple guide to thinking about AI below. It walks through seven dimensions of AI that are changing eDiscovery, including sections on efficacy, ethics, job impacts, and more. Each section includes a brief questionnaire to help you clarify where you stand—and what you stand to gain.
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From Data to Decisions, AI is Improving Accuracy for eDiscovery
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From Data to Decisions, AI is Improving Accuracy for eDiscovery
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05/28/2024
From Data to Decisions, AI is Improving Accuracy for eDiscovery
Learn through real scenarios how predictive and generative AI are helping to improve accuracy in eDiscovery.
You’ve heard the claims that AI can increase the accuracy of analytical tasks during eDiscovery. They’re true when the AI in question is being developed responsibly through proper scoping, iterative testing, and validation. As we have known for over a decade in legal tech circles, the computational power of AI (and machine learning in particular) is perfectly suited to the large data volumes at play for many matters and the types of classification assessments required for document review. But how much of a difference can AI make? And what impact do large language models (LLMs) have in the equation beyond traditional approaches to machine learning? How do these boosts in accuracy help legal teams meet deadlines, preserve budget, and achieve other goals? To answer these questions, we’ll look at several examples of privilege review from real-world matters. Priv is far from the only area where AI can make a difference, but for this article it’ll help to keep a tight focus. Also, we’ve been enhancing privilege review with AI since 2019, so when it comes to accuracy—we have plenty of proof. What accuracy means for the two primary types of AI
Before we explore examples, let’s review the two relevant categories of AI and what they do in an eDiscovery context. Predictive AI leverages historical data to predict outcomes on new data. For eDiscovery, we leverage predictive AI to provide us with a metric on the likelihood a document falls under a certain classification (responsive, privileged, etc.) based on a previously coded training set of documents.
Generative AI creates novel content based directly on input data. For eDiscovery, one example could be leveraging generative AI to develop summaries of documents of interest and answers to questions we may have about the facts present in these documents.
In today's context, both types of AI are built with LLMs, which learn from vast stores of information how to navigate the nuances and peculiarities of language as people actually write and speak it. (In a previous post, we share more information about LLMs and the two types of AI.) Because each of these types of AI are focused on different goals and have different outputs, predictive and generative AI also have different definitions of accuracy. Accuracy for predictive AI is tied to a traditional sense of the truth: How well can the model predict what is true about a given document?
Accuracy for generative AI is more fluid: A generative AI model is accurate when it faithfully meets the requirements of whatever prompt it was given. If you ask it to tell you what happened in a matter based on the facts at hand, it may make up facts in order to be accurate to the prompt. Whether the response is true or is based on the facts of the matter depends on the prompt, tuning mechanisms, and validation.
All that said, both types of AI have use cases that allow legal teams to measure their accuracy and impact. Priv classifiers prove to be more accurate than search terms
Our first example comes from a quick-turn government investigation of a large healthcare company. For this matter, we worked with counsel to train an AI model to identify privilege and ran it in conjunction with privilege search terms. The privilege terms came back with 250K potentially privileged documents, but the AI model found that more than half of them (145K) were unlikely to be privileged. Attorneys reviewed a sample of the disputed docs and agreed with the AI. That gave counsel the confidence they needed to remove all 145K from privilege review—and save their client significant time and money. We saw similar results in another fast-paced matter. Search terms identified 90K potentially privileged documents. Outside counsel wanted to reduce that number to save time, and our AI privilege model did just that. Read the full story on AI and privilege review for details. Let’s return to our definition of accuracy for predictive AI: How well did the model predict what was true about the documents? Very well and more accurately than search terms. Now what about generative AI? Generative AI can draft more accurate priv logs than people
We have begun to use generative AI to draft privilege log descriptions. That’s an area where defining accuracy is clear-cut: How well does the log explain why the doc is privileged? During the pilot phase of our AI priv log work, we partnered with a law firm to answer that very question. With permission from their client, the firm took privilege logs from a real matter and sent the corresponding documents through our AI solution. Counsel then compared the log lines created by our AI model against the original logs from the matter. They found that the AI log lines were 12% more accurate than those drafted by third party contract reviewers. They also judged the AI log lines to be more detailed and less repetitious. We have evidence from live matters as well. During one with a massive dataset and urgent timeline, outside counsel used our generative AI to create privilege logs and asked reviewers to QC them. During QC, half the log lines sailed through with zero edits, while the other half were adjusted only slightly. You can see what else AI achieved in the full case study about this matter. More accurate review = more efficient review (with less risk)
Those accuracy numbers sound good—but what exactly do they mean for legal teams? What material benefits do you get from improving accuracy? Several, including: Better use of attorney and reviewer time. With AI accurately identifying priv and non-priv documents, attorneys spend less time reviewing no-brainers and more time on documents that require more nuanced analysis. In cases where every document will be reviewed regardless, you can optimize review time (and costs) by sending highly unlikely docs to lower-cost contract resources and reserving your higher-priced review teams for close calls.
Opportunities for culling. Attorneys can choose a cutoff at a recall that makes sense for the matter (including even 100%) and automatically remove all documents under that threshold from review and straight into production. This is a crisp, no-fuss way to avoid spending time and resources on documents highly unlikely to be privileged.
Lower risk of inadvertently producing privileged documents. Pretty simple: The better your system is for classifying privilege, the less likely you are to let privileged info slip through review.
What does accuracy mean to you?
I hope this post helps clarify how exactly AI can improve accuracy during eDiscovery and what other benefits that can lead to. Now it’s time to consider what all this means to you, your team, and your work. How important is accuracy to you? How do you measure it? Where would it help to improve accuracy, and what would you get out of that? To help you think it through, we assembled a user-friendly guide that covers accuracy and six other dimensions of AI that change the way people think about eDiscovery today. The guide includes brief definitions and examples, along with key questions like the ones above to help you craft an informed, personal point of view on AI’s potential.
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Law & Candor Season 12: Five Views of Innovation and Risk Impacting AI, eDiscovery, and Legal
AI, generative AI, antitrust, second requests, HSR, eDiscovery, review, information governance, healthcare, legal operations, law firm, corporate counsel ai-and-analytics; compliance; corporate; corporate-legal-ops; data-analytics; healthcare; healthcare-litigation; innovative-technology; innovation; information-governance; law-firm; mergers; modern-data; phi; pii; podcast; self-service, spectra; regulation; production mitch montoya In a year of unprecedented advancement in AI capabilities and economic uncertainty, legal teams and attorneys have been given both a compelling look into what the future of their work may look like and a sharp picture of today’s challenges. With a critical eye on how to manage and capitalize on these dueling perspectives that define legal’s current landscape, the guests on the new season of Law & Candor offer insights on a range of issues, including generative AI, new M&A guidelines and HSR rules, collaboration data, strategic partnerships, and the future of the industry. Listen for news, AI and technology updates, and best practices from leaders confronting these challenges and charting new paths forward. Episode 1: The Power of Three: Maximizing Success with Law Firms, Corporate Counsel, and Legal Technology Episode 2: What You Need to Know About the New FTC and DOJ HSR Changes Episode 3: Why Your eDiscovery Program and Technology Need Scalability Episode 4: Generative AI and Healthcare: A New Legal Landscape Episode 5: The Great Link Debate and the Future of Cloud Collaboration To keep up with news and updates on the podcast, follow Lighthouse on LinkedIn and Twitter . And check out previous episodes of Law & Candor at lighthouseglobal.com/law-and-candor-podcast. For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.
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Why Legal Teams Need to Reduce Repeated Document Review
Similar matters often pull in the same documents for review during eDiscovery. Many legal teams default to manually reviewing these documents for each matter, but this is quickly becoming untenable.Legal teams can reduce the burden of repeated review through the application of advanced technology and proactive review strategies. They may encounter barriers, from limitations of their current tools to concerns about defensibility. But legal teams can take small steps now that overcome these barriers and prepare them to meet the time, budget, and other pressures they face today.Repeated review exacerbates today’s challengesWe're approaching a time when legal teams simply can’t afford to review the same documents multiple times across matters. The size of modern datasets requires teams to reduce eyes-on review wherever possible. Meanwhile, repeated review of the same documents opens the door to inconsistency, error, and risk.When teams succeed in reducing repeated review, they turn their most common pain points into new sources of value. They get more out of their review spend, help review teams work faster, and achieve the accuracy that they expect and the courts demand.In an earlier post, we dig more deeply into when repeated review happens, what it costs, and how technology can support a different approach. If you’re eager to explore solutions, that’s a great place to start.But many legal professionals are unable to think about solutions yet. They face a range of internal and external barriers that make it hard to move or even see past the status quo of repeated review.If that’s the boat you’re in, keep reading.Changing your approach may appear dauntingLegal teams often have solid reasons for persisting with repeated review. These include:Feasibility concerns Every matter is unique, and teams may assume this means nothing of value carries over from one matter to another.Attorneys may distrust the decisions or data practices associated with prior matters. They prefer starting over from scratch, even if it means repeating work.Technology barriers Legacy tools and software lack the advanced AI necessary to save work product and apply learnings from matter to matter, but adopting new technology takes time and money that legal teams are wary of spending.Companies who use multiple vendors and eDiscovery review teams may store their data in multiple places, making it hard to reuse past work product.It’s true that no two matters are exactly alike, adopting new technology can be challenging, and it’s hard to trust the reliability of something you’ve never used before. But this doesn’t mean that repeated review is still the best option. As shown above, the costs are simply too high.So, what do we do about these barriers? How are teams supposed to move past them? The answer: One step at a time.Explore what’s possible by starting smallThese barriers are most formidable when you imagine rethinking your entire review approach. The idea of looking for potential document overlap across a huge portfolio, or finding and implementing a whole new technology suite, may be too overwhelming to put into action.So don’t think of it that way. Take small steps that explore the potential for reducing repeated review and chip away at the barriers holding you back. Instead of “all or nothing,” think “test and learn.”Look ahead to future matters, perform hybrid QC on past decisionsTo explore the feasibility of reducing repeated review, look at one matter with an eye on overlap. Does it share fundamental topics or custodians with any recent or future matters? Is it likely to have spin-off litigations, such as cases in other jurisdictions or a civil suit that follows a federal one?To build trust in decisions made during prior matters, try performing QC with attorneys and technology working in tandem. This can provide a quick and informative assessment of past decisions and calibrate your parameters for review going forward.Find a technology partner who meets you where you areIf your team lacks the technology to reuse work product, the right partner can right-size a solution for your needs and appetite. The hybrid QC example above applies here too. Many legal teams find that QC is an ideal venue for assessing the performance of advanced AI and getting a taste for how it works, because it’s focused, confined, and accompanied by human reviewers. From there, your team might expand to using advanced AI on a single matter, and eventually, on multiple matters. In all cases, your partner can do the heavy lifting of operating the technology, while explaining each step along the way, with enough detail that you can articulate its use and merits in court (or can “tag in” to present that explanation for you). “The right partner” in this context is someone with the data science expertise to apply the technology in the ways you need, along with the legal experience to speak to your questions and need for defensibility.Likewise, when data or case work are spread across multiple teams and locations, a savvy partner can still find ways to avoid duplicate work. This story about coordinating review across 9 jurisdictions is a great example.Take your time—but do take actionThe beauty of starting small is how it respects both the need to improve and the difficulty of making improvements. Changing something as intricate and important as your document review strategy won’t happen overnight. That’s okay. Take your time. But don’t take repeated review as a given. It threatens timelines, budgets, and quality. And it’s not your only option.For more on the subject, including specific scenarios where teams can reduce repeated review, see our in-depth primer.ediscovery-review; ai-and-analyticsreview; ai-and-analytics; ediscovery; ediscovery-processsarah moran
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3 Reasons Traditional Document Review Isn’t Flexible Enough for Your Needs
Modern data volumes and complexity have ushered in a new era of document review. The traditional approach, in which paid attorneys manually review all or most documents in a corpus, fails to meet the intense needs of legal teams today.Specifically, legal teams need to:• Scale their document review capability to cover massive datasets• Rapidly build case strategy from key information hidden in those datasets• Manage the risk inherent in having sensitive and regulated information dispersed across those datasetsAdvanced review technology—including AI-powered search tools and analytics—enables teams to meet those needs, while simultaneously controlling costs and maintaining the highest standards of quality and defensibility. Rather than ceding decisions to a computer, reviewers are empowered to make faster decisions with fewer impediments. (For a breakdown of how technology sets reviewers up for success, see our recent blog post). In a nutshell, legal teams that use advanced technology can be more flexible, tackling large datasets with fewer resources, and addressing strategy and risk earlier in the process.A flexible approach to scale: refining the responsive setResponsiveness is the center of all matters. With datasets swelling to millions of documents, legal teams must reduce the responsive set defensibly, cost-efficiently, and in a way they can trust.With traditional eyes-on review, the only way to attempt this is to put more people or hours on the job. And this approach requires reviewers to make every coding decision, which is often mentally taxing and prone to error. Advanced review technology is purpose-built to scale for large datasets and provide a more nuanced assessment of responsiveness. Namely, it assigns a probability score—say, a given document is 90% or 45% likely to be responsive—that you can use to guide the review team. Often this means reviewers start with the highest-probability docs and then proceed through the rest, eventually making their way through the whole corpus. But legal teams have a lot of flexibility beyond that. Combining machine learning with rules-based linguistic models can make responsive sets vastly more precise, decreasing both risk and downstream review costs.Using this approach, machine learning is leveraged for what it does best—identifying clearly responsive and clearly non-responsive materials. For documents that fall in the middle of machine learning’s scoring band—those the model is least certain about—linguistic models built by experts target responsive language found in documents reviewed by humans, and then expand out to find documents with similar language markers. This approach allows legal teams to harness the strengths of both computational scalability and human reasoning to drive superior review outcomes.A flexible approach to strategy: finding key documents fasterOnly about 1% to 1.5% of a responsive set consists of key documents that are central to case planning and strategy. The earlier legal teams get their hands on those documents, the sooner they can start on that invaluable work.Whereas it takes months to find key documents with traditional review, advanced technology shortens the process to mere weeks. This is because key document identification utilizes complex search strings that include key language in context. For example, “Find documents with phrase A, in the vicinity of phrases B, C, and D, but not in documents that have attributes E and F,” and so on. A small team of linguistic experts drafts these searches and refines them as they go, based on feedback from counsel. In one recent matter, this approach to key document identification proved 8 times faster than manual review, and more than 90% of the documents it identified had been missed or discarded by the manual review team.The speed and iterative nature of this process are what enable legal teams to be more flexible with case strategy. First, they have more time to choose and change course. Second, they can guide the search team as their strategy evolves, ensuring they end up with exactly the documents they need to make the strongest case.A flexible approach to risk: assessing privilege and PII sooner and more cost effectivelyReviewing for privilege is a notoriously slow and expensive part of eDiscovery. When following a traditional approach, you can’t even start this chore until after the responsive set is established.With advanced technology, you can review for privilege, PII, and other classifications at the same time that the responsive set is being built. This shortens your overall timeframe and gives you more flexibility to prepare for litigation.Legal teams can even be flexible with their privilege review budget. As with responsiveness, advanced technology will rate how likely a document is to be privileged. Legal teams can choose to send extremely high- and low-scoring documents to less-expensive review teams, since those documents have the least ambiguity. Documents that score in the middle have the most ambiguity, so they can be reviewed by premium reviewers.It’s all about options in the endBroadly speaking, the main benefit of supporting document review with advanced technology is that it gives you a choice. Legal teams have the option to start key tasks sooner, calibrate the amount and level of eyes-on review, and strategize how they use their review budgets. With linear review, those options aren’t available. Legal teams that give themselves these options, by taking advantage of supportive technology, are better able to scale, strategize, and manage risk in the modern era of document review.ediscovery-review; ai-and-analyticsediscovery-review, ai-and-analytics, ai/big dataai-big-data eric pender
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Here Today, Gone Today: Managing Third-Party Messaging Apps in a New Regulatory Environment
When the Federal Rules of Civil Procedure were amended in December of 2006 to include “electronically-stored information” as an information category subject to discovery, even the most visionary eDiscovery practitioners could not have anticipated what this would mean in the years to come.Although the tech-savvy among them may have anticipated the future challenge of increasing data volumes, who could have foreseen the impact of the Cloud and the exponential growth of data types and communication applications? No one in 2006 could have anticipated the explosion of third-party messaging apps (think WhatsApp, Signal, Snapchat, Telegram, WeChat, etc.) proliferated by a worldwide pandemic. Some of these applications allow users to send encrypted messages or ephemeral messages (messages that disappear after sending) and usually exist outside of native Apple or Android apps. Therefore, they raise uniquely challenging data governance and eDiscovery issues. Unfortunately, for a variety of reasons, organizations have had trouble implementing compliance policies that directly address those downstream eDiscovery and data governance implications. Mobile device policies tend to focus heavily on security considerations, with little attention given to how corporate communications can be preserved, collected, and/or produced should the need arise.Information use policies that require employees to use certain systems for work-related communications and collaboration do not always account for the realities of the business. Additional complexities include the proliferation of chat applications in the market, practical challenges collecting mobile device data (including forensic imaging in some cases), the co-mingling of personal and work data, and privacy implications.But while organizations have struggled to implement policies that address the full breadth of these challenges, eDiscovery obligations remain constant. Given the rise in the use of third-party applications for work communications (in some cases to potentially evade recordkeeping policies for more traditional tools like email), government agencies and regulators have increased scrutiny of how these systems are being used and managed. In doing so, they increasingly consider company policies that manage records and whether adequate controls are in place to ensure compliance. Both in-house and outside counsel have a responsibility to their clients to stay abreast of this increased scrutiny in order to advise them. In light of this responsibility, we are providing an overview of recent regulatory changes, as well as best practices for companies to survive within this new regulatory era. Focus on messaging apps by government agencies and regulators Until very recently, government agencies and regulators investigating companies have focused their attention on communications contained in traditional ”workplace” messaging applications, i.e., systems designed purely for business purposes. Regulated entities have recordkeeping requirements that mandate the retention of specific categories of records for a designated period of time, including communications, with penalties for record-keeping violations. Financial institutions have paid billions in SEC and Commodity Future Trading Commission penalties to settle related allegations. Private equity firms have been in the crosshairs as well. In an ironic twist, the SEC itself has been under scrutiny for similar behavior as members of the House Financial Services Committee and other House panels question whether the agency has suffered similar recordkeeping lapses, illustrating how widespread these apps are and how difficult it is to curtail their use. The 2022 Monaco Memo and subsequent sanctionsAmidst this backdrop, the Department of Justice ("DOJ") stepped up significantly with new directives and corporate compliance guidelines for personal mobile devices and third-party chat applications. In September 2022, Deputy Attorney General Lisa Monaco issued a memo to the DOJ Criminal Division to provide "best corporate practices regarding use of personal devices and third-party messaging platforms" in what has become known as the "Monaco Memo." Monaco stated, "[t]he ubiquity of personal smartphones, tablets, laptops, and other devices poses significant corporate compliance risks, particularly as to the ability of companies to monitor the use of such devices for misconduct and to recover relevant data from them during a subsequent investigation. The rise in use of third-party messaging platforms, including the use of ephemeral and encrypted messaging applications, poses a similar challenge." 2023 DOJ best practice guidelines and DOJ sanctions In February of 2023, the DOJ filed a memorandum in support of sanctions against a large technology company for alleged "intentional and repeated destruction of company chat logs" that the U.S. government sought to use in an antitrust case against the company. The DOJ filing indicated that the company set chats to delete after 24 hours. The Federal Rules of Civil Procedure required the company to suspend its standard retention upon notice of the government's legal action in 2019, which it did not do until it received notice of the 2023 motion for sanctions. In March of 2023, after those sanctions, the DOJ updated its Evaluation of Corporate Compliance Programs ("ECCP") to emphasize the importance of preserving business communications on personal devices, various communications platforms, and messaging applications, including those offering ephemeral messaging. In subsequent remarks announcing the 2023 ECCP best-practice guidelines, Assistant Attorney General Kenneth A. Polite, Jr. pointedly noted that when companies fail to produce communications for DOJ investigations, "a company's answers—or lack of answers—may very well affect the offer it receives to resolve criminal liability. So when crisis hits, let this be top of mind." The 2023 DOJ guidelines state that prosecutors will consider three factors when evaluating the adequacy of corporate policies governing the use of personal devices, communication platforms, and messaging applications: 1. Existing communication channels2. Policies governing the existing communication channels3. Whether the corporation is adequately communicating and consistently enforcing the policiesThese new DOJ guidelines significantly expand the scope of an organization's duty to preserve corporate communications. They create a new preservation duty targeted at business-wide compliance operations. Where internal legal departments may have struggled in the past to implement culture-changing mobile device policies, compliance teams may succeed in garnering the requisite executive buy-in.A path forward for organizationsAs law enforcement agencies and regulators continue to take a more rigorous stance towards messaging applications, companies will need to explore more expansive policies to comply with various obligations to retain and preserve data. But it’s a sticky problem for both sides to address, given the different capabilities of each system, incompatibility of certain tools with regulatory recordkeeping requirements, and the hard realities of today’s workplace. For some organizations, the risks of using certain third-party applications (including the inability of the organization to comply with certain regulatory requirements) simply does not outweigh the benefit to the business, and in these circumstances, companies might choose to not permit them. There may be legitimate business reasons for employees to use these apps—they are readily available, convenient, and provide certain security and data reduction benefits. However, organizations will need to weigh whether those benefits are worth the risk of possibly losing relevant data or enabling potentially nefarious behavior.Policies, procedures, and information governance—again “Guidance” and “controls” are the operative words here. For most businesses—and certainly for those in regulated industries or frequently subject to litigation—information governance and compliance functions only increase in importance as the datasphere continues to become more complex. Guidance: To reduce exposure and risk, businesses first need to consider the requirements they are subject to and clearly define their stance on the use of ephemeral data apps. It helps to have in place a solid information governance framework, with applicable written policies and procedures that reflect that stance. As with all data-related responsibilities, employees should be provided explicit guidance regarding personal devices and messaging tools during onboarding with continual reinforcement during routine training on policies and procedures that should be a part of any robust compliance program. Evidence of rigor in communicating to employees the appropriate use of these messaging platforms vis à vis data retention obligations can only be a benefit in case of an investigation or litigation. Controls: In addition, appropriate controls should be in place to monitor compliance and ensure required preservation, with effective means to handle non-compliance. If personal devices are approved for use, they should be subject to mobile device management (MDM), as well as policies and procedures that address their use to help ensure data safety and security.Realistically, whether or not a company allows the use of third-party apps doesn’t mean employees are sticking with the plan. It is the responsibility of the business to know what their employees are doing. Periodic testing and auditing of messaging applications is well-advised, and any employee misconduct in violation of company policies related to ephemeral messaging should be addressed and documented. Voluntarily self-disclosed misconduct can go a long way in mitigating potential damage and fines. Due consideration should also be given to whether there is the necessary IT infrastructure, resources, and budget to undertake surveillance of employee behavior and to respond to regulatory or legal requests for information, including proper implementation of a legal hold. If ephemeral messaging is allowed, can it be disabled in the event of potential litigation so that potentially relevant material is preserved? If not, there could be a problem.ConclusionThe datasphere is only going to become increasingly complex as more data-creation (and deletion) tools emerge. With regulatory recordkeeping and data retention mandates likely to remain in place, government agencies will continue to scrutinize third-party messaging applications. A robust information governance approach, as usual, is key. Companies with a defensible and effective electronic records retention policy that covers the legitimate use of messaging apps—with employees that are trained in related policies and procedures and how best to use them—will have the best chance of avoiding trouble and/or defending themselves against potential wrongdoing. chat-and-collaboration-data; forensicsforensicsdaniel black; jodi daniels
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To Reduce Risk and Increase Efficiency in Investigations and Litigation, Data is Key
Handling large volumes of data during an investigation or litigation can be anxiety-inducing for legal teams. Corporate datasets can become a minefield of sensitive, privileged, and proprietary information that legal teams must identify as quickly as possible in order to mitigate risk. Ironically, corporate data also provides a key to speeding up and improving this process. By reusing metadata and work product from past matters in combination with advanced analytics, organizations can significantly reduce risk and increase efficiency during the review process.In a recent episode of Law & Candor, I discussed the complex nature of corporate data and ways in which the work done on past matters—coupled with analytics and advanced review tools—can be reused and leveraged to reduce risk and increase efficiency for current and future matters. Here are my key takeaways from the conversation.From burden to asset: leveraging data and analytics to gain the advantageThe evolution of analytical tools and technologies continues to change the data landscape for litigation and investigations. In complex matters especially—think multi-district litigation, second requests, large multi-year projects with multiple review streams—the technology and analytics that can now be applied to find responsive data not only helps streamline the review process but can extend corporate knowledge beyond a single matter for a larger purpose. Companies can now use their data to their advantage, transforming it from a liability into an asset. Prior to standardization around threading and TAR and CAL workflows, repository models were the norm. Re-use of issue coding was the best way to gain efficiency, but each matter still began with a clean slate. Now, with more sophisticated analytics, it’s not just coding and work product that can be re-used. The full analysis that went into making coding decisions can be applied to other matters so that the knowledge gained from a review and from the data itself is not lost as new matters come along. This results in greater overall efficiencies—not to mention major cost-savings—over time.Enhanced tools and analytics reduce the risk of PII, privilege, and other sensitive data exposureWith today’s data volumes, the more traditional methods used in review, such as search terms and regular expression (regex), can often result in high data recall with low precision. That is, such a wide net is cast that a lot of data is captured that isn’t terribly significant, and data that does matter can be missed. Analytical modeling can help avoid that pitfall by leveraging prior work product and coding to reduce the size of the data population from the outset, sometimes by as much as 90%, and to help find information that more traditional tools often miss.This is especially impactful when it comes to PII, PHI, and privileged or other sensitive data that may be in the population, because the risk of exposure is significantly reduced as accuracy increases. Upfront costs may seem like a barrier, but downstream cost savings in review make up for itWhen technology and data analytics are used to reduce data volume from the beginning, efficiencies are gained throughout the entire review process; there are exponential gains moving forward in terms of both speed and cost. Unfortunately, the upfront costs may seem steep to the uninitiated, presenting what is the likely barrier to the lack of wide adoption of many advanced technologies. The initial outlay before a project even begins can be perceived as a challenge for eDiscovery cost centers. Also, it can be very difficult for any company to keep up with the rapid evolution of both the complex data landscape and the analytics tools available to address it—the options can seem overwhelming. Finding the right technology partner with both expertise and experience in the appropriate analytics tools and workflows is crucial for making the transition to a more effective approach. A good partner should be able to understand the needs of your company and provide the necessary statistics to support and justify a change. A proof-of-concept exercise is a way to provide compelling evidence that any up-front expenditure will more than justify a revised workflow that will exponentially reduce costs of linear document review.How to get startedSeeing is believing, as they say, and the best way to demonstrate that something works is to see it in action. A proof-of-concept exercise with a real use case—run side-by-side with the existing process—is an effective way to highlight the efficiencies gained by applying the appropriate analytics tools in the right places. A good consulting partner, especially one familiar with the company’s data landscape, should be able to design such a test to show that the downstream cost savings will justify the up-front spend, not just for a single matter, but for other matters as well. Cross-matter analysis and analytics: the new frontierTAR and CAL workflows, which are finally finding wider use, should be the first line of exploration for companies not yet well-versed in how these workflows can optimize efficiency. But that is just the beginning. Advanced analytics tools add an additional level of robustness that can put those workflows into overdrive. Cross-matter analysis and analytics, for example, can address important questions: How can companies use the knowledge and work product gleaned from prior matters and apply them to current and future matters? How can such knowledge be pooled and leveraged, in conjunction with AI or other machine learning tools, to create models that will be applicable to future efforts?Marrying the old school data repository concept with new analytics tools is opening a new world of possibilities that we’re just beginning to explore. It’s a new frontier, and the most intrepid explorers will be the ones that reap the greatest benefits. For more information on data reuse and other review strategies, check out our review solutions page.ai-and-analytics; data-privacy; ediscovery-reviewcorporate; ai-and-analytics; analytics; big-data; compliance-and-investigations; corporationcassie blum
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Why Moving to the Cloud is a Legal Conversation
There is a common theme buzzing around the legal tech and eDiscovery industry – the Cloud and how in-house lawyers should be aware of the implications of their companies moving to the Cloud. Due to its regular appearance, there is an increasing focus on the legal implications of moving to the Cloud, rather than IT and operational considerations, within organisations.Setting the StageThe Cloud is familiar to most people thanks to the way we store photos and save emails. However, the impact of the Cloud in such a short space of time, even for personal users, is remarkable. Google now gives away cloud storage space worth around $15,000 per person at 1995 prices to its users (of which there are approximately 1 billion). In other words, what would have cost a combined $15 trillion just 24 years ago is now being offered for free (Goldin and Kutarna. Age of Discovery. 1990. Print.).The common response to the question of moving a companies' data to the Cloud is typically around perceived issues of both cost and security. Both of these topics are fundamental but are limited in scope when considering the wide-ranging potential of enterprise cloud technology from the perspective of data governance, compliance, and eDiscovery.Reducing or eliminating IT spend on building and maintaining infrastructure is a driving force for companies to move to the Cloud. Another is the need to provide employees with the tools they need to not only continue their everyday tasks but also to adapt and innovate. Microsoft recently quoted that, “97% of Fortune 500 and 95% of Fortune 1000 companies have Office 365 to benefit from streamlined infrastructure, data management, and collaborative technology opportunities.” They have discovered that cloud-based productivity has moved far beyond just standard applications like Word or Excel. Networked applications fuel employee innovation. According to a study by Vanson Bourne, “companies leveraging cloud services increased their time to market by 20.7%. At the same time, IT spending decreased by 15.1%, and, as for employees, productivity jumped 18.8%.”When compared to cost savings and data security, data governance, compliance, and eDiscovery often get less consideration. This is because a transition to the cloud is a core business decision, taken on at an enterprise-wide level to streamline the company and provide business-critical tools to employees. The legal capabilities of the technology may seem peripheral to the IT teams focusing on transitioning from on-premise infrastructure to cloud-based data centres. However, when you consider the variety of ways in which data is generated and the volume of this data, legal needs to lead the way in managing risk and adding value to how collaboration is managed across the company.Driving Home the PointIronically, cloud-based technologies like Office 365 make it even easier to generate ever-larger amounts of data. It is, therefore, no surprise that the same technology can (and should) be used to govern this data. Legal needs to consider how to take ownership of the companies' data for risk management purposes if nothing else.An example of this is persistent chat using Skype, Teams, Yammer, etc. Legal rather than IT needs to drive the key questions. Is this functionality available to everyone? How long is chat data stored? Does the company utilise more than one chat solution and do they interact with each other? Is the data discoverable if necessary and can it be searched? Can a legal hold be placed on this content? When deleted, does that fit with the overall data retention policy and is that consistent across multiple locations?Just one aspect of data governance that, of data retention and associated policies and logistics, can be overwhelming. Every organisation has many applications that employees use. A switch to a cloud-based environment doesn’t just mean the data is stored somewhere else. It means that tools are probably available for employees to work more intelligently and collaboratively. This is a positive thing for both efficiency and most likely profitability. It is also positive in terms of data governance and compliance. Policies such as data retention and categorisation can be refreshed so that they are not written and ignored. They can be hardwired into the very applications that generate the bulk of a company's data, from email and business documents to persistent chat applications, financial data, and internal social media.Cloud-based technology such as Office 365 can be utilised to manage contentious matters more effectively and proportionally (crucial for Subject Access Requests), without the need for large-scale intervention from third parties who deploy forensic data collection experts to ship large volumes of data elsewhere for eDiscovery purposes.Furthermore, failure to provide modern workplace technology often means that a shadow IT environment develops within a company, a phenomenon that makes governance and compliance even more difficult than it already is. Employees will use whatever technology they can to make their job easier, regardless of policy. Again, legal, not IT, can lead the way in aligning policies with the use of modern workplace tools.Fortunately, security concerns have done little to hold back the tide of progress to cloud-based infrastructure. Microsoft may be a company that has the most attempted external hacks, but it also has a budget of over $1 billion annually to ensure the data it holds is secure. Other cloud-based providers also understand the value of managing their clients’ data and have similar impressive ways and large budgets to protect it. Microsoft's share price demonstrates what shareholders think of their focus on the cloud over the last five years. Windows is not discussed as widely these days compared to Office 365.Looking Forward IT and security may be the departments responsible for a transition to the Cloud but legal and compliance are the departments that should take ownership of the generation and governance of the data. This should not be seen as a burden, but a welcome change in how to align a modern workplace with a comprehensive framework to manage risks inherent in big data.If you would like to discuss this topic further, please feel free to reach out to me at MBrown@lighthouseglobal.com.data-privacy; ediscovery-review; information-governance; microsoft-365cloud, information-governance, cloud-security, blog, data-privacy, ediscovery-review, information-governance, microsoft-365cloud; information-governance; cloud-security; blogmichael brown
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Legal Tech Innovation: Learning to Thrive in an Evolving Legal Landscape
The March sessions of Legalweek took place recently, and as with the February sessions, the virtual event struck a chord that reverberated deep from within the heart of a (hopefully) receding pandemic. However, the discussions this time around focused much less on the logistics of working in a virtual environment and much more on getting back to the business of law. One theme, in particular, stood out from those discussions – the idea that legal professionals will need to have a grasp on the technology that is driving our new world forward, post-pandemic.In other words, the days when attorneys somewhat-braggingly painted a picture of themselves as Luddites holed up in cobwebbed libraries are quickly coming to an end. We live in an increasingly digital world – one where our professional communications are taking place almost exclusively on digital platforms. That means each of us (and our organizations and law firms) are generating more data than we know what to do with. That trend will only grow in the future, and attorneys that are unwilling to accept that fact may find themselves entombed within those dusty libraries.Fortunately, despite our reputation as being slow to adapt, legal professionals are actually an innovative, flexible bunch. Whether a matter requires us to develop expertise in a specific area of the medical field, learn more about a niche topic in the construction industry, or delve into some esoteric insurance provision – we dive in and become laymen experts so that we can effectively advocate for our clients and companies. Thus, there is no doubt that we can and will evolve in a post-pandemic world. However, if anyone out there is still on the fence, below are four key reasons why attorneys will need to become tech savvy, or at least knowledgeable enough to understand when to call in technical expertise.1. Technological Competence is Imposed by Ethics and Evidence RulesFirst and foremost, attorneys have an ethical duty (under ABA Model Rule 1.1) to “keep abreast of changes in the law and its practice, including the benefits and risk associated with relevant technology.” Thirty seven states have adopted this language within their own attorney ethics rules. Thus, just as we have a duty to continue our legal education each year to stay abreast of changes in law, we also have an ethical duty to continue to educate ourselves on the technology that is relevant to our practice.We also have a duty to preserve and produce relevant electronically stored information (ESI) (under both the Federal Rules of Civil Procedure (FRCP), as well as the ABA model ethics rules)[1] during civil litigation. To do so, attorneys must understand (or work with someone who understands) where their client’s or company’s relevant ESI evidence is, how to preserve it, how to collect it, and how to produce it. This means preserving and producing not only the documents themselves but also the metadata (i.e., the information about the data itself, including when it was generated and edited, who created it, etc.). This overall process grows more complicated with each passing year, as companies migrate to the unlimited storage opportunities of the Cloud and employees increasingly communicate through cloud-based collaboration platforms. Working within the Cloud has a myriad of benefits, but it can make it more difficult for attorneys to understand where their client’s or company’s relevant information might be stored, as well as harder to ensure metadata is preserved correctly.Together, these rules and obligations mean that whether we are practicing law within a firm or as in-house counsel at an organization, we have a duty to understand the basics of the technology our clients are using to communicate so that at the very least, we will know when to call in technical experts to meet the ethical and legal obligations we owe to those we counsel.2. Data Protection and Data Privacy is Becoming Increasingly ImportantThe data privacy landscape is becoming a tapestry of conflicting laws and regulations in which companies are currently navigating as best they can. Within the United States alone, there were a multitude of state and local laws regulating personal data that came into effect or were introduced in 2020. For companies that have a global footprint, the worldwide data protection landscape is even more complicated – from the invalidation of the EU-US privacy shield to new laws and modifications of data protection laws across the Americas and Asia Pacific countries. It will not be long before most companies, no matter their location, will need to ensure that they are abiding within the constructs of multiple jurisdictional data privacy laws.This means that attorneys who represent those companies will need to understand not only where personal data is located within the company, but also how the company is processing that data, how (and if) that data is being transmitted across borders, when (and if) it needs to be deleted, the process for effectively deleting it, etc., etc. To do so, attorneys must also have at least some understanding of the technology platforms their companies and clients are using, as well as how data is stored and transferred within those platforms, to ensure they are not advertently running afoul of data privacy laws.As far as data protection, attorneys need to understand how to proactively protect and safeguard their clients’ data. There have been multiple high-profile data breaches in the last few months,and law firms and companies that routinely house personal data are often the target of those breaches. Protecting client data requires attorneys to have a semblance of understanding of where client data is and how to protect it properly, including knowing when and how to hire experts who can best offer the right level of protection.3. Internal Compliance is Becoming More Technologically Complicated There has been a lot of interest recently in using artificial intelligence (AI) and analytics technology to monitor internal compliance within companies. This is in part due to the massive amount of data that compliance teams now need to comb through to detect inappropriate or illegal employee conduct. From monitoring departing employees to ensure they aren’t walking out the door with valuable trade secret information, to monitoring digital interactions to ensure a safe work environment for all employees – companies are looking to leverage advances in technology to more quickly and accurately spot irregularities and anomalies within company data that may indicate employee malfeasance.Not only will this type of monitoring require an understanding of analytics and AI technology, but it will also require grasping the intricacies of the company’s data infrastructure. Compliance and legal teams will need to understand the technology platforms in place within their organization, where employees are creating data within those platforms, as well as how employees interact with each other within them.4. The Ability to Explain Technology Makes Us Better AdvocatesFinally, it is important to note that the ability to understand and explain the technology we are using makes us better and more effective advocates. For example, within the eDiscovery space, it can be incredibly important for our clients’ budgets and case outcomes to attain court acceptance of AI and machine-learning technology that can drastically limit the volume of data requiring expensive and tedious human review. To do so, attorneys often must first be able to get buy-in from their own clients, who may not be well versed in eDiscovery technology. Once clients are on-board, attorneys must then educate courts and opposing counsel about the technology in order to gain approval and acceptance.In other words, to prove that the methods we want to use (whether those methods relate to document preservation and collection, data protection, compliance workflows, or eDiscovery reviews) are defensible and repeatable, attorneys must be able to explain the technology behind those methods. And as in all areas of law, the most successful attorneys are ones who can take a very complicated, technical subject and break it down in a way that clients, opposing counsel, judges, and juries can understand (or alternatively are knowledgeable enough about the technology to know when it is necessary to bring experts in to help make their case).Best Practices for Staying Abreast of TechnologyReach out to technology providers to ask for training and tips when needed. When evaluating providers, look for those that offer ongoing training and support.For attorneys working as in-house counsel, work to build healthy partnerships with compliance, IT, and data privacy teams. Being able to ask questions and learn from each other will help head off technology issues for your company.For attorneys working within law firms, work to understand your clients’ data infrastructure or layout. This may mean talking to their IT, legal, and compliance teams so that you can ensure you are up to date on changes and processes that affect your ability to advocate effectively for your client.Look for CLEs, trainings, and vendor offerings that are specific to the technology you and your clients use regularly. Remember that cloud-based technology, in particular, changes and updates often. It is important to stay on top of the most recent changes to ensure you can effectively advocate for your clients.Recognize when you need help. Attorneys don’t need to be technological wizards in order to practice law, however, you will need to know when to call in experts…and that will require a baseline understanding of the technology at issue.To discuss this topic more, feel free to connect with me at smoran@lighthouseglobal.com. [1] ABA Model Rule 3.4, FRCP 37(e) and FRCP 26)ai-and-analytics; ediscovery-review; data-privacy; information-governanceanalytics, data-privacy, information-governance, ediscovery-process, blog, law-firm, ai-and-analytics, ediscovery-review, data-privacy, information-governanceanalytics; data-privacy; information-governance; ediscovery-process; blog; law-firmsarah moran
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Legal Tech Innovation: Gaining Trust in New Technology and Processes
LegalWeek’s April conference took place recently, and as with the sessions earlier this year, the April thought leadership panels touched on many of the struggles we are all facing in the legal technology space. But where the February sessions focused on the post-pandemic future of legal technology and the March sessions focused on getting back to the business of law, the April sessions weaved in a more nuanced theme: obtaining organizational buy-in from stakeholders around legal technology and processes.The need for stakeholder buy-in for any type of legal technology change is imperative. Without it, organizations and law firms stop evolving and become stagnant as more agile competitors onboard better, more efficient processes, tools, and teams. But perhaps more importantly, being unable to obtain stakeholder involvement and approval can also end up leaving the company and law firms open to risk.For an example of the ramifications of failing to obtain the necessary buy-in, let’s take look at the legal technology process that many organizations and law firms have been struggling to implement recently: defensible disposal of legacy data. Without an effective defensible data disposal process and policy, data volumes can balloon out of control – especially in a Cloud environment – meaning that organizations and/or law firms will needlessly waste money storing obsolete data that should have been disposed of previously. But it also can increase risk in several ways. For starters, legacy data may contain personally identifiable information (PII) that organizations may be legally required to dispose of after a specified time period, pursuant to sectorial or jurisdictional data privacy laws. Even if personal data does not fall within the purview of a disposal requirement, keeping it for longer than it is needed for business purposes can still pose a risk should the company or firm holding it suffer a data breach or ransomware attack. Additionally, even obsolete non-personal data can cause confusion, disruption, and increased cost and risk if it winds up subject to a legal hold or swept up in an internal investigation. But despite all this, implementing an effective defensible data disposal program is a challenge for many because it often requires sweeping organizational buy-in, from the highest C-Suite executive to the lowliest employee with access to a company-sponsored collaborative platform.So how can legal teams get the buy-in necessary to implement new legal technology and processes that enable organizations and law firms to compete and evolve? It is tempting to think that buy-in starts with learning to control stakeholders. But attempting to control other teams and individuals will only lead to misalignment, tension, and failed implementation. Instead, gaining stakeholder buy-in actually starts with trust. Stakeholders must trust that whatever you are proposing to implement (whether that is a new technology, a new policy, or a new workflow) will be beneficial to them, to their team, and to the organization as a whole and that implementation is actually feasible. Below I have outlined a few tips for gaining stakeholder trust and buy-in for new legal technology and processes.Identify all the necessary stakeholders. Whether you want to onboard a new legal technology or implement a new legal data policy, like an updated document retention schedule, you will need to understand who the decisions makers are, as well as identify anyone who will be affected by the new tools, processes, or workflow.Prepare, Prepare, Prepare. Once you have identified the stakeholders and all those affected by the planned change, you can start preparing to gain their trust. This means doing all the necessary research and legwork up front so that you are well informed and have a fully developed, practical plan in place to present to those stakeholders. For instance, if you are seeking to onboard advanced AI technology to help streamline your eDiscovery program, you can prepare to gain trust by first talking to peers in the industry, as well as legal technology providers, to find the best technology and pricing options. Once you’ve selected an option, choose a test case and run a proof of concept to validate the effectiveness within your own data.Run the numbers. Once you’ve done the research and are satisfied that the new technology or workflow will be a good fit for your organization, quantify that fit by focusing on the bottom line. How much money will this be able to save your organization or law firm? How much risk can it eliminate and how can you quantify that risk? How can this new process or tool improve efficiency and how much money will that efficiency save? What is at stake if this new technology or process is not implemented and how can you quantify that? What is your plan for how this new tool or process will be funded by the organization or law firm?Stop, Collaborate, and Listen. Once you have identified all relevant stakeholders and collected the data, it is time to gather everyone together to present your research (either individually or via cross-organizational working groups or teams). Note that the order in which you present data to stakeholders will depend on your organization or law firm. For some, it may be best to get management and executives on board first to help drive change further downstream. In others, it may be more impactful to get lower-level teams on board first before presenting to final decision makers. Whichever order you choose, it is imperative to remember to listen and accept feedback once you’ve made your pitch. Remember this process will be iterative. It will require you to be flexible and possibly deviate from your original plan. It may also necessitate going back to the drawing board completely and selecting a different workflow or tool that works better for other groups. It may end up changing your desired implementation timeline. But the key to gaining trust from stakeholders is to get them involved early and listen to their feedback regarding planning, onboarding, and implementation.Retain Trust. Congratulations! Once all stakeholders have come to a consensus and you have achieved buy-in from all necessary decision makers, you are ready to implement and onboard. But that is not the end of this process. After implementation, you will need to protect the trust you have worked so hard to earn. You can do this by ensuring that everyone has the necessary training to effectively use the tool or abide by the new workflow or process. Nothing erodes trust more than incorrect (or non-existent) utilization. Whether you’re seeking to onboard a new eDiscovery platform or you’re rolling out a new legal hold technology, people who are affected by the change will need to understand how to use the technology and/or comply with the program. Set up training programs and then have avenues of ongoing support where people can ask questions and continue to train should they need it.I hope these tips come in handy when you are looking for buy-in from stakeholders around legal technology and processes. To discuss this topic more, feel free to connect with me at smoran@lighthouseglobal.com. ai-and-analytics; ediscovery-review; legal-operationscloud, data-privacy, information-governance, ai-big-data, preservation-and-collection, blog, ai-and-analytics, ediscovery-review, legal-operations,cloud; data-privacy; information-governance; ai-big-data; preservation-and-collection; blogsarah moran
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Biden’s First 100 Days: A New Regulatory Forecast
What the administration’s early actions can spell for dynamic changes in regulation and compliance.On day one of his administration, President Biden got off to a bold start by signing more than a dozen executive orders on subjects ranging from student loans to deportation — including a freeze on all regulatory actions in process under the prior administration.In the subsequent 99 days, more orders, executive appointments, nominations, and legislative activities have contributed to a notable thaw in the regulatory sphere as the administration strives to fulfill the policy-driven promises made during the campaign. A recent Corporate Compliance Insights article suggests that companies “should look to bolster their compliance infrastructure ahead of this imminent wave of regulation,” an activity that legal departments would surely applaud.Although the full impact of activities from the first 100 days may not play out for some time, the combination of COVID-19 fallout and the actions of the new administration — especially the appointments of some agency leaders — is already beginning to change business, legal, and compliance dynamics. Many companies are already facing increased litigation and fraud investigations as a result of the pandemic with the expectation that incidents will rise; the potential for increased regulatory actions from agencies energized by new leadership will only intensify the need for a corporate response.Energized regulatory agencies with a consumer protection focus A more robust regulatory environment is expected under the Biden administration, especially for financial and monetary systems, with a greater focus on consumer protection. With Gary Gensler heading up the SEC, there will likely be an emphasis implementing regulatory measures or approaches to broaden the retail investor focus. The Federal Reserve Board will resume examination activities for all banks after previously announcing a reduced focus on exam activity in light of the coronavirus response. And, with Janet Yellen at the helm of the Treasury, there will likely be stepped-up enforcement and investigatory activities on several fronts, including a shoring up of the Dodd-Frank act, which was relaxed under the prior administration, and implementation of the Corporate Transparency Act to expose and combat money-laundering, which Yellen has said is “one of her highest priorities.”Rohit Chopra, awaiting confirmation as head of the Consumer Financial Protection Bureau, is also expected to play a role in increasing regulatory actions, reversing the prior administration’s more lax oversight and enforcement policies. Already, analysts say, bank examinations, student lending, subprime auto loans, debt collection, mortgage services, and payday loans are expected to come under renewed scrutiny.The M&A landscape is in flux, impacted substantially by the pandemic but now gaining renewed momentum. Due to COVID-19 and its impact on the economy, the DOJ and FTC have been on alert for antitrust violations. According to at least one major law firm’s assessment, there is likely to be increased antitrust enforcement by the DOJ in several key industries over the next several years including tech, health care, and agriculture as well as increased merger enforcement that will lead to more second requests and potential for litigation.Also affecting M&A activity is a possible increase in the capital gains tax that could spur even more activity ahead of its passage. The pending confirmation of Lina Kahn as a commissioner of the FTC marks the probability of greater investigative efforts to potentially break up the expanding reach of Big Tech. Google, Facebook, Microsoft, and Apple will be the most likely targets, but expanded investigations related to M&A in other industries are also probable. The healthcare and pharmaceutical industries, whose activities stand out in high relief due to the pandemic, are sure to face more scrutiny in terms of both monopoly pricing issues and market concentration, which Biden says he will aggressively tackle.The 100-day message? Be proactive and be prepared. One thing seems certain: the regulatory landscape will continue to be dynamic. The first 100 days is, after all, just the beginning. Increasing litigation and investigations, second requests, and the due diligence and regulatory reporting necessitated by just the few probable changes suggested above threaten to impact the workload of most corporate legal and compliance departments, which may already be overburdened and understaffed.The possibility of such activity is best met with well-prepared legal and compliance functions and a laser focus on corporate data, with the appropriate tools to manage it. Any proactive steps taken to ensure that the appropriate workflows are in place should stand companies in good stead, accelerating any necessary response and mitigating the costly effects of poorly handled document productions. Companies with teams at the ready to meet these data-heavy challenges will be in a much better position to respond quickly and efficiently should the need arise.antitrustblog, regulation, biden-administration, antitrustblog; regulation; biden-administrationlighthouse
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Google Drive: What Happened to Our Date?
Like most cloud-based productivity platforms, Google offers solutions for both home and business environments. Free for personal use applications such as Gmail, Google Docs, and Google Drive deliver a rich set of communication and Office-like functionality that have near feature parity with their commercial corporate-focused G Suite counterparts. From the perspective of evidence acquisition in the civil arena, we find a significant number of organizations bypassing the conventional Microsoft stack in favor of G Suite. These organizations tend to operate in the technology space including biotech, electronics, engineering, and all flavors of “garage” startups.While cloud platforms enable a limitless world of collaboration and information storage, they also introduce an alternative set of metadata that can trip up seasoned examiners and eDiscovery practitioners. This can be particularly problematic for metadata dates. Historically, determining the date of a file that moved between computers is quite simple; however, arriving at the “best” date for any given piece of cloud evidence can be a subjective exercise and is limited to metadata exposed and potentially altered by the cloud platform. In the following post, I’ll dive into how this issue arises so that practitioners and analysts can use the most accurate evidence date for their eDiscovery needs. A “document” in Google Docs is simply a set of records and field values stored in a database. This departs from the traditional concept of a document being contained in a stand-alone file on your computer’s desktop. Currently, to be reviewed alongside traditional ESI, a Google Doc (ie, a spreadsheet or presentation) must be pulled from Google’s database, converted into a traditional document file, and downloaded for processing and review.Thus, the handling of dates can become an issue for documents within G Suite. If a Microsoft (MS) Excel document is created by a user on their laptop, uploaded to Google Drive, edited in place, and then later downloaded for eDiscovery purposes, what is the document’s date? A typical MS Office (Excel, Word, PowerPoint, etc) document has three dates assigned by the file system (think: my laptop’s hard drive): Created, Modified, and Accessed. It also has up to three dates “embedded” inside the file itself: Created, Modified, and Last Printed. What happens when the Excel file makes a round trip to Google and back? With so many dates to choose from, it’s tough to pick just one!Before the upload to Google Drive, here are the file system dates for our MS Excel document. Notice that the file system is telling us the document was created on June 30, 2020, at 11:33 AM.And here are the embedded “application” dates. Note that “Date last saved” is essentially a “modified” date, and this document has not yet been printed. By looking at the application-level dates, we can also tell that the file was actually created at 11:04 AM, and then copied to its present location at 11:33 AM.After uploading to Google Drive, Google will assign its own Created and Modified dates to the item. You’ll notice in the graphic below that Google’s displayed Modified date of June 30 at 1:36 PM matches the Modified date of the original file. So far so good! But, take a look at Google’s recording of the Created Date: it’s been set by Google to simply “11:23 AM” on the date of the upload action (July 10, 2020.) Notice also that Google indicates the document was created “with Google Drive Web.”Now, let’s make an edit to the Excel file. There are two ways to accomplish this in Google Drive: 1) you can edit the document “in place” using Google Docs without abandoning the original MS Excel format, or 2) you can do a “Save As” and convert the document into Google Sheets format. In this example, we are going to use method #1 and make a couple of edits to our MS Excel file. Google Docs immediately auto saves the file for us. Let’s look at the dates.After editing in Google Drive, but leaving as Excel format, you’ll notice in the graphic below that Google’s Modified date has been changed to the time of the edit. This makes sense. The Created date, which Google previously set to the time of upload, remains the same.Let’s assume that this record is needed for e discovery purposes, and it is downloaded from Google Drive to a forensic examiner’s machine to pass along to the case team. When the file reaches the machine, the creation of the new file results in the following file system date values. Notice that they’ve all been changed to the date/time of the download action!However, if we take a look inside the Excel file at the embedded “application” dates, we notice that we have a creation date of 6/30/2020 at 11:04 AM that has remained unaltered throughout this entire process. However, the “Date last saved” is reflective of the time of the download action. We may have expected this date to be set to 11:27 AM, which was the time at which the document was edited in Google Drive, but it is unfortunately altered by the download action. The image on the right shows the “Info” tab from MS Excel itself, which indicates a blank value for “Last Modified.”Using the same Excel file, I will now choose to “Save as Google Sheets”.You’ll notice that the creation and modification timestamps in the graphic below have been set to the time at which the MS Excel file was converted to a Google Sheet. Google also indicates the application that created the document was “Google Sheets.”I made a couple of edits to the file in Google Sheets and then right clicked to download it to my workstation. First, Google converts the file from Google Sheets format into MS Excel format.chat-and-collaboration-data; information-governancecloud, g-suite, blog, chat-and-collaboration-data, information-governancecloud; g-suite; blogjosh headley
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Why Moving to the Cloud can Help with DSARs (and Have Some Surprise Benefits)
However you view a DSAR, for any entity who receives one, they are time consuming to complete and disproportionately expensive to fulfill. Combined with the increasing manner in which they are being weaponized, companies are often missing opportunities to mitigate the negative effects of DSARs by not migrating data to the Cloud.Existing cloud solutions, such as M365 and Google Workplace (formerly known as G-Suite) allow administrators to,for example, set data retention policies, ensuring that data cannot routinely be deleted before a certain date, or that a decision is made as to when data should be deleted. Equally, legal hold functionality can ensure that data cannot be deleted at all. It is not uncommon for companies to discover that when they migrate to the Cloud all data is by default set to be on permanent legal hold. Whilst this may be required for some market sectors, it is worth re-assessing any existing legal hold policy regularly to prevent data volumes from ballooning out of control.Such functionality is invaluable in retaining data, but can have adverse effects in responding to DSARs, as it allows legacy or stale data to be included in any search of documents and inevitably inflates costs. Using built-in eDiscovery tools to search and filter data in place in combination with a data retention policy managed by multiple stakeholders (such as Legal, HR, IT, and Compliance) can mitigate the volumes of potentially responsive data, having a significant impact on downstream costs of fulfilling a DSAR.Typically, many key internal stakeholders are frequently unaware of the functionality available to their organization. This can help to mitigate costs, such as Advanced eDiscovery (AED) in Microsoft 365, or Google Vault in Google Workspace. Using AED, a user can quickly identify relevant data sources, from mailboxes, OneDrive, Teams, Skype, and other online data sources, apply filters such as date range and keywords, and establish the potential number of documents for review within in minutes. Compare this to those who have on-premise solutions, where they are wholly dependent on an internal IT resource, or even the individual data custodians, to identify all of the data sources, confirm with HR / Legal that they should be collected, and then either apply search criteria or export the data in its entirety to an external provider to be processed. This process can take days, if not weeks, when the clock is ticking to provide a response in 30 days. By leveraging cloud technology, it is possible to identify data sources and search in place in a fraction of the time it takes for on-premise data.Many cloud platforms include functionality, which means that when data is required for a DSAR, it can now be searched, filtered, and, crucially, reviewed in place. If required, redactions can be performed prior to any data being exported externally. Subject to the level of license held, additional functionality, such as advanced indexing or conceptual searching, can also be deployed, allowing for further filtering of data and thus reducing data volumes for review or export.The technology also allows for rapid identification of multiple data types including:Stale dataSensitive data types (financial information/ PII)Customer-specific dataSuspicious / unusual activitiesBy using the inbuilt functionality to minimize the impact of such data types as part of an Information Governance / Records Management program, there can be significant changes and improvements made elsewhere, including data retention policies, data loss prevention, and improved understanding of how data is routinely used and managed in general day-to-day business. This, in turn, has significant time and cost benefits when required to search for data, whether for a DSAR, investigation, or a litigation exercise. Subject to the agreement with the cloud service provider, this may also have benefits in reducing the overall volume and cost of data hosted.With a sufficiently robust internal protocol in place, likely data sources can be identified and mapped. Now, when a DSAR request is received, an established process exists to rapidly search and cull potential cloud-based data sources, including using tools such as Labels or Sensitivity Type to exclude data from the review pool, and efficiently respond to any such request.Migrating to the Cloud may seem daunting, but the benefits are there and can be best maximized when all stakeholders work together, across multiple teams and departments. DSARs do not have to be the burden they are today. Using tools readily available in the Cloud might also significantly reduce the burdens and costs of DSARs.To discuss this topic further, please feel free to reach out to me at MBicknell@lighthouseglobal.com.data-privacy; ediscovery-review; information-governance; microsoft-365cloud, dsars, cloud-services, blog, data-privacy, ediscovery-review, information-governance, microsoft-365cloud; dsars; cloud-services; blogmatt bicknell
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Why You Need a Specialized Key Document Search Team in Multi-District Litigation
Few things are more ominous to a company’s in-house counsel than the prospect of facing thousands of individual lawsuits across 30-40 jurisdictions, alongside various other companies in a multi-district litigation (MDL) proceeding. In-house teams can, of course, lean on the expertise of external law firms that have strong backgrounds in MDLs. However, even for experienced law firms, coordinating an individual company’s legal defense with other law firms and in-house counsel within a joint defense group (JDG) can be a Sisyphean task. But this coordination is integral to achieving the best possible outcome for each company, especially when it comes to identifying and sharing the documents that will drive the JDG’s litigation strategies. An MDL can involve millions of documents, emanating from multiple companies and their subsidiaries. Buried somewhere within that complicated web of data is a small number of key documents that tell the story of what actually happened—the documents that explain the “who, what, where, and when” of the litigation. Identifying those documents is critical so that JDG counsel can understand the role each company played (or didn’t play) in the plaintiffs’ allegations, and then craft and prepare their defense accordingly. And the faster those documents are identified and shared across a JDG, the better and more effective that defense strategy and preparation will be. In short: A strong and coordinated key document search strategy that is specific to the unique ecosystem of an MDL is crucial for an effective defense. Ineffective search strategies leave litigators out at sea Unfortunately, outdated or ineffective search methodologies are often still the norm rather than the exception. The two most common strategies were created to find key documents in smaller, insular litigation proceedings involving one company. They are also relics of a time when average data volumes involved in litigation were much smaller. Those two strategies are: one, relying on linear document review teams to surface key documents as they review documents one by one in preparation for production, and, two, relying on attorneys from the JDG’s counsel teams to arbitrarily search datasets using whatever search terms they think may be effective. Let’s take a deeper look at each of these methodologies and why they are both ineffective and expensive: Relying on linear review teams to find key documents. Traditional linear review teams are often made up of dozens or even hundreds of contract attorneys with no coordination around key document searches and little or no day-to-day communication with JDG counsel. Each attorney reviewer may also only see a tiny fraction of the entire dataset and have a skewed view of what documents are truly important to the JDG’s strategy. The results are often both overinclusive (with thousands of routine documents labeled “key” or “hot” that JDG counsel must wade through) and underinclusive (with truly important documents left unflagged and unnoticed by review teams). This search method is also painfully slow. Key documents are only incidentally surfaced by the review team if they notice them while performing their primary responsibility—responsive review. Relying on attorneys from JDG counsel teams. Relying on individual attorneys from the JDG’s outside counsel to perform keyword searches to find key documents is also ineffective and wastefully expensive. Without a very specific, coordinated search plan, attorneys are left running whatever searches each thinks might be effective. This strategy inevitably will risk plaintiffs finding critical documents first, leaving defense deposition witnesses unprepared and susceptible to ambush. This search methodology is also a dysfunctional use of attorney time and legal spend. Merits counsel’s value is their legal analytic skillset—i.e., their ability to craft the best litigation strategy with the evidence at hand. Most attorneys are not technologists or linguistic experts. Asking highly skilled attorneys to craft the most effective technological and linguistic data search is a bit like asking an award-winning sushi chef to jump onboard a fishing vessel, navigate to the best fishing spot, select the best bait, and reel in the fish the chef will ultimately serve. Both jobs require a highly specialized skillset and are essential to the end goal of delighting a client with an excellent meal. But paying the chef to perform the fisherman’s job would be ineffective and a waste of the chef’s skillset and time. Both of these search strategies are also reactive rather than proactive, which drives up legal costs, wastes valuable resources, and worsens outcomes for each company in a JDG. A better approach to MDL preparation and strategy Fortunately, there is a more proactive, cost-efficient, holistic, and effective way to identify the key documents in an MDL environment. It involves engaging a small team of highly trained linguists and technology search experts, who can leverage purpose-built technology to find the best documents to prepare effective litigation strategies across the entire MDL data landscape. A specialized team with this makeup provides a number of key advantages: Precise searches and results—Linguistic experts can carefully craft narrow searches that consider the nuance of human language to more effectively find key documents. A specialized search team can also employ thematic search strategies across every jurisdiction. This provides counsel with a critical high-level overview of the evidence that lies within the data for each litigation, enabling each company to make better, more informed decisions much earlier in the process.Quick access to key documents—Technology experts leveraging advanced AI and analytics can ensure potentially damaging documents bubble up to the surface—even in the absence of specific requests from JDG counsel. Compare this to waiting for those documents to be found by contract attorneys as they review an endless stream of documents, one by one, during the linear review process. A flexible offensive and defensive litigation strategy—A team of this size and composition can react more nimbly, circulate information faster, and respond quicker to changes in litigation strategy. For example, once counsel has an overview of the important facts, the search team can begin to narrow their focus to arm counsel with the data needed for both offensive and defensive litigation strategies. The team will be incredibly adept at analyzing incoming data provided by opposing counsel—flagging any gaps and raising potential deposition targets. Defensively, they can be used by counsel to get ahead of any potentially damaging evidence and identify every document that bolsters potential defense arguments. An expert partner throughout the process—A centralized search team is able to act as a coordinated “search desk” for all involved counsel, as well as a repository and “source of truth” for institutional knowledge across every jurisdiction. As litigation progresses, the search team becomes the right hand of counsel—using their knowledge and expertise to prepare deposition and witness preparation binders and performing ad-hoc searches for counsel. Once a matter goes to trial in one jurisdiction, the search team can use the information gleaned from that proceeding to inform their searches and strategy for the next case. Conclusion Facing a complex MDL is an undoubtedly daunting process for any company. But successfully navigating this challenge will be downright impossible if counsel is unable to quickly find and understand the key facts and issues that lie buried within massive volumes of data. Traditional key document search methodologies are no longer effective at providing that information to counsel. For a better outcome, companies should look for small, specialized search teams, made up of linguistic and technology experts. These teams will be able to build a scalable and effective search strategy tailormade for the unique data ecosystem of a large MDL—thereby proactively providing counsel with the evidence needed to achieve the best possible outcome for each company. lighting-the-way-for-review; ai-and-analytics; ediscovery-review; lighting-the-path-to-better-review; lighting-the-path-to-better-ediscoveryreview, blog, ai, ai-and-analytics, ediscovery-reviewreview; blog; aikdisarah moran
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Worldwide Data Privacy Update
It was a tumultuous summer in the world of data privacy, so I wanted to keep legal and compliance teams updated on changes that may affect your business in the coming months. Below is a recap of important data privacy changes across multiple jurisdictions, as well as where to go to dive into these updates a little deeper. Keep in mind that some of these changes may mean heightened responsibilities for companies related to breach requirements and/or data subject rights.U.S. On September 17th, four U.S. Republican senators introduced the “Setting an American Framework to Ensure Data Access, Transparency, and Accountability Act” (SAFE DATA). The Act is intended to provide Americans “with more choice and control over their data and direct businesses to be more transparent and accountable for their data practices.” The Act contains data privacy elements that are reminiscent of the GDPR and California Consumer Privacy Act (CCPA) of 2018, including requiring tech companies to provide users with notice of privacy policies, giving consumers the ability to opt in and out of the collection of personal information, and requiring businesses to allow consumers the ability to access, correct, or delete their personal data. See the press release issued by the U.S. Senate Committee on Commerce, Science and Transportation here: https://www.commerce.senate.gov/2020/9/wicker-thune-fischer-blackburn-introduce-consumer-data-privacy-legislationCalifornia’s Proposition 24 (the “California Privacy Rights Act of 2020”) will be on the state ballot this November. In some ways, the Act expands upon the CCPA by creating a California Privacy Protection Agency and tripling fines for collecting and selling children’s private information. Proponents say it will enhance data privacy rights for California citizens and give them more control over their own data. Opponents are concerned that it will result in a “pay for privacy” scheme, where large corporations can downgrade services unless consumers pay a fee to protect their own personal data. See: https://www.sos.ca.gov/elections/ballot-measures/qualified-ballot-measures for access to the proposed Act.In mid-August, the Virginia Legislative Commission initiated study commissions to begin evaluating elements of the proposed Virginia Privacy Act, which would impose similar data privacy responsibilities on companies operating within Virginia as the GDPR does for those in Europe and the CCPA does for those in California. To access the proposed Act, see: https://lis.virginia.gov/cgi-bin/legp604.exe?201+sum+HB473.EuropeOn September 8, Switzerland’s Federal Data Protection and Information Commissioner (FDPIC) concluded that the Swiss-US Privacy Shield does not provide an adequate level of protection for data transfers from Switzerland to the US. The statement came via a position paper issued after the Commissioner’s annual assessment of the Swiss-US Privacy shield regime, and was based on the Court of Justice of the European Union (CJEU) invalidation of the EU-US Privacy Shield. You can find more about the FDPIC position paper here: https://www.edoeb.admin.ch/edoeb/de/home/kurzmeldungen/nsb_mm.msg-id-80318.htmlSimilarly, Ireland’s data protection commissioner issued a preliminary order to Facebook to stop sending data transfers from EU users to the U.S., based on the CJEU’s language in the Schrems II decision which invalidated the EU-US Privacy Shield. In response, Facebook has threatened to halt Facebook and Instagram services in the EU. Check out the Wall Street Journal’s reporting on the preliminary order issued by the Ireland Data Protection Commission here: https://www.wsj.com/articles/ireland-to-order-facebook-to-stop-sending-user-data-to-u-s-11599671980. For Facebook’s response filing in Ireland, see: https://www.dropbox.com/s/yngcdv99irbm5sr/Facebook%20DPC%20filing%20Sept%202020-rotated.pdf?dl=0Relatedly, in wake of the Schrems II judgment, the European Data Protection Board has also created a task force to look into 101 complaints filed with several data controllers in EEA member states related to Google/Facebook transfers of personal data into the United States. See the EDPB’s statement here: https://edpb.europa.eu/news/news/2020/european-data-protection-board-thirty-seventh-plenary-session-guidelines-controller_enBrazilIn September, the new Brazilian General Data Protection Law (Lei Geral de Proteção de Dados Pessoais or LGPD) became retroactively effective after the end of a 15-business-day period imposed by the Brazilian Constitution. This was a surprising turn of events after the Brazilian Senate rejected a temporary provisional measure on August 26th that would have delayed the effective date to the summer of 2021. Companies should be aware that the law is similar to the GDPR in that it is extra territorial and bestows enhanced privacy rights to individuals (including right to access and right to know). Be aware too, although administrative enforcement will not begin until August of 2021, Brazilian citizens now have a private right of action against organizations that violate data subjects’ privacy rights under the new law. For more information, check out the LGPD site (that can be translated via Google Chrome) with helpful guides and tips, as well as links to the original law: https://www.lgpdbrasil.com.br/. The National Law Review also has a good overview of the sequence of events that led up to this change here: https://www.natlawreview.com/article/brazil-s-data-protection-law-will-be-effective-after-all-enforcement-provisions.EgyptIn June, Egypt passed the Egyptian Data Protection Law (DPL), which is the first law of its kind in that country and aims to protect the personal data of Egyptian citizens and EU citizens in Egypt. The law prohibits businesses from collecting, processing, or disclosing personal information without permission from the data subject. It also prohibits the transfer of personal data to a foreign country without a license from Egypt. See the International Association of Privacy Professional’s reporting on the law here: https://iapp.org/news/a/egypt-passes-first-data-protection-law/To discuss this topic further, please feel free to reach out to me at SMoran@lighthouseglobal.com.data-privacyccpa, gdpr, data-privacy, blog, data-privacy,ccpa; gdpr; data-privacy; blogsarah moran
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What Skills Do Lawyers Need to Excel in a New Era of Business?
The theme at the last CLOC conference was all about how the legal function is going through a tremendous evolution. Businesses are changing rapidly through digital transformation and remote or hybrid work environments while trying to capture the attention of technology saturated consumers. To remain competitive, legal departments must evolve to handle new types of work and constantly advancing processes and technologies, and consider how the legal function impacts the broader organization. They need to do this while also showing that their own department is embracing change, staying up on technology, and becoming more efficient. To do this well, legal department heads and the lawyers and professionals in the department will have to learn, and practice, some new skills: embracing technology, project management, change management, and adaptability. Some good news—recent trends in the legal space are helping departments and professionals facilitate and adapt to these changes. The first is an uptick in legal technologies available to legal departments. Instead of adapting to whatever technology the business makes available to the department, there are technologies built by lawyers for running a legal department. This trend means that lawyers have already started down the path of being more technology-forward. Second, the advent of the legal operations role—putting business discipline and rigor around the functioning of the legal department— has brought more robust project management and change management into many law departments. With these foundational blocks in place, lawyers must evolve their skills to take their department to the next level.The first, and likely most obvious, skill an attorney needs in a rapidly evolving business environment is a firm grasp on existing and emerging technology. There are two important categories of technology to consider—the first is legal technology and the second is broader technology trends. Legal technology not only facilitates the day-to-day functioning of the legal department—with e-billing, contract management, and project intake and workflow software—but also includes more complex categories such as eDiscovery and data management. To learn more about these technologies you can attend CLEs about relevant technologies in your area of practice or attend a legal technology conference. Outside of the legal space, there are also many general technology trends that are important for lawyers to be immersed in, including digital transformation, artificial intelligence, and digital payments and cryptocurrency. Digital transformation is all about changing from a brick and mortar, paper-based business to one that strategically leverages technology, digital tools, and the cloud to do the work. This is important for lawyers because it impacts the way their organizations contract and manage these technologies. Migrating to the cloud also benefits lawyers because it provides new technologies to manage legal departments.[1] Like cloud, AI has the ability to transform how lawyers work (e.g., check out our recent blog post on utilizing chatbots) as well as how their companies work. For both AI and digital transformation, reading and watching videos for IT leaders can help—although made for a different audience, there are lots of resources out there and they can provide the information relevant to lawyers. Finally, the plethora of digital payment methods and the volatility of cryptocurrency will have legal impacts in the future and lawyers should learn to understand the differences.The next set of skills is about project execution and management. As businesses change through digital transformation, it is equally important to transform the way legal departments work. To do that, learning effective business case presentation, project management, and change management are incredibly valuable talents. While diving into a full 30-page business case can sometimes be necessary, focusing time on learning to create an executive summary business case is time better spent for lawyers. You can find resources and templates in many places, including SmartSheet and Asana.There is a whole discipline around project management as well as multiple ways to drive results most effectively. Whether you take an agile approach or a more traditional method, the following skills are necessary: Cross-functional collaboration, including understanding and empathy for other departments, and influencing othersCommunication, including how to communicate effectively with a remote team – a reality that is often the norm in today’s worldTime management and prioritizationLeadership – leading a team and inspiring a team, and keeping team members engaged and focused both in the same office or working remotelyFacilitating a learning mindset across the project and team – ensuring that people are looking out for ways to continuously improve, learning from each step of the project, and iterating on each phase of the projectA couple of good resources for developing these skills include PMI.org, and LinkedIn Learning courses such as Project Leadership, Project Management Foundations: Communication, and Project Management Tips. Note that this is a discipline that can take years to perfect so focus on getting familiar with the concepts and then look for ways to get real life experience in your business. The best way to master these skills is through practice.While project management focuses on the process where you create a change, change management is a separate set of skills focused on moving people through that change. There are two components of change management lawyers need to know. The first is how to manage their own reaction to change—being adaptable can bring a lot of value to a volatile world.[2] Professor Anne Converse Willkom of Drexel University provides some great ways to work on becoming more adaptable here. The second part of change management is helping others through change. This may be your team or it could be a team impacted by a project you are leading. Harvard Business Review has a whole category of writing dedicated to this area, highlighting the importance of leading through change.There is a lot of information and resources to move through so it’s important to prioritize the areas and skills that will impact your role now and as you move through your career. From there, identify the list of resources you want to access to master those areas then work it in to your schedule. It’s important to budget 2-4 hours a week, at minimum, building your skills in one of these areas. If that seems like a lot, keep in mind that it is only 5-10% of a standard work week.‍[1] You can find more information on what this change is in this article by CIO.[2] It is sometimes hard to judge adaptability because we tend to be surrounded by like-minded thinkers. As such, relying on a third party resource can help. There is a great Forbes article that shares the signs of an adaptable person. Evaluate yourself versus this list and work on areas where you may not be adaptable.ediscovery-review; legal-operationsediscovery-process, blog, project-management, ediscovery-review, legal-operationsediscovery-process; blog; project-managementlighthouse
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What is the Future of TAR in eDiscovery? (Spoiler Alert – It Involves Advanced AI and Expert Services)
Since the dawn of modern litigation, attorneys have grappled with finding the most efficient and strategic method of producing discovery. However, the shift to computers and electronically stored information (ESI) within organizations since the 1990s exponentially complicated that process. Rather than sifting through filing cabinets and boxes, litigation teams suddenly found themselves looking to technology to help them review and produce large volumes of ESI pulled from email accounts, hard drives, and more recently, cloud storage. In effect, because technology changed the way people communicated, the legal industry was forced to change its discovery process.The Rise of TARDue to growing data volumes in the mid-2000s, the process of large teams of attorneys looking at electronic documents one-by-one was becoming infeasible. Forward-thinking attorneys again looked to technology to help make the process more practical and efficient – specifically, to a subset of artificial intelligence (AI) technology called “machine learning” that could help predict the responsiveness of documents. This process of using machine learning to score a dataset according to the likelihood of responsiveness to minimize the amount of human review became known as technology assisted review (TAR).TAR proved invaluable because machine learning algorithms’ classification of documents enabled attorneys to prioritize important documents for human review and, in some cases, avoid reviewing large portions of documents. With the original form of TAR, a small number of highly trained subject matter experts review and code a randomly selected group of documents, which are then used to train the computer. Once trained, the computer can score all the documents in the dataset according to the likelihood of responsiveness. Using statistical measures, a cutoff point is determined, below which the remaining documents do not require human review because they are deemed statistically non-responsive to the discovery request.Eventually, a second iteration of TAR was developed. Known as TAR 2.0, this second iteration is based on the same supervised machine learning technology as the riginal TAR (now known as TAR 1.0) – but rather than the simple learning of TAR 1.0, TAR 2.0 utilizes a process to continuously learn from reviewer decisions. This eliminates the need for highly trained subject matter experts to train the system with a control set of documents at the outset of the matter. TAR 2.0 workflows can help sort and prioritize documents as reviewers code, constantly funneling the most responsive to the top for review.Modern Data ChallengesBut while both TAR 1.0 and TAR 2.0 are still widely used in eDiscovery today – the data landscape looks drastically different than it did when TAR first made its debut. Smartphones, social media applications, ephemeral messaging systems, and cloud-based collaboration platforms, for example, did not exist twenty years ago but are all commonly used within organizations for communication today. This new technology generates vast amounts of complicated data that, in turn, must be collected and analyzed during litigations and investigations.Aside from the new variety of data, the volume and velocity of modern data is also significantly different than it was twenty years ago. For instance, the amount of data generated, captured, copied, and consumed worldwide in 2010 was just two zettabytes. By 2020, that volume had grown to 64.2 zettabytes.[1]Despite this modern data revolution, litigation teams are still using the same machine learning technology to perform TAR as they did when it was first introduced over a decade ago – and that technology was already more than a decade old back then. TAR as it currently stands is not built for big data – the extremely large, varied, and complex modern datasets that attorneys must increasingly deal with when handling discovery requests. These simple AI systems cannot scale the way more advanced forms of AI can in order to tackle large datasets. They also lack the ability to take context, metadata, and modern language into account when making coding predictions. The snail pace of the evolution of TAR technology in the face of the lightning-fast evolution of modern data is quickly becoming a problem.The Future of TARThe solution to the challenge of modern data lies in updating TAR workflows to include a variety of more advanced AI technology, together with bringing on technology experts and linguistics to help wield them. To begin with, for TAR to remain effective in a modern data environment, it is necessary to incorporate tools that leverage more advanced subsets of AI, such as deep learning and natural language processing (NLP), into the TAR process. In contrast to simple machine learning (which can only analyze the text of a document), newer tools leveraging more advanced AI can analyze metadata, context, and even the sentiment of the language used within a document. Additionally, bringing in linguists and experienced technologists to expertly handle massive data volumes allows attorneys to focus on the actual substantive legal issues at hand, rather than attempting to become an eDiscovery Frankenstein (i.e., a lawyer + a data scientist + a technology expert + and a linguistic expert all rolled into one).This combination of advanced AI technology and expert service will enable litigation teams to reinvent data review to make it more feasible, effective, and manageable in a modern era. For example, because more advanced AI is capable of handling large data volumes and looking at documents from multiple dimensions, technology experts and attorneys can start working together to put a system in place to recycle data and past attorney work product from previous eDiscovery reviews. This type of “data reuse” can be especially helpful in tackling the traditionally more expensive and time-consuming aspects of eDiscovery reviews, like privilege and sensitive information identification and can also help remove large swaths of ROT (redundant, obsolete, or trivial data). When technology experts can leverage past data to train a more advanced AI tool, legal teams can immediately reduce the need for human review in the current case. In this way, this combination of advanced AI and expert service can reduce the endless “reinventing the wheel” that historically happens on each new matter.ConclusionThe same cycle that brought technology into the discovery process is again prompting a new change in eDiscovery. The way people communicate and the systems used to facilitate that communication at work are changing, and current TAR technology is not equipped to handle that change effectively. It’s time to start incorporating more modern AI technology and expert services into TAR workflows to make eDiscovery feasible in a modern era.To learn more about the advantages of leveraging advanced AI within TAR workflows, please download our white paper, entitled “TAR + Advanced AI: The Future is Now.” And to discuss this topic more, feel free to connect with me at smoran@lighthouseglobal.com. [1] “Volume of data/information created, captured, copied, and consumed worldwide from 2010 to 2025” https://www.statista.com/statistics/871513/worldwide-data-created/practical-applications-of-ai-in-ediscovery; ai-and-analytics; ediscovery-reviewai-big-data, tar-predictive-coding, ediscovery-process, prism, blog, data-reuse, ai-and-analytics, ediscovery-reviewai-big-data; tar-predictive-coding; ediscovery-process; prism; blog; data-reusesarah moran
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Why do Lawyers Demand More Transparency with TAR?
Since Judge Andrew Peck’s ruling over nine years ago in Da Silva Moore v. Publicis Groupe & MSL Group, the use of Technology-Assisted Review (TAR) for managing review in eDiscovery has been court approved. Yet many lawyers and legal professionals still don’t use machine learning (which, for many, is synonymous with TAR) in litigation. In the eDiscovery Today 2021 State of the Industry report, only 31.1% of respondents said they use TAR in all or most of their cases; 32.8% of respondents said they use it in very few or none of their cases. So, why don’t more lawyers use TAR?Transparency and TAROne possible reason that lawyers avoid the use of TAR is that requesting parties often demand more transparency with a TAR process than they do with a process involving keyword search and manual review. Judge Peck (retired magistrate judge and now Senior Counsel with DLA Piper) stated in the eDiscovery Today State of the Industry report: “Part of the problem remains requesting parties that seek such extensive involvement in the process and overly complex verification that responding parties are discouraged from using TAR.”In the article Predictive Coding: Can It Get A Break?, author Gareth Evans, a partner at Redgrave, states: “Probably the greatest impediment to the use of predictive coding has been the argument that the party seeking to use it should agree to share its coding decisions on the documents used to train the predictive coding model, including providing to the opposing party the irrelevant documents in the training sets.”Lawyer training vs. “black box” technologyWhy do lawyers expect that they are entitled to more transparency with TAR? Perhaps a better question might be: why do they demand less transparency for keyword search and manual review? One reason might lie in the education and training that they receive to become lawyers. Many lawyers cut their teeth on the keyword search used for resources like Westlaw and Lexis. Consequently, keyword search is part of their experience and they feel comfortable using it.Those same lawyers see keyword search and manual review for discovery as an extension of what they learned in law school. But it’s not. Search (aka “information retrieval”) is an expertise. Effective keyword search for discovery purposes is an iterative process that requires testing and verification of the search result set and the discard pile to confirm that the scope of the search wasn’t too narrowly focused. The end goal is to construct a search with both high recall and high precision; to identify those documents potentially responsive to a production request without also capturing non-responsive information, which can significantly increase review costs. This is very different from the goal of identifying a handful of documents that can assist in a case precedents argument.With regard to TAR, many lawyers still see the technology as a “black box” that they don’t understand. So, when the other side proposes using TAR, they want a lot more transparency about the particular TAR process to be used. It’s simply human nature to ask more questions about things we don’t understand. But, truth be told, lawyers should probably be just as vigilant in seeking information about the opposing’s use of keyword search as they are when TAR is the approach being proposed.TAR technology in daily livesWhat many lawyers may not realize is that they’re already using the type of technology associated with TAR elsewhere in their lives — albeit with a different goal and lower stakes than in a legal case. TAR is based on a supervised machine learning algorithm, where the algorithm learns to deliver similar content based on human feedback. Choices we make in Amazon, Spotify, and Netflix influence what those platforms deliver to us as other choices we might want to see in terms of items to buy, songs to listen to or movies to watch. The process of “training” the algorithms that drive these platforms makes them more useful to us — just as the feedback we provide during a predictive coding process helps train the algorithm to identify documents most likely to be responsive to the case.ConclusionWhat should lawyers do when opposing counsel makes transparency demands regarding TAR processes to be used? Certainly, cooperation and discussion of the protocol as soon as possible — such as the Rule 26(f) “meet and confer” between the parties — can help everyone get “on the same page” about what information can or should be shared, no matter what approach is proposed.However, if the parties can’t reach an accord regarding TAR transparency, perhaps another case ruling by Judge Peck — Hyles v. New York City — can be instructive here, where Judge Peck cited Sedona Principle 6. This principle states: “Responding parties are best situated to evaluate the procedures, methodologies, and technologies appropriate for preserving and producing their own electronically stored information.” Ironically, in Hyles, the requesting party was trying to force the responding party to use TAR, but Judge Peck, despite being an acknowledged “judicial advocate for the use of TAR in appropriate cases” denied the requesting party’s motion in that case. Transparency demands from requesting parties shouldn’t deter you from realizing the potential efficiency gains and cost savings resulting from an effective TAR process.For more information on H5 Litigation Services, including review for production with the H5 unique TAR as a Service, click here.ediscovery-reviewediscovery-reviewblog; tar; litigation; technology-assisted-review; predictive-coding; ediscovery; machine-learningmitch montoya
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Top Four Considerations for Law Firms When Choosing a SaaS eDiscovery Solution
“The world’s most valuable resource is no longer oil, but data.” That’s what The Economist said in a fascinating opinion piece in 2017 that really stuck with me. This bold statement now seems more prescient than ever, as digital data continues to explode in volume and the advent of the cloud is significantly expanding where that valuable data, or electronically stored information (ESI), lives. So how has the legal world, and particularly all of us in the eDiscovery realm, fared?While this data revolution developed, lawyers, as per usual, have been a bit slow to adapt. As we’ve grappled with how to manage the explosion of data and cloud storage has gone mainstream, new and advanced SaaS solutions tied to cloud-based technology have taken the rest of the world by storm. It was only a matter of time before corporate clients would get on board and make the move to the cloud as is evident with the large majority of corporations who have transitioned to Office 365.So as clients focus more and more on controlling their budgets and demanding more eDiscovery efficiency, shifting to modernized, cloud-based SaaS technology seems like a no-brainer for law firms. What’s not to love about immediately eliminating the inefficiencies and manual tasks that accompany traditional eDiscovery workflows and creating satisfied clients in the process?In my previous two blogs, I discussed the top reasons why SaaS, self-service, spectra eDiscovery is exactly the right solution and the way of the future for law firms, and also best practices for embracing the data revolution. In this blog, I wrap up my SaaS exploration and present the top things to consider when choosing the best and most versatile SaaS solution for your eDiscovery program.1. Quick to Onboard - Software in the eDiscovery space has had a notoriously rocky road as far as simplicity and user friendliness. Many iterations of self-service, spectra, on-prem software are too complicated and require training fit for advanced users only. Another missing piece of the puzzle has often been the lack of clear and consumable metrics on areas like billing, usage, ingestion, and processing stats which are the key to helping inform users to make better decisions. With the new generation of eDiscovery technology, lawyers and litigation support professionals would most benefit from choosing a SaaS, self-service, spectra tool that’s quick and easy to understand. Look for a tool where cases with multiple users can be easily managed across matters and locations, and where you can create, upload, and process matters quickly, all with a customizable reporting dashboard.2. Access to Industry Leading Tools - One of the biggest issues we’ve seen as eDiscovery software has evolved is the need for users of on-prem software to purchase, install, and maintain multiple tools and systems in order to have a comprehensive internal workflow that spans the EDRM. This is not only expensive, but time consuming and risky considering the security implications that come with holding client data on your own servers. With SaaS, it’s critical to choose a platform that will provide access to all of the industry leading tools from processing to analytics to production in one comprehensive tool that is purchased, maintained, and upgraded by the solution provider. Users will immediately see direct cost savings from not having to manage multiple systems themselves when they adopt this type of end-to-end SaaS solution.3. Full-Service Support - Another important consideration when selecting a self-service, spectra, SaaS tool is to choose a flexible solution provider who can scale up if your matter changes and you end up needing full-service support. While having a self-service, spectra tool allows for complete independence in key areas like processing and production, what happens when your matter gets much bigger than anticipated and the data is too unwieldy to handle in-house, or if your internal team simply needs to shift their focus to something else? In this case, it’s critical to partner with a solution provider who has solid and experienced client support teams that can jump in any time you need help in your self-service, spectra journey.4. Secure Infrastructure - Last but not least, in this age of data breaches and cybersecurity on the top of the list of concerns for law firms and corporate clients alike, make sure you fully vet any SaaS tool you’re considering by thoroughly researching the solution provider’s back-end infrastructure. Look for vendors who have a scalable architecture for data processing and automation that you’ll be able to take full advantage of while eliminating the overhead that comes with infrastructure development and management on your end. That infrastructure should come with the peace of mind of security certifications such as SOC 2 and ISO 27001. You can also eliminate the concern that often comes with the security of a public cloud by choosing a solution provider that hosts data within their own private cloud or within their own data centers.Ultimately, as the global economy continues to shift from traditional commodities and lands squarely on data as its main driver, there’s a world of opportunity ahead for the legal world and eDiscovery. With data already moved to the cloud for most companies and their focus shifted to reducing expenses and risk, eDiscovery and SaaS for law firms is a perfect fit.ediscovery-review; ai-and-analyticscloud, self-service, spectra, blog, ediscovery-review, ai-and-analyticscloud; self-service, spectra; bloglighthouse
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What Attorneys Should Know About Advanced AI in eDiscovery: A Brief Discussion
What does Artificial Intelligence (AI) mean to you? In the non-legal space, AI has taken a prominent role, influencing almost every facet of our day-to-day life – from how we socialize, to our medical care, to how we eat, to what we wear, and even how we choose our partners.In the eDiscovery space, AI has played a much more discreet but nonetheless important role. Its limited adoption so far is due, in part, to the fact that the legal industry tends to be much more risk averse than other industries. The innate trust we have placed in more advanced forms of AI technology in the non-legal world to help guide our decision making has not carried over to eDiscovery – partly because attorneys often feel that they don’t have the requisite technological expertise to explain the results to opposing counsel or judges. The result: most attorneys performing eDiscovery tasks are either not using AI technology at all or are using AI technology that is generations older than the technology currently being used in other industries. All this despite the fact that attorneys facing discovery requests today must regularly analyze mountains of complicated data under tight deadlines.One of the most prominent roles AI currently plays in eDiscovery is within technology assisted review (TAR). TAR uses “supervised” machine learning algorithms to classify documents for responsiveness based on human input. This classification allows attorneys to prioritize the most important documents for human review and, often, reduce the number of documents that need to be reviewed by humans. TAR has proven to be especially helpful in HSR Second Requests and other matters with demanding deadlines. However, the simple machine learning technology behind TAR is already decades old and has not been updated, even as AI technology has significantly advanced. This older AI technology is quickly becoming incapable of handing modern datasets, which are infinitely more voluminous and complicated than they were even five years ago.Because the legal industry is slower to adopt more advanced AI technology, many attorneys have a muddled view of what advanced AI technology exists, how it works, and how that technology can assist attorneys in eDiscovery today. That confusion becomes a significant detriment to modern attorneys, who must start being more comfortable with adopting and utilizing the more advanced AI tools available today if they stand a chance overcoming the increasingly complicated data challenges in eDiscovery. This confusion behind AI can also lead to a vicious cycle that further slows down technology adoption in the legal space: attorneys who lack confidence in their ability to understand available AI technology subsequently resist adoption of that technology; that lack of adoption then puts them even further behind the technology learning curve as technology continues to evolve. This is where legal technology companies with dedicated technology services can help. A good legal technology company will have staff on hand whose entire job it is to evaluate new technology and test its application and accuracy within modern datasets. Thus, an attorney who has no interest in becoming a technology expert just needs to be proficient enough to know the type of tools that might fit their needs – the right technology vendor can do the rest. Technology experts can also step in to help provide detailed explanations of how the technology works to stakeholders, as well as verify the outcome to skeptical opposing counsel and judges. Moreover, a good technology provider can also supply expert resources to perform much of the day-to-day utilization of the tool. In essence, a good legal technology vendor can become a trusted part of any attorney team – allowing attorneys to remain focused on the substantive legal issues they are facing. With that in mind, it’s important to “demystify” some common AI concepts used within the eDiscovery space and explain the benefits more advanced forms of AI technology can provide within eDiscovery. Once comfortable with the information provided here, readers can take a deeper dive into the advantages of leveraging advanced AI within TAR workflows in our full white paper – “TAR + Advanced AI: The Future is Now.” Armed with this information, attorneys can begin a more thoughtful conversation with stakeholders and legal technology companies regarding how to move forward with more advanced AI technology within their own practice.Demystifying AI Jargon in eDiscoveryAt its most basic, AI refers to the science of making intelligent machines – ones that can perform tasks traditionally performed by human beings. Therefore, AI is a broad field that encompasses many subfields and branches. The most relevant to eDiscovery are machine learning, deep learning, and natural language processing (NLP). As noted above, the technology behind legacy TAR workflows is supervised machine learning. Supervised machine learning uses human input to mimic the way humans learn through algorithms that are trained to make classifications and predictions. In contrast, deep learning eliminates some of that human training by automating the feature extraction process, which enables it to tackle larger datasets. NLP is a separate branch of machine learning that can understand text in context (in effect, it can better understand language the way humans understand it).The difference between the AI technology in legacy TAR workflows and more advanced AI tools lies in the fact that advanced AI tools use a combination of AI subsets and branches (machine learning, deep learning, and NLP) rather than just the supervised machine learning used in TAR. Understanding the Benefits of Advanced AIThis combination of AI subsets and branches used in advanced AI tools provides additional capabilities that are increasingly necessary to tackle modern datasets. These tools not only utilize the statistical prediction that supervised machine learning produces (which enables traditional TAR workflows), but also include the language and contextual understanding that deep learning and NLP provide. Deep learning and NLP technology also enable more advanced tools to look at all angles of a document (including metadata, data source, recipients, etc.) when making a prediction, rather than relying solely on text. Taking all context into consideration is increasingly important, especially when making privilege predictions that lead to expensive attorney review if a document is flagged for privilege. For example, with traditional TAR, the word “judge” in the phrases, “I don’t think the judge will like this!” on an email thread between two attorneys and, “Don’t judge me!” on a chat thread with 60 people regarding a fantasy football league will be classified the same way – because statistically, there is not much difference between how the word “judge” is placed within both sentences. However, newer tools that combine supervised machine learning with deep learning and NLP can learn the context of when the word “judge” is used as a noun (i.e., an adjudicator in a court of law) within an email thread with a small number of recipients versus when the word is being used as a verb on an informal chat thread with many recipients. The context of the data source and how words are used matters, and an advanced AI tool that leverages a combination of technologies can better understand that context.Using Advanced AI with TAROne common misconception regarding using newer, more advanced AI tools is that old workflows and models must go out the window. This is simply not true. While there may be some changes to review workflows due to the added efficiency generated by advanced AI tools (the ability to conduct privilege analysis simultaneously with responsive analysis, for example), attorneys can still use the traditional TAR 1.0 and TAR 2.0 workflows they are familiar with in combination with more advanced AI tools. Attorneys can still direct subject matter experts or reviewers to code documents, and the AI tool will learn from those decisions and predictive responsiveness, privilege, etc.The difference will be in the results. A more advanced AI tool’s predictions regarding privilege and responsiveness will be more accurate due to its ability to take nuance and context into consideration –leading to lower review costs and more accurate productions.ConclusionMany attorneys are still hesitant to move away from the older, AI eDiscovery tools they have used for the last decade. But today’s larger, more complicated datasets require more advanced AI tools. Attorneys who fear broadening their technology toolbox to include more advanced AI may find themselves struggling to stay within eDiscovery budgets, spending more time on finding and less time strategizing – and possibly even falling behind on their discovery obligations.But this fear and hesitancy can be overcome with education, transparency, and support from legal technology companies. Attorneys should look for the right technology partner who not only offers access to more advanced AI tools, but also provides implementation support and expert advisory services to help explain the technology and results to other stakeholders, opposing counsel, and judges.To learn more about the advantages of leveraging advanced AI within TAR workflows, download our white paper, “TAR + Advanced AI: The Future is Now.” And to discuss this topic more, feel free to connect with me at smoran@lighthouseglobal.com.ai-and-analytics; chat-and-collaboration-data; ediscovery-review; lighting-the-path-to-better-ediscoveryreview, ai-big-data, tar-predictive-coding, blog, ai-and-analytics, chat-and-collaboration-data, ediscovery-review,review; ai-big-data; tar-predictive-coding; blogai-analyticssarah moran
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Trends Analysis: New Sources of Evidentiary Data in Employment Disputes
Below is a copy of a featured article written by Denisa Luchian for The Lawyer.com that features Lighthouse's John Shaw.A highlight of the challenges arising from the increased use of collaboration and messaging tools by employees in remote-work environments.Our “top trends” series was born out of a desire to help in-house lawyers with their horizon scanning and with assessing the potential risks heading their way. Each post focuses on a specific area, providing companies and their lawyers with quick summaries of some of the challenges heading their way.Our latest piece in the series looks at the top 3 trends in-house lawyers should take notice of in the area of employment disputes, and was carefully curated by one of our experts – Lighthouse director of business development John Shaw. The Covid-19 pandemic has affected every sector of law and litigation, and employment law is certainly no exception. From navigating an ever-changing web of COVID-19 compensation regulations, to ensuring workplaces are compliant with shifting government health guidelines – the last six months have been chaotic for most employers. But as we all begin to regain our footing in this “new normal”, there is another COVID-19-related challenge that employers should be wary of: the increased use of collaboration and messaging tools by employees in remote-work environments.This past spring, cloud-based collaboration tools like Slack and Microsoft’s Teams reported record levels of utilisation as companies around the world were forced to jettison physical offices to keep employees safe and comply with government advice. Collaboration tools can be critical assets to keep businesses running in a remote work environment but employers should be aware of the risks and challenges the data generated from these sources can pose from an employment and compliance perspective.Intermingling of personal and work-related data over chatAs most everyone has noticed by now, working remotely during a pandemic can blur the line between “work life” and “home life.” Employees may be replying to work chat messages on their phone while simultaneously supervising their child’s remote classroom, or participating in a video conference while their dog chases the postman in the background. Collaboration and chat messaging tools can blur this line even further. Use of chat messaging tools is at an all-time high as employees who lost the ability to catch up with co-workers at the office coffee station transition these types of casual conversation to work-based messaging tools. These tools also make it easy for employees to casually share non-work related pictures, gifs, and memes with co-workers directly from their mobile phone.The blurring line between home and work, as well as the increased use of work chat messaging can also lead to the adoption of more casual written language among employees. Most chat and collaboration tools have emojis built into their functionality, which only furthers this tendency. Without the benefit of facial expressions and social cues, interpretation of this more casual written communication style can vary greatly depending on age, context, or culture.All of this means that personal, non-work related conversations with a higher potential for misinterpretation or dispute are now being generated over employer-sanctioned tools and possibly retained by the company for years, becoming a part of the company’s digital footprint.Evidence gathering challengesEmployers should expect that much of the data and evidence needed in future employment disputes and investigations may originate from these new types of data sources. Searching for and collecting data from cloud-based collaboration tools can be a more complicated process than traditional searching of an employee’s email or laptop. Moreover, the actual evidence employers will be searching for may look different when coming from these data sources and require additional steps to make it reviewable. Rather than using search terms to examine an employee’s email for evidence of bad intent, employers may now be examining the employee’s emoji use or reactions to chat comments on Teams or Slack.Evidence for wage and hour disputes may also look a bit different in a completely remote environment. When employees report to a physical office, employers can traditionally look to data from building security or log-in/out times from office-based systems to verify the hours an employee worked. In a remote environment, gathering this type of evidence may be a bit more complex and involve collecting audit logs and data from a variety of different platforms and systems, including collaboration and chat tools. A company’s IT team or eDiscovery vendor will need to understand the underlying architecture of these tools and ensure they have the capacity to search, collect, and understand the data generated from them.Employer best practicesEmployers should consider implementing an employee policy around the use of collaboration tools and chat functionality, as well as a comprehensive data retention schedule that accounts for the data generated from these tools. Keep these plans updated and adjust as needed. Ensure IT teams or vendors know where data generated by employees from these new data sources is stored, and that they have the ability to access, search, and collect that data in the event of an employment dispute.chat-and-collaboration-data; microsoft-365microsoft, cloud, emerging-data-sources, blog, chat-and-collaboration-data, microsoft-365microsoft; cloud; emerging-data-sources; blogthe lawyer
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Top Three Tips for Structuring an Effective eDiscovery Security Evaluation
In the modern age of legal technology, cybersecurity and eDiscovery are unquestionably intertwined. As cybersecurity threats escalate and bad actors find success with new methods and sophisticated tools to gain access to the ever-growing volumes and types of confidential electronic data, legal departments and law firms are getting hit daily by cybersecurity incidents and breaches, with many not even knowing when the incidents have occurred. The legal world, and eDiscovery in particular, are enticing targets, as matters typically involve huge volumes of sensitive information and data often resides across multiple providers who play a part in the collection, processing, hosting, review, and production of data.From a security perspective, corporations are constantly dealing with the data their employees create, and thus they typically maintain a solid system focused on maintenance, protection, back-ups, and defense of that data. This internal process is implemented using governance, risk, and compliance standards that run pretty well from the inside. But security gaps arise when that data becomes subject to a legal hold for litigation and that once well-protected data gets sent out to law firms and/or outside providers.So how can organizations feel confident they’re effectively evaluating the cybersecurity stability of their law firms, third parties, cloud providers, etc.? Do your providers have relevant security controls in place to ensure your data resides in a reasonably similar method as you would store the data yourself? Here are the top three tips for structuring an effective and comprehensive eDiscovery security evaluation and creating a strong relationship with your providers:Leverage Industry-Standard CertificationsAt the security evaluation stage, it’s critical to get to know your providers well and develop trusted relationships. The best way to first evaluate their overall security is to leverage industry-standard certifications. If the provider has access to and holds your data, they should be able to demonstrate that they’re ISO 27001 and SOC 2 certified as those have become the standard security environment protocol in the eDiscovery industry. Industry-standard questionnaires such as the SIG can also be used to validate a provider’s security structure. If a provider already has a completed and updated the SIG, this can be immediately accepted without needing to recreate the wheel and require another type of basic security assessment. This should serve as your baseline and will aid your risk assessments overall. It’s also important for organizations to audit, on an annual basis, those fundamental controls your providers have in place as the industry continues to focus deeper into all areas of each certification. The days of checking the standard audits off your list and being considered compliant are quickly becoming a thing of the past. With the increase in breaches, we are also seeing deeper and more thorough inspections beyond your own company and a shift to the provider space. So make sure you’re getting involved and staying involved with your suppliers. They are critical elements of your success and you need to treat them as such.Devise Security Questions That Go Beyond the BasicsIn addition to the standard certifications and questions the SIG and other general security audits give you, it’s also important to go beyond the basics and devise questions for your eDiscovery vendors that will uncover any existing gaps. Outside of questionnaires that simply ask for “yes” or “no” answers, consider doing regular audits with specific and focused questions. For example, ask your providers to discuss what different technologies they’re considering in the next 12 months or what new security certifications they’re planning to pursue. This ensures that you’re acting in a forward-thinking manner and developing better insight into your partners’ future development. To combat the growing cybersecurity threat, organizations need to remain one step ahead and devise questions to find forward-thinking suppliers rather than ones that just check the boxes. It’s also crucial to apply focused energy to the evolution of the organization and its suppliers. Take the time to have open dialogue and explore different solutions with the goal of prevention of threats. In today’s market, most organizations are still operating in a reactive state, meaning solutions are in place to detect malicious behaviors already inside your boundaries. Remember the clock always wins and prevention is the preferred way to stay ahead of attacks. Ask your technology providers the tough questions around ransomware and look to see what kinds of SLAs or guarantees they can offer. This is a great place to start to separate products and services by the maturity of their offering.Consider a Managed Services EnvironmentIn the most ideal of situations, a corporation would know in advance their list of trusted providers for investigations and litigation, and they would have a regular flow of communication with those providers that includes updates on standard certifications as well as regular audits including questions that go beyond the basics. Many times, this secure workflow can be best served by establishing a dedicated managed services environment that can support a more seamless and secure flow of data when a matter transitions to eDiscovery. Taking advantage of the dedicated services that come with a managed services environment, the corporation gets a technically skilled and more diverse talent base to draw from – one that becomes an extension of your team and treats the security of your data as if it were their own. Within that environment, law firms and document review lawyers all log into the same database and a partnership develops between all parties, creating a more secure environment. In addition, you’ll see cost savings by not having to invest in your own security infrastructure and separate cybersecurity personnel.Overall, vendor security is an integral part of an organization’s cybersecurity strategy. It’s imperative for corporations who transfer sensitive data out of their control to third parties to make sure that each and every supplier who handles the data meets all of the organization’s internal security requirements, as well as established regulatory requirements. This can be achieved by choosing providers who maintain industry-standard security certifications, performing regular audits outside of standard security questionnaires, and at the most secure level, by creating a managed services environment with your suppliers. data-privacy; ediscovery-reviewcybersecurity, cloud-security, ediscovery-process, blog, data-privacy, ediscovery-reviewcybersecurity; cloud-security; ediscovery-process; bloglighthouse
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What I Wish I Knew Then - Common Challenges in Building a Legal Operations Department and How to Avoid Them
Legal Operations is a relatively new field and one that is constantly evolving. With that comes lots of new challenges as well as lessons learned around building an effective Legal Operations department. Below are six key takeaways from a recent Illumination Webinar Series webinar, where legal operations veterans discussed common pitfalls in legal operations, how to avoid them, and best practices for the future.Legal Operations is an Evolving Field - Whether you define it as herding cats, the land of misfit toys, or the grey space in legal, one thing is certain - legal operations is a multi-disciplinary evolving field. If you use the membership numbers from the Corporate Legal Operations Consortium (CLOC) as a barometer of the growth of the profession, the increase of professionals is 1000% from 2016 to 2019. The work these professionals are doing varies from organization to organization. However, there are a few core areas that most legal operations departments focus on - ebilling, contract lifecycle management, vendor management, legal workflows, and legal department data and analytics.Change Management is One of the Biggest Challenges - Legal operations is a cross-functional department that is responsible for driving change in legal. As such, it is not a huge surprise that change management and the things that go along with that are big struggles for the function. Gaining executive support, getting enough funding, and identifying key stakeholders are all critical in the first stage of trying to make a change. Additionally, gaining adoption after a change is made can be a challenge as lawyers don’t tend to be early adopters.Understanding the Issue and Putting in Time at the Outset of a Project Can Help You Overcome Challenges - When considering what to solve for, make sure you understand the impact and pervasiveness of each and prioritize the most pervasive and impactful. Then, take the time to truly diagnose the problem. Don’t get distracted by the symptoms. Once you have identified the right problems, make sure you spend plenty of time clarifying all the specifications and understanding where the blockers may be. This will prevent missteps later and allow you to move quickly if you hit any roadblocks. Finally, make sure you get buy in along the way. This starts with buy in from your stakeholders on the specifications. Then, as you start to execute, share out your successes at each step and get stakeholder buy in on those successes. These steps will increase the success of any project you are leading.Knowing your Audience and your Data Can Really Help With Success in This Field – At the onset of any project, identify who you cheerleaders and naysayers are, that way you can identify the challenges that may arise. It is also wise to take a look at what is working and incorporate that into your future state so you don’t inadvertently break something that is going well. Make sure that you are leveraging relevant data to both identify the proposed improvements as well as to show them once achieved. And finally, to create supporters and build relationships across functions, you should look at ways to fill in the gaps in the legal department and offer support on projects. With these tips, your projects should be smoother to roll out.Analytics and AI are the Future - As in much of the world, artificial intelligence and business analytics are a big point of discussion in the legal operations space. This can be anything from analytics on top of a single existing platform all the way to cross-software AI to predict the outcome of litigation. Discussions about and the implementations of these tools are expected to continue in the next several years. Another exciting change for the field is the influx of new talent. As this is a new field, many of the current professionals transferred from another discipline. However, programs are being created to train for this area that will generate an influx of new talent that will move our profession forward. Finally, we expect more defined rules of engagement, both within legal operations but also with other departments in the company. This field is new so those rules have only recently started to form. That should solidify over the next several years.The Impacts of COVID-19 Should Not Drastically Change the Profession - Operationally, we were in a good situation given that legal operations is in the technology space. Departments were easily able to shift to work from home. Additionally, budgetary impacts have been different than any impacts that companies as a whole have felt.Legal operations has evolved significantly and will continue to change as the field matures. legal-operationslegal-ops, blog, legal-operations,legal-ops; bloglighthouse
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Unlocking Key HSR Second Request Data
The landscape for Hart-Scott-Rodino (HSR) filings has undergone immense flux over the last two years. The economic upheaval of the COVID-19 pandemic and regulatory shifts of a new presidential administration have impacted both the volume of large merger and acquisition (M&A) transactions and the scrutiny they receive from regulatory agencies. This makes it hard for businesses and law firms to know what to expect from upcoming M&As, including the likelihood of receiving a Second Request and how regulators will handle that investigation.Data on recent Second Requests can help by giving parties at least a general sense of what their peers are experiencing. Official numbers for 2021 won’t be published until autumn of this year — but we can look at past trends to try to predict those numbers to a reasonable degree.A close reading of historical data and current context suggests something of a paradox: The number of Second Requests in 2021 was likely fairly high but, at the same time, may have represented a historically small share of the year’s HSR filings. This is due to the extraordinary surge in HSR transactions and other factors, which are summarized below. For a full analysis, see our 2021 Second Request Trends Report.HSR filings plummet and rebound amid pandemic In 2020, the economic lockdown and business hesitancy caused by the COVID-19 pandemic brought HSR filings to their lowest total in 7 years. The Federal Trade Commission (FTC) and Department of Justice (DOJ) reported 1,673 filings for the year, of which 48 resulted in Second Requests. While this is less than the 61 Second Requests issued in 2019, it reflects the same annual percentage. That rate of 3% is slightly higher than the rates in both 2017 and 2018, which landed between 2 and 2.5%.Then, the economy surged in late 2020 and early 2021, bringing HSR filings with it. Preliminary data from federal agencies show HSR filings in 2021 more than doubled from the year before, reaching 3,644.Second Requests in 2021 likely resembled 2020 Most likely, the number of Second Requests in 2021 was close to the total in 2020. However, that means the percentage rate of Second Requests versus total HSR filings likely dropped significantly, by half or more.This is because maintaining the 3% rate from 2019-2020 seems unattainable. At that rate, agencies would have to investigate more than 100 proposed M&As — far beyond anything we’ve seen in the last 20 years.It’s also far too many for the FTC and DOJ to manage, given their recent struggles with capacity. Since December 2020, both agencies have made multiple budget requests and policy changes to help them keep up with the volume of transactions and workload associated with them. For example, FTC officials have publicly called for more time to review filings, saying the traditional review period of 30 days hasn’t, “kept pace with the increased volume and complexity of transactions and their related data and documents.”A more realistic rate for 2021, therefore, is somewhere between 1 and 2%. That would produce around 50 Second Requests — a total consistent with last year, as well as the average annual number over the last 20 years.HSR is more complex for everyone While HSR filings have clearly bounced back from their dip in 2020, the overall Second Request landscape is marked by complexity and uncertainty. Officials continue to make and seek revisions to regulations, making the terms of engagement a moving target. The soaring data volumes and diverse data sources cited by the FTC pose challenges for companies as well, who may find it increasingly difficult and expensive to meet HSR deadlines and other requirements.This was evident in a recent survey conducted by Lighthouse of more than 100 experts from corporations and law firms, who selected the following challenges as top of mind during the Second Request process:Getting the data in and processed quicklyEnsuring the deal goes throughProducing quicklyChoosing the right technologyThese responses underscore the need for parties to accurately read the landscape and leverage outside tools and expertise to improve speed and efficiency.For a deeper dive into the Second Request landscape, including insights from experienced attorneys in the field, a detailed primer on regulatory changes, and what to expect in the current year, check out our 2021 Second Request Trends Report.antitrusthsr-second-requests, blog, acquisitions, mergers, antitrusthsr-second-requests; blog; acquisitions; mergerslighthouse
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To Reinvigorate Your Approach to Big Data, Catch the Advanced AI Wave
Emerging challenges with big data—large sets of structured or unstructured data that require specialized tools to decipher— have been well documented, with estimates of worldwide data consumed and created by 2025 reaching unfathomable volumes. However, these challenges present an opportunity for innovation. Over the past few years, we’ve seen a renaissance in AI products and solutions to help address and evolve past these issues. From smaller players creating bespoke algorithms to bigger technology companies developing solutions with broader applications, there are substantial opportunities to harness AI and rethink how to manage data.A recent announcement of Microsoft’s Syntex highlights the immense possibilities for, and investment in, leveraging AI to manage content and augment human expertise and knowledge. The new feature in Microsoft 365 promises advanced AI and automation to classify and extract information, process content, and help enforce security and compliance policies. But what do new solutions like this mean for eDiscovery and the legal industry?There are three key AI benefits reshaping the industry you should know about:1. Meeting the challenges of cloud and big data2. Transforming data strategies and workflows3. Accelerating through automationMeeting the challenges of cloud and big data Anyone close to a recent litigation or investigation has witnessed the challenge posed by today’s explosion of data—not just volume, but the variety, speed, and uncertainty of data. To meet this challenge, traditional approaches to eDiscovery need to be updated with more advanced analytics so teams can first make sense of data and then strategize from there. Simultaneous with the need to analyze post-export documents, it’s also clear that proactively managing an organization’s data is increasingly essential. Organizations across all industries must comply with an increasingly complex web of data privacy and retention regulations. To do so, it is imperative that they understand what data they are storing, map how that data flows throughout the organization, and have rules in place to govern the classification, deletion, retention, and protection of data that falls within certain regulated categories of data types. However, the rise of new collaboration platforms, cloud storage, and hybrid working have introduced new levels of data complexity and put pressure on information governance and compliance practices—making it impossible to use older, traditional means of information governance workflows. Leveraging automation and analytics driven by AI advances teams from a reactive to proactive posture. For example, teams can automate a classification system with advanced AI where it reads documents entering the organization’s digital ecosystem, classifies them, and labels them according to applicable sensitivity or retention categories implemented by the organization—all of which is organized under a taxonomy that can be searched later. This not only helps an organization better manage data and risks upfront—creating a more complete picture of the organization’s data landscape—but also informs better and more efficient strategies downstream. Transforming data strategies and workflows New AI capabilities give legal and data governance teams the freedom to think more holistically about their data and develop strategies and workflows that are updated to address their most pressing challenges. For eDiscovery, this does not necessarily mean discarding legacy workflows (such as those with TAR) that have proven valuable, but rather augmenting them with advanced AI, such as natural language processing or deep learning, which has capabilities to handle greater data complexity and provide insights to approach a matter with greater agility. But the rise of big data means that legal teams need to start thinking about the eDiscovery process more expansively. An effective eDiscovery program needs to start long before data collection for a specific matter or investigation and should contemplate the entire data life cycle. Otherwise, you will waste substantial time, money, and resources trying to search and export insurmountable volumes of data for review. You will also find yourself increasingly at risk for court sanctions and prolonged eDiscovery battles if your team is unprepared or ill-equipped to find and properly export, review, and produce the requested data within the required timeline. For compliance and information governance teams, this proactive approach to data has even greater implications since the data they’re handling is not restricted to specific matters. In both cases, AI can be leveraged to classify, organize, and analyze data as it emerges—which not only keeps it under control but also gives quicker access to vital information when teams need it during a matter.Advanced AI can be applied to analyze and organize data created and held by specific custodians who are likely to be pulled into litigation or investigations, giving eDiscovery teams an advantage when starting a matter. Similarly, sensitive or proprietary information can be collected, organized, and searched far more seamlessly so teams don’t waste time or resources when a matter emerges. This allows more time for case development and better strategic decisions early on.Accelerating through automation Data growth continues to show no signs of slowing, emphasizing the need for data governance systems that are scalable and automated. If not, organizations run the risk of expending valuable resources on continually updating programs to keep pace with data volumes and reanalyzing their key information.The best solutions allow experts in your organization to refine and adjust data retention policies and automation as the organization’s data evolves and regulations change. In today’s cloud-based world, automation is a necessity. For example, a patchwork of global and local data privacy regulations (GDPR, California’s CCPA, etc.) include restrictions related to the timely disposal of personal information after the business use for that data has ended. However, those restrictions often conflict with or are triggered by industry regulations that require companies to keep certain types of documents and data for specific periods of time. When you factor in the dynamic, voluminous, and complex cloud-based data infrastructure that most company’s now work within, it becomes obvious why a manual, employee-based approach to categorizing data for retention and disposal is no longer sustainable. AI automation can identify personal information as it enters the company’s system, immediately classify it as sensitive data, and label it with specific retention rules. This type of automation not only keeps organizations compliant, it also enables legal and data governance teams to support their organization’s growth—whether it’s through new products, services, or acquisitions—while keeping data risk at bay. Conclusion Advancements in AI are providing more precise and sophisticated solutions for the unremitting growth in data—if you know how to use them. For legal, data governance, and compliance teams, there are substantial opportunities to harness the robust creativity in AI to better manage, understand, and deploy data. Rather than be inhibited by endless data volumes and inflexible systems, AI can put their expertise to work and ultimately help to do better at the work that matters. practical-applications-of-ai-in-ediscovery; ai-and-analytics; chat-and-collaboration-data; microsoft-365; lighting-the-path-to-better-information-governancemicrosoft, ai-big-data, cloud-security, blog, record-management, ai-and-analytics, chat-and-collaboration-data, microsoft-365,microsoft; ai-big-data; cloud-security; blog; record-managementmitch montoya
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Three Steps to Tackling Data Privacy Compliance Post GDPR
Recently we took Lighthouse’s legal technology podcast series Law and Candor on the road and broadcast a special live edition to our audience straight from Legaltech. One episode focused on the issue that’s at the forefront of the eDiscovery and information governance world: data privacy compliance in the post-GDPR world. Our distinguished Law and Candor hosts spoke with special guest Kelly Clay, global eDiscovery counsel and head of information governance at GlaxoSmithKline (GSK), about the key challenges or “opportunities” that GDPR, CCPA, and other burgeoning laws around data privacy have presented, and subsequently how the associated risks have permanently shifted the legal landscape.With the two-year anniversary of GDPR’s first day of implementation right around the corner, it’s a perfect time to reflect on where we are now. Organizations around the world have become more comfortable with the idea that data governance, privacy, and security are more than just new challenges they are being forced to solve. Businesses are beginning to see the new opportunities that come from data privacy regulations as they realize the benefits that come from cross-functional stakeholders working together across all of their internal support functions.So what are organizations doing to get a handle on the information governance side of the house and ensure compliance in this post-GDPR era? Here are three steps to take on the road to continual compliance:Understand where your data resides. It might seem obvious, but the number one place to start (and some would argue the most important) is taking a detailed look at your data and understanding all of the different types your organization generates, and the various locations where it all resides. Many who have already embarked on this journey have found silos during the process and encountered complications in understanding the full extent of their data and where it is. Now’s the time to use the information you gather to create a detailed and comprehensive data map that can be easily and automatically updated as new locations and new data are constantly created.Focus on the general principles. It’s easy to get overwhelmed in the data mapping process, especially if you’re a large organization whose employees utilize many different communication methods and IT has traditionally employed disparate storage methods for that never-ending mountain of data. Once your data map is in place, take a step back and realize you can’t tackle every potential compliance issue at the same time. Instead, continue to focus on the overall general principles like understanding where the data is flowing from and where it’s going, whether it’s email, chats, or data in the Cloud.Change the narrative. Historically, Legal and IT have operated separately and handled data based on the nature of their specific job functions. For example, Legal views data and information through the lens of risk management, while IT has a different approach in how it views managing and archiving data within an enterprise. With GDPR, CCPA, and likely many more privacy regulations to come, organizations need to handle data differently and understand everyone is accountable and must work cross functionally. Key players from the technology group to the procurement team to the business strategy group must change their mindset and be mindful of how they deal with data while keeping legal risk at the forefront.Ultimately, the post-GDPR era is here to stay and organizations should treat these dramatic changes in how we view and handle data as an opportunity not a challenge. Getting a handle on how to create an effective compliance program is a team effort that requires everyone to get on the same page, and it’s particularly important to involve your key stakeholders early on in the process.More on this topic can be found in this article, How GDPR and DSARs are Driving a New, Proactive Approach to eDiscovery. data-privacy; information-governanceccpa, gdpr, cloud-security, blog, data-privacy, information-governanceccpa; gdpr; cloud-security; bloglighthouse
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Three Reasons Why Law Firms Should Adopt SaaS for eDiscovery
Lawyers, and the legal field in general, are not exactly known for their willingness to embrace new technology and change the tried and true, traditional ways they’ve always used to practice law. But as technology has taken over our everyday lives and become the norm across most industries, there’s no time like the present for lawyers and litigation support professionals to take a second look at how they can get up to speed on the best and newest eDiscovery technology that will ultimately transform their business, and in turn, create happier clients who are laser focused on reducing costs and increasing efficiency.Like cassette tapes and the beloved Walkman, when it comes to eDiscovery, that old model of managing your own IT infrastructure and utilizing on-prem review platforms is becoming a thing of the past. This reminds me of other eDiscovery relics we knew and loved… not to call anyone out, but dare I mention Concordance or Clearwell in case you’re still using them?!In this changing technology landscape where most clients are moving (or have moved) their data to the cloud, it’s a perfect match to also modernize your law firm’s eDiscovery program and adopt a self-service, spectra model that will work seamlessly with data stored in the cloud, and deliver less risk and more benefits for both you and your clients.Just what are those benefits? Here are three reasons why adopting new technology and going to a SaaS eDiscovery solution will bring added efficiency, more billable hours, and happier clients.Eliminate the Risk and Expense of Managing Your Own IT Infrastructure - For law firms, managing an IT infrastructure and maintaining servers for the purpose of hosting client data is expensive and involves a large amount of risk. Electronic data has become overwhelmingly voluminous and types of data have become so much more complex than when law firms first got into this business and we were primarily dealing with email. Think about mobile devices, chat data, ephemeral communication, etc. as just the tip of the iceberg. With cybersecurity as a top concern for corporations, I think it’s fair to say that law firms probably never meant to take on the risk that comes with managing a complex IT infrastructure for their clients. Having a self-service, spectra, modern SaaS solution at their fingertips, law firms can lower costs and transfer the risk of hosting client data to the SaaS solution provider.Using SaaS Review Platforms Improves Client Services - Not only will a SaaS solution provide the benefit of relieving the security and risk burden, it will improve client services which is a win-win for the firm and the client. Although on-prem review platforms are what law firms have typically used, a SaaS platform reduces costs and improves efficiency. With an on-prem solution, license fees and infrastructure maintenance fees generally create out-of-pocket costs with no cost recovery mechanism. Moving to a SaaS solution introduces new ways to recover costs and makes solving substantive client concerns the primary job, rather than the inefficiencies that come along with maintaining an on-prem solution. To make the process of implementing a SaaS solution much easier, it’s important to note at this stage that building a business case and getting senior management on board with upgrading to a SaaS solution is critical. That way all parties understand the benefits to both the firm and its clients will be on the same page with making the change.Upgrading to SaaS Allows Firms to Provide the Latest Technology to Clients - Wouldn’t it be amazing if you could easily and quickly upgrade your eDiscovery technology and always provide the latest and greatest technology to clients? Moving to a SaaS platform immediately provides this benefit as the service provider maintains the infrastructure and makes technology upgrades behind the scenes for you. In case you’re feeling a little nervous that opportunity for some portions of internal work will disappear with this eDiscovery model, in fact the opposite is true. This isn’t a threat to the traditional litigation support model. It will instead allow for a greater focus on more valuable and strategic work while a solid partnership is established with the trusted service provider who runs the infrastructure of the SaaS platform and will work alongside you.If your primary goal is to create efficiency, lower costs, and ultimately make your clients happy, now’s the time to take your eDiscovery program to the next level and adopt a SaaS, self-service, spectra solution. You’ll have a modernized eDiscovery platform that allows for independent access and control to process, review, and produce data, while removing the risk and cost that comes with managing an IT infrastructure.ediscovery-review; ai-and-analyticscloud, self-service, spectra, cloud-security, blog, ediscovery-review, ai-and-analyticscloud; self-service, spectra; cloud-security; bloglighthouse
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Top Five Questions to Ask When Choosing an eDiscovery Vendor
We often get questions from our clients about how best to select an electronic discovery vendor. Important considerations in this process are what questions to ask, how best to compare vendors and what are the important issues that are typically missed in the selection process. In particular, our clients often tell us that they sometimes struggle in the vendor selection phase to be able to best assess the quality and capabilities of a vendor. Given the challenges of choosing the right vendor, we often hear that law firms default to making their decision based almost exclusively on price considerations. Our list of questions can help you make the right decision based on more than just price.Top Questions To Ask When Choosing an eDiscovery VendorScope of ServicesWhat services does the vendor offer?If case parameters change, will the vendor be able to meet your needs and time frames?Are there volume benefits/discounts if you use multiple services (e.g. processing, hosting and production versus just hosting)?What services are sub-contracted out and does data ever leave the vendor’s site?What size or type of case is too big for the vendor?What have been vendor’s toughest cases?Expertise (Not all vendors are created equal; and it is not all about price)What is the vendor’s knowledge level of the technical issues?Are the vendor’s employees certified in the tools they use?What is the vendor’s level of understanding of the legal process?Are there legal professionals on staff?How does the vendor’s expertise compare to other vendors?Quality of ServicesIs this a vendor that you could see yourself establishing a longer term relationship?How does the vendor manage ensuring high quality service consistently: accurate and on-time?Are errors tracked? What are considered errors? How are errors addressed?What do the references say about the vendor?Customer ServiceWhat hours does the vendor operate?How available are the vendor’s employees during non-business hours?How much lead time is needed for processing and production?How are cases staffed?Who is the primary point of contact? Is it the same throughout the case?What is the nature of the vendor’s project management team and approach?How are issues escalated?Technical SpecificationsDoes the vendor use proprietary versus non-proprietary software and what are the benefits/trade-offs?If the data is not being processed locally, what is the vendor’s FTP connection speeds and how does this compare with the law firm’s FTP speeds?What is the vendor’s policy on backing up data?What is the vendor’s policy regarding storing data?ediscovery-reviewediscovery-process, blog, ediscovery-review,ediscovery-process; bloglighthouse
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The Impact of Schrems II & Key Considerations for Companies Using M365: The Background
In 2016, European companies doing business in the US were able to breathe a sigh of relief. The European Commission deemed the Privacy Shield to be an adequate privacy protection. For the next half a decade, this shield, as well as Standard Contractual Clauses (SCCs), created the foundation upon which most global businesses were able to manage the thousands of data transfers that occur in each of their business days.Everything changed in July 2020 when the Court of Justice of the European Union gave its seismic judgment in a case generally known as Schrems II. As we will see, the decision has a particular impact on any companies relying on, or moving to, a cloud computing strategy. Businesses have been left needing to make a risk decision with seemingly no ideal outcome. Some legal, privacy, and compliance teams may be advocating for staying away from a cloud approach in light of the decision. The business teams, however, are focused on the vast array of benefits that cloud software offers.So what is the right decision? Where does the law stand and how do you manage your business in this uncertain time? In this four-part blog series, we&rsquo;ll explain the impact of Schrems II, provide practical tips for companies in the midst of making a cloud decision, give specific advice regarding companies who have, or are implementing, Microsoft&rsquo;s cloud offering (M365), and offer our view as to the future.Schrems II and Its ImpactFirst, let;s look at the Schrems II decision. The background to the case is well worth exploring but for the sake of brevity and providing actionable information we&rsquo;ll focus on the outcome and the consequences. The key outcomes impact the two primary ways in which most data transfers between Europe and the US:The EU-US Privacy Shield was invalidated with immediate effect.SCCs (the template contracts created by the EU Commission which are the most common way in which data is moved from the EU) were declared valid, but companies using SCCs could no longer just sign up and send. A company relying on SCCs would have to verify on a case-by-case basis that the personal data being transferred was adequately protected. This process is sometimes called a Transfer Impact Assessment, although the court did not coin that phrase. If the protection is inadequate, then additional safeguards could be needed.The consequences of the decision are still revealing themselves, but as things stand:The Privacy Shield (used by more than 5,000 mostly small-to-medium enterprises) has gone with no replacement in sight (although the Biden administration appears to recognise its importance with the rapid appointment of the experienced Christopher Hoff to oversee the process).There have been significant developments in relation to SCCs, additional safeguards, and transfer impact assessments:The US published a white paper to help organisations make the case that they should be able to send personal data to the US using approved transfer mechanisms.The European Data Protection Board (EDPB) published guidance on how to supplement transfer tools.The European Commission published draft replacement SCCs.The EDPB and the European Data Protection Supervisor adopted a joint opinion on the draft replacement SCCs requesting several amendments.There is not a clear timetable as to when the replacement SCCs or EDPB guidance (which has completed a period of publication consultation) will be finalised. The sooner the better because there seem to be inconsistencies between them. For example, the Schrems II judgment and draft replacement SCCs permit a risk assessment (i.e., it is possible to conclude that personal data might not be completely protected, but that the risk is so small that the parties can agree to proceed), whereas the EPDB recommendations seem to deal in black and white with no shades between (i.e., there is either adequate protection or there is not). It will be important to monitor which, if any, of these drafts moves and in which direction. Whether the SCCs are supported with a risk assessment or analysis along the lines of the EDPB recommendations (or perhaps both), going forward using SCCs may be rather cumbersome particularly in a cloud environment where the location and path of the data is not always crystal clear. Companies are therefore in something of a grey triangle, the sides of which are a judgment of the highest European Court, a draft replacement to the SCCs the Court reviewed in its judgment, and draft guidance about additional safeguards. In part two </span><span>of the series, we will offer companies some practical guidance on how to move forward in light of this grey triangle.To discuss this topic further, please feel free to reach out to us at info@lighthouseglobal.com.data-privacy; microsoft-365; information-governancemicrosoft, data-privacy, blog, privacy-shield, data-privacy, microsoft-365, information-governance,microsoft; data-privacy; blog; privacy-shieldlighthouse
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Three Ways to Use eDiscovery Technology to Reduce Repeated Review
By now, legal teams facing discovery are aware of many of the common technology and technology-enabled workflows used to increase the efficiency of document review on a single matter. But as data volumes grow and legal budgets shrink, legal teams must begin to think beyond a “matter-by-matter” approach. They must start applying technology more innovatively to create efficiencies across matters to minimize the burden of repeatedly reviewing the same documents again and again. Fortunately, many common technology-enabled review workflows (e.g., technology assisted review (TAR), advanced search guided by linguistic experts, and AI-powered review analytics) can help teams apply work product and insights from past matters to current and future matters. This not only saves time but also increases consistency and lowers the risk of inadvertent disclosures and cumbersome clawbacks.The opportunity to reduce repeated review is quite large, both because the problem is rampant and the technology that can help solve it is underutilized. A 2022 survey by the ABA showed that “predictive coding” is the least common application of eDiscovery software, used by only one in five law firms. In fact, 73% of respondents said they don’t know what predictive coding is (we explain it below). As document review continues to grow in complexity, and budget and other constraints apply pressure from other directions, more organizations should consider taking advantage of everything that technology has to offer.Repeated review is a large and familiar burdenRepeated review is baked into the status quo. Matters spanning multiple jurisdictions, civil litigations tied to government investigations, and matters involving the same or related IP are just a few examples in which the same documents could come up for review multiple times. Instead of looking across matters holistically, legal teams often feel obligated to roll up their sleeves, lower their heads, and review the same documents all over again—even when relevancy overlaps and for categories of information that remain relatively static across matters (privilege, trade secret, personally identifiable information (PII), etc.). This has obvious consequences for time and cost. The time invested on reviewing documents for privilege in a current matter, for example, becomes time saved on future matters involving those same documents. Risk is a factor as well. A document classified as privileged, or that contains PII or another sensitive category, in one matter should be classified the same way in the next one. But without a record of past matters, attorneys start over from scratch each time, which opens the door to inconsistency. And while it’s certainly possible to undo the mistake of producing sensitive documents, it can be quite time-consuming and expensive.Rejecting the status quo While the burden and risks associated with repeated review are felt every day, few legal teams and professionals are searching for a solution. Those willing to look beyond the status quo, however, will see that repeated review isn’t actually necessary, at least not to the degree that it’s done today. We also find that the keys to reducing repeated review lie in technology that many teams already use or have access to.Reusing work product from TAR and CAL workflows TAR 1.0, TAR 2.0, and Continuous Active Learning (CAL) workflows use machine learning technology to search and classify documents based on human input and their own ability to learn and recognize patterns. This is called predictive coding and it’s most often used to prioritize responsive documents for human review. The parameters for responsiveness change with the topics of each matter, so it’s not always possible to reuse those classifications on other matters. TAR and CAL tools can also be effective at making classifications around privilege, PII, and junk documents, which are not redefined from matter to matter. If a document was junk last time (say company logos attached to emails, blank attachments, etc.) it’s going to be junk this time too. Therefore, reusing these classifications made by technology on one matter can save legal teams even more time in the future. Refining review with linguistic expertsLinguistic experts add an extra layer of nuance to document review technology that makes them more precise and effective at classification. They develop complex criteria, based on intricate rules of syntax and language, to search and identify documents in a more targeted way than TAR and CAL tools.They can also help reduce repeated review by conducting bespoke searches informed by past matters. This process is more hands-on than using TAR and CAL tools; human linguists take lessons learned from one matter and incorporate them into their work on a related matter. It’s also more refined, so it can help in ways that TAR and CAL tools can’t.Litigation related to off-label drug use offers a good example. A company might have multiple matters tied to different drugs, making relevance unique for each matter. In this scenario, linguistics experts can identify linguistic markers that show how sales reps communicated with healthcare providers within that company. Then when the next off-label document review project begins, documents with those identifiers can be segregated for faster review. In this way, work from linguistic experts in one matter can help improve efficiency and minimize first-level review work on new matters. Apply learnings across matters using AI Review tools built on AI can reduce repeated review by classifying documents based on how they were classified before. AI tools can act as a “central mind” across matters, using past decisions on company data to make highly precise classifications on new matters. The more matters the AI is used on, the more precise its classifications become. The beauty here is that it applies to any amount of overlap across matters. The AI will recognize any documents that it has reviewed previously and will resurface their past classifications.Some AI tools can even retain the decision on past documents and associate it with a unique hash tag, so that it can tell reviewers how the same or similar documents were coded in previous matters—without the concern of over-retaining documents from past matters. Curious to challenge your status quo?TAR, AI, and other solutions can be invaluable parts of a legal team’s effort to curb repeated review — but they’re not the only part. In fact, the most important factor is a team’s mindset. It takes forethought and commitment to depart from the status quo, especially when it involves unfamiliar tools or strategies.The benefits can be profound, and the road to achieving them may be more accessible than you think.Find tips for starting small, as well as more information about how and why to address the burden of repeated review, in our deep dive on the subject.ai-and-analytics; ediscovery-review; lighting-the-path-to-better-ediscoveryreview, ai-big-data, blog, ai-and-analytics, ediscovery-reviewreview; ai-big-data; blogminimizing-re-reviewsarah moran
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The U.S Privacy Shield Is No Longer Valid – What Does that Mean for Companies that Transfer Data from the EU into the US?
It feels fitting that the summer of 2020 would bring us Schrems II. This surprising Court of Justice of the European Union (CJEU) decision wreaked havoc in late July by invalidating the EU - U.S. Privacy Shield and calling into question other mechanisms for transferring the personal data of EU citizens into the United States (and beyond) under the GDPR. Let’s take a deeper dive into that decision and what it means for companies that need to transfer EU citizens’ data into the U.S.Shrems HistorySchrems II is the second decision by the CJEU that is based on privacy complaints made against Facebook by Austrian privacy activist Max Schrems. Both cases stem from privacy concerns related to the U.S. National Security Agency (NSA)’s ability to access the personal data of EU citizens, famously disclosed by Edward Snowden in 2013.In the first Schrems decision in 2015, the CJEU invalidated the U.S. - EU Safe Harbor Framework (the predecessor to the EU - U.S. Privacy Shield) as a means to transfer personal data from the EU into the U.S., finding that the protections afforded by the Safe Harbor framework did not meet fundamental privacy rights guaranteed within the EU to EU citizens.In the aftermath of the first Schrems decision, the U.S. Department of Commerce and the EU Commission collaborated to implement the EU-U.S. Privacy Shield as a replacement to the Safe Harbor Framework, again allowing for a broader transfer mechanism of personal data into the U.S. compared to the alternatives (namely, “standard contractual clauses” (SCCs) and “binding corporate rules” (BCRs) – more on those below). Since its implementation in 2016, over 5,000 organizations have met the requirements administered by the International Trade Administration to join the Privacy Shield. Meeting those requirements can mean a large investment for organizations in overhauling their data privacy practices.That brings us to Schrems II, wherein Schrems brought a second complaint against Facebook, this time challenging the validity of SCCs as a mechanism to transfer personal data into the U.S. In Schrems II, he argued that the same privacy concerns related to the NSA’s ability to access EU citizens’ personal data under the Safe Harbor framework also applied to personal data transferred via an SCC. It should be noted here that around the same time, European privacy advocates also filed a challenge to the new EU-U.S. Privacy Shield with the European Court.Schrems II CJEU DecisionIn the Schrems II ruling in July, the CJEU ultimately decided to address both the EU-U.S. Privacy Shield and SCC issues.The Court upheld the validity of SCCs as a means to transfer personal data from the EU into the U.S. However, rather than carte blanche approval, the Court laid out obligations for both parties of an SCC and data protection supervisory authorities within the EU. Those obligations include:Entities that are transferring personal data of EU citizens into the U.S. must verify “on a case by case basis” that the protections afforded by the SCC can be met and that there is an “adequate level of protection” in the U.S. to protect the personal data of EU citizens.Entities that are receiving personal data of EU citizens in the U.S. have an obligation to notify the data exporter if they are unable to comply with the SCC for any reason.Data protection supervisory authorities within the EU have a mandatory obligation to evaluate not only the terms of the SCCs themselves, but also whether the data protections afforded by the U.S. legal system can meet those terms. If the SCC is found to be insufficient, the supervisory authority has an obligation to stop the transfer.This decision puts SCCs (and thereby BCRs) on shaky ground throughout the entire world, because the threshold set by the Court applies to any third country, not just the U.S. (see Questions 2 and 6 of the FAQ issued by the European Data Protection Board for more information on these points).However, the real kicker of Schrems II for U.S.-based companies with an international presence is that the CJEU completely invalidated the EU-U.S. Privacy Shield. The Court found that the U.S. does not provide sufficient protection of EU citizens’ personal data because of the access the U.S. government has to EU citizens’ personal data and because EU citizens have no means of redress against U.S. authorities should their privacy rights be violated.What Does Shrems II Mean for Companies that Need to Transfer Personal Data from the EU into the U.S.Companies that were relying on the Privacy Shield to transfer EU data into the U.S. should:Work to put individual SCCs or BCRs in place to achieve these transfers. There is no grace period during which a company can keep transferring data using the Privacy Shield mechanism, according to the European Data Protection Board (see Question 3 for more information).Continue to comply with all current Privacy Shield obligations. While the CJEU decision invalidates the Privacy Shield, it does not relieve current participant organizations of their obligations.Watch for further guidance from both the European Data Protection Board and the U.S. Department of Commerce (DOC). DOC and the European Commissioner for Justice issued a joint press release in early August, stating that they have initiated discussions to evaluate the potential for an enhanced EU-U.S. Privacy shield framework that would meet the requirements laid out by the CJEU.Companies that rely on SCCs or BCRs as a means to transfer personal data should: Conduct a risk assessment to determine whether those agreements and the recipient of the data in the U.S. can provide an adequate level of data protection, according to the European Data Protection Board (see Questions 5 and 6 for more information).Watch for further guidance from data protection authorities in relevant countries related to SCCs and BCRs in the wake of Schrems II. The transfer of personal data between countries is vital to the lifeblood of many companies, large and small. While Schrems II has thrown a wrench into the legality of those transfers… all is not lost. Stay tuned for updates from U.S. and EU authorities that may help ease the burden of this unexpected decision by the CJEU. Resources for More Information CJUE Schrems II full decision: http://curia.europa.eu/juris/document/document.jsf?text=&docid=228677&pageIndex=0&doclang=en&mode=lst&dir=&occ=first&part=1&cid=16606736CJEU press release on its Schrems II decision: https://curia.europa.eu/jcms/upload/docs/application/pdf/2020-07/cp200091en.pdfEU – U.S. Privacy Shield Program Schrems II FAQs: https://www.privacyshield.gov/article?id=EU-U-S-Privacy-Shield-Program-UpdateEuropean Data Protection Board Schrems II FAQs: https://edpb.europa.eu/our-work-tools/our-documents/ovrigt/frequently-asked-questions-judgment-court-justice-european-union_enS. Secretary of Commerce Wilbur Ross Statement on Schrems II ruling and the importance of EU-U.S. data flows: https://www.commerce.gov/news/press-releases/2020/07/us-secretary-commerce-wilbur-ross-statement-schrems-ii-ruling-andJoint press statement from the U.S. Secretary of Commerce and the European Commissioner regarding initiated discussions for a new privacy shield: https://www.commerce.gov/news/press-releases/2020/08/joint-press-statement-us-secretary-commerce-wilbur-ross-and-europeanUK’s Information Commissioner’s Office updated statement on the Schrems II decision: https://ico.org.uk/make-a-complaint/eu-us-privacy-shield/To discuss this topic further, please feel free to reach out to me at SMoran@lighthouseglobal.com. Or, take a look at other Worldwide Data Privacy Updates.data-privacycloud-security, blog, data-privacycloud-security; blogsarah moran
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Three Key Tips to Keep in Mind When Leveraging Corporate G Suite for eDiscovery
In the eDiscovery space, we are always spotting new trends. Our industry has seen text messages, chat message platforms, websites, and various unstructured data sources become increasingly relevant during discovery. Over the past several years, we have started to see another new trend emerge - many of our clients are using Corporate G Suite rather than Office 365.The use of emerging technologies is part of everyday life for many companies in the space. However, we are beginning to see established biotech, healthcare, manufacturing, and retailers shift to G Suite, an area that was once almost exclusively dominated by on-prem Microsoft products. This transition introduces some new considerations around managing discovery. In this post, we talk about three impacts that G Suite data has on downstream eDiscovery workflows, and the need to factor these items into your discovery plan. Recipient Metadata: Gmail renders email header information in a unique format. While the last-in-time email in a given string will have all expected sender and recipient information (From, To, CC, BCC), all other previous messages exchanged in the email string will display only the sender information and will not display the recipient information. This is not a collection, processing, metadata, or threading issue. Rather, this relates to how Gmail stores and exports recipient information. This presents some unique document review challenges, as previous parts of the thread could include recipients that are not visible to the reviewer, and may include attorneys who have sent privileged communications. As a result, it is important to work closely with your project management team to create workflows related to Gmail. ‚ÄçLinks: Historically, we have all attached copies of documents (e.g. Word, Excel, and PowerPoint files) to an email during the normal course of business. Due to the emergence of technologies such as SharePoint and Google Drive, we now have the ability to send emails with embedded links that reference documents rather than attaching the document itself. When Gmail is exported from Google Vault, the documents referenced in links embedded throughout email exchanges are not exported. As a result, reviewers will encounter these links, but will be unable to readily view the corresponding document referenced in said link. At present, Google Vault does not allow for the mass search and export of these links. However, you do have the ability to manually pull documents referenced in these links. You should be mindful of this issue when drafting your ESI protocol, as opposing parties and regulators may request that your company retrieve these documents.‚ÄçExported Load File: Unlike a standard PST export, when you export a mailbox or set of documents from Google Vault, you have the ability to retrieve a corresponding load file that contains metadata captured in G Suite. Sometimes, the date-related metadata extracted during processing, will not align with dates exported from G Suite. There are a variety of legitimate reasons for this. You will need to determine if you want to produce the date metadata extracted from the processing platform, date values exported from Vault, or both.All of the above items are manageable when in-house legal teams, outside counsel, and eDiscovery vendors work together to proactively implement appropriate downstream eDiscovery workflows. If you have experience with G Suite data or thoughts on managing the discovery of G Suite data, please reach out to me at ashier@lighthouseglobal.com.chat-and-collaboration-data; information-governancechat-and-collaboration-data, information-governanceemerging-data-sources; g-suite; preservation-and-collection; blogalison shier
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The Impact of Schrems II & Key Considerations for Companies Using M365: The Future
The Schrems II decision invalidated the EU-US Privacy Shield – the umbrella regulation under which companies have been transferring data for the last half-decade. In earlier parts of this four-part series, we described the impact of the Schrems decision, discussed how companies should evaluate their risk in using cloud technologies, and took a deeper dive on M365 in light of Schrems II. In sum, if you are a global business that previously relied upon Standard Contractual Clauses (SCCs) to transfer data, there is no clear guidance on what to do currently.It is even murkier in a cloud environment because the location of the data is not as transparent. Fortunately, there are ways to undertake a risk assessment to determine whether to proceed with any new cloud implementations. In the case of Microsoft products, there is also additional support from Microsoft with changes in its standard contractual terms and features in the product to mitigate some risks. Even so, many companies are holding off making any changes because the legal landscape is evolving. In this final part, we opine on what the future may hold. We can expect in the first half of this year that the European Commission will finalise the amended SCCs. We can anticipate that the EDPB will also produce another draft of its recommendations concerning data transfers. We should see plenty of risk assessments taking place. Even for companies adopting a “wait and see” policy in terms of taking significant steps, those companies should still be looking at their data transfers and carrying out risk assessments to make sure they are as well placed as possible for the moment when the draft SCCs and EDPB guidance are finalised.It would not be a surprise to see Microsoft continue to expand and develop M365 so that it offers yet more services that could be used as technical measures to reduce the risk around data transfers. These changes would strengthen the position of any company doing business between Europe and the US using M365.We do not have a crystal ball, and like many of you, are eager to see what happens next in this space. We will continue to monitor and keep you up to date with developments and our thoughts. If you have any questions in the meantime, feel free to reach out to us at info@lighthouseglobal.com.data-privacy; microsoft-365; information-governance; chat-and-collaboration-datamicrosoft, cloud, data-privacy, blog, law-firm, data-privacy, microsoft-365, information-governance, chat-and-collaboration-datamicrosoft; cloud; data-privacy; blog; law-firmlighthouse
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The Impact of Schrems II & Key Considerations for Companies Using M365: The Cloud Environment
In part one of this series, we described the state of the EU-US Privacy Shield and the mechanisms global companies have relied upon to transfer data from their multiple locations. In short, a recent decision – Schrems II – invalidated the Privacy Shield and shook the foundation of Standard Contractual Clauses (SCCs). Companies are now left asking the question of how to respond.In this post, we will share our view on how to navigate forward. If your organization is not already highly reliant on cloud software, we recommend weighing the benefits and risks of making that move. As you assess your options, keep in mind that this move may come at a higher cost because of the need to do periodic risk assessments during this uncertain time. For those already in the Cloud, the motto here is “do everything that you reasonably can.” The position no company wants to find itself in is one of stasis. It is difficult to see such a position being looked upon favourably should regulators start to investigate how companies are responding to Schrems II and the consequences that go along with it.The touchstone is the EDPB guidance and its six-stage approach to assessing data transfers, which we recommend companies undertake:Identify your data transfers: It is an obvious first step, although in practice this could prove challenging. You’ll need to know all the scenarios where your data is moved to a non-European Economic Area (EEA) country (at the time of writing this article, the UK, although out of Europe, is still under the European umbrella until at least the 30th of June).Identify the data transfer mechanisms: You need to decide the grounds upon which the transfer is taking place, such as on the basis of an adequacy decision (this does not apply to the US), SCCs, or a specific derogation (such as consent).Assess the law in the third country: You need to assess “if there is anything in the law or practice of the third country that may impinge on the effectiveness of the appropriate safeguards of the transfer tools you are relying on, in the context of your specific transfer.” There is more guidance from the EDPB as to how the evaluation should be carried out (i.e., an independent oversight mechanism should exist). How effective or practical it is to suggest each company has to perform its own thorough legal assessment as the entire range of relevant legislation in any importing country is open to debate and might perhaps be considered further as these recommendations are refined.Adopt supplementary measures if necessary to level up protection of data transfers: The EDPB has published a non-exhaustive list of such measures, which essentially fall into one of three categories - technical (i.e., encryption), contractual (i.e., transparency), and organisational (i.e., involvement of a Data Protection Officer on all transfers). We’ll have a look at these measures in more detail below in relation to Microsoft 365.Adopt necessary procedural steps: If you have made changes to deliver the required level of protection, these need to be embedded into your operation (i.e.., by means of policy).Re-evaluate at appropriate intervals: This is not a job that can be completed and then left. It needs continual monitoring. There is no specific guideline as to what an appropriate interval is, but quarterly is probably a reasonable approach.Essentially this boils down to carrying out a risk assessment and taking steps to mitigate the risks that are uncovered. If your cloud strategy includes Microsoft 365, the next part of this blog series is a must-read. We will share what Microsoft has done in response to Schrems II as well as some specific configuration options that will influence steps 4 and 5, listed above. Bear in mind that these recommendations could change and you should watch the space. To continue the discussion or to ask questions, please feel free to reach out to us at info@lighthouseglobal.com.data-privacy; microsoft-365; information-governancemicrosoft, cloud, data-privacy, blog, corporate-legal-ops, data-privacy, microsoft-365, information-governance,microsoft; cloud; data-privacy; blog; corporate-legal-opslighthouse
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The Fearless 5: Spotlighting 5 Women Who “Choose to Challenge” Gender Bias in the Legal and Tech Fields
The International Women’s Day (IWD) theme for 2021 is “choose to challenge.”What a fitting theme for a year when 5.4 million women lost their jobs and over 2.1 million women left the workforce, while the COVID-19 pandemic wreaked havoc, and social and racial inequity issues were raised to the forefront of the international consciousness. There was certainly no shortage of challenges for women to choose from this past year.However, the IWD initiative website elaborates on the “choose to challenge” theme by noting that “a challenged world is an alert world and from challenge comes change.” It is that idea that should really resonate with us, as we move past 2020 and into 2021. There have been many examples this year of women who have chosen to rise to the challenges presented in 2020 and by doing so, have created change for other women.In keeping with this theme, Lighthouse is featuring five such women in the legal and technology fields. Five women who have risen to the challenges presented this year and created change. Those five women are:Laura Ewing-Pearle, eDiscovery Project Manager at Baker Botts LLPJenya Moshkovich, Assistant General Counsel at GenentechGina M. Sansone, Counsel – Litigation Support at Axinn Veltrop & Harkrider LLPAmy Sellars, Director, Discovery Center of Excellence at Cardinal HealthRebecca Sipowicz, VP and Assistant General Counsel at Ocwen Financial CorporationWe had the honor of interviewing these inspirational women about the “choose to challenge theme” – including the stressors of 2020, how to empower other women, how to leverage innovation to shape a more gender-equal world, and how to address social justice issues. That discussion led to some powerful lessons on how to rise to our current challenges and create meaningful, lasting change.Empowering Women Durning a PandemicLike any societal change, empowering women starts small, at the individual level. We do not have to wait for some grand opportunity or postpone our effort until we have the time to volunteer – especially during a pandemic when our personal time may feel even more precious and many in-person volunteer opportunities have halted. Empowerment can happen by simply reaching out to the women around us – women we work with, women in our personal lives, and women within our own families.Laura Ewing-Pearle noted, “One principle to keep in mind is that women are not a monolithic bloc, and that empowering women usually means empowering the individual. A woman with twenty years’ experience in the legal world caring for aging parents has a different set of stressors and goals than a woman fresh out of school with a toddler, especially under the new Covid protocols…Seeing past “woman” to the individual brings us all closer to a more gender-equal world.”In our professional lives, empowering at the individual level can mean reaching out to our women co-workers, teammates, and those that may be on “lower rungs” of the corporate or law firm ladders and offering them a chance to sit down (virtually) for a cup of coffee to talk about their personal goals and challenges. This provides women a space to be heard and seen, first and foremost. It is from these conversations that the seeds of change are often planted.Rebecca Sipowicz stated, “During the summer I became responsible for co-oversight of our back-office team in India, which is approximately 25% female. For at least the past 10 years, the India team has not reported, directly or indirectly, to a woman. I have reached out on an individual level to these women to discuss their career goals and how we can work together to achieve them. I also started a monthly “catch-up” where, in this virtual environment, we can meet for 30 minutes to talk about work, life, and the state of the world. Through these conversations, I have not only gotten to know better my colleagues who are located off-shore but also have been able to share life experiences, such as how to take advantage of our remote work world while parenting and managing online school. The continued growth of this group of employees is one of my most important goals for 2021.”These conversations often help us learn not only about individual ambitions and challenges, but also may help us learn about unsung accomplishments and milestones that women often are less apt to tout about themselves within their own organizations and networks. In turn, this can provide an excellent opportunity to be a champion for those women, by calling out successes that would otherwise go unrecognized.Gina Sansone said, “I am a strong believer in being a vocal cheerleader for the women around me who may be less comfortable with promoting their strengths and accomplishments. Women often play multiple roles at work and at home that are not obvious to others and get overlooked because they tend to be less measurable in a traditional sense. These contributions are nonetheless valuable and crucial to an organization and the lives of others, and it’s really important to notice and appreciate them along the way.”Empowering at the individual level also means leading by example during these conversations. The stressors of the pandemic have changed our lives dramatically, both professionally and personally. It is unchartered territory for everyone, and studies are showing that women are shouldering the brunt of the burden at home – often juggling full-time virtual schooling with children while working full-time jobs or dealing with the bulk of household maintenance. Leading by example and being honest about ourselves and our own hurdles during our conversations can empower women to be honest about their own struggles and needs.Jenya Moshkovich stated, “[I empower other women by] being honest about my own challenges and creating and holding space for others to be their true, authentic selves with all the complexities and messiness that can bring. The line between our private lives and work is blurrier now than it has ever been and we have to let go of trying to pretend that we have it all together all the time because no one does, especially these days.”The example we set and the honesty with which we portray ourselves can especially be important for those closest to us – the people within our own families and homes.Rebecca Sipowicz mentioned, “…Having my children home from school for six months enabled my 11-year-old daughter to witness firsthand how involved my job is and to learn how difficult but rewarding it is to juggle parenting and a career. This is a valuable lesson for all children, not just girls.”Leveraging Innovation to Shape a More Gender Equal WorldIf the legal and technology industries have anything in common, it is that women have been historically under-represented in both spaces. Fortunately, technological innovation can help close the gender gap in both industries:Rebecca Sipowicz shared, “The pandemic really pushed all of corporate America to take steps that will help to advance gender equality in the workplace – namely the move from in-office to remote work. This unquestionably provides working mothers with more equal access to the workplace. Through the use of video software such as Zoom and Teams, and the ability to work around parenting responsibilities, fewer women should feel the pressure to leave the workforce in order to parent….This flexibility allows women to continue to contribute to the workforce and grow in their careers while caring for their families, without feeling like they are short-changing either side. This should enable women to continue to take on more prominent roles and push women throughout the world to request an equal seat at the table.”Technological innovation can also help people push their organizations and law firms to empower women and support equality. Many companies have seen how innovation and technology can help close the gender gap, and we can work within those systems to further those efforts.Gina Sansone said, “I really don’t know how we can begin to work toward a gender-equal world without leveraging innovation. To me, innovation means creating a dynamic work environment that encourages everyone to move forward, which could mean training and managing members of the same team differently. While consistency is important, recognizing differences, being flexible, and empowering people to think differently and not simply check a box are steps toward shaping a more gender-equal world.”Laura Ewing-Pearle added, “Encouraging and leveraging more on-line training certainly helps anybody juggling family and career to keep pace with new technology and change. I’m grateful that Baker Botts as a firm encourages everyone to create new, innovative ideas to improve business processes and culture.”Jenya Moshkovich mentioned, “I am very fortunate to work for a company that has started innovating in this space years ago and where I am in the position to benefit from these efforts. Since 2007, Genentech has more than doubled the percentage of female officers from 16 to 43% and today over half of our employees and over half of our directors are women. In our legal department, ALL of our VPs are women. Genentech’s efforts to move towards gender equality have included senior leadership commitments, programs to drive professional development and open up opportunities for career advancement, among others.”Going forward, it will be equally important to continue efforts to support changes in our industry. While we have come a long way and made considerable progress, it is still important to push companies and law firms to recognize equity gaps and encourage the use of innovation and technology to help close those gaps.Amy Sellars stated, “Corporate practices favor men, and Covid exacerbates this problem. Will companies acknowledge that women took on most of the additional burdens of children at home, education at home, of people at home all the time (more dishes, more cleaning, more cooking, less dry cleaning, and more laundry)?”Rebecca Sipowicz said, “It is up to all of us to make sure that the realization that flexibility can result in increased productivity and satisfaction continues long after the pandemic, allowing women (and men of course) to have the best of both worlds.”Addressing Social Justice and Equality Issues2020 was also a devastating year for people of color, as well as underrepresented and low-income communities. The tragic events throughout the year brought social inequality issues and systemic racism to the forefront of the conversation in many families, workplaces, and social circles. Many of the lessons learned in the fight for gender equality can also be applied to the fight for racial and social equality. For instance, just as empowering women can start at the individual level, the fight for social and racial equality can also start with small, individual acts.These acts can be as simple as personally working to educate ourselves on the work to be done, so that we can act on social justice issues in the most impactful way:Jenya Moshkovich said, “2020 was a difficult year in so many ways including the tragic deaths of George Floyd, Breonna Taylor, and Ahmaud Arbery and many incidents of xenophobic violence against Asian Americans. My personal focus has been on educating myself, speaking up for others, listening, and fostering belonging. And there is so much more that needs to be done.”Gina Sansone added, “The social issues raised in 2020 were unfortunately just a magnification of issues that have existed for a long time. It was a perfect storm of events that certainly made me and others face the thought patterns, inequalities, and general civil unrest that has been festering in our society. It is very easy to live in a bubble and lose sight. I think one of the most important things that happened was people stopped being quiet and just accepting. Change will not happen unless it is absolutely forced and we need to continue recognizing that the world is not equal.”Creating social justice change also can mean utilizing the education we do have about these issues, and working within our communities to help in any way possible – both at the individual level and on a broader scale:Amy Sellars stated, “My husband and I have always been passionate about voting rights and participate in get out the vote efforts. 2020 was a particularly important year for voting issues, as so many people were isolated and had even less access to register to vote or get to polls than normal. Working with the League of Women Voters, we did neighborhood registration drives, and we volunteered as non-partisan poll watchers. We also picked up Meals on Wheels shifts. All around the country, meal recipients who used to be fed at central locations were transitioned to home deliveries, and it has taken an army of volunteers in personal vehicles…We are also volunteering on the domestic crisis hotline.”We can also leverage the networks and programs put in place within forward-thinking organizations to help bring about social change. More and more law firms and organizations are working to help close the gender gap and fight racial and social inequity. Employees of those organizations are in a unique position to join those initiatives to make more of an impact:Laura Ewing-Pearle said, “While (Baker Botts) had resources in place prior to the events of last year, the firm has also increased efforts over the past twelve months to address social issues including greater outreach to diverse communities, and creating a significant pro bono partnership with Official Black Wall Street, among other major initiatives.”Rebecca Sipowicz added, “I am a member of the Ocwen Global Women’s Network (OGWN), which supports the attainment of Ocwen’s goals in diversity, inclusion, and talent development. I am also on the planning committee for the National Association of Women Lawyers (NAWL) mid-year meeting. NAWL’s mission is to empower women in the legal profession, while cultivating a diverse membership dedicated to equality, mutual support and collective success. Membership in and support of organizations such as NAWL and OGWN provide me with a platform to address the diversity and social issues that permeated 2020.”‍ConclusionThe lesson learned from these strong women during a year full of challenges is that seemingly “small” acts can have big impacts. Change starts with all of us, at an individual level, working to empower women and make impactful societal changes – one person, one organization, and one community at a time.Thank you to the five women who participated in our 2021 International Women's Day Campaign! Take a look at our 2020 and 2019 International Women's Day campaigns for more inspiring stories of women in our industry making bold moves to promote gender equality.For more information, please reach out to us at info@lighthouseglobal.com.diversity-equity-and-inclusionblog, diversity-equity-and-inclusion,bloglighthouse
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The Truth Behind Self-Service Pricing in eDiscovery
eDiscovery pricing has always been nuanced and inconsistent across vendors and technology providers, making it difficult for law firms and corporations alike to compare and contrast options. So, it is no big surprise that this same challenge exists across self-service, spectra eDiscovery tools and software as well, making it extremely challenging to model out an apples-to-apples comparison across solutions. This inability to accurately compare costs across different platforms leaves you and your team in the dark when it comes to choosing the right tool and pricing model to fit your needs.The ChallengeToday’s self-service, spectra solutions are frequently priced based on data sizes/volumes at different phases of the eDiscovery processing, review, and production workflow, often with each of these steps having their own cost trigger associated with them. For example, many solutions charge based off of hosted volume, raw data size, or even post-extraction data volume, while others charge a flat-fee per matter.Although attractive on their face, on a per matter plan you may be in good shape if you are able to entirely self-support, but any requests for help or training are frequently not included in the flat-fee. The lack of the ability to predict the future needs for support make the flat-fee a riskier choice. While paying for eDiscovery based off of per GB sizes is a very popular method, not knowing the expansion rates, the hosted volume, or not needing an entire data-set post culling and filtering means you may fall victim to data size anomalies or paying for data you don’t need.Lastly it is important that you make sure to understand the full ecosystem of potential charges to avoid any surprises. Make sure to understand if there are other costs or “gotchas” you need to be aware of around user fees, OCR costs, Bates endorsement fees, user trainings, additional license fees to other platforms, costs to process specific file types, language translation, etc. Not to mention, you also have to consider the various technology platforms that are included and assess the need for ongoing expert support.There is no perfect pricing model. The key to all of this is choosing the right model for you and your eDiscovery profile, but, how do you go about that?The SolutionWhen you are evaluating pricing for self-service, spectra platforms and you have narrowed down to a few technology providers that offer technology that fits your needs, make sure to leverage the following tips to ensure you’re making an informed comparison:Trust but verify. Ask the technology provider to explain the price point and both how and when it is measured. Discuss how the confluence of the eDiscovery workflow and cost actually come together. Will all workflows trigger all cost points? Do you have to pay for technology you don’t want or need? Understanding the answers to these questions will allow you to get a big picture understanding and to get a feel for where you may see your costs rise or decrease.Set up a real case example. Ask the potential providers to use your actual data volumes to illustrate what the cost would like look for a given period of time (i.e. a month or even a few years). This will allow you to see what actuals would be across platforms as well as give you the opportunity to explore different pricing models with the vendor to meet your budgetary constraints.Use a pricing calculator. Create a pricing calculator to compare self-service, spectra tools. Add as many variables as you would like to understand across all possible scenarios and across the different platforms you are evaluating. Leverage this to compare bottom-line numbers and determine the right fit for you. Additionally, lean on your vendor to help you build this out and make a comparison.To discuss this topic more or to learn how we can help you make an apples-to-apples comparison, feel free to reach out to me at bthompson@lighthouseglobal.com.ediscovery-reviewcloud, self-service, spectra, ediscovery-process, blog, ediscovery-review,cloud; self-service, spectra; ediscovery-process; blogbrooks thompson
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The Sinister Six…Challenges of Working with Large Data Sets
Collectively, we have sent an average of 306.4 billion emails each day in 2020. Add to that 23 billion text messages and other messaging apps, and you get roughly 41 million messages sent every minute[1]. Not surprisingly, there have been at least one or two articles written about expanding data volumes and the corresponding impact on discovery. I’ve also seen the occasional post discussing how the methods by which we communicate are changing and how “apps that weren’t built with discovery in mind” are now complicating our daily lives. I figured there is room for at least one more big data post. Here I’ll outline some of the specific challenges we’ll continue to face in our “new normal,” all while teasing what I’m sure will be a much more interesting post that gets into the solutions that will address these challenges.Without further delay, here are six challenges we face when working with large data sets and some insights into how we can address these through data re-use, AI, and big data analytics:Sensitive PII / SHI - The combination of expanding data volumes, data sources, and increasing regulation covering the transmission and production of sensitive personally identifiable information (PII) and sensitive health information (SHI) presents several unique challenges. Organizations must be able to quickly respond to Data Subject Access Requests (DSARs), which require that they be able to efficiently locate and identify data sources that contain this information. When responding to regulatory activity or producing in the course of litigation, the redaction of this content is often required. For example, DOJ second requests require the redaction of non-responsive sensitive PII and/or SHI prior to production. For years, we have relied on solutions based on Regular Expressions (RegEx) to identify this content. While useful, these solutions provide somewhat limited accuracy. With improvements in AI and big data analytics come new approaches to identifying sensitive content, both at the source and further downstream during the discovery process. These improvements will establish a foundation for increased accuracy, as well as the potential for proactively identifying sensitive information as opposed to looking for it reactively.Proprietary Information - As our society becomes more technologically enabled, we’re experiencing a proliferation of solutions that impact every part of our life. It seems everything nowadays is collecting data in some fashion with the promise of improving some quality of life aspect. This, combined with the expanding ways in which we communicate means that proprietary information, like source code, may be transmitted in a multitude of ways. Further, proprietary formulas, client contacts, customer lists, and other categories of trade secrets must be closely safeguarded. Just as we have to be vigilant in protecting sensitive personal and health information from inadvertent discloser, organizations need to protect their proprietary information as well. Some of the same techniques we’re going to see leveraged to combat the inadvertent disclosure of sensitive personal and health information can be leveraged to identify source code within document populations and ensure that it is handled and secured appropriately.Privilege - Every discovery effort is first aimed at identifying information relevant to the matter at hand, and second to ensure that no privileged information is inadvertently produced. That is… not new information. As we’ve seen the rise in predictive analytics, and, for those that have adopted it, a substantial rise in efficiency and positive impact on discovery costs, the identification of privileged content has remained largely an effort centered on search terms and manual review. This has started to change in recent years as solutions become available that promise a similar output to TAR-based responsiveness workflows. The challenge with privilege is that the identification process relies more heavily on “who” is communicating than “what” is being communicated. The primary TAR solutions on the market are text-based classification engines that focus on the substantive portion of conversations (i.e. the “what” portion of the above statement). Improvments in big data analytics mean we can evaluate document properties beyond text to ensure the “who” component is weighted appropriately in the predictive engine. This, combined with the potential for data re-use supported through big data solutions, promises to substantially increase our ability to accurately identify privileged, and not privileged, content.Responsiveness - Predictive coding and continuous active learning are going to be major innovations in the electronic discovery industry…would have been a catchy lead-in five years ago. They’re here, they have been here, and adoption continues to increase, yet it’s still not at the point where it should be, in my opinion. TAR-based solutions are amazing for their capacity to streamline review and to materially impact the manual effort required to parse data sets. Traditionally, however, existing solutions leverage a single algorithm that evaluates only the text of documents. Additionally, for the most part, we re-create the wheel on every matter. We create a new classifier, review documents, train the algorithm, rinse, and repeat. Inherent in this process is the requirement that we evaluate a broad data set - so even items that have a slim to no chance of being relevant are included as part of the process. But there’s more we can be doing on that front. Increases in AI and big data capabilities mean that we have access to more tools than we did five years ago. These solutions are foundational for enabling a world in which we continue to leverage learning from previous matters on each new future matter. Because we now have the ability to evaluate a document comprehensively, we can predict with high accuracy populations that should be subject to TAR-based workflows and those that should simply be sampled and set aside.Key Docs - Variations of the following phrase have been uttered time and again by numerous people (most often those paying discovery bills or allocating resources to the cause), “I’m going to spend a huge amount of time and money to parse through millions of documents to find the 10-20 that I need to make my case.” They’re not wrong. The challenge here is that what is deemed “key” or “hot” in one matter for an organization may not be similar to that which falls into the same category on another. Current TAR-based solutions that focus exclusively on text lay the foundation for honing in on key documents across engagements involving similar subject matter. Big data solutions, on the other hand, offer the capacity to learn over time and to develop classifiers, based on more than just text, that can be repurposed at the organizational and, potentially, industry level.Risk - Whether related to sensitive, proprietary, or privileged information, every discovery effort utilizes risk-mitigation strategies in some capacity. This, quite obviously, extends to source data with increasing emphasis on comprehensive records management, data loss prevention, and threat management strategies. Improvements in our ability to accurately identify and classify these categories during discovery can have a positive impact on left-side EDRM functional areas as well. Organizations are not only challenged with identifying this content through the course of discovery, but also in understanding where it resides at the source and ensuring that they have appropriate mechanisms to identify, collect and secure it. Advances in AI and big data analytics will enable more comprehensive discovery programs that leverage the identification of these data types downstream to improve upstream processes.As I alluded to above, these big data challenges can be addressed with the use of AI, analytics, data reuse, and more. Now that I have summarized some of the challenges many of you are already tasked with dealing with on a day-to-day basis, you can learn more about actual solutions to these challenges. Check out my colleague’s write up on how AI and analytics can help you gain a holistic view of your data.To discuss this topic more or to ask questions, feel free to reach out to me at NSchreiner@lighthouseglobal.com.[1] Metrics courtesy of Statistachat-and-collaboration-data; ai-and-analyticsprivilege, analytics, ai-big-data, data-re-use, phi, pii, blog, chat-and-collaboration-data, ai-and-analyticsprivilege; analytics; ai-big-data; data-re-use; phi; pii; blognick schreiner
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The Impact of Schrems II & Key Considerations for Companies Using M365: Microsoft’s Response
In our four-part blog series on Schrems II and its impacts, we have already given the state of data transfers in light of the Schrems II decision as well as some practical tips on how to conduct a risk assessment. In sum, the foundation upon which companies have transferred data overseas for the last half-decade was recently shaken. Companies are left with no good legal options for data transfer so, instead, they need to make calculated risk assessments based on business need and convenience versus compliance with an unknown and quickly changing legal landscape.For those companies who have chosen Microsoft as their cloud provider, Microsoft has taken additional steps to alleviate some of the risks. In addition, there are some specific supplementary measures companies can take in their Microsoft 365 (M365) environment to mitigate some risk. In this third part of our series, we will consider the position if you are analysing data transfers that take place using M365, Microsoft’s flagship software-as-a-service tool, which is in use by many entities operating within Europe.It is worth pointing out that Microsoft has responded quickly to the upheaval. The EDPB issued its supplementary measures on November 11th, 2020, and by November 19th, Microsoft issued a press release entitled “New Steps to Defend Your Data.” Microsoft explained it was strengthening the rights of its public sector and enterprise customers in relation to data by including an Additional Safeguards Addendum into standard contractual terms. That addendum would give contractual force to the new steps Microsoft laid out in terms of defending customers’ data, namely that Microsoft:will challenge every government request for public sector or enterprise data from any government where there is a lawful basis for doing so; andwill compensate a public-sector or enterprise-customer user if data is disclosed in response to a government request in violation of the GDPR.Microsoft pointed out that these commitments exceeded the EDPB’s recommendations (presumably referring to the contractual supplementary measures in the EDPB guidance). These changes have received a mixed response, but it is interesting to see that the data protection authorities within three of the German states (Baden -Württemberg, Bavaria, and Hesse) issued a joint opinion that this was a move in the right direction since it included significant improvements for the rights of European citizens and was a clear signal to other providers to follow suit.So at a macro level, Microsoft has taken very public steps. However, that does not remove the need to carry out the analysis set out by the EDPB or, in general, carry out a risk assessment to give you a thorough understanding of any risks associated with using M365. Here are some specific considerations to keep in mind:As to the first step of the EDPB recommendations, identifying your data transfers, it is our understanding that Microsoft will shortly be publishing more detailed data maps which will help.The Microsoft white paper on the necessary elements for monitoring, securing, and assessing cloud storage is a very helpful resource. An updated version of this is also expected shortly.As part of your assessment, you should review the Microsoft Online Services Data Protection Addendum, in particular, the Data Transfers and Location sections, and the amended terms arising from Microsoft’s recent press release.When carrying out your risk assessment or transfer impact assessment, you should consider carefully the extent to which M365 can be configured to reduce the amount of personal data leaving Europe. More specifically, there are six areas upon which you could focus: Multi-geo: With multi-geo, a company operating in Europe can choose to have its Exchange Online (i.e., email), its SharePoint Online, and its OneDrive for Business data stored, at rest, within Europe. Multi-geo reduces the amount of data that would be transferred to the US in comparison to having the geo (Microsoft’s word for the central hub where data is stored) within the US. This is probably the most significant step a company can take to reduce data transfers. Choosing whether or not to enable applications: Certain applications such as Sway, Microsoft’s newsletter application, will have their data stored in the US irrespective of whether a company chooses to have a multi-geo setup. A company might weigh the pros and cons of each application, which involves data being stored in the US, and decide that it could operate without that application.Configuration settings at an application level: There are many settings within M365 at an application level that will vary the amount of data being generated and processed. Assessing each application in turn and deciding the specific configuration within that application can make a significant difference to the amount of personal data being created, moved, or stored. For more details on how to evaluate this for the popular collaboration tool, Teams, you can review this write-up.Encryption: Explore encryption thoroughly and look to implement it, if practical, as an additional technical safeguard. There a number of good resources explaining how encryption operates and the options available to add additional encryption. Here is a good starting point for learning about Microsoft’s encryption options.Customer lockbox: If you configure M365 so that the number of data transfers is reduced to the bare minimum, one area where transfers might still be needed is when there is a need for remote access by Microsoft engineers to provide support. Customer lockbox allows you to give final and limited approval for such access, which you can do after carrying out a specific risk assessment.Audit logs: All significant events in M365 are audited so you should put in place a review of audit logs to support any risk assessments that you complete.It is also more than just good practice to put in place a retention policy within M365, it is essential to ensure that personal data is not being retained for longer than is necessary. Reducing the amount of personal data within an organisation reduces the risk of data breaches that could result in problems under the provisions of the GDPR. Microsoft is following the legal landscape closely so expect to see quick responses from them as things change. But what kinds of changes should companies expect and when? Read the final part of this blog series on what the future may hold.To discuss this topic further, please feel free to reach out to us at info@lighthouseglobal.com.data-privacy; microsoft-365; information-governancemicrosoft, cloud, data-privacy, blog, corporate-legal-ops, data-privacy, microsoft-365, information-governance,microsoft; cloud; data-privacy; blog; corporate-legal-opslighthouse
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The Disclosure Pilot Scheme Is Here to Stay: What That Means for Your Practice
On July 15, 2022, the mandatory Disclosure Pilot Scheme (PD51U) was officially approved and will operate on a permanent basis within the Business and Property Courts (BP&C) of England and Wales. Originally implemented in 2019 on a temporary pilot basis, it was extended twice and had been set to expire in December of 2022. Its approval means that on October 1, 2022, the pilot will end, and the scheme will officially be known as Practice Direction (PD) 57AD “Disclosure in the Business and Property Courts.”This approval is no surprise to those familiar with the modern disclosure process in the UK. PD51U was originally implemented to address the key issues associated with standard disclosure under Civil Procedure Rule (CPR) 31, such as unwieldly costs and the insurmountable scale of disclosure due to ever-growing corporate data volumes. As per UTB LLC v Sheffield United, the pilot was meant to effect a “culture change” in the reasonableness and proportionality of disclosure requests by streamlining the process in a variety of ways. One of the most notable is through the encouragement of leveraging technology (such as technology assisted review or TAR) and data analytics for document review—even going so far as to mandate the use of TAR in cases where the document count exceeds 50,000.Over the last two years, this push toward implementing more technology to streamline the disclosure process has proven to be a wise one. With a worldwide shift to cloud-based infrastructures and remote working, corporate data volumes have exploded and will only continue to grow. Therefore, the traditional means of disclosure review, wherein a team of reviewers looks at each electronic document one-by-one, is quickly becoming untenable. Utilising technology to streamline review is more imperative than ever and will only grow in importance as data volumes continue to balloon. What 57AD does not mean, however, is that solicitors faced with disclosure need to be data science or technology experts. It simply means that it will become increasingly important for solicitors who are not comfortable with disclosure technology to find a solid managed review partner that can help streamline the disclosure process with technology and meet Practice Direction 57AD requirements. Below are key attributes to look for when seeking such a partner.Look for a managed review partner with expertise on the Disclosure Review Document (DRD)The DRD is meant to facilitate an agreement between parties about what constitutes proportional disclosure, and how to achieve that goal in a cost-effective manner. To do so, it requires parties to identify the key issues of the case and then detail the method of disclosure for each issue, with five methods from which to choose.[1] Each method can have severe impacts on the cost of a matter, as well as the overall outcome of the case for clients. It is vital that someone with in-depth disclosure expertise is involved in the negotiation and completion of this document. Some managed review vendors may be able to provide staffing and project management when it comes to disclosure document review but will not have experts available and capable to provide advice on effective disclosure strategy, including DRD assistance. Without this expertise, a party may find itself agreeing to disclosure methods that significantly balloon budgets or even worse, result in harmful outcomes for clients. Look for a managed review partner who has developed strong defensible workflowsOne of the hallmarks of and impetuses for PD 51U (soon to be PD 57AD) was to streamline the disclosure process in the face of ever-growing and unprecedented data volumes. Understanding when and how to leverage technology to cull and prioritise data for review, as well as how to leverage TAR, is imperative. However, the technology and workflows can seem overwhelming, especially to those who don’t perform disclosure often. Thus, it is essential to find a managed review partner who has access to the best review technology and knows how to leverage that technology to achieve the best results in every type of matter. It is also important that that managed review partner has developed strong defensible workflows for data reduction that can be customised to meet the individual needs of each client.Look for a managed review partner who thinks outside of the traditional linear review approachWhile it may seem simpler to fall back on traditional approaches to the disclosure document review process (i.e., hiring many reviewers to read and categorize each document), it is important to remember that PD 57AD was enacted because that approach is quickly becoming too burdensome for parties. The traditional approach also opens parties up to risk, when reviewers cannot effectively review the volume of documents within the time frames required for disclosure. Today’s larger data volumes and more complicated data increase the risk that human reviewers will miss important documents that were required to be disclosed, or conversely, that they will disclose harmful or sensitive documents that should not have been disclosed. Forward-thinking managed review partners have anticipated this change and have invested in technology and human expertise that can defensibly minimise document volumes so that a discrete number of subject matter experts can look at prioritised categories of pertinent documents, maximizing the value of human review. In this way, a managed reviewer partner can help solicitors move away from an outdated approach to review, while streamlining the disclosure process, keeping litigation budgets in check, minimising risk, and achieving better outcomes. Look for a partner who will help prepare bespoke briefing documentation, right from the outsetWhen a matter needs to scale up quickly and on short notice, the painstaking process of adding new reviewers can explode budgets—not only because of the additional overhead, but also because of the churn and inefficiency created by inconsistent work product from inexperienced, new reviewers. A good managed review partner will prepare for and minimise this churn from the outset, by creating customised briefing documentation that enables new reviewers to roll onto matters seamlessly, without a heavy lift from the client or review manager. Documentation like term glossaries for niche cases (for example, medical inquiries) that are kept in a central repository will help case teams quickly scale up and onboard new reviewers at short notice, while minimizing the churn and risk often thought of as inevitable when adding new reviewers. Look for a partner who has developed ways to ensure quality work from review teamsInconsistent or incorrect decisions from review teams creates additional work, which can decimate budgets. Even when data volumes are culled to more manageable levels, inaccurate review work product can still open clients up to risk, especially when sensitive data is involved. Look for managed review partners who have systems in place to ensure the accuracy of the review team from the outset. For example, some managed review providers will rigorously “test” the work product of review teams, directly after training has finished. This testing process can ensure that each reviewer assigned to the team understands the subject matter and review process, and that from the start of the matter their work product aligns with the case team’s direction. This type of quality control, started at the reviewer selection process, can greatly reduce risk while keeping budgets under control. Look for a managed review partner who ensures value for money in terms of candidatesIn a traditional approach, first pass review for relevance, privilege, and issues are undertaken by UK-based paralegals, with proven experience in reviewing and redacting documents together with a law degree, LPC/GDL, or NALP certification. However, these reviewers can be expensive, and billed at exorbitant hourly rates. Forward-thinking managed review partners often have partnerships with reviewers who have been admitted to Bars outside of the UK, providing an added layer of experience offered at a reduced cost. This complies with the overall message of PD 57AD, in that it offers a reliable basis for costs which promotes the cost-effective and efficient conduct of disclosure. [1] Model A – No order for disclosure; Model B – Limited disclosure; Model C – Request-led, search-based disclosure; Model D – Narrow search-based disclosure (with or without narrative documents); Model E – Wide search-based disclosureediscovery-reviewreview, blog, ediscovery-review,review; blogjennifer cowman
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TAR Protocols 101: Avoiding Common TAR Process Issues
A recent conversation with a colleague in Lighthouse’s Focus Discovery team resonated with me – we got to chatting about TAR protocols and the evolution of TAR, analytics, and AI. It was only five years ago that people were skeptical of TAR technology and all the discussions revolved around understanding TAR and AI technology. That has shifted to needing to understand how to evaluate the process of your team or of opposing counsel’s production. Although an understanding of TAR technology can help in said task, it does not give you enough to evaluate items like the parity of types of sample documents, the impact of using production data versus one’s own data, and the type of seed documents. That discussion prompted me to grab one of our experts, Tobin Dietrich, to discuss the cliff notes of how one should evaluate a TAR protocol. It is not totally uncommon for lawyers to receive a technology assisted review methodology from producing counsel – especially in government matters but also in civil matters. In the vein of the typical law school course, this blog will teach you how to issue spot if one of those methodologies comes across your desk. Once you’ve spotted the issues, bringing in the experts is the right next step.Issue 1: Clear explanation of technology and process. If the party cannot name the TAR tool or algorithm they used, that is a sign there is an issue. Similarly, if they cannot clearly describe their analytics or AI process, this is a sign they do not understand what they did. Given that the technology was trained by this process, this lack of understanding is an indicator that the output may be flawed.Issue 2: Document selection – how and why. In the early days of TAR, training documents were selected fairly randomly. We have evolved to a place now where people are being choosy about what documents they use for training. This is generally a positive thing but does require you to think about what may be over or under represented in the opposing party’s choice of documents. More specifically, this comes up in 3 ways:Number of documents used for training. A TAR system needs to understand what responsive and non-responsive looks like so it needs to see many examples in each category to approach certainty on its categorization. When using too small a sample, e.g. 100 or 200 documents, this risks causing the TAR system to incorrectly categorize. Although a system can technically build a predictive model from a single document, it will only effectively locate documents that are very similar to the starting document. The reality of a typical document corpus is that it is not so uniform as to rely upon the single document predictive model.Types of seed documents. It is important to use a variety of documents in the training. The goal is to have the inputs represent the conceptual variety in the broader document corpus. Using another party’s production documents, for example, can be very misleading for the system as the vocabulary used by other parties is different, the people are different, and the concepts discussed are very different. This can then lead to incorrect categorization of documents. Production data, specifically, can also add confusion with the presence of Bates or confidentiality stamps. If the types of seed documents/training documents used do not mirror typical types of documents expected from the document corpus, you should be suspicious.Parity of seed document samples. Although you do not need anything approaching the perfect parity of responsive and non-responsive documents, it can be challenging to use 10x the number of non-responsive versus responsive documents. This kind of disparity can distort the TAR model. It can also exacerbate either of the above issues, number, or type of seed documents.Issue 3: How is performance measured? People throw around common TAR metrics like recall and precision without clarifying what they are referring to. You should always be able to tell what population of documents these statistics relate to. Also, don’t skip over precision. People often throw out recall as sufficient, but precision can provide important insight into the quality of model training as well.By starting with these three areas, you should be able to flag some of the more common issues in TAR processes and either avoid them or ask for them to be remedied. ai-and-analytics; ediscovery-reviewanalytics, ai-big-data, tar-predictive-coding, blog, ai-and-analytics, ediscovery-reviewanalytics; ai-big-data; tar-predictive-coding; bloglighthouse
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TAR 2.0 and the Case for More Widespread Use of TAR Workflows
Cut-off scores, seed sets, training rounds, confidence levels – to the inexperienced, technology assisted review (TAR) can sound like a foreign language and can seem just as daunting. Even for those legal professionals who have had experience utilizing the traditional TAR 1.0 model, the process may seem too rigid to be useful for anything other than dealing with large data volumes with pressing deadlines (such as HSR Second Requests). However, TAR 2.0 models are not limited by the inflexible workflow imposed by the traditional model and require less upfront time investment to realize substantial benefits. In fact, TAR 2.0 workflows can be extremely flexible and helpful for myriad smaller matters and non-traditional projects, including everything from an initial case assessment and key document review to internal investigations and compliance reviews.A Brief History of TARTo understand the various ways that TAR 2.0 can be leveraged, it will be helpful to understand the evolution of the TAR model, including typical objections and drawbacks. Frequently referred to as predictive coding, TAR 1.0 was the first iteration of these processes. It follows a more structured workflow and is what many people think of when they think of TAR. First, a small team of subject-matter experts must train the system by reviewing control and training sets, wherein they tag documents based on their experience with and knowledge of the matter. The control set provides an initial overall estimated richness metric and establishes the baseline against which the iterative training rounds are measured. Through the training rounds, the machine develops the classification model. Once the model reaches stability, scores are applied to all the documents based on the likelihood of being relevant, with higher scores indicating a higher likelihood of relevance. Using statistical measures, a cutoff point or score is determined and validated, above which the desired measure of relevant documents will be included. The remaining documents below that score are deemed not relevant and will not require any additional review.Although the TAR 1.0 process can ultimately result in a large reduction in the number of documents requiring review, some elements of the workflow can be substantial drawbacks for certain projects. The classification model is most effectively developed from accurate and consistent coding decisions throughout the training rounds, so the team of subject-matter experts conducting the review are typically experienced attorneys who know the case well. These attorneys will likely have to review and code at least a few thousand documents, which can be expensive and time consuming. This training must also be completed before other portions of the document review, such as privilege or issue coding, can begin. Furthermore, if more documents are added to the review set after the model reaches stability (think, a refresh collection or late identified custodian) the team will need to resume the training rounds to bring the model back to stability for these newly introduced documents. For these reasons, the traditional TAR 1.0 model is somewhat inflexible and suited best for matters where the data is available upfront and not expected to change over time (i.e. no rolling collections) so that the large number of documents being excised from the more costly document review portion of the project will offset the upfront effort expended training the model.TAR 2.0, also referred to as continuous active learning (CAL), is a newer workflow (although it has been around for a number of years now) that provides more flexibility in its processes. Using CAL, the machine also learns as the documents are being reviewed, however, the initial classification model can be built with just a handful of coded documents. This means the review can begin as soon as any data is loaded into the database, and can be done by a traditional document review team right from the outset (i.e. there is no highly specialized “training” period). As the documents are reviewed, the classification model is continuously updated as are the scores assigned to each document. Documents can be added to the dataset on a rolling basis without having to restart any portion of the project. The new documents are simply incorporated into the developing model. These differences make TAR 2.0 well suited for a wider variety of cases and workflows than the traditional TAR 1.0 model.TAR 2.0 Workflow ExamplesOne of the most common TAR 2.0 workflows is a “prioritization review,” wherein the highest scoring documents are pushed to the front of the review. As the documents are reviewed the model is updated and the documents are rescored. This continuous loop allows for the most up-to-date model to identify what documents should be reviewed next, making for an efficient review process, with several benefits. The team will review the most likely relevant, and perhaps important, documents first. This can be especially helpful when there are short timeframes within which to begin producing documents. While all documents can certainly be reviewed, this workflow also provides the means to establish a cutoff point (similar to TAR 1.0) where no further review is necessary. In many cases, when the review reaches a point where few relevant documents are found, especially in comparison to the number of documents being reviewed, this point of diminishing returns signals the opportunity to cease further review. The prioritization review can also be very effective with incoming productions, allowing the system to identify the most relevant or useful documents.An alternative TAR 2.0 workflow is the “coverage” or “diverse” review model. In this model, rather than reviewing the highest scoring documents first, the review team focuses on the middle-scoring range documents. The point of a diverse review model is to focus on what the machine doesn’t know yet. Reviewing the middle range of documents further trains the system. In this way, a coverage TAR 2.0 review model provides the team with a wide variety of documents within the dataset. When using this workflow for reviews for productions, the goal is to end up with the documents separated between those likely relevant and those likely not relevant. This workflow is similar to the TAR 1.0 workflow as the desired outcome is to identify the relevant document set as quickly or directly as possible without reviewing all of the documents. To illustrate, a model will typically begin with a bell-shaped curve of the distribution of documents across the scoring spectrum. This workflow seeks to end with two distinct sets, where one is the relevant set and the other is the non-relevant set.These workflows can be extremely useful for initial case assessments, compliance reviews, and internal investigations, where the end goal of the review is not to quickly find and produce every relevant document. Rather, the review in these types of cases is focused on gathering as much relevant information as possible or finding a story within the dataset. Thus, these types of reviews are generally more fluid and can change significantly as the review team finds more information within the data. New information found by the review team may lead to more data collections or a change in custodians, which can significantly change the dataset over time (something TAR 2.0 can handle but TAR 1.0 cannot). And because the machine provides updated scoring as the team investigates and codes more documents, it can even provide the team with new investigational avenues and leads. A TAR 2.0 workflow works well because it gives the review team the freedom to investigate and gain knowledge about a wide variety of issues within the documents, while still ultimately resulting in data reduction.ConclusionThe above workflow examples illustrate that TAR does not have to be the rigid, complicated, and daunting workflow feared by many. Rather, TAR can be a highly adaptable and simple way to gain efficiency, improve end results, and certainly to reduce the volume of documents reviewed across a variety of use cases.It is my hope that I have at least piqued your interest in the TAR 2.0 workflow enough that you’ll think about how it might be beneficial to you when the next document review project lands on your desk.If you’re interested in discussing the topic further, please freely reach out to me at DBruno@lighthouseglobal.com.ai-and-analytics; ediscovery-reviewtar-predictive-coding, blog, ai-and-analytics, ediscovery-reviewtar-predictive-coding; blogdavid bruno
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Self-Service eDiscovery for Corporations: Three Tips for a Successful Implementation
Given the proliferation of data and evolving variety of data sources, in-house counsel teams are beginning to exhaust resources managing increasingly complex case data. self-service, spectra eDiscovery legal technology offers a compelling solution. Consider the impact of inefficiencies faced by in-house counsel, today - from waiting for vendors to load data or provide platform access, to scrambling, to keeping up with advancing technologies, and managing data security risks - it’s a lot. The average in-house counsel team isn’t just dealing with these inefficiencies on large litigations, they’re encountering these issues in even the smallest compliance and internal investigations matters.self-service, spectra solutions offer an opportunity to streamline eDiscovery programs, allowing in-house legal teams to get back to the business of case management and legal counseling. It’s understandable we’re witnessing more and more companies moving to this model.So, once your organization has decided it is ready to step into the future and take advantage of the benefits self-service, spectra eDiscovery solutions have to offer, what’s next? Below, I’ve outlined three best practices for implementing a self-service, spectra eDiscovery solution within your organization. While any organizational change can seem daunting at the outset, keeping the below tips in mind will help your company seamlessly move to a self-service, spectra model.1. Define how you leverage your self-service, spectra eDiscovery solution to scale with ease.One of the key benefits of a quality self-service, spectra solution is that it puts your organization back in the eDiscovery driver’s seat. You decide what cases you will handle internally, with the advantage of having access to an array of eDiscovery expertise and matter management services when needed, even if that need arises in the middle of an ongoing matter. Cloud-based self-service, spectra solutions can readily handle any amount of data, and a quality self-service, spectra solution provider will be able to seamlessly scale up from self-service, spectra to full-service without any interruption to case teams.Having a plan in place regarding how and when you will leverage each of these benefits (i.e. self-service, spectra vs. full-service) will help you manage internal resources and implement a pricing model that fits your organization’s needs.2. Select a pricing model that works for your organization.Every organization’s eDiscovery business is different and self-service, spectra pricing models should reflect that. After determining how your organization will ideally leverage a self-service, spectra platform, decide what pricing model works best for that type of utilization. self-service, spectra solution providers should be able to provide a variety of licensing options to choose from, from an a la cart approach to subscription and transaction models.Prior to communicating with your potential solution provider, define how you plan to leverage a self-service, spectra solution to meet your needs. Then you can consider the type of support you require to balance your caseload with team resources and prepare to talk to providers about whether they can accommodate that pricing. Once you have on-boarded a self-service, spectra solution, be sure to continue to evaluate your pricing model, as the way you use the solution may change over time.3. Discuss moving to a self-service, spectra model with your IT and data security teams .Another benefit of moving to a self-service, spectra model is eliminating the burden of application and infrastructure management. Your in-house teams will be able to move from maintaining (and paying for) a myriad of eDiscovery technologies to a single platform providing all of the capabilities you need without the IT overhead. In effect, moving to a self-service, spectra solution gives your team access to industry-leading eDiscovery technology while removing the cost and hassle of licensing and infrastructure upkeep.A self-service, spectra model also allows you to transfer some of your organization’s data security risk to a solution provider. You gain peace of mind knowing your eDiscovery data and the supporting tech is administered by a dedicated IT and security team in a state-of-the-art IT environment with best-in-class security certifications.Finally, to ensure your organization can realize the full benefit of moving to a self-service, spectra solution, it’s imperative that your IT team has a seat at the table when selecting a solution platform. They can help to ensure that whatever service is selected can be fully and seamlessly integrated into your organization’s systems. Keeping these tips in mind as your organization begins its self-service, spectra journey will help you realize the benefits that a quality self-service, spectra eDiscovery platform can provide. For more in-depth guidance on migrating to self-service, spectra platforms, Brooks Thompson’s blog posts discussing tips for overcoming self-service, spectra objections and building a self-service, spectra business case.ediscovery-review; ai-and-analyticsself-service, spectra, blog, ediscovery-review, ai-and-analyticsself-service, spectra; bloglighthouse
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Self-Service eDiscovery: Who’s Really in Control of Your Data?
self-service, spectra as a topic has grown significantly in the recent past. With data proliferating at astronomical amounts year over year it makes sense that corporations and firms are wanting increasing control over this process and its cost. Utilizing a self-service, spectra eDiscovery tool is helpful if you want control over your queue as well as your hosted footprint. It is beneficial if your team has an interest and the capability of doing your own ECA. Additionally, self-service, spectra options are useful as they provide insight into specific reporting that you may or may not be currently receiving.Initially, the self-service, spectra model was introduced to serve part of the market that didn’t require such robust, traditional full eDiscovery services for every matter. Tech-savvy corporations and firms with smaller matters were delighted to have the option to do the work themselves. Over time there have been multiple instances in which a small matter scales unexpectedly and must be dealt with quickly, in an all hands on deck approach, to meet the necessary deadlines. In these instances, it’s beneficial to have the ability to utilize a full-service team. When these situations arise it’s critical to have clean handoffs and ensure a database will transfer well.Moreover, we have seen major strides in the self-service, spectra space regarding the capabilities of data size thresholds. self-service, spectra options can now handle multiple terabytes, so it’s not just a “small matter” solution anymore. This gives internal teams incredible leverage and accessibility not previously experienced.self-service, spectra considerations and recommendationsIt’s important to understand the instances in which a company should utilize a self-service, spectra model or solution. Thus, I recommend laying out a protocol. Put a process in place ahead of time so that the next small internal investigation that gets too large too quickly has an action plan that gets to the best solution fast. Before doing this, it’s important to understand your team’s capabilities. How many people are on your team? What are their roles? Where are their strengths? What is their collective bandwidth? Are you staffed for 24/7 support or second requests or are you not?Next, it’s time to evaluate what part of the process is most beneficial to outsource. Who do you call for any eDiscovery related need? Do you have a current service provider? If so, are they doing a good job? Are they giving you a one-size-fits-all solution (small or large), or are they meeting you where you are and acting as a true partner? Are they going the extra mile to customize that process for you? It’s important to continually audit service providers.Think back to past examples. How prepared has your team and/or service provider been in various scenarios? For instance, if an investigation is turning into a government investigation, do you want your team pushing the buttons and becoming an expert witness, or do you have a neutral third party to hand that responsibility off to?After the evaluation portion, it’s time to memorialize the process through a playbook, so that everyone has clear guidelines regardless of which litigator or paralegal internally is working on the case. What could sometimes be a complicated situation can be broken down into simple rules. If you have a current protocol or playbook, ensure your team understands it. Outline various circumstances when the team would utilize self service or full service, so everyone is on the same page.For more on this topic, check out the interview on the Law & Candor podcast on scaling your eDiscovery program from self service to full service. ediscovery-reviewcloud, self-service, spectra, cloud-services, blog, ediscovery-review,cloud; self-service, spectra; cloud-services; bloglighthouse
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Sitting at the Same Lunch Table: 3 Key Ways to Ensure Legal and IT are in Sync
Legal and IT teams do not necessarily sit at the same lunch table (to use an over-simplified high-school analogy), however, organizations can quickly run into challenges when these teams are not aligned. As corporate data volume and types continue to grow at record speed, it is critical to maintain a technology infrastructure that is not only secure, but also satisfies the legal requirements for managing information. I recently had the privilege of chatting with Craig Shaver, the eDiscovery Program Director at Hilton Worldwide, about the challenges of this electronic data mosaic and innovative strategies to enable collaboration between these groups on the Law and Candor podcast. In this blog, I will review the key challenges we discussed as well as summarize three key solutions to overcoming them in the hopes it will help align your IT and legal teams.To level set, both teams have different priorities. Legal is generally focused on ensuring that the company’s data is protected and retention policies are upheld, while IT is looking for new ways to manage the ever-increasing volume of data to drive efficiency while maintaining budgets. So, when IT moves forward with new technology solutions, large data migrations, moves to the Cloud, or even simple contractual agreements and is not in sync with Legal due to other priorities or lack of communication, items may be missed and can create large downstream issues such as potentially responsive documents going uncollected, being slapped with spoliation charges, or costly and time-consuming rework.Nobody wants unforeseen charges or to loose time and money, so let’s look at some solutions to overcoming these challenges by ensuring collaboration between these two teams. Begin by:Establishing Legal Processes and Policies – Legal needs to first ensure they have effective legal hold processes in place, clear and consistent policies on data retention, as well as defensible deletion policies. Without these in place there is no formal process.Ensuring Participation on Both Sides – It is important to identify and designate a legal and IT liaison to sit on various steering committees and be a part of any technology decisions, migration projects, etc. In some larger, global organizations, you may want at least two or three people from each group involved to attend these meetings, as it can be a lot of work and require travel. Legal will understand the impact on the overall eDiscovery process and can review service-level agreements and SOWs as well.Continuing the Ongoing Partnership and Communication – Post project, it is important to continue to meet regularly (weekly or monthly) with key stakeholders to continue to communicate around upcoming migrations, technology changes, etc., as well as build trust and a further develop relationships. Legal can help IT enforce their deployment and security policies with other departments within the company as well as ensure GDPR compliance and other factors are considered when looking at new products.Enacting these three solutions will help you ensure your teams stay in sync. When legal and IT sit at the same lunch table and stay in communication, organizations are more likely to experience seamless or near-seamless integration of processes, better understand project timelines, reduce friction between very busy teams, maintain a shared understanding each other’s workloads and processes, as well as gain trust amongst the teams, which helps with future projects and getting folks to support one another.To discuss this topic more, reach out to me at bmariano@lighthouseglobal.com.legal-operations; information-governance; data-privacygdpr, ediscovery-process, blog, legal-operations, information-governance, data-privacy,gdpr; ediscovery-process; blogbill mariano
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Overcoming eDiscovery Trepidation - Part I: The Challenge
In this two-part series, I interview Gordon J. Calhoun, Esq. of Lewis Brisbois Bisgaard & Smith LLP about his thoughts on the state of eDiscovery within law firms today, including lessons learned and best practices to help attorneys overcome their trepidation of electronic discovery and build a better litigation practice. This first blog focuses on the history of eDiscovery and the logical reasons that attorneys may still try to avoid it, often to the detriment of their clients and their overall practice. IntroductionThe term “eDiscovery” (i.e., electronic discovery) was coined circa 2000 and received significant consideration by The Sedona Conference and others, well in advance of November 2006. That’s when the U.S. Supreme Court amended the Federal Rules of Civil Procedure to include electronically stored information (ESI), which was widely recognized as categorically different from data printed on paper. The amendments specifically mandated that electronic communications (like email and chat) would have been preserved in anticipation of litigation and produced when relevant. In doing so, it codified concepts explored by Judge Shira Scheindlin’s groundbreaking Zubulake v. UBS Warburg decisions.By 2012, the exploding volumes of data led technologists assisting attorneys to employ various forms of artificial intelligence (AI) to allow analysis of data to be accomplished in blocks of time that were still affordable to litigants. The use of predictive coding and other forms of technology-assisted review (TAR) of ESI became recognized in U.S. courts. By 2013 updates to the American Bar Association (ABA) Model Rules of Professional Conduct officially required attorneys to stay current on “the benefits and risks” of developing technologies. By 2015, the FRCP was amended again to help limit eDiscovery scope to what is relevant to the claims and defenses asserted by the parties and “proportional to the needs of the case,” as well as to normalize judicial treatments of spoliation and related sanctions associated with ESI evidence. In the same year, California issued a formal ethics opinion obligating attorneys practicing in California to stay current with ever changing eDiscovery technologies and workflows in order to comply with their ethical obligation of competently providing legal services.In the 15 years that have passed since those first FRCP amendments designed to deal with the unique characteristics of ESI, we’ve seen revolutionary changes in the way people communicate electronically within organizations, as well as explosive growth in the volume and variety of data types as we have entered the era of Big Data. From the rise of email, social media, and chat as dominant forms of interpersonal communication, to organizations moving their data to the Cloud, to an explosion of ever-changing new data sources (smart devices, iPhones, collaboration tools, etc.) – the volume and variety of which makes understanding eDiscovery’s role in litigation more important than ever.And yet, despite more than 20 years of exposure, the challenges of eDiscovery (including managing new data forms, understanding eDiscovery technology, and adhering to federal and state eDiscovery standards) continue to generate angst for most practitioners.So why, in 2021, are smart, sophisticated lawyers still uncomfortable addressing eDiscovery demands and responding to them? To find out, I went to one of the leading experts in eDiscovery today, Gordon J. Calhoun, Esq. of Lewis Brisbois Bisgaard & Smith LLP. Mr. Calhoun has over 40 years of experience in litigation and counseling, and he currently serves as Chair of the firm’s Electronic Discovery, Information Management & Compliance Practice. Over the years he has found creative solutions to eDiscovery challenges, like having a court enter a case management order requiring all 42 parties in a complex construction defect case to use a single technology provider, which dropped the technology costs to less than 2.5% of what they would have been had each party employed its own vendor. In another case (which did not involve privileged communications), he was able to use predictive coding to rank 600,000 documents and place them into tranches from which samples were drawn to determine which tranches could be produced without further review. It was ultimately determined that about 35,000 documents would not have to be reviewed after having put eyes on fewer than 10,000 of the original 600,000.I sat down with Mr. Calhoun to discuss his practice, his views of the legal and eDiscovery industries, and to try to get to the bottom of how attorneys can master the challenges posed by eDiscovery without having to devote the time needed to become an expert in the field.Let’s get right down to it. With all the helpful eDiscovery technology that has evolved in the market over the last 10 years, why do you think eDiscovery still poses such a challenge for attorneys today? Well, right off the bat, I think you’re missing the mark a bit by focusing your inquiry solely around eDiscovery technology. The issue for many attorneys facing an eDiscovery challenge today is not “what is the best eDiscovery technology?” – because many attorneys don’t believe any eDiscovery technology is the best “solution.” Many believe it is the problem. No technology, regardless of its efficacy, can provides value if it is not used. The issue is more fundamental. It’s not about the technology, it is about the fear of the technology, the fear of not being able to use it as effectively as competitors, and the fear of incurring unnecessary costs while blowing budgets and alienating clients.Practitioners fear eDiscovery will become a time and money drain, and attorneys fear that those issues can ultimately cost them clients. Technology may, in fact, be able to solve many of their problems – but most attorneys are not living and breathing eDiscovery on a day-to-day basis (and, frankly, don’t want to). For a variety of reasons, most attorneys don’t or can’t make time to research and learn about new technologies even when they’re faced with a discovery challenge. Even attorneys who do have the inclination and aptitude to deal with the mathematics and statistical requirements of a well-planned workflow, who understand how databases work, and who are unfazed by algorithms and other forms of AI, often don’t make the time to evaluate new technology because their plates are already full providing other services needed by their clients. And most attorneys became lawyers because they had little interest in mathematics, statistics, and other sciences, so they don’t believe they have the aptitude necessary to deal with eDiscovery (which isn’t really true). This means that when they’re facing gigabytes or even terabytes of data that have to be analyzed in a matter of weeks, they often panic. Many lawyers look for a way to make the problem go away. Sometimes they agree with opposing counsel not to exchange electronic data; other times they try to bury the problem with a settlement. Neither approach serves the client, who is entitled to an expeditious, cost effective, and just resolution of the litigation. Can you talk more about the service clients are entitled to, from an eDiscovery perspective? By that, I mean – can you explain the legal rules, regulations, and obligations that are implicated by eDiscovery, and how those may impact an attorney facing an electronic discovery request? Sure. Under Rule 1 of the FRCP and the laws of most, if not all, states, clients are entitled to a just resolution of the litigation. And ignoring most of the electronic evidence about a dispute because a lawyer finds dealing with it to be problematic rarely affords a client a just result. In many cases, the price the client pays for counsel’s ignorance is a surcharge to terminate the litigation. And, counsel’s desire to avoid the challenge of eDiscovery very often amounts to a breach of the ethical duty to provide competent legal services.The ABA Model Rules (as well as the ethical rules and opinions in the majority of states) also address the issue. The Model Rules offer a practitioner three alternatives when undertaking to represent a client in a case that involves ESI (which almost every case does). To meet his or her ethical obligation to provide competent legal services, the practitioner can: (1) become an expert in eDiscovery matters; (2) team up with an attorney or consultant who has the expertise; or (3) decline the engagement. Because comparatively few attorneys have the aptitude to become eDiscovery experts and no one who wants to practice law can do so by turning down virtually all potential engagements, the only practical solution for most practitioners is finding an eDiscovery buddy.In the end, I think attorneys are just looking for ways to make their lives (and thereby their clients’ lives) easier and they see eDiscovery as threatening to make their lives much harder. Fortunately, that doesn’t have to be the case.So, it sounds like you’re saying that despite the fact that it may cost them clients, there are sophisticated attorneys out there that are still eschewing legal technology and responding to discovery requests the way they did when most discovery requests involved paper documents? Absolutely there are. And I can empathize with their thought process, which is usually something along the lines of “I don’t understand eDiscovery technology and I’m facing a tight discovery deadline. I do know how to create PDFs from scanned copies of paper documents and redact them, if necessary. I’m just going to use the method I know and trust.” While this is an understandable way to think, it will immediately impose on clients the cost of inefficient litigation and settlements or judgments that could have been reduced or avoided if only the evidence had been gathered. Ultimately, when the clients recognize that their counsel’s fear of eDiscovery is imposing a cost on them, that attorney will lose the client. In other words, counsel who refuse to delve into ESI because it is hard is similar to a person who lost car keys in a dark alley but insists on only looking under the streetlight because it is easier and safer than looking in the dark alley.That’s such a great analogy. Do you have any real-world examples that may help folks understand the plight of an attorney who is basically trying to ignore ESI?Sure. Here’s a great example: Years ago, my good friend and partner told me he would retire without ever having to learn about eDiscovery. My partner is a very successful attorney with a great aptitude for putting clients at ease. But about a week after expressing that thought, he came to me with 13 five-inch three-ring binders. He wanted help finding contract paralegals or attorneys to prepare a privilege log listing all the documents in the binders. An arbitrator had ordered that if he did not have a privilege log done in a week, his expert would not be able to testify. His “solution” was to rent or buy a bunch of dictating machines and have the reviewers dictate the information about the documents and pay word processers overtime to transcribe the dictation into a privilege log. I asked what was in the binders. Every document was an email thread and many had families. My partner had received the data as a load file, but he had the duplications department print the contents rather than put them into a review platform. Fortunately, the CD on which the data was delivered was still in the file.I can tell this story now because he has since turned into quite the eDiscovery evangelist, but that is exactly the type of situation I’m referring to: smart, sophisticated attorneys who are just trying to meet a deadline and stay within budget will do whatever takes to get the documents or other deliverable (e.g., a privilege log) out the door. And without the proper training, unfortunately, the solution is to throw more bodies at the problem – which invariably ends up being more costly than using technology properly.Can you dive a bit deeper there? Explain how performing discovery the old-fashioned way on a small case like that would cost more money than performing it via a dedicated eDiscovery technology.Well, let me finish my story and then we’ll compare the cost of using 20th and 21st Century technologies to accomplish the same task. As I said, when I agreed to help my partner meet his deadline, I discovered all the notebooks were filled with printed copies of email threads and attachments. My partner received a load file with fewer than 2 GBs and gave it to the duplications department with instructions to print the data so he could read it. We gave the disk to an eDiscovery provider, and they created a spreadsheet using the email header metadata to populate the log information about who the record was from, who it was to, who was copied, whether in the clear or blind, when it was created, what subject was addressed, etc. A column was added for the privilege(s) associated with the documents. Those before a certain date were attorney-client only. Those after litigation became foreseeable were attorney-client and work product. That made populating the privilege column a snap once the documents were chronologically arranged. The cost to generate the spreadsheet was a few hundred dollars. Three in-house paralegals were able to QC, proofread, and finalize the log in less than three days for a cost of about $2,000.Had we done it the old-fashioned way, my partner was looking at having 25 or 30 people dictating for five days. If the reviewers were all outsourced, the cost would have been $12,000 to $15,000. He planned to use a mix of in-house and contract personnel - so, the cost would have been 30% to 50% higher. The transcription process would have added another $10,000. The cost of copying the resulting privilege log that would have been about 500 pages long with 10 entries per page for the four parties and arbitrator would have been about $300. So even 10 years ago, the cost of doing things the old-fashioned way would have been about $35,000. The technology-assisted solution was about $2,500. Stay tuned for the second blog in this series, where we delve deeper into how attorneys can save their clients money, achieve better outcomes, and gain more repeat business once they overcome common misconceptions around eDiscovery technology and costs. If you would like to discuss this topic further, please reach out to Casey at cvanveen@lighthouseglobal.com and Gordon at Gordon.Calhoun@lewisbrisbois.com.ediscovery-review; ai-and-analyticsediscovery-process, blog, spectra, law-firm, ediscovery-review, ai-and-analyticsediscovery-process; blog; spectra; law-firmcasey van veen
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Self-Service eDiscovery: Top 3 Technical Pitfalls to Avoid
Whether it’s called DIY eDiscovery, SaaS eDiscovery, or self-service, spectra eDiscovery, one thing is clear—everyone in the legal world is interested in putting today’s technologies to work for them to get more done with less. It’s a smart move, given that many legal teams are facing an imbalance between needs and resources. As in-house legal budgets are being slashed, actual workloads are increasing.Now more than ever, legal teams need to ensure they’re choosing and using the right tools to effectively manage dynamic caseloads—a future-ready solution capable of supporting a broad range of case types at scale. Given the variety of options on the market, it’s understandable there’s some uncertainty about what to pursue, let alone what to avoid. Below, I have outlined guidance to help your legal team navigate the top three potential pitfalls encountered when seeking a self-service, spectra eDiscovery solution.1. Easy vs. PowerfulThere are a lot of eDiscovery solutions out there making bold promises, but many still force users to choose between ease of use and full functionality. While a platform may be simple to learn and navigate, it may fail to offer advanced features like AI-driven analysis and search, for example.Think of it like the early days of cell phones, when we were forced to choose between a classic brick-style device or a new-to-market smartphone. Older phones were easy to use, offering familiar capabilities like calling and text exchange, while newer smartphones provided impressive, previously unknown functionalities but came with a learning curve. With the advancement of technology, today’s device buyers can truly have it all at hand—a feature-rich mobile phone delivered in an intuitive user experience.The same is true for dynamic eDiscovery solutions. You shouldn’t have to choose between power and simplicity. Any solution your team considers should be capable of delivering best-in-class technology over one simple, single-pane interface.2. Short-Term Thinking vs. Long-Term Gains As organizations move to the seemingly unlimited data storage capacities of cloud-based platforms and tools, legal teams are facing a landslide of data. Even the smallest internal investigation may now involve hundreds of thousands of documents. And with remote working being the new global norm, this trend will only continue to grow. Legal teams require eDiscovery tools that are capable of scaling to meet any data demand at every stage of the eDiscovery process.When evaluating an eDiscovery solution, keep the future in mind. The solution you select should be capable of managing even the most complex case using AI and advanced analytics—intelligent functionality that will allow your team to efficiently cull data and gain insights across a wide variety of cases. Newer AI technology can aggregate data collected in the past and analyze its use and coding in previous matters—information that can help your team make data-driven decisions about which custodians and data sources contain relevant information before collection. It also offers the ability to re-use past attorney work product, allowing you to save valuable time by immediately identifying junk data, attorney-client privilege, and other sensitive information.3. Innovation vs. UpkeepThanks to the DIY eDiscovery revolution, your organization no longer has to devote budget and IT resources to upkeeping a myriad of hardware and software licenses or building a data security program to support that technology. Seek a trusted solution provider that can take on that burden with development and security programs (with the requisite certifications and attestations to prove it). This should include routine technology assessment and testing, as well as using an approach that doesn’t disrupt your ongoing work.As you’re asked to do more with less, the right cloud-based eDiscovery platform can ensure your team is able to meet the challenge. By avoiding the above pitfalls, you’ll end up with a solution that’s able to stand up against today’s most complex caseloads, with powerful features designed to improve workflow efficiency, provide valuable insights, and support more effective eDiscovery outcomes.If you’re interested in moving to a DIY eDiscovery solution, check out my previous blog series on self-service, spectra eDiscovery for corporations, including how to select a self-service, spectra eDiscovery platform, tips for self-service, spectra eDiscovery implementation, and how self-service, spectra eDiscovery can make in-house counsel life easier. ediscovery-review; ai-and-analyticsself-service, spectra, ediscovery-process, corporation, prism, blog, spectra, corporate, ediscovery-review, ai-and-analyticsself-service, spectra; ediscovery-process; corporation; prism; blog; spectra; corporatelighthouse
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Rethinking the EDRM for Today’s Evolving eDiscovery Data Landscape
The approach of a new year is often a good time to step back and take stock of the eDiscovery industry, so that we can be better prepared to move forward. One of the most dramatic changes over the past few years has been the seismic shift across the legal and corporate data landscapes. That shift has slowly been expanding the concept of eDiscovery beyond a single-litigation focus, to encompass data governance, data privacy and security, and an overall more holistic, strategic approach to review and analysis.As we prepare to move forward in this brave new world, it’s important to understand how those industry changes affect the traditional framework of the eDiscovery process: the Electronic Discovery Reference Model (EDRM). Recently, I was lucky enough to join a panel of industry experts, including Microsoft’s EJ Bastien, TracyAnn Eggen from CommonSpirit Health, and Lighthouse’s Sarah Barsky-Harlan, to dive deeper into that specific issue. Together, we tackled questions like: Does the EDRM still apply in today’s more complex eDiscovery environment? If so, how is the evolving data and eDiscovery landscape reshaping how organizations and law firms think about the EDRM? How can the EDRM be used to meet today’s more complex communication, data, and business challenges?Below are some of the key themes and ideas that emanated from that discussion: A Brave New Data World: Dynamic Changes in eDiscoverySince its inception, the EDRM has been the industry’s standard approach to the eDiscovery process (i.e., identification, collection, processing, review, analysis, and production of electronically stored information (ESI)). However, what we’re seeing today is that organizations and law firms now must think about eDiscovery in much broader terms than that traditionally very linear method. There are three primary reasons for this change:New cloud-based and Software as a Service (SaaS) systems: Enterprise systems are not nearly as controlled by the underlying organization as they used to be. Even five years ago, IT departments could more closely manage what software was installed, as well as when, how, and what upgrades were rolled out. Now those updates and installations are managed by cloud providers, with upgrades rolling out on an almost weekly basis – often with no notice to the organization. All those changes have downstream eDiscovery impacts, which must be dealt with at each stage of the EDRM process.New data formats: Data is no longer structured in the traditional document “family” of an email parent with attachment children. The shift to chat and collaboration platforms within organizations means that communications and workflows generate more data across multiple data sources and are much more fluid and informal. For instance, instead of an employee working on a static document saved on a desktop and then passing that document back and forth to co-workers via email, those employees may work on that document together while it’s saved on a cloud-based collaboration platform, chat about it via an in-office chat application, post updates on it via the collaboration tool channel, as well as email copies back and forth to each other. This means counsel must analyze how relevant data ties together and analyze the relationships between data sources in order to understand the full story of a communication during an investigation or litigation.New capabilities with eDiscovery technology: There are many new types of capabilities that are native to enterprise systems, as well as new types of analytics and artificial intelligence (AI) that can handle more data at scale. These new capabilities are allowing case teams to leverage past data on new cases and get to key data more quickly in the EDRM process. The Impact: How Those Changes Affect the EDRM FrameworkThinking of the EDRM as a monolithic linear process that flows straight from beginning (collection) to end (production) does not fit the way eDiscovery takes place in practice anymore. There is a world of complexity within each step of the EDRM – one that is highly dependent on the data source. And the decisions made along the way for each data source at each new step will impact what happens next – often in a non-linear fashion: Sometimes that next step will send practitioners back to collection again, because they found another data source during review. Sometimes review takes place simultaneously with collection or processing phases, depending on the data source and those newer capabilities discussed above. In short, the old model of collecting all data, exporting it all, and then reviewing it all, in large chunks, one step at a time, is no longer applicable nor practical.Instead, a “mini-EDRM” framework might make more sense, where organizations prepare workflows for the preservation, collection, processing, and review of each particular data source. Thinking of the EDRM in this way also helps the framework stay relevant and future-proof as practitioners deal with the sea-change happening across our data landscape. Practitioners need to be agile enough to handle new data sources as they pop up, for each step of the EDRM process, and then be prepared to do it all over again when someone in a deposition mentions another new data source, and to adapt it when something changes in the data source. A mini-EDRM framework would help organizations and practitioners better meet those challenges.The EDRM and Data-in-PlaceAs noted above, the eDiscovery process is now much broader and has much more of an impact on organizational information governance and data-in-place than ever before. This presents an opportunity to use learnings from across the EDRM to more effectively manage data “to the left” of that traditional process. For example, if a particular data source was problematic during review, that information can be disseminated at the organizational level and help inform how that source is used within the organization moving forward. Or if practitioners notice a large volume of irrelevant data during review that shouldn’t exist in the system at all, that information can be used to redraft document retention policies. In this way, eDiscovery (and the EDRM framework) can now be a force for change over the entire organization.Thinking Beyond a Single MatterIn today’s more dynamic and voluminous data landscape, the work we did in the past is more valuable than ever before and it can be used to inform and impact current processes across the EDRM.This can come in the form of people and institutional knowledge: experienced and consistent staff and outside partners are an invaluable resource. These organizational experts can use their understanding and experience with an organization’s past matters, system architecture, data sources, workflows etc. to improve eDiscovery efficiency and solve current problems more effectively. It can also come in the form of technology: when the EDRM first evolved, data analytics were a much heavier lift. The process and tools were expensive and the amount of data that they could be applied to was much smaller than today. Advancements in AI capabilities now allow us to analyze much larger volumes of data with much more accurate results. Thus, this newer, advanced AI technology is now capable of leveraging the goldmine of millions of previous decisions made by attorneys on an organization’s past matters. That work product is baked into the data, and advanced AI can use it to make more accurate decisions on current data at a much larger scale than ever before.Tips to Keep the EDRM Applicable in an Evolving Data LandscapeStrive to retain institutional knowledge across matters: The constantly evolving eDiscovery landscape makes continuity and retaining institutional knowledge incredibly important. Starting from scratch each time you confront a new data source or problem along the EDRM is no longer practical with today’s diversified and larger data volumes. Work to cultivate valuable partners and staff who will work to understand your organization’s data architecture, as well as the eDiscovery workflows that are effective within your environment.Lean on your peers: Chances are, if you’re facing a problem with a challenging data source at one stage of the EDRM, someone in your peer group has also faced the same or a similar problem. Don’t be afraid to reach out and ask folks to benchmark. Peer experience can help each practitioner learn and move forward, solving challenging industry problems along the way.Open the lines of communication: Because the EDRM process is much more iterative and each step impacts other steps, it is incredibly important that the people working on those steps do not work in silos. Everyone should know the downstream impacts of their decisions and workflows.Test… and test again: Employ a testing framework to test the impact of eDiscovery workflows on the underlying platforms, and then have a feedback loop to apply changes. This will ensure your eDiscovery program is forward-thinking, as opposed to reactive. Automate where possible: When striving for repeatable, defensible eDiscovery processes, predictability is key. And automation, when feasible, is a great way to achieve that predictability. Automating workflows across the EDRM will not only help improve efficiency and lower costs, it will also help minimize risk and keep your eDiscovery program defensible.information-governance; ediscovery-review; chat-and-collaboration-datacloud, analytics, information-governance, ediscovery-process, blog, information-governance, ediscovery-review, chat-and-collaboration-data,cloud; analytics; information-governance; ediscovery-process; bloglighthouse
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Self-Service eDiscovery for Corporations: Four Considerations For Selecting the Solution That’s Right for You
Let’s begin by setting the stage. You’ve evaluated the ways a self-service, spectra eDiscovery solution could benefit your organization and determined the approach will help you boost workflow efficiency, free up internal resources, and reduce eDiscovery practice and technology costs. You’ve also researched how to ideally implement a solution and armed yourself with strategies to build a business case and overcome stakeholder objections that may arise.You’re now ready to move on to the next step in your organization’s self-service, spectra eDiscovery journey: selecting the right solution provider. When it comes to selecting a solution provider, one size does not fit all. Every organization has different eDiscovery needs—including yours—and those needs evolve. From how attorneys and eDiscovery teams are structured within the organization and their approach to investigations and litigations, to the types of data sources implicated in those matters and how those matters are budgeted—there’s a lot to be considered.The self-service, spectra solution you choose should be able to adapt to your changing needs and grow with your organization. Below, I’ve outlined four key considerations that will help you select a fitting self-service, spectra solution for your organization.1. Is the solution capable of scaling to handle any matter? ‍It’s important to select a self-service, spectra eDiscovery solution capable of efficiently handling any investigation or litigation that comes your way. A cloud-based solution can easily, swiftly scale to handle any data volume.You’ll also want to ensure your solution can handle the type of data your organization routinely encounters. For example, collecting, processing, and reviewing data generated by collaborative applications like Microsoft Teams may require special tools or workflows. The same can be said for data generated by chat messages or cellphone data. Before selecting a self-service, spectra solution, you’ll benefit from outlining the types of data your organization must handle and asking potential solution providers how their platform supports each.Additionally, you may be interested in the ability to move to a full-service model with your provider, should the need arise. With scalable service, your team will have access to reliable support if a matter become too challenging to manage in house. With a scalable solution bolstered by a flexible service model, your organization can bring on help as needed, without disruption. 2. Does the solution drive data reduction and review efficiency across the EDRM?‍Organizational data volumes are increasing year after year—meaning even small, discrete internal investigations can quickly balloon into hundreds of thousands of documents. Collecting, processing, analyzing, and producing large amounts of data can be costly, complicated, time consuming, and may open up your organization to legal risk if the right tools and workflows are not in place.Look for a self-service, spectra solution capable of managing data at scale, with the ability to actively help your organization reduce its data footprint. This means choosing a provider that can offer expert guidance around data reduction techniques and tools. Ask potential solution providers if they have resources to address the cost burden of data and mitigate risk through strategies like defensible data collections, effective search term selection, or crafting early case assessment (ECA), and technology assisted review (TAR) workflows.The provider should also be able to deliver technology engineered to reduce data resource draw, like processing that allows access to data faster, tools to cut down on hosted review data volume, and AI and analytics that provide the ability to re-use attorney work product across multiple matters. In short, seek a self-service, spectra solution that gives your organization the ability to defensibly and efficiently reduce the amount of costly human review across your organization’s portfolio. 3. Will the solutions’ pricing model align to your organization’s changing needs? Your organization’s budget requirements are unique and will likely change over time. Look for a solution provider that can change in accord and offer a variety of pricing models to fit your budgetary requirements. Ask prospective providers if they are able to design pricing around your organization’s expectations for utilization. Modern pricing models can be flexible yet predictable to prevent unexpected charges or overages, and ultimately align to your organization’s financial needs.4. Is the solution’s roadmap designed to take your organization into the future? When selecting a self-service, spectra solution it’s easy to focus on your current needs, but it’s equally important to consider what a self-service, spectra solution provider has planned for the future. If a vendor is not forward thinking, an organization may find itself being forced to used outdated technology that’s not able to take on new security challenges or process and review emerging data sources.Pursue a provider that demonstrates the ability to anticipate market trends and design solutions to address them. Ask potential providers to articulate where they see the market moving and what plans they have in place to update their technology and services to reflect what’s new. It can be helpful to question if a provider’s roadmap aligns to your organization’s direction. For example, if you know your company is planning to make a systematic change, like moving to a bring your own device (BYOD) policy or migrating to the cloud, you’ll want to confirm the self-service, spectra solution can support that change. Asking these types of questions before selecting a provider will guarantee the solution you choose will be able to grow with both your organization and the eDiscovery industry as a whole. With awareness and understanding of the true potential offered in a self-service, spectra solution, you can ultimately choose a provider that will help you level up your organization’s eDiscovery program. ediscovery-review; ai-and-analyticsself-service, spectra, blog, ediscovery-review, ai-and-analyticsself-service, spectra; bloglighthouse
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Now Live! Season Two of Law & Candor
This eDiscovery Day, the day that focuses on educating industry professionals around growing trends and current challenges, we are excited to announce that season two of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution, is now live.Co-hosts, Bill Mariano and Rob Hellewell, are back for season two of Law & Candor with six easily digestible episodes that cover a range of hot topics from cybersecurity to privilege tools. This dynamic duo, alongside industry experts, discuss the latest topics and trends within the eDiscovery, compliance, and information governance space as well as share key tips for you and your team to take away. Check out the latest season's lineup below:Bridge the Gap: Innovative Ways to Enable eDiscovery Collaboration Between Legal and ITThe Privilege in Leveraging Privilege Review ToolsData Preservation in the World of Ephemeral Data, Mobile Devices, and Other New Challenges in Forensic TechnologyCybersecurity in eDiscovery: Protecting Your Data from Preservation through ProductionWould a No-Deal Brexit Change How We Handle Cross-Border Collections in Europe?Understanding and Creating Effective and Best eDiscovery Practices for G-SuiteEpisodes are created to be short and bingeable so that you can listen on the platform of your choice with ease. Check them out now or bookmark them to listen to later.Follow the latest updates on Law & Candor and join in the conversation on Twitter. Catch up on season one today.For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.ediscovery-reviewgdpr, privilege, cybersecurity, ediscovery-process, cross-border-data-transfers, blog, ediscovery-review,gdpr; privilege; cybersecurity; ediscovery-process; cross-border-data-transfers; bloglighthouse
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Productizing Your Corporate Legal Department’s Services: Internally Marketing Your Solutions
In my last two blogs, I discussed how your legal department can productize services to become more efficient as well as shared some tips for how to determine the legal needs within your organization. Now that you know the added benefits and understand the legal needs, the natural next step is to determine what legal service “products” to offer, as well as any gaps. However, if nobody knows what these repeatable solutions are, what good are they? This is where creating an internal marketing plan to get the word out about your department’s legal services is critically important. In this blog, we’ll talk about how to do that by answering who, what, when, where, and why.Who?When you create your internal plan, the first thing you need to do is understand who you are marketing to. The easiest way to do this is to create some simple “personas.” You can easily do this based on the interviews you conducted as part of your earlier search. You should build a persona for each distinct type of user coming to you – typically this aligns with internal departments. In detailing each persona, you should include the following:Typical day-to-day work of your personaTypical interaction with legalTop of mind issues/challengesOther notesWhat?Next, you will need to decide what you are going to market to these personas (i.e repeatable workflows). Common ones in the legal arena are contract, litigation, HR investigation, and patent workflows. Once you have the workflows applicable to your company identified, detail the features of each workflow. For example, it is automated; has six common template documents, a clause library, and contract status; and leverages existing company technology.Once you have your personas, workflows, and features, you’re ready to create a positioning document. You should create one document for every problem/solution set (i.e. workflow). This will form the basis of how you share the information with others. The goal of this document is to position your solution in a way that resonates with the internal users. Below is a format that I find helpful to follow and I have inserted an example based on a contract workflow.PROBLEM: There is a problem in the company today. Contract negotiations are long, cumbersome, and not transparent. This can delay revenue opportunities. In addition, final contracts are difficult to locate and manage.SOLUTION: The ideal solution to this problem is an easy-to-use process, with some contracts being able to avoid legal review. The solution would allow easy access to status for interested parties and would allow those, or other, interested parties to access the contractual information at a later date.PRIMARY MESSAGE (SHORT - 1 SENTENCE): The Corporate Legal Department delivers a business-driven model for negotiating and managing contracts that accelerates, not hinders, company growth.SERVICE DESCRIPTION (2-3 SENTENCES): By leveraging an intake form, employees are directed to a self-service, spectra portal for template contracts or put in touch with an attorney for more complex matters. The status of their request, as well as information about all finalized contracts, is displayed in our JIRA system giving users full access to contract status as well as important contractual data of finalized contracts.HIGHLIGHTS (THESE SHOULD BE PROBLEM-ORIENTED FEATURES):Reduces contract turnaround by leveraging templated contracts and clausesAllows users access to contract status anytime, anywhereNo new systems (i.e. leverages existing company tools)Etc.The above will create a lot of different worksheets and information. Since I like to keep things a little simpler, I also create a cliff notes version of this to show the all-up view of your corporate legal department’s services.Once you have completed your positioning, don’t be afraid to run the messaging by some of the people you interviewed. You want to make sure that it is clear how legal will be helping them get their work done. I would suggest selecting people who are friendly to your department and who you have a good working relationship with since you are running draft information by them and not a final product.Where, When, and Why?Third, you need to think about where, when, and why you are getting the message out. The goal is to get it out wherever your users are, often, and in a way that they like to consume the information. At a minimum, I would suggest doing a launch of the updated services and including information about that launch on:The company wiki page/internal siteAny internal ticketing toolA company newsletter (or a company meeting if appropriate)Any onboarding materials/presentations your company does for new hiresOr even a “roadshow,” where you present to each department within your organization what services the legal team offersDuring any presentation, it is always helpful to inject some fun into the presentation. I have heard of some legal departments doing humorous videos or skits to capture the attention of their employees. Partner with your internal marketing team, as they may have some great suggestions on how you can get the word out.Finally, don’t forget about post-launch messaging. Though you may see an uptick in users after a launch, some people will have missed the information the first time around or will have forgotten it by the time they get to an issue that they want to bring to legal. To that end, make sure you have a plan for continued marketing. I like to showcase successes in follow-up marketing (e.g. a contract turnaround case study showing the reduced times or some metrics on impact). This information can be shared in an employee newsletter or as a quick email to leaders asking them to share it in their department meetings.This is quite a robust process and you should expect it will take several weeks, or even months, to complete. You will also likely continue to refine this marketing plan as you address gaps by adding services and gathering feedback. The benefit of going through this process is that it brings clarity to what legal does, brings efficiency by advertising repeatable workflows, and gives everyone in legal visibility into the challenges in the business and how legal addresses those.legal-operationslegal-ops, blog, legal-operations,legal-ops; bloglighthouse
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Purchasing AI for eDiscovery: Tips and Best Practices
eDiscovery is currently undergoing a fundamental sea change, including how we think about data governance and the EDRM. Linear review and older analytic tools are quickly becoming outdated and unable to handle modern datasets, i.e., eDiscovery datasets that are not only more voluminous than ever before, but also more complicated – emanating from an ever-evolving list of new data sources and steeped in variety of text and non-text-based languages (foreign language, slang, emojis, video, etc.).Fortunately, technological advancements in AI have led to a new class of eDiscovery tools that are purpose built to handle “big data.” These tools can more accurately identify and classify responsiveness, privileged, and sensitive information, parse multiple formats, and even provide attorneys with data insights gleaned from an organization’s entire legal portfolio.This is great news for legal practitioners who are faced with reviewing and analyzing these more challenging datasets. However, evaluating and selecting the right AI technology can still present its own unique hurdles and complexities. The intense purchasing process can raise questions like: Is all AI the same? If not, what is the difference between AI-based tools? What features are right for my organization or firm? And once I’ve found a tool I like, how do I make the case for purchasing it to my firm or organization?These are all tough questions and can lead you down a rabbit hole of research and never-ending discussions with technology and eDiscovery vendors. However, the right preparation can make a world of difference. Leveraging the below steps will help you simplify the process, obtain answers to your fundamental questions, and ultimately select the right technology that will help you overcome your eDiscovery challenges and up level your eDiscovery program.1. Familiarize Yourself with Subsets of AI in eDiscoveryNewer AI technology is significantly better at tackling today’s modern eDiscovery datasets than legacy technology. It can also provide legal teams with previously unheard-of data insights, improving efficiency and accuracy while enabling more data-driven strategic decisions. However, not all technology is the same – even if technology providers tend to generally refer to it all as “AI.” There are many different subsets of AI technology, and each may have vastly different capabilities and benefits. It’s important to understand what subsets of AI can provide the benefits you’re looking for, and how those different technology subsets can work together. For example, Natural Language Processing (NLP) enables an AI-based tool to understand text the same way that humans understand it – thus providing much more accurate classifications results – while AI tools that leverage deep learning technology together with NLP are better able to handle large and complex datasets more efficiently and accurately. Other subsets of AI give tools the ability to re-use data across matters as well as across entire legal portfolios. Learning more about each subset and the capability and benefits they can provide before talking to eDiscovery vendors will give you the knowledge base necessary to narrow down the tools that will meet your specific needs. 2. Learn How to Measure AI ROIAs a partner to human reviewers, advanced AI tools can provide a powerful return on investment (ROI). Understanding how to measure this ROI will enable you to ask the right questions during the purchasing process to ensure that you select a tool that aligns with your organization or law firm’s priorities. For example, if your team struggles with review accuracy when utilizing your current tools and workflows, you’ll want to ensure that the tool you purchase is quantifiably more accurate at classifying documents for responsiveness, privilege, sensitive information, etc. The same will be true for other ROI metrics that are important to your team, such as lower overall eDiscovery spend or increased review efficiency.These metrics will also help you build a strong business case to purchase your chosen tool once you’ve selected it, as well as a verifiable way to confirm the tool is performing the way you want it to after purchase.3. Come Prepared with a List of QuestionsIt’s easy to get swept up in conversations about tools and solutions that end without the metrics you need. A simple way to control the conversation and ensure you walk away with the information you need is to prepare a thorough list of questions that reflect your priorities. Also be sure to have a method to record each vendor’s response to your questions. A list of standard questions will keep conversations more productive and provide a way to easily contrast and compare the technology you’re evaluating. Ensure that you also ask for quantifiable metrics and examples to back up responses, as well as references from clients. This will help you verify that vendor responses are backed by data and evidence.4. Know the Pitfalls of AI Adoption—and How to Avoid ThemIt won’t matter how much you understand AI capabilities, whether you’ve asked the right questions, or whether you understand how to measure ROI, if you don’t know how to avoid common AI pitfalls. Even the best technology will fail to return the desired results if it’s not implemented properly or effectively. For example, there are some workflows that work best with advanced AI, while other workflows may fail to return the best results possible. Knowing this type of information ahead of time will help you get your team on board early, ensure a smooth implementation, and enable you to unlock the full potential of the technology.These tips will help you better prepare for the AI purchasing process. For more information, be sure to download our guide to buying AI. This comprehensive guide offers a deep dive into tips and tactics that will help you fully evaluate potential eDiscovery AI tools to ensure you select the best tool for your needs. The guide can also be used to reevaluate your current AI and analytic eDiscovery tools to confirm you’re using the best available technology to meet today’s eDiscovery challenges.lighting-the-way-for-review; ai-and-analytics; ediscovery-review; lighting-the-path-to-better-review; lighting-the-path-to-better-ediscoveryreview, ai-big-data, blog, ai-and-analytics, ediscovery-reviewreview; ai-big-data; blogai-analyticssarah moran
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Productizing Your Corporate Legal Department’s Services: Making Build vs. Buy vs. Outsourcing Decisions
For years, general counsel have weighed the pros and cons of doing a task internally versus sending the work to outside counsel – this is not a new dichotomy. What is newer, however, is the proliferation of technology available for legal and the business savvy now being applied to internal legal departments. This has opened up more choices for legal departments. First, you have to figure out whether you can apply technology, then whether you should build or buy that technology, and finally if you should outsource any portion of the process.Before you start down the path of buy vs. build vs. outsource, I would recommend assessing your department’s offerings. In the earlier parts of this series, I outline how you can do that. Once you understand your services and your gaps, you can better determine where you may need to apply build vs. buy decisions. Whether you are a general counsel or a legal operations professional, this blog will outline four key aspects to include in your framework as you make these decisions.1. Problem/Solution ListStart with a list of services your company needs and possible solutions. If you followed the productization process, you will have a good list. If you have not yet done this, you can at least jot down a list of your company’s legal needs, how pervasive and urgent they are, whether they further the company strategy, as well as any potential solutions.Next, order that list from most pervasive to least pervasive. Where there is a tie, look to the problem’s relationship to company strategy.Next, work through all of the items in box A. You want to be able to answer the following questions:Is there an existing solution?Is there a software solution that may apply?What are the costs/benefits of all possible solutions?Is there typically urgency around the request?All other things being equal, do we have the expertise to handle this in house?If you have gaps in A, B, or C, I would recommend addressing those before process improvement items.2. Cost-Benefit AnalysisNext, for any change (either addressing a gap or a process improvement) you should do a cost-benefit/return on investment analysis. Note that if you are just trying to get a sense of which problem on your list to address, you can do a high-level analysis by categorizing the solutions into low, medium, or high financial impact. If, however, you are getting to the point of suggesting a change internally and asking for budget, you want to do a much more in-depth quantitative analysis. On the benefit side, you want to consider any revenue acceleration for the company (e.g., customers’ revenue hits a quarter earlier) as well as costs reduced and avoided (e.g. outside counsel fees). If there are other quantifiable benefits, you should include them as well. On the expense side, make sure to consider licensing, annual maintenance, user fees, implementation, infrastructure, training, hourly support/expert charges, and any ongoing costs. You should predict these benefits and costs for the next 3 years, as that is a common period to see whether there is a return on your investment. You can also prepare a version of this document showing the same cost/benefit of building the solution internally as well as outsourcing it to outside counsel.3. Additional Factors: Urgency and ExpertiseOnce you have the cost-benefit analysis for the various solutions, you usually have a preferred direction. However, don’t forget to account for time and expertise. You should then consider how urgent the requests are. The more urgent a request, the more likely it should be handled by technology or outsourced, as those solutions typically can bring more resources to bear. You should then consider expertise. More specifically, does one need specific knowledge about the company to solve this problem or will there be a lot of need to liaise internally? If so, the solution should likely stay with the internal corporate legal department. Conversely, does this require niche expertise and is it better handled by an outside counsel with that expertise? Make notes of these considerations with your cost-benefit analysis, as these factors can sway a decision in one direction or another.4. Decision TimeUltimately, making these decisions is more of an art than a science. They are also decisions that can and should be revisited as things change in your business and legal department. The above should give you the right information to make an informed decision. Ultimately, you will want to share your decision with others and get input before finalizing a direction.By following the productization process, orienting your solutions towards your customers, streamlining how you deliver services, and applying the right sets of resources through build versus buy decisions, your legal department will operate more efficiently. legal-operationslegal-ops, blog, legal-operations,legal-ops; bloglighthouse
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Productizing Your Corporate Legal Department’s Services: Understanding the Needs of the Business
Many law departments are reactionary. Someone comes to legal with a “legal” question and they help that person. Although this makes a lot of sense, as legal is a support department, it makes it very difficult to thematically explain the value legal is driving as well as understand the work the department is doing. As legal operations matures and legal departments look to be more efficient, productizing the services in the department is a natural progression. This approach was a central discussion at the 2021 CLOC conference and the subject of this blog series. In order to productize something effectively, however, you need a very good understanding of your customer and prospective customers’ needs. In this article, I will give you an overview of how to get that.A central theme in product management is building resonators – products that resonate with the buyers. You may have the best idea but, if it doesn’t meet a pervasive market need, nobody will buy it. There are many great examples of products that failed and dozens of lessons we can learn from those failures. Most of the lessons come back to misunderstanding the customer's need and the nature of that need. For example, people may say they want a better mousetrap but if you don’t ask how much they would pay for that mousetrap, whether they would replace any current mousetraps with a better one, and whether it matters if the new mousetrap gives off an odor of chemicals, you can see how you might not make a best seller. To give an example in the legal services space, in my first general counsel role, I heard from many people how it was frustrating that they could never find contracts when they needed them. I immediately set upon a mission to create a contracts database. After investing a lot of time, we had a wonderfully organized database, and the only person who ever used it was the legal team. So what happened to all the frustrated employees from other departments? It turns out I didn’t ask them how often they needed to look up contracts and whether that need was part of another legal request (meaning that legal was the one actually looking up the contract anyway). In the end, the contract database was extremely helpful for the legal department but I could have saved myself the time of making it self-service, spectra and figuring out permissions for different users had I asked some questions upfront. To avoid the same fate, there are four principles you can use when asking your company about its legal needs.1. Don’t rely on the users to define the needs. Instead, be curious about their day-to-day and in that curiosity, you will be able to see the legal needs. The theory is this: if you ask someone what they need from legal, they will overlay their belief system about what legal should provide before they answer. Instead, when you ask them about their role, their goals, how they are measured, and what their biggest challenges are, you are more likely to be able to understand them and see where legal may be able to help.2. Create a template interview form and use it religiously with each person.When you do 10-15 interviews, you want to be able to discern themes and compare interviews. When multiple people are conducting interviews, you want to be sure you are all hitting the same topics. This is much easier to do when you start from a template. For a 30-minute interview, I would suggest 3-5 template questions. Always get background information before the interview starts including their name, title, department, and contact information. Put this information at the top of your interview summary. Do not include this in your 3-5 questions. Having this information clearly labeled and available allows you to easily follow up later. Next, move on to background and devote 2-3 questions to this area including what are their main goals for the year, how is their department measured, what are their biggest pain points. Finally, go on to any specific areas you may want to ask about. For example, you may want to know how they have used the legal department in the past, how much they interact with overseas colleagues, etc. Here is a list of common questions:What are your department’s goals for the year?How is your department measured?What are your biggest roadblocks in achieving your goals?What are your biggest roadblocks in getting your job done?If you had a magic wand and could change one thing about your job, what would it be?What are your most common needs outside your department?What is your perception of what the legal department does?What kinds of things have you come to legal for?3. Interview a diverse group. It may seem obvious that you need a good sample size, however, you will be surprised at how varied the needs are at different levels and across different departments. If you are only interviewing one person to represent a specific level or department, you should ask them “how representative do you think your pain points/goals are of the department?” This will give you a good idea of whether you can rely on this person’s interview as representative of the department or whether you will have to do some follow-up interviews with others.4. Always ask follow-up questions.The guidance for limiting your template to 3-5 questions above ensures you have time for follow up on each response. More specifically, you want to be sure you are really understanding the responses and quantifying the level and frequency of any relevant pain points. I would set a goal to ask 2 follow-up questions for every first response. For example, if your first question is “what are your goals for 2021?” then you should expect to ask 2 follow-up questions after your interviewee responds. If at any point the person you are interviewing mentions a challenge that you think legal can help to solve, this is your queue to follow up around the pain and pervasiveness. Here are some questions you can ask to get into how big a problem they are facing:How often do you run into this roadblock: daily, weekly, monthly, quarterly?When you run into this roadblock, how much time do you spend resolving it: 1-2 hours, 2-5 hours, 5-10 hours, 10+ hours?Does this roadblock impact multiple people? If so, how many?Does this roadblock (or a stoppage in you moving towards your goals) impact other departments?Are there workarounds for this roadblock? If so, how cumbersome are they on a scale of 1-5?If you had to reach out to another department and work with someone to remove this roadblock each time it came up, would you do that or would you continue with the workaround?How long would you wait for an outside resource to help before you proceed with your current workaround?Does the challenge have an impact on revenue?Whether you are a general counsel just getting to know your organization, a legal operations professional tasked with making your department more efficient, or a lawyer who is interested in ensuring you are providing great services, the above should give you a good place to start to understand your customer. Once you understand your customer, you’re able to provide great resonating services and position your existing solutions. legal-operationslegal-ops, blog, legal-operations,legal-ops; bloglighthouse
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Preparing for Big Data Battles: How to Win Over AI and Analytics Naysayers
Artificial intelligence (AI), advanced analytics, and machine learning are no longer new to the eDiscovery field. While the legal industry admittedly trends towards caution in its embrace of new technology, the ever-growing surge of data is forcing most legal professionals to accept that basic machine learning and AI are becoming necessary eDiscovery tools.However, the constant evolution and improvement of legal tech bestow an excellent opportunity to the forward-thinking eDiscovery legal professional who seeks to triumph over the growing inefficiencies and ballooning costs of older technology and workflow models. Below, we’ll provide you with arguments to pull from your quiver when you need to convince Luddites that leveraging the most advanced AI and analytics solutions can give your organization or law firm a competitive and financial advantage, while also reducing risk.Argument 1: “We already use analytical and AI technology like Technology Assisted Review (TAR) when necessary. Why bring on another AI/analytical tool?”Solutions like TAR and other in-case analytical tools remain worthwhile for specific use cases (for example, standalone cases with massive amounts of data, short deadlines, and static data sets). However, more advanced analytical technology can now be used to provide incredible insight into a wider variety of cases or even across multiple matters. For example, newer solutions now have the ability to analyze previous attorney work product across a company’s entire legal portfolio, giving legal teams unprecedented insight into institutional challenges like identifying attorney-client privilege, trade secret information, and irrelevant junk data that gets pulled into cases and re-reviewed time and time again. This gives legal teams the ability to make better decisions about how to review documents on new matters.Additionally, new technology has become more powerful, with the ability to run multiple algorithms and search within metadata, where older tools could only use single algorithms to search text alone. This means that newer tools are more effective and efficient at identifying critical information such as privileged communications, confidential information, or protected personal information. In short, printing out roadmap directions was advanced and useful at the time, but we’ve all moved on to more efficient and reliable methods of finding our way.Argument 2: “I don’t understand this technology, so I won’t use it” This is one of the easiest arguments to overcome. A good eDiscovery solution provider can offer a myriad of options to help users understand and leverage the advances in analytics and AI to achieve the best possible results. Whether you want to take a hands-off approach and have a team of experts show you what is possible (“Here are a million documents. Show me all the documents that are very likely to be privileged by next week”), or you want to really dive into the technology yourself (“Show me how to use this tool so that I can delve into the privilege rate of every custodian across multiple matters in order to effectuate a better overall privilege review strategy”), a quality solution provider should be able to accommodate. Look for providers that offer training and have the ability to clearly explain how these new technologies work and how they will improve legal outcomes. Your provider should have a dedicated team of analytics experts with the credentials and hands-on experience to quell any technology fears. Argument 3: “This technology will be too expensive.”Again, this one should be a simple argument to overcome. The efficiencies that the effective use of AI and analytics achieve can far outweigh the cost to use it. Look for a solution provider that offers a variety of predictable pricing structures, like per gig pricing, flat fee, fees generated by case, fees generated across multiple cases, or subscription-based fees. Before presenting your desired solution to stakeholders, draft your battle plan by preparing a comparison of your favored pricing structure vs. the cost of performing a linear review with a traditional pricing structure (say, $1 per doc). Also, be sure to identify and outline any efficiencies a more advanced analytical tool can provide in future cases (for example, the ability to analyze and re-use past attorney work product). Finally, when battling against risk-averse stakeholders, come armed with a cost/benefit analysis outlining all of the ways in which newer AI can mitigate risk, such as by enabling more accurate and consistent work product, case over case.ai-and-analyticsanalytics, ai-big-data, blog, ai-and-analytics,analytics; ai-big-data; bloglighthouse
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Productizing Your Corporate Legal Department’s Services: Getting Started
The 2021 CLOC conference focused a lot on applying product principles to legal services. General Counsel are often in the position of having to show the value of their team’s services and why, as a cost center, it makes sense to continue to grow their department or to buy technology to support their department. In addition to showing that value, there is pressure to be more efficient while providing excellent customer services. By productizing services, you can provide repeatable, measurable solutions that address the needs above. There is also the great benefit of being connected to your client’s needs by providing the services that match the most pervasive and urgent needs. However, if you don’t have a background in product management, how does one go about productizing legal services, and what does that even mean? As someone who is Pragmatic Marketing Certified through the Pragmatic Institute, I am here to help. This blog, and the blog series to follow, will show you how to get started, interview people internally to understand the needs, position your existing solutions internally, and make build vs. buy vs. outsourcing decisions. Let’s start with a high-level overview of where to begin.What does productizing legal services mean? Productizing your legal services focuses on creating solutions that apply to multiple customers in a repeatable way. This means that you first have to understand your customers’ problems by listening, asking, and observing. It then means that you create several repeatable processes to address those problems. Finally, it means you market those solutions internally and show how they bring value to the business. Taking it one step further, it also means that you leverage technology to support these services and continue to develop and improve the services based on feedback.So how does one go about creating these solutions inside a legal team? The first step is all about understanding the needs of the business. You can look internally at the requests the legal department receives to get an understanding of what the business is coming to the legal department for. Next, you want to speak to leaders from different groups in the business to understand what legal needs exist that are not coming into the legal department but should be addressed. Which leaders to speak to will depend a bit on your organization but I would recommend connecting with the following, at minimum: sales, finance, engineering (or product) as well as regional leaders in any key regions. More on this to come in my next blog on interviewing people internally to understand the organization’s needs.Once you have the information, it is helpful to create a list. I like to use the format below:Problems to SolveOnce you have a pretty solid list, you should brainstorm high-level recommended solutions (not the detailed how). This will include things like solving a certain need through documentation (e.g. a “how-to guide” or a template contract). It may include things like facilitating the intake of legal requests or facilitating access to contract information. Once you have your list of potential solutions, there are two next steps. For the set of existing solutions, you should group those into categories and make sure that you are adequately marketing and reporting on those (more on this in a future post). For the set of solutions that are future state, identify how you are going to address this need. When looking at the gaps, I like to categorize the gaps in the following ways so I can understand the budget impact and the division of work.Note that urgency speaks to how quickly the need needs to be solved overall and not necessarily the urgency of a specific request. For example, it speaks to how urgently people need a contract database as opposed to how quickly someone needs information about a specific contract. Pervasiveness addresses how many internal departments/employees have this need. Is it centered around just a small group within one department or is it a need expressed by multiple departments? The relationship to the company strategy should be focused on how much this need moves the business forward. Does it facilitate the company’s #1 strategy? When you complete this list, I recommend grouping it into like needs. If there are overlapping needs, you may want to create a consolidated item but make sure you capture the pervasiveness of it.Recommendations for Filling The GapsBy going through the above process you will have a good understanding of the various needs and solutions in your organization. In the next blog in the series, I will overview how to interview people internally to understand the organization’s needs.legal-operationslegal-ops, blog, legal-operations,legal-ops; bloglighthouse
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Privilege Mishaps and eDiscovery: Lessons Learned
Discovery in litigation or investigations invariably leads to concerns over protection of privileged information. With today’s often massive data volumes, locating email and documents that may contain legal advice or other confidential information between an attorney and client that may be privileged can be a needles-in-a-haystack exercise. There is little choice but to put forth best efforts to find the needles.Whether it’s dealing with thousands (or millions) of documents, emails, and other forms of electronically stored information, or just a scant few, identifying privileged information and creating a sufficient privilege log can be a challenge. Getting it right can be a headache — and an expensive one at that. But get it wrong and your side can face time-consuming and costly motion practice that doesn’t leave you on the winning end. A look at past mishaps may be enlightening as a reminder that this is a nuanced process that deserves serious attention.Which Entity Is Entitled to Privilege Protection?A strong grasp of what constitutes privileged content in a matter is important. Just as important? Knowing who the client is. It may seem obvious, but history suggests that sometimes it is not; especially when an in-house legal department or multiple entities are involved.Consider the case of Estate of Paterno v. NCAA. The court rejected Penn State’s claim of privilege over documents Louis Freeh’s law firm generated during an internal investigation. Why? Because Penn State wasn’t the firm’s client. The firm’s engagement letter said it was retained to represent the Special Investigations Task Force that Penn State formed after Pennsylvania charged Jerry Sandusky with several sex offenses. There was a distinct difference between the university and its task force.The lesson? Don’t overlook the most fundamental question of who the client is when considering privilege.The Trap of Over-Designating DocumentsWhat kind of content involving the defined client(s) is privileged? This can be a tough question. You can’t claim privilege for every email or document a lawyer’s name is on, especially for in-house counsel who usually serve both a business and legal function. A communication must be confidential and relate to legal advice in order to be considered privileged.Take Anderson v. Trustees of Dartmouth College as an example. In this matter, a student was expelled in a disciplinary action filed suit against Dartmouth. Dissatisfied with what discovery revealed, the student (representing himself) filed a motion to compel, asking the judge to conduct an in camera review of what Dartmouth had claimed was privileged information. The court found that much of the information being withheld for privilege did not, in fact, constitute legal advice, and that Dartmouth’s privilege claim exceeded privilege’s intended purpose.Dartmouth made a few other unfortunate mistakes. It labeled entire email threads privileged instead of redacting the specific parts identified as privileged. It also labeled every forwarded or cc’ed email the in-house counsel’s name was on as privileged without proving the attorney was acting as a legal advisor. To be sure, the ability to identify only the potentially privileged parts of an email thread — which could include any number of direct, forwarded and cc’d recipients and an abundance of inclusive yet non-privileged content — is not an easy task, but unfortunately, it is a necessary one.The lesson? If the goal of discovery is to get to the truth — foundational in American jurisprudence — courts are likely to construe privilege somewhat narrowly and allow more rather than fewer documents to see the light of day. In-house legal departments must be especially careful in their designations given the flow and volume of communications related to both business and legal matters, and sometimes the distinction is difficult to make.Be Ready to Back Up Your ClaimNo matter how careful you are during the discovery process, the other party might challenge your claim of privilege on some documents. “Because we said so” (aka ipse dixit) is not a compelling argument. In LPD New York, LLC v. adidas America, Inc, adidas claimed certain documents were privileged. When challenged, adidas’ response was to say LPD’s position wasn’t supported by law. The court said: Not good enough. Adidas had the burden to prove the attorney-client privilege applied and respond to LPD’s position in a meaningful way.The lesson? For businesses, be prepared to back up a privilege claim that an in-house lawyer was acting in their capacity as a legal advisor before claiming privilege.A Protection Not Used Often Enough: Rule 502(d)Mistakes do happen, however, and sometimes the other party receives information they shouldn’t through inadvertent disclosure. With the added protection of a FRE 502(d) order, legal teams are in a strong position to protect privileged information and will be in good shape to get that information back. Former United States Magistrate Judge Andrew Peck, renowned in eDiscovery circles, is a well-known advocate of this order.The rule says, “A federal court may order that the privilege or protection is not waived by disclosure connected with the litigation pending before the court — in which event the disclosure is also not a waiver in any other federal or state proceeding.”Without a 502(d) order in place, a mistake usually means having to go back and forth with your opponent, arguing the elements under 502(b). If you’re trying to claw back information, you have to spend time and money proving the disclosure was inadvertent, that you took reasonable steps to prevent disclosure, and you promptly took steps to rectify the error. It’s an argument you might not win.Apple Inc. v. Qualcomm Incorporated is a good example. In 2018, Apple lost its attempt to claw back certain documents it mistakenly handed over to Qualcomm during discovery in a patent lawsuit. The judge found Apple didn’t meet the requirements of 502(b). Had Apple established a 502(d) order to begin with, 502(b) might not have come into play at all.The lesson? Consider Judge Peck’s admonition and get a 502(b) order to provide protection against an inadvertent privilege waiver.Advances in Privilege IdentificationLuckily, gone are the days where millions of documents have to be reviewed by hand (or eyes) alone. Technological tools and machine learning algorithms can take carefully constructed privilege instructions and find potentially privileged information with a high degree of accuracy, reducing the effort that lawyers must expend to make final privilege calls.Although automation doesn’t completely take away the need for eyes on the review process, the benefits of machine learning and advanced technology tools are invaluable during a high-stakes process that needs timely, accurate results. Buyer beware however, such methods require expertise to implement and rigorous attention to quality control and testing. When you’re able to accurately identify privileged information while reducing the stress of creating a privilege log that will hold up in court, you lessen the risk of a challenge. And if a challenge should come, you have the data to back up your claims.ai-and-analyticsprivilege, ai-big-data, blog, ai-and-analytics,privilege; ai-big-data; bloglighthouse
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Prioritize Fact-Finding in Your Litigation and Discovery Strategy
A good discovery strategy goes beyond complying with production obligations. When preparing for discovery matters, law firms and legal corporate departments most often focus on developing a compliant and cost-effective responsive review capability with the appropriate expert personnel, technology, and workflows. After all, once in place, a tested responsive review capability can provide legal counsel the cost predictability, security, and control needed to focus on legal strategy early on in large litigation matters.Yet, while it is necessary to develop a reliable in-house or managed responsive review capability for document-intensive litigation, being ready for the demands of modern day discovery extends beyond complying with production obligations. Most notably, the work of fact-finding often continues well after production, and introduces its own unique complexities and opportunities requiring special tactical attention.Responsive review and finding key documents require different workflows. There is a substantive difference between identifying what is responsive for production versus honing in on the key information that ultimately decides a case or investigation. While responsive review focuses on compliance with negotiated and documented requests for production, targeted fact-finding focuses on legal hypothesis-testing and story development in an actively changing and open-ended context.As such, the mix of skills, technologies, and workflows required for responsive review does not necessarily extend beyond the production phase. Honing in on key documents and dispositive information buried in large data sets requires tactical agility and adaptation that efficient responsive review approaches limit by design in order to achieve production compliance at scale.Targeted fact-finding requires an iterative process and an expert team.A common need shared across fact-finding case teams is quick identification of key documents to help develop a robust and coherent fact-based narrative. Rather than casting a broad net to look for similarities among documents as you would do in a responsive review, fact-finding teams require an ability to sleuth through large data sets in order to identify key players, reveal hidden connections between them, and establish an overall picture and timeline of what happened.More specifically, rather than leveraging linear review workflows—even those optimized by technology-assisted review (TAR)—targeted fact-finding is best supported by iterative workflows in which attorneys and discovery experts deeply familiar with the case conduct tailored interrogations of the data to find the information that will best help with developing the case team’s understanding of the matter.Broaden the notion of discovery for better preparedness. Limiting discovery preparedness to achieving scalable responsive review gives short-shrift to developing a capacity for targeted fact-finding. Broadening the notion of discovery preparedness to include fact-finding means reassessing your discovery capabilities beyond production-oriented questions, such as what number of documents will require eyes-on review or what level of accuracy can be achieved. It makes sense to make more qualitative, legal expert-based assessments such as: Have we been able to uncover the full extent of the relevant fact pattern? How confident are we that we have connected the dots regarding who acted improperly and who had knowledge of it?To answer these sorts of questions, senior members of the litigation team need to be actively informed at a granular level regarding fact-finding approaches and outcomes. A robust and effective fact-finding function can provide a critical advantage in not only witness and trial preparation, but also in early case assessment, internal investigations, and government subpoenas, increasingly important discovery contexts to consider in light of increased regulatory, shareholder, and public scrutiny of corporate fraud and wrong-doing.For more on fact-finding, see: eDiscovery for Investigations: Different Goal, Different Approach. ediscovery-reviewblog, ediscovery-reviewbloglighthouse
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Now Live! Special Edition of Law & Candor
The overall impacts of COVID-19 are widespread and still very uncertain. The Law & Candor podcast team wanted to come together with this special edition to reflect on the current impacts and how they are affecting those the legal space and beyond.In this special edition, co-hosts Bill Mariano and Rob Hellewell, are joined by Lighthouse’s CEO, Brian McManus, to discuss his take on the industry impacts of COVID-19. The group discusses shifts in company priorities, common themes being heard throughout the industry, as well as the downstream implications this pandemic could have on the legal space by answering the following key questions:What are key company priorities?What are current employee safety priorities and items to be aware of?What is the industry saying?What will be the lasting impact of COVID-19 on the legal space?In conclusion, they share top takeaways from the episode. If you are interested in listening, click here. To join the conversation on Twitter, click here.Catch up on past seasons by clicking the links below:‍Season 1Season 2Season 3For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.ediscovery-reviewcloud, self-service, spectra, cloud-security, blog, ediscovery-review,cloud; self-service, spectra; cloud-security; bloglighthouse
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Overcoming Top Objections for Moving to a Self-Service eDiscovery Model
In a world of ever-increasing and evolving self-service, spectra models (think Amazon Go, fast food self-order kiosks, or even the self-service, spectra check in and check out at hotels), it’s no wonder the eDiscovery industry is headed in the same direction. In the last few years, new and improved SaaS eDiscovery tools have exploded onto the scene as corporations and law firms have started to embrace a self-service, spectra approach for executing the discovery work associated with both internal investigations and proper legal matters.As the historically risk-averse legal world has been slow to get on board with self-service, spectra eDiscovery models, you’re likely to still encounter objections if you ask your team to take the leap and invest in a self-service, spectra eDiscovery tool. Below, I outline the common objections I have encountered to self-service, spectra models and how you can overcome them by sharing some key value differentiators of on-demand eDiscovery tools that should persuade your team to embrace these new offerings and leave the antiquated, expensive on-prem solutions for good.Data Security Risks – The first, and potentially biggest, objection to the adoption of a self-service, spectra program often centers on concerns over data security and the associated risk. Corporations and law firms alike are concerned that self-service, spectra means cloud-based and as a result a lack of security and an increased exposure to risk. Historically, companies have been more comfortable with on-prem eDiscovery solutions because they have viewed that as meaning that they had complete control of their data without having to rely on a vendor or worry about their data being commingled with other clients’ data.However, with that control comes with a lot of risk, which can be greatly minimized by having a SaaS vendor that offers a private cloud. This private cloud can be a perfect solution because they do not have the same security concerns that are involved with the public cloud. When vetting potential SaaS partners, make sure to look for those that carry SOC 2, ISO, and HIPAA security certifications to ensure that your providers are staying up to speed on the latest security requirements.Steep Learning Curves – Oftentimes people I chat with will associate self-service, spectra with steep learning curves and lots of tedious training. This isn’t always the case.Although this may be true with some self-service, spectra solutions, but it’s important to note that not all platforms are created equal. Some solutions provide extensive functionality with a complex, hard to use, difficult to understand interface, while others strive to provide a simple interface often at the expense of functionality, while a rare few bridge the two finding that perfect blend of robust functionality and ease of use. Start the assessment into usability by understanding the true training required for the solutions you are evaluating, weigh the functionality vs. your team’s needs and skillset, talk to other users who have already adopted the solutions to validate the actual training lift, and finally showcase those findings with your team.Lack of Support – A common objection to self-service, spectra solutions is that they lack on-demand support and access to additional training and help if needed. Today’s lawyers and eDiscovery managers need to move through matters quickly and efficiently, and without access to readily-available help it frequently stalls the matter’s progress significantly. When looking into self-service, spectra solutions, choose one that offers on-demand support when, where, and how you need it. There are companies out there that offer this blend of autonomous control and augmented support and it is an easy objection to overcome if you can showcase that to your team. Minimal Flexibility – Frequently there is a hesitation to move forward with self-service, spectra due to the fear of getting stuck managing a matter in a self-service, spectra tool that could become large and/or complex and require additional help/support outside of your team’s capabilities or availability.Like I mentioned above, select a tool that also offers expert support. You can ease your team members’ worries by sharing that some self-service, spectra tools offer the ability to move from self-service, spectra to full service support when needed and scale up or down quickly.Too Pricey – The last major objection that I want to address is around the fact that many still believe self-service, spectra tools are too pricey and do not offer the ROI they need to see in order to make the switch.However, in an on-prem, behind the firewall model, there often are large up-front costs to purchase and install the technology as well as continued maintenance costs during the life of the product. In addition to the hardware costs there is the increased headcount necessary to support these platforms 24x7. With SaaS, the vendor purchases and maintains the software, as well as manages ongoing costs like upgrades and licensing. Managing an IT infrastructure and maintaining servers for eDiscovery data is a big cost for law firms and corporations often with no cost recovery mechanism. This cost burden can be greatly minimized with a SaaS solution.These top objections often come up in conversations around the adoption of a new self-service, spectra solution and I hope this blog has better prepared you to address them as you work to get your team on board. Feel free to reach out to further discuss these or other objections you may be facing at bthompson@lighthouseglobal.com.ediscovery-reviewcloud, self-service, spectra, blog, ediscovery-review,cloud; self-service, spectra; blogbrooks thompson
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Overcoming eDiscovery Trepidation - Part II: A Better Outcome
In this two-part series, I interview Gordon J. Calhoun, Esq. of Lewis Brisbois Bisgaard & Smith LLP about his thoughts on the state of eDiscovery within law firms today, including lessons learned and best practices to help attorneys overcome their trepidation of electronic discovery and build a better litigation practice. This second blog focuses on how attorneys within law firms can save their clients money, achieve better outcomes, and gain more repeat business once they overcome common misconceptions around eDiscovery.You mentioned earlier that you think attorneys who try to shoehorn volumes of electronic data into older workflows developed for paper discovery will likely cause attorneys to lose clients. Can you explain how? Sure. My point was that non-technological workflows often pop into the minds of attorneys because they are familiar, comfortable approaches to responding to document requests. Because they are familiar and can be initiated immediately, there is a great temptation to jump in and avoid planning and employing the expertise essential for an optimal workflow. Unfortunately, jumping in without much planning produces a result that is often unnecessarily costly to clients, particularly if the attorneys employ in-house resources (which are usually several times more costly than outsourced staff). In-house resources often regard document review and analysis as an undesirable assignment and have competing demands for their time from other projects and cases. This can result in unexpected delays in project completion and poor work product (in part because quality degrades when people are required to perform tasks they dislike). The end result is untimely, lower quality, and more costly than anticipated, which will ultimately cost the attorney their client.Clients will always gravitate towards the professional who can deliver a better, more cost-effective, and more efficient solution while avoiding motion expenses. That means that attorneys who are informed enough to use technology to save clients money on multiple cases are going to earn the trust and confidence of more and more clients. And that is the answer to the question as to what’s in it for the professional if he or she takes the time to learn about or partners with someone who already knows eDiscovery.Well, coming from a legal technology company, I agree with that sentiment. But we also tend to see attorneys from the other end of the spectrum: lawyers who understand the benefits advanced eDiscovery technology can provide, but avoid it because of fears around overhead expense and surprise fees. Have you seen this within your own practice? If so, how do you advise attorneys who may have similar feelings? I experience the same thing and, again, this type of thought process is completely understandable. When eDiscovery technologies were comparatively new, they seemed disproportionately expensive. The cost to process a GB of data could exceed $1,000, hosting charges ran into the many tens of dollars per month and there were no analytics to expedite review. When the project management service was in its infancy, too many of those providing services simply followed uninformed instructions from counsel. An instruction to process data was not met with inquiries as to whether all data collected should be processed or if an alternative should be explored when initial analysis indicated the data expansion would be unexpectedly large. Further, early case assessment (ECA) strategies utilizing only extracted text and metadata were years in the future. The only saving grace was that data volumes were miniscule compared to what they are today. But that was not enough to prevent widespread reports about massive eDiscovery vendor bills. As you might suspect, the problem was not so much the technology or even the lack thereof as it was the failure to spend the time to develop an appropriate workflow and manage the eDiscovery process so the results were cost effective. Any tips on how attorneys can overcome the remnant fear of eDiscovery “sticker shock”?This challenge can be met by research, planning, and negotiation: research into the optimal technologies and which providers are equipped to provide them, planning an appropriate workflow, and negotiation with eDiscovery platform providers to customize the offerings to the needs of your case. If you have the aptitude, consider investing some time and doing some research about eDiscovery solutions that provide predictable, transparent prices outside of the typical hourly and per-GB fee structure. A good eDiscovery platform provider should work with you to develop a fee arrangement that makes sense for your caseload and budget. There is no reason why even a small firm or individual practitioner cannot negotiate subscription-based or consumption-based fees for eDiscovery solutions the same way that forward thinking serial litigants like large corporations and insurers have. The pricing models exist and there is no reason they cannot be scaled for users with smaller demands. Under this type of arrangement, there will be no additional costs or surprise fees, which in turn will allow any practitioner to pass that price predictability on to his or her clients. Ultimately, this lower cost, increased predictability, and efficiency will enable an attorney to grow his or her book of business with repeat customers and referrals.So, if an attorney is able to negotiate an alternative fee arrangement with a legal technology provider, is that the end of the problem? Should that solve all an attorney’s eDiscovery concerns? It’s a start – but no. Even with a customized eDiscovery technology solution, part of the concern for most attorneys is the magnitude of the effort required to respond to discovery requests. On one hand, they’re faced with document requests fashioned by opposing counsel fearful of missing something that might be important unless they are massively overinclusive. They ask for each, every, and all documents and any form of electronic media that involves, concerns, or otherwise relates to 30, 50, 100, or more discrete topics. On the other hand, the attorney must reconcile this task of preserving, identifying, collecting, processing, analyzing, reviewing and producing ESI in a manner that complies with the applicable discovery laws or case specific discovery orders… all under what may be a modest budget approved by the client. This is where experience (or guidance from an experienced attorney), as well as a good eDiscovery technology provider can be a huge help. The principle that underlies a solution to the conundrum as to how to manage an overly broad discovery request with a limited budget is: proportionality. Emphasizing this principle is a major focus of the 2015 amendments to the FRCP. Got it. I think the logical follow up question to that answer is: how can attorneys attain “proportionality” in the face of ridiculous discovery requests (while also not exceeding the limited amount the client is prepared to spend)?The key to balancing these conflicting demands is insisting upon proportionality early and often. The principle needs to be addressed at a granular level with a robust understanding of the client’s data that will be the subject of opposing counsel’s discovery requests. For example, the number of custodians from whom data should be collected should not be a laundry list of everyone who might have knowledge about the issues in the case. Rather, counsel should be focused on the key players and how much data each has. The volume of data that counsel can afford to collect, process, analyze, review, and produce should depend largely on what the litigation budget is, which in turn should generally depend on the amount in controversy. There are exceptions to this rule of thumb, but this approach to proportionality needs to be raised during the initial meetings of counsel in advance of the first case management order. If the case is one where the general rule does not apply (e.g., a matter of public interest), the client should be informed immediately because the cost of litigation is likely to be disproportionate to its economic value and the client may prefer to have some other entity litigate the issue. An experienced attorney should be involved in this meet and confer process because the results of these early efforts are likely to create the foundation and guard rails for the remainder of the case. Any issues that are left to future negotiation create a potential for costs to balloon in unexpected ways. Can you dive a bit deeper into proportionality at different phases of the discovery process? Is there anything else attorneys can do to keep cost from ballooning before data is collected?As I alluded to a moment ago, one key to controlling scope and cost is to negotiate a limited number of custodians that is proportional to the value of the case. In larger cases, it will be appropriate to create tiers of custodians and limit progression into the lower tier custodians to those instances where opposing counsel make a good faith showing that additional discovery is necessary based on identifiable gaps of information rather than upon speculation about what might be found if more discovery is permitted. If opposing counsel doesn’t agree to a limited number of custodians or staging discovery in larger cases, counsel would be well advised to prepare a case management order or a protective order to keep the scope of discovery proportional to the value of the case. To be successful, an attorney and his or her technology provider will have to understand the data in the client’s possession and provide metrics and costs associated with the alternative approaches to discovery.Great advice. How about once data is collected and analysis has begun? How can attorneys keep costs within budget once they've got the data into an eDiscovery platform?Attorneys should continue to budget proportionally throughout the case. This budget will obviously include the activities identified by the Electronic Discovery Reference Model (EDRM). The EDRM provides a roadmap to respond to opposing parties’ discovery requests: identifying those documents that are needed to make our case, regardless of whether opposing parties requested them; winnowing the documents identified to a subset for use in deposition preparation; drafting potentially dispositive motions; and preparing for mediation; and, if necessary, preparing for inclusion on the trial exhibit list. The EDRM was designed to help attorneys identify documents that are reasonably calculated to lead to the discovery of admissible evidence or relate to claims and defenses asserted in the case. In a case with 100,000 documents collected, that could easily be 10,000 to 15,000 documents. The documents considered for use in depositions, law and motion, or mediation will be a small fraction of that amount and will include a similar culling of those documents produced by other parties and third parties. Only a fraction of those will make it onto the trial exhibit list and fewer will be presented to the trier of fact.Responding to discovery and preparing the case for resolution are two very different tasks and the attorney’s budget must accommodate these two different activities. Monies must be reserved for other written discovery requests, both propounding them and responding to them, and for depositions. Because the per-GB prices for these activities are predictable, an attorney and technology provider should be able to readily determine how much information they can afford to collect and put into the eDiscovery workflow. Counsel needs to be ready to share this information with opposing parties during the early meetings of counsel. But what happens when there is just a legitimately large amount of data, even after applying all the proportionality tactics you described earlier? Counsel should only agree to look at more data than that to which the parties originally agreed if opposing counsel can show good cause to incur that time and expense. If more data needs to be analyzed, the only reliable way to avoid busting the budget is to use AI to build on the document classification that occurred during the initial round of eDiscovery activities. Counsel should take advantage of statistically defensible sampling to determine the prevalence of responsive documents in the data and cut off analysis and review when a defensible rate of recall has been achieved. The same technologies should be employed to identify documents that should not be produced, e.g., those that are privileged or contain trade secrets unrelated to the pending litigation or other data exempt from discovery – enabling counsel to reduce the amount of expensive attorney review required on a given case.By proactively managing eDiscovery proportionality and leveraging all the efficiency that modern eDiscovery platforms provide (either by developing the necessary expertise to do so or associating with an attorney who does) – any lawyer will be able to handle any discovery request in a cost-effective manner.You mentioned choosing a database and legal technology provider. Do you have any advice for attorneys on how to choose the best one to meet their needs?I won’t weigh in on specifics, but I will say this: do the necessary research or consult with someone who has. In addition to investigating the various technologies available, counsel must become familiar with a variety of pricing models for delivery of the technologies needed to respond to eDiscovery requests. Instead of treating every case as an a la carte proposition, consider moving to a subscription-based self-service eDiscovery platform solution. This allows counsel savvy with the technology to control his or her cases within the platform and manage costs in a much more granular way than is possible when using a full-service eDiscovery technology provider, without incurring additional licensing, hosting, and technology fees. With a self-service solution, a provider hosts the data within their own cloud (and thus takes on the data security, hosting, and technology fees), while counsels gain access to all the current versions of eDiscovery tools to help manage the client’s costs. It will also allow counsel to customize the platform and automate workflows to meet his or her own specific needs, so that no one is spending time and money re-inventing the wheel with every new case. A self-service solution also comes with the added benefit of being immediately available from any web browser and gives counsel the ability to transfer data into platform at the touch of a button. (This means that when a prospective client asks whether you have a solution to handle the eDiscovery component of a case, the answer will always be an immediate “yes”).What happens if counsel does not feel ready to take on all eDiscovery responsibilities in a “self-service” model?If counsel is not ready to take on full responsibility for managing the eDiscovery process but still wants the cost-savings of a self-service model, find a technology provider that offers project management services and guidance that will act as training wheels until counsel is ready to navigate the process without assistance. There are also service providers who offer flexible arrangements, where large matters can be handled by their full-service team while smaller matters or investigations can remain “self-service” and be handled directly by counsel.Those are great tips, Gordon – I couldn’t have said it better myself. Any last thoughts for attorneys related to discovery and leveraging eDiscovery technology? Thank you, it’s been a pleasure. As for last thoughts, I think it would be this: in 2021, no attorney should fear responding to eDiscovery requests. Attorneys who still have that fear need to start asking, “If the data exists electronically, can I use technology to extract what I need less expensively than if I put eyeballs on every document?” The answer is almost always, “Yes.” The next question those attorneys should ask is, “How do I go about extracting the information I need at the lowest possible cost?” The answer to that question may be unique to each attorney, and this is where I recommend doing some up-front research and preparation to identify the best technology solution before you are looking down the barrel at a tight discovery deadline.Ultimately, finding the right technology solution will enable you to meet every discovery request with confidence and ultimately grow your book of business. If you would like to discuss this topic further, please reach out to Casey at cvanveen@lighthouseglobal.com and/or Gordon Calhoun at Gordon.Calhoun@lewisbrisbois.com.ediscovery-review; ai-and-analyticsediscovery-process, blog, spectra, law-firm, ediscovery-review, ai-and-analyticsediscovery-process; blog; spectra; law-firmcasey van veen
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Now Live! Season Four of Law & Candor
We're excited to announce that season four of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution, is now available. Click the image below to binge season four now or keep scrolling for more details on the latest season. Co-hosts, Bill Mariano and Rob Hellewell, are back for season four of Law & Candor with six easily digestible episodes that cover a range of hot topics from cybersecurity to privilege tools. This dynamic duo, alongside industry experts, discuss the latest topics and trends within the eDiscovery, compliance, and information governance space as well as share key tips for you and your team to take away. Check out the latest season's lineup below:Emerging Data Sources: Get a Handle on eDiscovery for Collaboration Tools Myth Busters: The Managed Services Edition Legal Operations 101: Skills for SuccesseDiscovery Program Starter Pack: Uncover Key Ways to Build an Effective & Efficient eDiscovery ProgramManaging Cybersecurity in eDiscoveryTake the Mystery out of Machine Learning: Success Stories from Real-Life Examples and How Data Scientists Impact eDiscoveryEach episode is bingeable and available on your podcast platform of choice including Apple, Spotify, Stitcher, and Google. Follow the latest updates on Law & Candor by subscribing on the podcast home page and join in the conversation on Twitter. Catch up on past seasons by clicking the links below:‚ÄçSeason 1Season 2Season 3Special Edition: Impacts of COVID-19For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.ediscovery-reviewcloud, cybersecurity, emerging-data-sources, cloud-security, tar-predictive-coding, ediscovery-process, legal-ops, managed-services, blog, ediscovery-review,cloud; cybersecurity; emerging-data-sources; cloud-security; tar-predictive-coding; ediscovery-process; legal-ops; managed-services; bloglighthouse
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Now Live! Season Five of Law & Candor
We are thrilled to announce the one-year anniversary of our Law & Candor podcast. One year, five seasons, and 30 episodes later, we are still here and wholly devoted to pursuing the legal technology revolution. Click the image to listen to season five now or scroll down for more details. Co-hosts Bill Mariano and Rob Hellewell are back for season five of Law & Candor with six easily digestible episodes that cover a range of hot topics from cloud migrations to managing DSARs. This dynamic duo, alongside industry experts, discuss the latest topics and trends within the eDiscovery, compliance, and information governance space as well as share key tips for you and your team to take away. Check out the latest season's line-up below:Achieving Information Governance Through a Transformative Cloud Migration Scaling Your eDiscovery Program: Self Service to Full Service Leveraging AI and Analytics to Detect PrivilegeEffective Strategies for Managing DSARsFacilitating a Smooth and Successful Large Review Project with Advanced AnalyticsTop Microsoft 365 Features to Leverage in Your eDiscovery ProgramEpisodes are created to be short and bingeable so that you can listen on the platform of your choice with ease. Check them out now or bookmark them to listen to later. Follow Law & Candor on Twitter to get the latest updates and join the conversation.Catch up on past seasons by clicking the links below:Season 1Season 2Season 3Season 4Special Edition: Impacts of COVID-19For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.ediscovery-reviewcloud, information-governance, ai-big-data, blog, ediscovery-review,cloud; information-governance; ai-big-data; bloglighthouse
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Now Live! Season Three of Law & Candor
Season three of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution, is now available for your listening pleasure. Click the image below to binge season three now or keep scrolling for more details on the latest season. Law & Candor co-hosts, Bill Mariano and Rob Hellewell, have done it again. They have developed yet another riveting season of content by bringing on industry experts from AstraZeneca, Dentons, Dignity Health, Goulston & Storrs, GSK, and Lighthouse to discuss hot topics within the eDiscovery, compliance, and information governance space. Season three is filled with valuable takeaways, practical tips, and lots of banter along the way. See the season three episode lineup below:Tackling Big Data ChallengesData Privacy in a Post-GDPR World: Facing Regulators and Ensuring Compliance Through Rock-Solid Information Governance PracticeThe Future of On-Demand SaaS Software for Small Matters – A self-service, spectra Model StoryNew Efficiency Gains in TAR 2.0 and CMML RevealedHow Microsoft 365 and GDPR Are Driving a Proactive Approach to eDiscovery Across the GlobeeDiscovery Shark Tank - What’s Worth Your Investment in 2020?Each episode is bingeable and available on your podcast platform of choice including Apple, Spotify, Stitcher, and Google. Check them out now or bookmark them and listen later. Follow the latest updates on Law & Candor and join in the conversation on Twitter. Catch up on past seasons by clicking the links below:Season 1Season 2‍‍For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.ediscovery-reviewmicrosoft, cloud, gdpr, self-service, spectra, data-privacy, ai-big-data, cloud-security, tar-predictive-coding, blog, ediscovery-review,microsoft; cloud; gdpr; self-service, spectra; data-privacy; ai-big-data; cloud-security; tar-predictive-coding; bloglighthouse
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Now Live! Reed Smith's M365 in 5 Podcast Series
Lighthouse Microsoft 365 (M365) experts, John Holliday and John Collins, recently teamed up with Reed Smith to present the M365 in 5 Foundation Series on Reed Smith’s Tech Law Talks podcast. The series dives into operational considerations when rolling out M365 tools related to governance, retention, eDiscovery, and data security across a broad range of applications, from Exchange and SharePoint to all things Microsoft Teams.Check out the lineup below and click the titles of each podcast to give them a listen.M365 in 5 – Part 1: Exchange Online – Not just a mailboxDiscover the enhanced functionality of EXO, including new data types and the potential for enhanced governance.M365 in 5 – Part 2: SharePoint Online – The new file-share environmentHear about the enhanced file share and collaboration functionality in SharePoint Online, including real-time collaboration, access controls, and opportunities to control retention and deletion.M365 in 5 – Part 3: OneDrive for Business – Protected personal collaborationLearn about OneDrive for Business and how organizations can use it for personal document storage, such as giving other users access to individual documents within an individual’s OneDrive and acting as the storage location for all Teams Chats.M365 in 5 – Part 4: Teams – An introduction to collaborationListen to an introduction to Teams and how it is transforming the way organizations are working and communicating.M365 in 5 – Part 5: Teams Chats – Modern communicationsUncover the enhanced functionality of M365’s new instant messaging platform, including persistent chats, modern attachments, expressive features, and priority messaging, which enhance communication but can bring increased eDiscovery or regulatory risks.M365 in 5 – Part 6: Teams Channels – The virtual collaboration workspaceHear how Teams Channels are changing not only the way organizations work and collaborate, but also key legal and risk considerations that should be contemplated.M365 in 5 – Part 7: Teams Audio/Video (A/V) ConferencingDive into the functionality and controls of audio/video conferencing capabilities, including the integration of chats, whiteboards, translation, and transcription services.The Tech Law Talks podcast hosts regular discussions about the legal and business issues around data protection, privacy and security; data risk management; intellectual property; social media; and other types of information technology. For more information regarding the show, follow the link here: https://reedsmithtech.podbean.com.If you have questions about how to develop and maintain legal and compliance programs around M365, reach out to us at info@lighthouseglobal.com.microsoft-365; information-governancemicrosoft, blog, microsoft-365, information-governancemicrosoft; bloglighthouse
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New Opportunities, New Risks: A Disrupted Workforce Reshapes the Data Landscape
In case the complexities of corporate data weren’t creating enough turbulence to keep corporate and legal teams up at night, along comes a prolonged pandemic to really shake things up. Because now, a complex data landscape has also become a complex employee landscape.What has been dubbed the “great resignation” (approximately 38 million workers voluntarily quit their jobs in 2021) has left many companies shaken as they struggle to adapt their organizations to a reconfigured and remote workforce. With little time to plan for the risks and contingencies such a seismic shift would normally entail, companies are now playing catch-up, seeking ways to ensure proper data management, better responses to fast-moving litigation and internal investigations, and enhanced security as they grapple with offsite employees, transformative applications, and the impact of an exodus that may have caused company data to escape its bounds.These unique circumstances present a number of challenges for companies and their legal teams alike. In a webinar with Today’s General Counsel, I was pleased to join Scott McVeigh, industry principal from Onna, to discuss the ways in which many companies have been affected. We looked at the recent workplace disruption and considered the impact: What data risks have emerged or intensified? What efficiencies or advantages? What areas of the company data environment deserve renewed focus? What steps can internal teams take to help ensure that data concerns are addressed and legal imperatives met? A Shift to Remote Work Accelerates Transition to the CloudPrior to the pandemic, an estimated 20% of the U.S workforce was working remotely. By December, 2020, that number had increased to 71%. Even with offices now deemed safer as the pandemic wanes, it is anticipated that more than 51% of the U.S. workforce will continue to be remote or hybrid.The impact of this shift has already been profound, reshaping the use, format, and storage of data. As many as 81% of organizations say the pandemic accelerated their cloud timelines as they raced to engage with new tools and applications that flooded the market to accommodate the remote workforce. Online collaboration has now become the new normal, with document sharing apps, chat functionalities, and web conferencing becoming the dominant forces that underpin daily work. Enhanced Collaboration — A Mixed Blessing While this shift may have resulted in some efficiencies as more informal practices took hold, the explosion of collaborative data technologies has also created significant challenges, especially for data and records management, security, and legal teams. As a result, some important enterprise areas are ripe for renewed attention and innovation:Information governance models: The disrupted workforce has made information governance efforts more complicated—and more necessary. Remote collaboration and sharing applications mean more data in more places, making it harder for internal teams to create and maintain a cohesive vision of the data landscape to contain and control growing data volumes.Rapid data growth from both authorized and unauthorized tools and new forms of communication (think gifs, memes, and emojis) makes it easier for data to proliferate, morph, even disappear, which may call for modified or additional policies and procedures. From a data security standpoint, privacy breaches coupled with other security stressors are magnified as siloed data, a perennial problem, pressure-tests existing processes and policies.eDiscovery and preservation imperatives: In the implementation of cloud applications, preserving and collecting data in a defensible manner has not been a top priority. More tools enabling informal, dispersed, and fluid content challenge the paradigm of traditional collection and review. Where is a particular kind of data living and who controls it? Who is the custodian or author of content in shared collaborative spaces? With so many new data types, what is now the definition of a “document” or a conversation?Employee transitioning: As employees moved offsite or departed during the pandemic, company data may have gone with them — if not through malicious exfiltration, then just because HR and IT, with reduced teams as well, could not keep up with the onboarding and offboarding process. One top concern for organizations is that the lost data or IP could have gone to a competitor. Training requirements: With workers at a distance, training on company privacy, security, and preservation policies — which should be intensifying — may be taking a back seat to other business priorities impacted by the pandemic. Too, cultivating a data-sensitive culture is now more difficult with employees often untethered from the norms of company data access and storage and little to no face-to-face interaction with other employees and their own managers. Law Firms and Legal Departments Not Exempt from DisruptionTo complicate matters, as companies were transformed by the pandemic, so too were the law firms and legal departments that support them. Already in a state of flux, the legal market was highly impacted by both employee departures and the migration to remote work, relatively foreign to an entrenched in-office culture. Lack of attention to document management, often a law firm weakness, has just added fuel to the fire.The resignation-induced talent drain has likely affected workflows, adding to inefficiencies and duplicative work as corporate and legal knowledge, both in-house and outside, dissipated with the overall disruption of formerly routine processes and responsibilities. It has certainly impacted eDiscovery processes; legal professionals are still working to master the art of conducting discovery remotely from cloud-based data sources.Bucking the Trends: Take These Steps to Reduce RiskThe disrupted workplace calls for renewed diligence, nimbleness, and a certain amount of creativity on the part of internal teams responsible for data and its management. Most of all, it requires rigorous attention to potential risks exacerbated by a still-evolving landscape.Here are some important steps companies can take to reduce risk: Scrutinize what may now be a very different data landscape. As in pre-pandemic times, knowing where data resides and in what format is a big part of the battle. With new tools and cloud storage locations making everything even more complex, thinking through applications and the data they generate before they roll out can save time, effort, and grief down the line. Analyze: Who uses what applications? Where does the data go and how is it stored? Who has control over it? From an eDiscovery standpoint, with so much data in play, it pays to scale efforts to potential returns; focusing on the most-used data sources is more fruitful than “boiling the ocean.” Cultivate stakeholder partnerships. As the workforce transforms, partnerships among internal stakeholders, especially IT, compliance, data privacy, records management, and information security teams — in close coordination with business units — are more important than ever in controlling how and by whom data is created and used. Corporate silos only enhance risk, especially when workers are remote and unsanctioned applications may be proliferating. Remember, though, that data initiatives are most effective when they come from the top, especially if funding is required. Engage the C-suite as much as possible. Improve information governance capabilities. As data pools from multiple collaborative sources and cloud applications proliferate, making prior linear processes cumbersome and expensive, a shift in focus to the left side of the Electronic Discovery Reference Model (EDRM) makes even more sense now. With the right cloud-based tools and services, as well as good information governance models, teams can perform better upstream and reduce downstream costs.Foster a culture of data awareness and protection. Training, training, training — for both current and incoming employees — is critical. Sound policies mean nothing if employees are unaware of or don’t abide by them or don’t understand the nature of the risk they are meant to address. Educate employees on data “ownership” best practices. Encourage sound data hygiene and enhance onboarding and offboarding procedures to take data risks into account, especially those related to preservation imperatives. Remember that inbound data from new employees that works its way into the company can be just as problematic as data exfiltration. Review and, if necessary, update records management policies. Records management policies should be considered programmatically to align with the nature of the business. Reducing company exposure by updating policy gaps that may be caused by evolving privacy regulations (e.g., GDPR, CCPA/CPRA, etc.) should be a top priority for any company’s records and data management teams. Remember that training goes hand in hand with any policy changes.Engage experts where you need them. Data complexities of today, especially related to privacy and security, may require the expertise beyond that routinely found in-house. Be sure to work with providers and experts well-versed in today’s challenges.Leverage technology where possible, with expertise in mind. Various data automation tools can provide the power to import, manage, and modify records in ways never before possible. AI and categorization tools can be used to assess data in place, potentially mitigating the need for linear collection, processing, and review of data in discovery. Automated tools can enable a more managed examination of departing employee data. But technology not carefully deployed or without the right experts behind the scenes can diminish the potential benefits. Know what questions to ask. Be an informed and thoughtful user: implement wisely. If you are interested in this topic, feel free to reach out to me at dblack@lighthouseglobal.com. chat-and-collaboration-data; forensics; information-governanceemerging-data-sources, cloud-security, red-flag-reporting, departing-onboarding-employee, pii, blog, record-management, risk-management, chat-and-collaboration-data, forensics, information-governance,emerging-data-sources; cloud-security; red-flag-reporting; departing-onboarding-employee; pii; blog; record-management; risk-managementdaniel black
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Navigating the Intersections of Data, Artificial Intelligence, and Privacy
While the U.S. is figuring out privacy laws at the state and federal level, artificial and augmented intelligence (AI) is evolving and becoming commonplace for businesses and consumers. These technologies are driving new privacy concerns. Years ago, consumers feared a stolen Social Security number. Now, organizations can uncover political views, purchasing habits, and much more. The repercussions of data are broader and deeper than ever.Lighthouse (formerly H5) convened a panel of experts to discuss these emerging issues and ways leaders can tackle their most urgent privacy challenges in the webinar, “Everything Personal: AI and Privacy.”The panel featured Nia M. Jenkins, Senior Associate General Counsel, Data, Technology, Digital Health & Cybersecurity at Optum (UnitedHealth Group); Kimberly Pack, Associate General Counsel, Compliance, at Anheuser-Busch; Jennifer Beckage, Managing Director at Beckage; and Eric Pender, Senior Director at Lighthouse (formerly with H5); and was moderated by Sheila Mackay, Managing Director at Lighthouse (formerly with H5).While the regulatory and technology landscape continues to rapidly change, the panel highlighted some key takeaways and solutions to protect and manage sensitive data leaders should consider:Build, nurture, and utilize cross-functional teams to tackle data challengesDevelop robust and well-defined workflows to work with AI technology Understand the type and quality of data your organization collects and stores Engage with experts and thought leadership to stay current with evolving technology and regulations Collaborate with experts across your organization to learn the needs of different functions and business units and how they can deploy AI Enable your company’s innovation and growth by understanding the data, technology, and risks involved with new AIDevelop collaboration, knowledge, and cross-functional teamsWhile addressing challenges related to data and privacy certainly requires technical and legal expertise, the need for strong teamwork and knowledge sharing should not be overlooked. Nia Jenkins said her organization utilizes cross-functional teams, which can pull together privacy, governance, compliance, security, and other subject matter experts to gain a “line of sight into the data that’s coming in and going out of the organization.”“We also have an infrastructure where people are able to reach out to us to request access to certain data pools,” Jenkins said. “With that team, we are able to think through, is it appropriate to let that team use the data for their intended purpose or use?”In addition to collaboration, well-developed workflows are paramount too. Kimberly Pack explained that her company does have a formalized team that comes together on a bi-monthly basis and defined workflows that are improving daily. She emphasized that it all begins with “having clarity about how business gets done.”Jennifer Beckage highlighted the need for an organization to develop a plan, build a strong team, and understand the type and quality of the data it collects before adopting AI. Businesses have to address data retention, cybersecurity, intellectual property, and many other potential risks before taking full advantage of AI technology.Engage with internal and external experts to understand changing regulations Keeping up with a dynamic regulatory landscape requires expanding your information network. Pack was frank that it’s too much for one person to learn themselves. She relies on following law firms, becoming involved in professional organizations and forums, and connecting with privacy professionals on LinkedIn. As she continually educates herself, she creates training for various teams at her organization, including human resources, procurement, and marketing.“Really cascade that information,” said Pack. “Really try to tailor the training so that it makes sense for people. Also, try to have tools and infographics, so people can use it, pass it along. Record all your trainings because everyone’s not going to show up.”The panel discussed how their companies are using AI and whether there’s any resistance. Pack noted her organization has carefully taken advantage of AI for HR, marketing, enterprise tools, and training. She noted that providing your teams with information and assistance is key to comfort and adoption.“AI is just a tool, right?” Pack said. “It’s not good, it’s not bad.” The privacy team conducts a privacy impact assessment to understand how the business can use the technology. Then her team places any necessary limitations and builds controls to ensure the team uses the technology ethically. Pack and Jenkins both noted that the companies must proactively address potential bias and not allow automated decision-making.Evaluate the benefits and risks of AI for your organization The panel agreed organizations should adopt AI to remain competitive and meet consumer expectations. Pack pointed out the purpose of AI technology is for it to learn. Businesses adopting it now will see the benefits sooner than those that wait.Eric Pender noted advanced technologies are becoming more common for particular uses: cybersecurity breach response, production of documents, including privilege review and identifying Personally Identifiable Information (PII), and defensible disposal. Many of these tasks have tight timelines and require efficiency and accuracy, which AI provides.The risks of AI depend on the nature of the specific technology, according to Beckage. It’s each organization’s responsibility to perform a risk assessment, determine how to use the technology ethically, and perform audits to ensure the technology is working without unintended consequences.Facilitate innovation and growth It is also important to remember that in-house and outside counsel don’t have to be “dream killers” when it comes to innovation. Lawyers with a good understanding of their company’s data, technology, and ways to mitigate risk can guide their businesses in taking advantage of AI now and years down the road.Pack encouraged compliance professionals to enjoy the problem-solving process. “Continue to know your business. Be in front of what their desires are, what their goals are, what their dreams are, so that you can actively support that,” she said.Pender says companies are shifting from a reactive approach to a proactive approach, and advised that “data that’s been defensively disposed of is not a risk to the company.” Though implementing AI technology is complex and challenging, managing sensitive, personal data is achievable, and the potential benefits are enormous.Jenkins encouraged the “four B’s.” Be aware of the data, be collaborative with your subject matter experts, be willing to learn and ask tough questions of your team, and be open to learning more about the product, what’s happening with your business team, and privacy in an ever-changing landscape.Beckage closed out the webinar by warning organizations not to reinvent the wheel. While it’s risky to copy another organization’s privacy policy word for word, organizations can learn from the people in the privacy space who know what they’re doing well.ai-and-analytics; data-privacyprivilege, cybersecurity, ai-big-data, pii, blog, preservation, ai-and-analytics, data-privacyprivilege; cybersecurity; ai-big-data; pii; blog; preservationlighthouse
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New Rules, New Tools: AI and Compliance
We live in the era of Big Data. The exponential pace of technological development continues to generate immense amounts of digital information that can be analyzed, sorted, and utilized in previously impossible ways. In this world of artificial intelligence (AI), machine learning, and other advanced technologies, questions of privacy, government regulations, and compliance have taken on a new prominence across industries of all kinds.With this in mind, H5 recently convened a panel of experts to discuss the latest compliance challenges that organizations are facing today, as well as ways that AI can be used to address those challenges. Some key topics covered in the discussion included:Understanding use cases involving technical approaches to data classification.Exploring emerging data classification methods and approach.Setting expectations within your organization for the deployment of AI technology.Keeping an AI solution compliant.Preventing introducing bias into your AI models.The panel included Timia Moore, strategic risk assessment manager for Wells Fargo; Kimberly Pack, associate general counsel of compliance for Anheuser-Busch; Alex Lakatos, partner at Mayer Brown; and Eric Pender, engagement manager at H5; The conversation was moderated by Doug Austin, editor of the eDiscovery Today blog.Compliance Challenges Organizations Are Facing TodayThe rapidly evolving regulatory landscape, vastly increased data volumes and sources, and stringent new privacy laws present unique new challenges to today’s businesses. Whereas in the recent past it may have seemed liked regulatory bodies were often in a defensive position, forced to play catch-up as powerful new technologies took the field, these agencies are increasingly using their own tech to go on the offensive.This is particularly true in the banking industry and broader financial sector. “With the advent of fintech and technology like AI, regulators are moving from this reactive mode into a more proactive mode,” said Timia Moore, strategic risk assessment manager for Wells Fargo. But the trend is not limited to banking and finance. “It’s not industry specific,” she said. “I think regulators are really looking to be more proactive and figure out how to identify and assess issues, because ultimately they’re concerned about the consumer, which all of our companies are and should be as well.”Indeed, growing demand by consumers for increased privacy and better protection of their personal data is a key driver of new regulations around the world, including the General Data Protection Regulation (GDPR) in the European Union and the California Consumer Privacy Act (CCPA) and various similar laws in the United States. It’s also one of the biggest compliance challenges facing organizations today, as cyber attacks are now faster, more aggressive, and more sophisticated than ever before.Other challenges highlighted by the panel included:Siloed departments that limit communications and visibility within organizationsA dearth of subject matter expertiseThe possibility of simultaneous AI requests from multiple regulatory agenciesA more remote and dispersed workforce due to the pandemicUse Cases for AI and ComplianceIn order to meet these challenges head on, companies are increasingly turning to AI to help them comply with new regulations. Some companies are partnering with technology specialists to meet their AI needs, while some are building their own systems.Anheuser-Busch is one such company that is using an AI system to meet compliance standards. As Kimberly Pack, associate general counsel of compliance for Anheuser-Busch, described it: “One of the things that we’re super proud of is our proprietary AI data analyst system BrewRight. We use that data for Foreign Corrupt Practices Act compliance. We use it for investigations management. We use it for alcohol beverage law compliance.”She also pointed out that the BrewRight AI system is useful for discovering internal malfeasance as well. “Just general employee credit card abuse…We can even identify those kinds of things,” Pack said. “We’re actively looking for outlier behavior, strange patterns or new activity. As companies, we have this data, and so the question is how are we using it, and artificial intelligence is a great way for us to start being able to identify and mitigate some risks that we have.”Artificial intelligence can also play a key role in reducing the burden from alerts related to potential compliance issues or other kinds of wrongdoing. The trick, according to Alex Lakatos, partner at Mayer Brown, is tuning the system to the right level of sensitivity—and then letting it learn from there. “If you set it to be too sensitive, you’re going to be drowned in alerts and you can’t make sense of them,” Lakatos said. “You set it too far in the other direction, you only get the instances of the really, really bad conduct. But AI, because it is a learning tool, can become smarter about which alerts get triggered.”Lakatos also pointed out that when it comes to the kind of explanations for illegal behaviors that regulators usually want to see, AI is not capable of providing those answers. “AI doesn’t work on a theory,” he said. “AI just works on correlation.” That’s where having some smart people working in tandem with your AI comes in handy. “Regulators get more comfortable with a little bit of theory behind it.”H5 has identified at least a dozen areas related to compliance where AI can be of assistance, including: key document retention and categorization, personal identifiable information (PII) location and remediation, first-line level reviews of alerts, and policy applicability and risk identification.Data Classification, Methods, and ApproachesThere are various methods and approaches to data classification, including machine learning, linguistic modeling, sentiment analysis, name normalization, and personal data detection. Choosing the right one depends on what companies want their AI to do.“That’s why it’s really important to have a holistic program management style approach to this,” said Eric Pender, engagement manager at H5. “Because there are so many different ways that you can approach a lot of these problems.”Supervised machine learning models, for instance, ingest data that’s already been categorized, which makes them great at making predictions and predictive models. Unsupervised machine learning models, on the other hand, which take in unlabeled, uncategorized information, are really good at data pattern and structure recognition.“Ultimately, I think this comes down to the question of what action you want to take on your data,” Pender said. “And what version of modeling is going to be best suited to getting you there.”Setting Expectations for AI DeploymentOnce you’ve determined the type of data classification that best suits your needs, it’s crucial to set expectations for the AI deployment within your company. This process includes third-party evaluation, procurement, testing, and data processing agreements. Buying an off-the shelf solution is a possibility, though some organizations—especially large ones—may have the resources to build their own. It’s also possible to create a solution that features elements of both. In either case, obtaining C-suite buy-in is a critical step that should not be overlooked. And to maintain trust, it’s important to properly notify workers throughout the organization and remain transparent throughout the process.Allowing enough time for proper proof of concept evaluation is also key. When it comes to creating a timeline for deploying AI within an organization, “it’s really important for folks to be patient,” according to Pender. “People who are new to AI sometimes have this perception that they’re going to buy AI and they’re going to plug it in and it just works. But you really have to take time to train the models, especially if you’re talking about structured algorithms and you need to input classified data.”Education, documentation, and training are also key aspects of setting expectations for AI deployment. Bear in mind, at its heart implementing an AI system is a form of change management.“Think about your organization and the culture, and how well your employees or impacted team members receive change,” said Timia Moore of Wells Fargo. “Sometimes—if you are developing that change internally, if they’re at the table, if they have a voice, if they feel they’re a meaningful part of it—it’s a lot easier than if you just have some cowboy vendor come in and say, ‘We have the answer to your problems. Here it is, just do what we say.’”Keeping AI Solutions Compliant and Avoiding BiasWhen deploying an AI system, the last area of consideration discussed by the panel was how to keep the AI solution itself compliant and free of bias. Best practices include ongoing monitoring of the system, A/B testing, and mitigating attacks on the AI model.It’s also important to always keep in mind that AI systems are inherently dependent on their own training data. In other words, these systems are only as good as their inputs, and it’s crucial to make sure biases aren’t baked into the AI from the beginning. And once the system is up and running—and learning—it’s important to check in on it regularly.“There’s an old computer saying, ‘Garbage in, garbage out,’ said Lakatos. “The thing with AI is people have so much faith in it that it is become more of ‘garbage in, gospel out.’ If the AI says it, it must be true…and that’s something to be cautious of.”In today’s digital world, AI systems are becoming more and more integral to compliance and a host of other business functions. Educating yourself and making sure your company has a plan for the future are essential steps to take right away.The entire H5 webcast, “New Rules, New Tools: AI and Compliance,” can be viewed here.ai-and-analytics; data-privacyccpa, gdpr, blog, ai, big-data, -data-classification, fcpa, artificial-intelligence, compliance, ai-and-analytics, data-privacyccpa; gdpr; blog; ai; big-data; data-classification; fcpa; artificial-intelligence; compliancemitch montoya
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More Than a Seat at the Table: Women Leaders in LegalTech on Gender Equity Part Two
Building on our conversation from part one, we explore some practical advice and steps for achieving equity, including the role of allies, and how this work will benefit us in the future.True equity in the workplace starts from the topWhile grassroot employee efforts can be impactful, they will never be enough if diversity is not exemplified and valued at the highest levels of an organization. This means that it is not enough for leaders to verbalize a commitment to diversity and inclusion campaigns. Leaders must also back up that commitment with action: In times of economic volatility, companies can and should continue to devote a portion of their budget to equity and inclusion initiatives, and make sure these initiatives are supported by senior leadership. — Brooke OppenheimerWhen you have leadership at the top that truly values diversity and equity in all its forms— gender diversity, racial diversity, sexual orientation diversity, etc.— that priority will flow down from the leadership to the rest of company. It is incumbent on organizations to ensure their leaders are prioritizing diversity, because the rest of the organization will follow what the leadership is exemplifying. — Ashley BaynhamWhen you have strong leadership serving in the capacity of championing equity in the workplace on a day-to-day basis, it not only sets a tone and expectation across the organization that diversity is top of mind, but it becomes seamless to follow in their footsteps. —Jeannie E. FarrenThis means that, in order to become truly equitable, organizations have a duty to break up inequitable leadership structures. Historically in corporate America, we have seen an abundance of white, hetero, male leaders in positions of power. It’s hard to think of achieving true equity within the legal industry if that power structure at the top is not diverse. To make that change, it becomes incumbent on those leaders to stand up and say, “I want to lead an organization that doesn’t just resemble me. I want to lead an organization that more strongly resembles this country as whole.” —Michelle Six Lack of gender diversity in certain roles perpetuates existing biases, leading to inadequate representation in leadership positions. —Brooke OppenheimerThis duty also applies to individual leaders. Leaders have a responsibility to not only leave the door open for women and other underrepresented groups, but also to proactively help diversify inequitable power structures:If you are fortunate enough to be trusted to be in a leadership role within your organization, you have an ongoing responsibility to continuously assess how you are applying fairness across the team on a day-to-day basis. Look around your team and make sure that the “shiny” opportunities are being spread evenly across the team and that the women on your team are being provided with the chance to be in the spotlight as often as possible. — Jeannie E. FarrenThat idea leads directly to an essential point about the power of allies…Allies are integral to the fight for gender equityTrue gender equity cannot be achieved by women alone. Equity can only be achieved when women and allies come together to support individual women and push for progress, together. If you are surrounded by people in your (personal and professional) life who share a common goal as important as equity for all, you have already accomplished one of the most difficult hurdles. — Jeannie E. FarrenBecause of longstanding historical and systemic gender inequities, our allies are often in a better position within an organization to effect real change. It is therefore imperative that allies remain vigilant, proactive, and unafraid to call out gender biases and inequities when they occur. As an ally, stay cognizant of some of the ways that unconscious or conscious gender bias can play out in the workplace. For example, if you see someone cutting off a colleague in a meeting, speak up. It becomes very hard to constantly have to champion yourself or work to overcome those gender biases on our own. And for women, there’s always a concern that championing yourself comes off as self-promotion. That’s where a third party may be in a better position to stand up and raise their voice as ally. So, my advice for allies would be: Speak up, in the moment that your voice is needed.” — Ashley BaynhamTo help facilitate this, organizations committed to diversity and inclusion can put systems in place that make it easier for individuals and allies to report instances of gender bias when it occurs.When we witness inequities, we may not stand up because we think that “others” have already raised the issue. But oftentimes, the bystander effect is at play—which leads to no one saying anything at all. This demonstrates the value of having established channels of communication so that people know who they can go to for help. It also shows us that we all have to be comfortable being a little uncomfortable if we want to fight for an equitable workplace for all. —M. Alexandra BillebIn this way, advocates and allies can create an environment that fosters organizational-wide accountability and responsibility in the fight for gender equity.Each of us can contribute in ways large and small to ensure that it isn’t just the person with the loudest voice or most senior title who is heard. And we should point out ways in which individuals and organizations are not living up to those principles. It is not enough to say what is important to us. We have to hold each other accountable when we fall short. — M. Alexandra Billeb Gender equity requires the creation of an inclusive culture that does not tolerate inequity and that supports, champions, and encourages women's contributions. —Brooke Oppenheimer It is critical to champion equity and inclusion more broadly in order to expand upon gender allies through standing up support groups and creating measurable data points for accountability. — Jeannie E. FarrenThis community of advocates and allies, committed to a culture of accountability, has a much better chance at rectifying some of the most challenging and persistent gender equity issues—for example wage inequity:One of things we can look for from our allies with decision making power is better wage transparency— so that we can more effectively advocate for better wage consistency. One of the biggest barriers to gender equity in the legal profession is unequal compensation. The gender-based wage gap still remains and the legal industry has more work to do in this regard. I believe that greater salary transparency across the legal industry will potentially lead to more wage equity, which is a goal we should all prioritize. — Michelle Six Conclusion While there are still significant obstacles ahead, our conversation with these industry leaders demonstrated that by consistently championing equity goals, women and allies can continue the progress that generations of women have made before us towards a more gender equal world. diversity-equity-and-inclusionblog, dei, diversity-equity-and-inclusionblog; deisarah moran
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More Than a Seat at the Table: Women Leaders in LegalTech on Gender Equity
This year’s International Women’s Day theme is “embracing equity.” The theme challenges us to consider why “equal opportunities are not enough” and reminds us that allies are “incredibly important for the social, economic, cultural, and political advancement of women.”This challenge, presented to both women and allies alike, to keep striving for gender equity and resist settling into complacency seems particularly fitting in 2023. The past year has brought with it a growing acceptance that the only constant we can depend on is change. Three years after a global pandemic altered our world, there seems to be a growing acceptance that this constant state of unpredictability and volatility across the global economic, social, political, and ecological environments, may be “the new norm” we all talked about in 2020. This broader acceptance of instability brings with it a silver lining: A parallel realization that we cannot afford to wait for “things to return to normal” in order to continue fighting for gender equity. If we do, we risk backsliding and losing the ground that generations of women before us fought so hard to gain. For example, studies have shown that women and girls are more negatively impacted by global economic crises than men, and that the recent rise in inflation rates more negatively impacts women than men. Now more than ever, it is imperative to remain focused on the fight for gender equity. In celebration of International Women’s Day, Lighthouse invited six leaders in the legal industry to provide their perspectives and advice on this topic:Ashley Baynham, Senior Counsel, Litigation, Kaiser PermanenteM. Alexandra Billeb, Senior Practice Manager, Cleary Gottlieb Steen & Hamilton LLPJeannie E. Farren, Director of Case Management and Technology | eDiscovery and Information Governance, MetaKayann Fitzgerald, Director of eDiscovery & Practice Technologies, Davis Wright Tremaine LLP Brooke Oppenheimer, Counsel, eDiscovery, Cyber & Data Protection, Axinn Veltrop & HarkriderMichelle Six, Partner, Litigation, Kirkland & EllisThey have each consistently championed women while fighting for broader equity and inclusion within their own careers and practices. Lighthouse is honored to highlight the valuable insight these leaders provided regarding the current state of gender equity and how we can all continue to strive for progress.In part one of our series, we explore what gender equity means in 2023 and its impact on work and life. And tomorrow, part two will highlight practical advice for achieving greater equity and its benefits in the future. True gender equity is more than a woman’s presence in a conference roomBefore we can discuss how to move forward, we must first define the goal: What would it mean to achieve true gender equity? The overwhelming consensus was that in 2023, a woman’s mere presence in a meeting is not a realization of ‘gender equity.’ Rather, true gender equality comes when women not only have a seat at table, but an equal voice in the conversation: Gender equity is an intentional awareness that creates the fairness in that “seat at the table” where ideas, views and decisions are exchanged and made. While progress has been made, we still have a long way to go as a society to ensure women’s voices are heard and regarded, not ignored and unnoticed. In the words of the late Honorable Ruth Bader Ginsburg, "Women belong in all places where decisions are being made… It shouldn't be that women are the exception."—Kayann FitzgeraldTrue gender equity would mean that women would never have to walk into a conference room wondering what percentage of the participants will be women. It would mean women would never have to wonder if their compensation was equal to that of a male counterpart. The fact that we must still be counted or tallied as “women lawyers” or “women in the industry” is a sign that we have not yet achieved parity. We still have an asterisk next to our name. True gender equity would mean we could eliminate that asterisk. —Michelle SixEquity for women is having a seat at the table, a voice that is heard, listened to, and respected and equal access to opportunities for leadership. —M. Alexandra BillebAchieving equity for women includes ensuring women have a seat at the table, participate in decision-making, and have their perspectives and contributions valued and respected. —Brooke OppenheimerWith that vision for gender equity in mind, our featured leaders provided a few key suggestions for individuals and organizations seeking to create a more gender equal environment. Recognize the true value of our differencesA surprising first step toward creating a truly equal environment may be to recognize our differences. At its core, diversity means variety. It means there are real immutable differences between gender identification, between races, between religions, between sexual orientations, between nationalities, etc. Rather than trying to erase those differences, individuals and companies must recognize those differences:A truly equitable world would not only give equal opportunities to women in the workplace—it would also be fully appreciative of our differences. If you look across certain industries where equal opportunities are given, there's still minimal accounting for societal and biological differences between women and men. Those differences may take a variety of forms. For example, differences in the economic status between men and women due to systemic pay inequities, differences in the mental and physical workload women often carry compared to male partners in family units, differences in the communications styles due to generational gender bias and social pressure on women, etc. A truly equitable workplace must recognize and account for those differences. —Ashley BaynhamOnly once we recognize our differences, can we then recognize and account for the true value (both intangible and monetary) those differences bring to the table:Gender equity and other diversity and equity efforts should not be relegated to a ‘nice to have’ or be put on a shelf during times of economic volatility. Having different and diverse voices represented in the room provides a real and significant value to our clients and to the business as a whole. Without it, we retreat into the predictability of hearing the same voices over and over in an echo chamber. We miss out on new and innovative ideas and lose the potential to learn from a diverse group of people who bring different perspectives, experiences, and backgrounds to the table. —Michelle SixOnce the value of diversity is accounted for, companies and law firms are less likely to marginalize equity efforts during times of economic volatility. Recognize that gender equity is not just a “women’s rights issue”In the same vein, individuals and companies are more likely to focus on rectifying gender inequities when they can clearly see how these solutions will be beneficial to a broader group. There are systemic equity issues that I don’t know how we will address as individual organizations until there is a shared societal understanding that these are issues that affect everyone—this is an obstacle at the very core. —M. Alexandra BillebWe must stay focused on providing opportunities and platforms to empower women to build each other up, while continuing to tear down stereotypes and create cultures focused on the equity mission. The quote, “Gender equality is not a woman’s issue, it is a human issue. It affects us all,” speaks loudly to this point. —Kayann Fitzgerald Historically, we have seen this dynamic play out on a larger stage. When we look back at the history of women’s rights, we can see that the equity issues that women have been fighting for generations (equal educational and career opportunities, better and more affordable childcare options, financial and wage equity, etc.) are not specific to women—they are broader human rights issues.I am fortunate to have a mother who played a significant role to me and many others regarding equity for women. She continually encouraged and pushed against the status-quo during a time where it was more common for women to be married shortly out of high school, have children, and don the homemaker hat. She networked before networking was a thing, created an enviable career in her chosen profession (nursing) while raising three children…all while scratching, clawing, and climbing the equity ladder, bringing along many a female colleague with her. —Kayann Fitzgerald Any progress that previous generations of women have made toward gender equity has exponentially made the world a better, more equitable place for everyone. Equity for women was instilled in me (by my mother) and has deeply influenced my professional endeavors…and now I have a front row seat watching my two daughters create their respective paths and define their “seat at the table.” This awareness, empowerment, and creating access to opportunities is paramount in forming a truly equitable society. —Kayann Fitzgerald Once viewed in this lens, it is easy to recognize how the work we do today to close gender equity gaps will positively impact future generations, regardless of gender. In fact, many of our featured industry leaders recommend focusing on the next generation as one the best ways to make impactful and real change. No matter our gender or background, we all desire to live in a world where our children are not negatively impacted by stereotypes or biases.A truly equitable world for women would be one where gender roles are not engrained into young girls, where young women are encouraged to pursue any career that interests them, not just ones which are stereotypically earmarked for women. —Brooke Oppenheimer I see society evolving from generation to generation in terms of how people think about gender and gender norms. I think the biggest impact we can have on the creation of a more equitable society for women continues to push for that evolution—and that starts with our children. It means stamping out perceptions of gender bias in young kids, and remaining cognizant of the unconscious biases that can develop in children. It means working to ensure that my young son and daughter know they can both play with dolls and they can both play with trucks. We need to continue to evolve past the idea from older generations that "this is for boys and this is for girls." —Ashley BaynhamThis recognition of the universally beneficial impact of closing gender equity gaps is also exemplified in in other areas traditionally associated with the fight for gender equality. For example, one area of significant improvement noted by many of our featured industry leaders was a change to more flexible work environments. Law firms especially have typically required associates to work long hours in an office in order to secure a partnership. Because women have traditionally held the role of primary caregivers in family structures, this requirement led to a high percentage of women dropping out of big law in favor of less structured work environments. For this reason, prior to the COVID-19 pandemic, the fight for more flexible schedules and remote work options was often primarily framed as a gender equity issue. But when the world shut down in 2020, millions of employees experienced the benefits of more flexible work environments, and pushed back against returning to offices and rigid schedules once pandemic restrictions began to fade. In terms of improvement, I think that flexible work arrangements have been a real silver lining of the COVID pandemic. We have proven, over and over, that we can be effective at our jobs at home as well as in the office and early in the morning as well as late at night. Successful organizations will be those that understand we can’t go back to 2019 with 9 to 5 schedules worked on site. —M. Alexandra BillebBecause a broader spectrum of people began to contemplate, recognize, and advocate for the benefits of flexible schedules and remote work options, organizations were pressured to make real, structural changes. In the same vein, many law firms and corporations have also made progress in broadening “maternity leave” to include “paternity leave” or “family leave,” due in part to the increasing diversity of modern family structures. Because there are now more voices advocating for the need for paid time off to spend with new children (beyond just the traditional paradigm of mothers who gave birth to biological children), many companies have begun to broaden their parental leave benefits. In turn, as more people experience the benefit paid time off provides to new parents and children, we can expect increasing advocacy for companies to open that same door for other types of caregivers.I have seen great improvement in work flexibility and a huge commitment to maternity and family leave for both men and women. However, I know that the private sector still fails to position family leave equally. Whether you’re adopting an infant or a teenager, giving birth via surrogacy, or caring for an elderly or sick family member—all of those scenarios should be afforded the same types of family leave options that an employer provides to any employee. We should be striving for a world where there is a uniform family leave policy. —Michelle SixTo impact change more quickly, women and allies can highlight the broader benefits of closing gender equity gaps. For instance, women often face higher rates of workplace burnout caused by remote working because we are still statistically more likely to be considered the primary caregiver in family structures: Working remotely for women in particular has essentially blurred all of the lines and guardrails that use to separate home-life responsibilities from work-life responsibilities. I’m seeing burnout now more than ever before, and it has forced me to become more thoughtful and creative around meeting the women on my team exactly where they are in life. This is a moment in time where we have to allow people to own their schedule, to have the flexibility to be present in their lives in ways deemed most important to them, to blaze their own unique trail and to write their own story. —Jeannie E. FarrenWhile this issue may impact more women than men, it is easy to see how guidelines and tactics that help define clearer boundaries between home and work would be universally beneficial to all remote workers, regardless of gender identity. The same can be said for broader issues that statistically have a greater and more adverse impact on women, like the pressure to cover gaps in school schedules:A significant obstacle to gender equality actually lies in the mismatch between school systems and the reality of modern work environments. In order to have career advancement, you have to be showing up at work— undistracted and focused. Unfortunately, our school systems are still working off a 1940s/1950s model of having one parent at home. That simply is not the reality for most families today. Because women often still tend to carry the physical and mental load of being the primary caregiver in a family, that school structure puts added pressure on women to work around school schedules. This pressure often includes taking more time from work than male partners to accommodate weeks of school holidays and vacations, school start, and dismissal times that do not align with traditional work schedules, etc. And those obstacles and pressure impact people with lesser means much, much harder. —Ashley Baynham Here again, while the issue may impact more women than men, it is easy to see how a better, more modern school system would benefit not only women, but children, families, and those with limited or lesser incomes. Ultimately, then, the fight for gender equity is a fight for equity for all, regardless of gender identity: I believe one the biggest obstacles in advancing equity in the workplace is assumptions. In 2023, we need to remove conventional gender roles, especially post-pandemic, to realign, invest, and lean in on workplace equity. —Kayanne FitzgeraldOnce we can quantify and recognize the value gender equity provides to women and others, the next step is to find practical ways to minimize gender equity gaps. In part two of our series, our featured industry leaders discuss tips and advice for helping us achieve these goals.diversity-equity-and-inclusionblog, dei, diversity-equity-and-inclusionblog; deisarah moran
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Managed Services for Law Firms: The Six Pillars of a Successful Managed Service Relationship
By Steven L. Clark, E-Discovery and Litigation Support Director, Dentons and John Del Piero, Vice President, LighthouseWhether your firm is just beginning to consider a move to a managed service eDiscovery model or you’re a managed service veteran, it is imperative to understand what makes this type of eDiscovery program model successful. After all, if you don’t know how to measure success, it will be difficult to know what to look for when selecting a provider, and equally as hard to monitor the quality of the services provided once you have selected one.However, measuring success can be complex. There are many different metrics that could be used to measure success and each may be of a varying level of importance to different firm stakeholders, as the priorities of these stakeholders will be determined by their particular role and focus. However, a successful managed service partnership can be based on a foundation of six core pillars. These pillars can be used as guideposts when evaluating whether a managed service partner will truly add value to a law firm’s eDiscovery process.Pillar 1: Access to Best-of-Breed Technology and Teams of Experts to Help Leverage ItA managed service partnership should always make a law firm (and its clients) feel like the best eDiscovery technology is right at their fingertips. But more than that, a successful managed service relationship should enable a law firm to stay technologically agile, while lowering technology costs.For example, if an eDiscovery tool or platform becomes obsolete or outdated, the firm’s managed service partner should be able to quickly move the firm to better technology, with little cost to the firm. In other words, in a successful managed service partnership, gone are the days where a litigation support team was stuck using an obsolete platform simply because the law firm purchased an enterprise license for that technology. Rather, the managed service partner should bear the cost burden of leveraging continuously evolving technology because the partner can easily spread that technological risk across its client base. In assuming this burden, the managed services partner ultimately provides law firms much greater flexibility in terms of leveraging the most appropriate technology to meet their clients’ needs.In addition to simply providing access to the best technology, a successful managed service partnership should also provide teams of experts who are wholly dedicated to helping law firms leverage that technology for optimal impact. These experts should be continuously vetting new applications and technology upgrades, enabling litigation support teams to stay up to date on evolving applications and tools. These teams will also be able to create and test customized workflows that enable law firms to handle how data flows through technically robust collaborative platforms like Microsoft Teams or Slack, as well as keep firms apprised of any updates to cloud-based platforms that may affect existing eDiscovery workflows.This type of devoted technological expertise and guidance can provide firms a significant competitive boost, as internal litigation support teams rarely have the resources available to devote staff solely to testing new technology and building customized workflows.Pillar 2: A Scalable and More Diversified eDiscovery Team In comparison to a traditional law firm litigation support team which, naturally, is somewhat static in size, a successful managed service relationship allows law firm teams to quickly and seamlessly scale up or down, depending on case needs. For example, when a large matter comes in, a managed service provider should have the ability to quickly pull a project manager in to help manage the case while the internal law firm team still retains day-to-day control of the matter. This alleviates the firm from having to choose between hiring additional staff (only to be faced with too big of a team once the larger matter ends) or outsourcing the case to an external, inflexible eDiscovery provider (where the firm may be unable to retain full control of the matter and will undoubtedly have to adapt to different processes and workflows).A managed service partner’s bench should also be deep, allowing a law firm to pull from a diverse pool of expertise. Whether the law firm needs a review workflow expert or a processing expert, an analytics expert or a migration and normalization expert, a quality managed service provider should be able to swiftly provide someone who knows the teams involved and has the qualifications and technological background to ensure that all stakeholders trust their expertise and guidance.Pillar 3: eDiscovery Expertise 24/7/365A managed service provider should not only provide law firms with top-notch eDiscovery expertise but also provide access to that expertise whenever it is needed. Unfortunately, most litigation support teams are all too familiar with the fact that eDiscovery is almost never a 9 to 5 job. The nature of litigation today means that a Monday production deadline involving a terabyte of data may be doled out by a judge on a Friday morning, or that data for a pressing production may arrive at 9:00 p.m. The list of eDiscovery off-hour emergencies is somewhat endless.Unfortunately, most internal litigation support teams at law firms are located in one geographic area (and therefore, one time zone), meaning that even when internal teams have the required expertise, they may not have those resources available when they’re needed.A quality managed service partner, however, will be able to provide resources whenever they are needed because it can structure its hiring and team assignments with team members located across multiple time zones. Access to full-time eDiscovery expertise and coverage enables law firms to swiftly handle any eDiscovery task with ease, with no permanent increase in staffing overhead.Pillar 4: Less Talent Acquisition RiskA successful managed service relationship should also significantly lower law firm risk related to talent acquisition and training. While hiring in today’s job climate may seem like a simple task, the cost of sufficiently vetting candidates and then providing the appropriate training can be incredibly time consuming and expensive.If law firm vetting misses a candidate red flag or even if a candidate just needs more training than expected, staffing costs and time expenses can skyrocket even further. For example, the task of having to substantially re-train a new hire from the ground up can take up the valuable time of other internal experts. In this way, even the most routine hire can often slow productivity and lower the morale of the entire internal team (at least in the short term) until the hire can be fully integrated into the department’s daily workflow.In a successful managed service relationship, however, the law firm can transfer those types of hiring and training risks directly to the provider. The managed service provider is already continuously evaluating, vetting, and training talent across different geographies in order to hire the best eDiscovery experts. Law firms can simply reap the benefit of this process by partnering with the service provider and leveraging that talent once the vetting and training process has been completed.Pillar 5: Lower Staffing Overhead To put it simply, all of the above means that moving to a managed service model should allow a law firm to significantly lower its overhead costs related to staffing and management. In addition to taking on the hiring risks, a managed service provider should also take on much of the overhead related to maintaining staff. From payroll, to benefits, to overtime costs, a quality managed service provider handles those costs and time expenses for their own on-staff experts, leaving the law firm free to reap the benefits of on-demand expertise without the staffing overhead costs.Pillar 6: Better Billing MechanicsMost law firms are not set up to bill eDiscovery services efficiently. eDiscovery billing has evolved over the last few years, and a quality managed service provider should be following suit and offering simplified, predictable cost models in order for law firms to pass that predictability on to their clients. This kind of simplified pricing enables all parties to understand exactly how much they are going to spend for the eDiscovery services provided. However, this billing structure differs significantly from the way traditional legal work is billed out, and most law firms’ billing infrastructures have not evolved to offer the same level of predictability or cost certainty. This is where a quality managed service provider can provide another benefit, by heavily investing its own resources into building out automated reporting, ticketing, and billing systems that can generate proformas and integrate into the firm’s existing billing systems.If a managed service provider can take care of these billing tasks, law firm teams can spend more time in furtherance of client work, rather than devoting resources into eDiscovery billing metrics and workarounds.SummaryAccess to and expertise in appropriate technology, flexible staffing models, lower overhead, and simplified pricing are the six pillars of a successful managed service partnership in a law firm setting. When all six of these pillars are in place, the managed service partnership will result in more satisfied internal and external law firm customers and an increasing caseload year after year. For more information or to discuss this topic, reach out to us at info@lighthouseglobal.com.legal-operations; ediscovery-reviewmanaged-services, blog, law-firm, legal-operations, ediscovery-reviewmanaged-services; blog; law-firmlighthouse
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Managing Your (Legal Ops) Budget with Five Simple Tips
Have you created, or were handed, a budget but you don’t know where to start? Or, have you managed a budget for a while but want some other perspectives on what to look for throughout the year? Well this is the post for you. As I mentioned in my prior post about creating budgets, I have managed budgets for a long time in legal, operations, and other departments, as well as gotten input on this topic from many peers. Below you will find five of my top tips.Align team goals with budget - The success of your budget increases if everyone is working toward the common goal of staying within that budget. As such, when creating your team goals as well as when creating an individual team member’s goals, they should all support what you have put in your budget. There are a number of ways to do this. First, you could put a specific goal – e.g., come within 5% of budget – in their personal goals. You could also tie a part of an employee’s bonus to the department meeting its budget. Second, you could make the goals a bit more indirect by having each employee have a goal around coming up with cost-savings measures. Finally, you could be even less direct by just ensuring that nobody has goals related to projects that do not have any budget and that all funded projects do have owners. I use all three of these concepts in combination to set up the department for budget success.Operationalize your budget review - Reviewing your spend (actuals) against your budget on a monthly basis is critical to being able to stay on budget. You should involve your team in these budget reviews. The agenda should include an update on the prior month’s spend, a discussion of anything unusual from the prior month, and a discussion about any expectations for the coming month. Be open during these discussions and encourage people to speak up. You want to foster a positive environment where people feel comfortable bringing up anything that will impact the budget. Every team member should understand how their work impacts the budget. Any team member heading up a particular project should understand the budget of that project and where they are vis-à-vis budget. Transparency of this information will allow people to make well-informed decisions.Constantly look for ways to get better – automation and different suppliers - Even if you are at or under budget, it is important to continuously look for ways to get more efficient with resources. This can be done in conjunction with monthly budget reviews as your team will likely have some great suggestions. There are three main questions I ask:What can be automated? What can be outsourced?Are there opportunities to get better pricing from any outsourced providers (including technology)?Of these three, I lean towards automation because of the dramatic cost savings over time, but also the additional benefits. Automation will typically have an initial cost to fund the development effort. However, that initial investment can eliminate certain resources for a long period, sometimes even bringing ongoing costs to $0. Automation also can provide information, such as auditing and data, that were not available with manual methods. For example, implementing an e-billing solution not only saves on the people cost for reviewing bills, but also gives better visibility into where the money is being spent, leading to new areas for savings.Always have a plan B and C - Things change as the year goes on – revenue may not come in as expected, there could be a global pandemic that impacts your business, or you could decide to fund a higher priority business item – and you may be asked to change or reduce your budget. This can be frustrating but you should be ready for unexpected changes. The first thing you can do to be ready is to know what you will cut first, second, and third, etc. When you have a prioritized list, you can respond to any budget cuts or freezes pretty quickly. Second, you should have alternative, cheaper ways to still move forward on your top legal department strategy or strategies. For example, instead of hiring a full-time employee to manage and implement your e-billing system, perhaps you can hire a temporary employee, consultant, or an intern to move you forward on the research and design phases. Also consider whether you can move forward with any projects in phases or by doing a scaled back proof of concept first. For example, you could procure fewer licenses of your e-billing system and implement it for only 10% of matters (e.g., litigations over $1M). Both of these moves will allow you to still advance your project, but for a lower cost. The proof of concept also has the added benefit of allowing you to demonstrate the value of the project to the business, thereby making any associated budget requests for a full-scale implementation easier to get approved.Communicate changes early - A budget is an estimate based on your knowledge at one point in time. It won’t be perfect and you will have to make changes. Make sure you understand the process to communicate those changes. As soon as you have knowledge of anything that will be significantly under or over budget, which you will likely get from your monthly budget review, make sure to communicate that. If it is something that will put you over budget, make sure to have the details about why the spend is necessary, what alternative options you have looked into, and what benefits will come to the business from this spend. The threshold for when to communicate these changes differs at each organization so be sure to work with your partners in the finance organization to understand what is expected at your organization.legal-operationsediscovery-process, legal-ops, blog, legal-operations,ediscovery-process; legal-ops; bloglighthouse
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Minimizing Self-Service eDiscovery Software Tradeoffs: 3 Tips Before Purchasing
Legal professionals often take for granted that the eDiscovery software they leverage in-house must come with capability tradeoffs (i.e., if the production capability is easy to use, then the analytics tools are lacking; if the processing functionality is fast and robust, then the document review platform is clunky and hard to leverage, etc.).The idea that these tradeoffs are unavoidable may be a relic passed down from the history of eDiscovery. The discovery phase of litigation didn’t involve “eDiscovery” until the 1990s/early 2000s, when the dramatic increase in electronic communication led to larger volumes of electronically stored information (ESI) within organizations. This gave rise to eDiscovery software that was designed to help attorneys and legal professionals process, review, analyze, and produce ESI during discovery. Back then, these software platforms were solely hosted and handled by technology providers that weren’t yet focused entirely on the business of eDiscovery. Because both the software and the field of eDiscovery were new, the technology often came with a slew of tradeoffs. At the time, attorneys and legal professionals were just happy to have a way to review and produce ESI in an organized fashion, and so took the tradeoffs as a necessary evil.But eDiscovery technology, as well as legal professionals’ technological savvy, has advanced light years beyond where it was even five years ago. Many firms and organizations now have the knowledge and staff needed to move to a “self-service, spectra” eDiscovery model for some or all of their matters – and eDiscovery technology has advanced enough to allow them to do so. Unfortunately, despite these technological advancements, the tradeoffs that were so inherent in the original eDiscovery software still exist in some self-service, spectra eDiscovery platforms. Today, these tradeoffs often occur when technology providers attempt to develop all the technology required in an eDiscovery platform themselves. The eDiscovery process requires multiple technologies and services to perform drastically different and overlapping functions – making it nearly impossible for one company to design the best technology for each and every eDiscovery function, from processing to review to analytics to production.To make matters worse, the ramifications of these tradeoffs are much wider than they were a decade ago. Datasets are much larger and more diverse than ever before – meaning that technological gaps that cause inefficiency or poor work product will skyrocket eDiscovery costs, amplify risk, and create massive headaches for litigation teams. But because these types of tradeoffs have always existed in one form or another since the inception of eDiscovery, legal professionals still tend to accept them without question.But rest assured best-in-class technology does exist now for each eDiscovery function. The trick is being able to identify the functionality that is most important to your firm or organization, and then select a self-service, spectra eDiscovery platform that ties all the best technology for those functions together under one seamless user interface.Below are three key steps to prepare for the research and purchasing process that will help drastically minimize the tradeoffs that many attorneys have grown accustomed to dealing with in self-service, spectra eDiscovery technology. Before you begin to research eDiscovery software, you’ve got to fully understand your firm or organization’s needs. This means finding out what eDiscovery technology capabilities, functionality, and features are most important to all relevant stakeholders. To do so:Talk to your legal professionals and lawyers about what they like and dislike about the current technology they use. Don’t be surprised if users have different (or even opposing) positions depending on how they use the software. One group may want a review platform that is scaled down without a lot of bells and whistles, while another group heavily relies on advanced analytics and artificial intelligence (AI) capabilities. This is common, especially among groups that handle vastly different matter types, and can actually be a valuable consideration during the evaluation process. For instance, in the scenario above, you know you will need to look for eDiscovery software that can flex and scale from the smallest matter to the largest, as well as one that can create different templates for disparate use cases. In this way, you can ensure you purchase one self-service, spectra eDiscovery software that will meet the diverse needs of all your users.Communicate with IT and data security teams to ensure that any platform conforms with their requirements.These two groups often end up being pulled into discussions too late once purchasing decisions have already been made. This is unfortunate, as they are integral to the implementation process, as well as to ensuring that all software is secure and meets all applicable data security requirements. Data security in eDiscovery is non-negotiable, so you want to be sure that the eDiscovery technology software you select meets your firm or organization’s data security requirements before you get too far along in the purchasing process.Create a prioritized list of the most important capabilities, functionality, and attributes to all the stakeholders once you’ve gathered feedback.Having a defined list of must-haves and desired capabilities will make it easier to vet potential technology software and ultimately help you identify a technology platform that fits the needs of all relevant stakeholders.ConclusionWith today’s advanced technology, attorneys and legal professionals should not have to deal with technology gaps in their self-service, spectra eDiscovery software, just as law firms and organizations should not have to blindly accept the higher eDiscovery cost and risk those gaps cause downstream. Powerful best-in-class technology for each step of the eDiscovery process is out there. Leveraging the steps above will help you find a self-service, spectra eDiscovery software solution that ties all the functionality you need under one seamless, easy-to-use interface.For more detailed advice about navigating the purchasing process for self-service, spectra eDiscovery software, download our self-service, spectra eDiscovery Buyer’s Guide here. ediscovery-review; ai-and-analyticsself-service, spectra, review, analytics, processing, blog, production, ediscovery-review, ai-and-analyticsself-service, spectra; review; analytics; processing; blog; productionsarah moran
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Making the Case for Information Governance and Why You Should Address it Now
You know that cleaning out the garage is a good idea. You would have more storage space and would even be able to put the car into the garage, which is better for security, for keeping it clean, and for ensuring an easy start on a frozen winter morning. Even if you don’t have a garage, you likely have an equivalent example such as a loft or that cupboard in the kitchen, yet somehow these tasks are often put off and rarely top of the “to do” list. Information governance often falls in this category; a great idea that struggles to make it to the top ahead of competing corporate priorities.For both the garage and information governance, the issue is the creation of a compelling business case. For the garage, the arrival of a new car or a spate of car thefts in the area is enough to push this task to the front. For information governance, the business case might be that a company is enlightened enough to realize that its data is an under-utilized asset or it might be a question of time and effort being wasted in the struggle to find the information when needed. However, these positive drivers might not be enough. Sometimes you need to look at the risk if nothing is done.In our view, building a strong business case for information governance will be a laconic combination of both the carrot and the stick. This blog will focus on the stick because that is often the hardest factor to spell out in clear terms. We will take you on a journey through the GDPR fines that have been levied since it came into force in May 2018, show how European regulators see information governance as an essential element of a companies’ data protection obligations, and give you the necessary background to prepare your business case.Why address information governance now? It is worth just pausing to ensure we are all talking about the same thing, so let’s define information governance. You can see Gartner’s definition here. For our purposes, we can talk in simpler terms and define information governance as “the people, processes, and technology involved in seeking to ensure the effective and efficient creation, storage, use, retention, and deletion of information.”Now, let’s turn to the GDPR. The total of fines under the GDPR, since it came into force in May 2018, approaches €300m. The big fines usually relate to processing personal data without good reason or consent (e.g. Google - €50m), or for inadequate security leading to data breaches (e.g. British Airways - £20m). As a result, many organizations prioritize this type of work.However, after a thorough trawl, we see a growing body of decisions where fines have been imposed by regulators for information governance failures. In our view, the top 5 reported “information governance” fines are:€15m Deutsche Wohnen (Berlin DPA) – set aside on procedural grounds​€2.25m Carrefour (France)​€290,000 HUF (Hungary)​€250,000 Spartoo (France)​€160,000 Taxa4x35 (Denmark)​GDPR fines, in detailThe largest fine is the Deutsche Wohnen matter. In 2017, the Berlin Data Protection Authority (DPA) investigated Deutsche Wohnen and found its data protection policies to be inadequate. Specifically, personal data was being stored without a necessary reason and some of it was being retained longer than necessary. In 2019, the DPA conducted a follow-up investigation and found these issues were not sufficiently remedied and thus issued a fine of €15m. The Berlin DPA explained that Deutsche Wohnen could have readily complied by implementing an archiving system which separates data with different retention periods thereby allowing differentiated deletion periods, as such solutions are commercially available. In February 2021, Criminal Chamber 26 of the District Court of Berlin closed the proceedings on the basis the decision was invalid and not sufficiently substantiated. The Berlin DPA had not specified the acts by the management of the company that supposedly led to a violation of the GDPR. The Berlin DPA has announced it would ask the public prosecutor to file an appeal.​ It would be a mistake to interpret the nullification of the fine as evidence that information governance / data retention is not an important issue for DPAs. Such an interpretation would be ignoring that fact that there is no criticism as to the substance of the findings made by the Berlin DPA in relation to Deutsche Wohnen’s approach to data retention.Holding data without necessary purpose or not actively deleting data has been a theme of fines by other DPAs as well. In Denmark, the Data Protection Authority recommended fines for similar inadequacies as follows:1.2m DKK (€160,000) on Taxa4x35. A DPA inspection discovered that although customer names were deleted after 2 years, their telephone numbers remained for 5 (as a key field in the CRM database)1.1m DKK (€150,000) on Arp-Hansen Hotel Group. Personal data was being stored longer than was necessary and in breach of Arp-Hansen’s own retention policies​1.5m DKK (€200,000) on ID Design. A routine DPA inspection revealed old customer data not being adequately deleted.​ Although, like Deutsche Wohnen, this fine was subsequently reduced on technical grounds, the commentary on the corporate information governance policies still holds.In France, three fines have been imposed relating to the holding customer data well past what the regulators deemed necessary:In the Carrefour​ matter, there was a fine of €2.25m​ for various infringements including that Carrefour had retained the data of more than 28 million inactive customers, through its customer loyalty programme, for an excessive period.In SERGIC​, there was a fine of €400,000​ for various infringements including that SERGIC had stored the documents of unsuccessful rental candidates beyond the necessary time to achieve the purpose for which the data was collected and processed​.In Spartoo​, there was a fine of €250,000​ for reasons including that Spartoo retained data for longer than was necessary for more than 3 million customers​. In Spartoo, the regulators also called out that the company had not set up a retention period for customer and prospect data​, did not regularly erase personal data​, and retained names and passwords in a non-anonymised form for over 5 years​.Although the authorities in France and Denmark have been the most active, they are not alone. In Hungary, HUF​ was issued with a fine of approximately €290,000​ based on the absence of a retention policy for a database containing personal data. And in Germany, Delivery Hero failed to delete accounts of former customers who had not been active on the company’s delivery service platform for years ​and was fined €195,000.Other authorities may not yet have imposed fines, but their attention is turning in the direction of information governance. A number of DPAs have issued guidance, the scope of which includes data retention (e.g. the Irish DPA, in Sept 2020, on how long COVID contact details should be retained; the French DPA, in October 2020, on how long union-member files should be retained)​.How to get started on your business caseThere is a genuine threat to companies stalling in relation to information governance, particularly around personal data. The decisions to date represent a small percentage of the activity in this area, as many of the violations are dealt with by regulators directly. We don’t know what, if any, settlements have been agreed upon, but the decisions that we have located are helpful and instructive for building the business case for prioritizing this work.The first thing to do is create an internal overview for why this area matters – use the above to show that there is risk and that regulators are paying attention. Hopefully, our overview will help you to identify the size of the stick. As to the carrot, that will be very company-specific, but our clients who have successfully made the case focus on the efficiency gains that can be made if information is properly governed as well as the opportunity to mine more effectively their own information for its real business value. Next, take a look at your policies and areas that may require adjustment based on the above in order to gain some insight into the scale of the activity. Now your business case should be taking shape. You might also consider looking wider than the GDPR, such as the increasing number of state data protection frameworks within the US.We recognize this process is an oversimplification and each step requires a significant time investment by your organization, but spending time focusing on the necessity of retaining personal data, as well as the length of retention (and subsequent deletion), are critical elements in minimizing your risk.information-governancedata-privacy, blog, record-management, information-governance,data-privacy; blog; record-managementlighthouse
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Mitigating eDiscovery Risk of Collaboration Tools
Below is a copy of a featured article written by Kimberly Quan of Juniper Networks and John Del Piero of Lighthouse for Bloomberg Law.Whether it's Teams, Slack, Zendesk, GChat, ServiceNow, or similar solutions that have popped up in the market over the last few years, collaboration and workflow platforms have arrived. According to Bloomberg Law's 2020 Legal Technology Survey, collaboration tools are being used by 77% of in-house and 44% of law firm attorneys. These tools are even more widely used by workers outside of the legal field.With many companies planning to make remote working a permanent fixture, we can expect the existing collaboration tools to become even more entrenched and new competitors to arrive on the scene with similarly disruptive technologies.This will be a double-edged sword for compliance and in-house legal teams, who want to encourage technology that improves employee productivity, but are also wary of the potential information governance and eDiscovery risks arising because of these new data sources. This article explains the risks these tools can pose to organizations and provides a three-step approach to help mitigate those risks.Understand Litigation and Investigation RiskThe colloquial and informal nature of collaborative tools creates inherent risk to organizations, much like the move from formal memos to email did 20 years ago. Communications that once occurred orally in the office or over the phone are now written and tracked, logged, and potentially discoverable. However, a corporation's ability to retain, preserve, and collect these materials may be unknown or impossible, depending on the initial licensing structure the employee or the company has entered into or the fact that many new tools do not include features to support data retention, preservation, or collection.Government agencies and plaintiffs’ firms have an eye on these new applications and platforms and will ask specifically about how companies and even individual custodians use them during investigations and litigations. Rest assured that if a custodian indicates during an interview or deposition that she used the chat function in a tool like Teams or Slack, for example, to work on issues relevant to the litigation, opposing counsel will ask for those chat records in discovery. Organizations can mitigate the risk of falling down on their eDiscovery obligations because of the challenges posed bycollaboration tool data using this three-step approach:Designate personnel in information technology (IT) and legal departments to work together to vet platforms and providers.Develop clear policies that are regularly reviewed for necessary updates and communicated to the platform users.Ensure internal or external resources are in place to monitor the changes in the tools and manage associated retention, collection, and downstream eDiscovery issues.Each of these steps is outlined further below.Designate IT & Legal Personnel to Vet Platforms and Providers‍Workers, especially those in the tech industry, naturally want to be free to use whatever technology allows them to effectively collaborate on projects and quickly share information.However, many of these tools were not designed with legal or eDiscovery tasks in mind, and therefore can pose challenges around the retention, preservation and collection of the data they generate.Companies must carefully vet the business case for any new collaboration tool before it is deployed. This vetting process should entail much more than simply evaluating how well the tool or platform can facilitate communication and collaboration between workers. It also involves designating personnel from both legal and IT to work together to evaluate the eDiscovery and compliance risks a new tool may pose to an organization before it is deployed.The importance of having personnel from both legal and IT involved from the outset cannot be understated. These two teams have different sets of priorities and can evaluate eDiscovery risks from two different vantage points. Bringing them together to vet a new collaboration tool prior to deployment will help to ensure that all information governance and eDiscovery downstream effects are considered and that any risks taken are deliberate and understood by the organization in advance of deployment. This collaborative team can also ensure that preservation and discovery workflows are tested and in place before employees begin using the tool.Once established, this dedicated collaborative IT and legal team can continue to serve the organization by meeting regularly to stay abreast of any looming legal and compliance risks related to data generation. For example, this type of team can also evaluate the risks around planned organizational technology changes, such as cloud migrations, or develop workflows to deal with the ramifications of the near-constant stream of updates that roll out automatically for most cloud-based collaborative tools.Develop Clear Policies That Are Regularly Reviewed‍The number of collaborative platforms that exist in the market is ever evolving, and it is tempting for organizations to allow employees to use whatever tool makes their work the easiest. But, as shown above, allowing employees to use tools that have not been properly vetted can create substantial eDiscovery and compliance risks for the organization.Companies must develop clear policies around employee use of collaborative platforms in order to mitigate those risks. Organizations have different capabilities in restricting user access to these types of platforms. Historically, technology companies have embraced a culture where innovation is more important than limiting employees’ access to the latest technology. More regulated companies, like pharmaceuticals, financial services, and energy companies, have tended to create a more restrictive environment. One of the most successful approaches, no matter the environment or industry, is to establish policies that restrict implementation of new tools while still providing users an avenue to get a technology approved for corporate use after appropriate vetting.These policies should have clear language around the use of collaboration and messaging tools and should be frequently communicated to all employees. They should also be written using language that does not require updating every time anew tool or application is launched on the market. For instance, a policy that restricts the work-related use of a broad category of messaging tools, like ephemeral messaging applications, also known as self-destructing messaging applications, is more effective than a policy that restricts the use of a specific application, like Snapchat. The popularity of messaging tools can change every few months, quickly leading to outdated and ineffective policies if the right language is not used.Make sure employees not only understand the policy, but also understand why the policy is in place. Explain the security, compliance, and litigation-related risks certain types of applications pose to the organization and encourage employees to reach out with questions or before using a new type of technology.Further, as always with any policy, consider how to audit and police its compliance. Having a policy that isn't enforced issometimes worse than having no policy at all.Implement Resources to Manage Changes in Tools‍Most collaboration tools are cloud-based, meaning technology updates can roll out on a near-constant basis. Small updates and changes may roll out weekly, while large systemic updates may roll out less frequently but include hundreds of changes and updates. These changes may pose security, collection, and review challenges, and can leave legal teams unprepared to respond to preservation and production requests from government agencies or opposing counsel. In addition, this can make third-party tools on which companies currently rely for specific retention and collection methodologies obsolete overnight.For example, an update that changes the process for permissions and access to channels and chats on a collaborative platform like Teams may seem like a minor modification. However, if this type of update is rolled out without legal and IT team awareness, it may mean that employees who formerly didn't have access to a certain chat function may now be able to generate discoverable data without any mechanism for preservation or collection in place.The risks these updates pose mean that is imperative for organizations to have a framework in place to monitor and manage cloud-based updates and changes. How that framework looks will depend on the size of the organization and the expertise and resources it has on hand. Some organizations will have the resources to create a team solely dedicated to monitoring updates and evaluating the impact of those updates. Other organizations with limited internal access to the type of expertise required or those that cannot dedicate the resources required for this task may find that the best approach is to hire an external vendor that can perform this duty for the organization.When confronted with the need to collect, process, review, and produce data from collaboration tools due to an impending litigation or investigation, an organization may find it beneficial to partner with someone with the expertise to handle the challenges these types of tools present during those processes. Full-scale, cloud-based collaboration tools like Microsoft Teams and Slack are fantastic for workers because of their ability to combine almost every aspect of work into a single, integrated interface. Chat messaging, conference calling, calendar scheduling, and group document editing are all at your fingertips and interconnected within one application. However, this aspect is precisely why these tools can be difficult to collect, review, and produce from an eDiscovery perspective.With platforms like Teams, several underlying applications, such as chat, video calls, and calendars, are now tied together through a backend of databases and repositories. This makes a seemingly simple task like “produce by custodian” or “review a conversation thread” relatively difficult if you haven't prepared or are not equipped to do so. For example, in Teams communications such as chat or channel messages, when a user sends a file to another user, the document that is attached to the message is no longer the static, stand-alone file.Rather, it is a modern attachment, a link to the document that resides in the sender's OneDrive. This can beg questions as to which version was reviewed by whom and when it was reviewed. Careful consideration of versioning and all metadata and properties will be of the utmost importance during this process, and will require someone on board who understands the infrastructure and implications of those functions.The type of knowledge required to effectively handle collection and production of data generated by the specific tools an organization uses will be extremely important to the success of any litigation or investigation. Organizations can begin planning for success by proactively seeking out eDiscovery vendors and counsel that have experience and expertise handling the specific type of collaboration tools that the organization currently uses or is planning on deploying. Once selected, these external experts can be engaged early, prior to any litigation or investigation, to ensure that eDiscovery workflows are in place and tested long before any production deadlines.ConclusionCloud-based collaboration tools and platforms are here to stay. Their ability to allow employees to communicate and collaborate in real time while working in a remote environment is becoming increasingly important in today's world. However, these tools inherently present eDiscovery risks and challenges for which organizations must carefully prepare. This preparation includes properly vetting collaboration tools and platforms prior to deploying them, developing and enforcing clear internal policies around their use, monitoring all system updates and changes, and engaging eDiscovery experts early in the process.With proper planning, good collaboration between IT and legal teams and expert engagement, organizations can mitigate the eDiscovery risks posed by these tools while still allowing employees the ability to use the collaboration tools that enable them to achieve their best work.Reproduced with permission. Published March 2021. Copyright © 2021 The Bureau of National Affairs, Inc.800.372.1033. For further use, please contact permissions@bloombergindustry.com.chat-and-collaboration-data; ediscovery-review; microsoft-365emerging-data-sources, blog, corporate, chat-and-collaboration-data, ediscovery-review, microsoft-365,emerging-data-sources; blog; corporatebloomberg law
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Legal Tech Trends from 2020 and How to Prepare for 2021
Legal tech was no match for 2020. Everyone’s least favorite year wreaked havoc on almost every aspect of the industry, from data privacy upheavals to a complete change in the way employees work and collaborate with data.With the shift to a remote work environment by most organizations in the early spring of 2020, we saw an acceleration of the already growing trend of cloud-based collaboration and video-conferencing tools in workplaces. This in turn, means we are seeing an increase in eDiscovery and compliance challenges related to data generated from those tools – challenges, for example, like collecting and preserving modern attachments and chats that generate from tools like Microsoft Teams, as well compliance challenges around regulating employee use of those types of tools.However, while collaboration tools can pose challenges for legal and compliance teams, the use of these types of tools certainly did help employees continue to work and communicate during the pandemic – perhaps even better, in some cases, than when everyone was working from traditional offices. Collaboration tools were extremely helpful, for example, in facilitating communication between legal and IT teams in a remote work environment, which proved increasingly important as the year went on. The irony here is that with all the data challenges these types of tools pose for legal and IT teams, they are increasingly necessary to keep those two departments working together at the same virtual table in a remote environment. With all these new sources and ways to transfer data, no recap of 2020 would be complete without mentioning the drastic changes to data privacy regulations that happened throughout the year. From the passing of new California data privacy laws to the invalidation of the EU-US privacy shield by the Court of Justice of the European Union (CJEU) this past summer, companies and law firms are grappling with an ever-increasing tangle of regional-specific data privacy laws that all come with their own set of severe monetary penalties if violated. How to Prepare for 2021The key-takeaway here, sadly, seems to be that 2020 problems won’t be going away in 2021. The industry is going to continue to rapidly evolve, and organizations will need to be prepared for that.Organizations will need to continue to stay on top of data privacy regulations, as well as understand how their own data (or their client’s data) is stored, transferred, used, and disposed of.Remote working isn’t going to disappear. In fact, most organizations appear to be heading to a “hybrid” model, where employees split time working from home, from the office, and from cafes or other locations. Organizations should prepare for the challenges that may pose within compliance and eDiscovery spaces.Remote working will bring about a change in employee recruiting within the legal tech industry, as employers realize they don’t have to focus talent searches within individual locations. Organizations should balance the flexibility of being able to expand their search for the best talent vs. their need to have employees in the same place at the same time.Prepare for an increase in litigation and a surge in eDiscovery workload as courts open back up and COVID-related litigation makes its way to discovery phases over the next few months.AI and advanced analytics will become increasingly important as data continues to explode. Watch for new advances that can make document review more manageable.With continuing proliferation of data, organizations should focus on their information governance programs to keep data (and costs) in check.To discuss this topic further, please feel free to reach out to me at SMoran@lighthouseglobal.com. ai-and-analytics; ediscovery-review; legal-operationscloud, analytics, emerging-data-sources, data-privacy, ai-big-data, blog, ai-and-analytics, ediscovery-review, legal-operations,cloud; analytics; emerging-data-sources; data-privacy; ai-big-data; blogsarah moran
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Listen Now! Law & Candor Podcast
We're excited to announce that season one of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution, is now live!We at Lighthouse recognize that podcasting has become a popular form of content consumption, and to support our mission of providing valuable information around the eDiscovery, compliance, and information governance space via our thought leadership efforts, we have decided to launch a podcast dedicated to just that.Law & Candor co-hosts, Bill Mariano and Rob Hellewell, alongside industry experts, explore the impacts and possibilities that new technology is creating for the space. Our dynamic duo, who have their finger on the pulse of the rapidly evolving world of legal technology, will discuss the latest trends and newsworthy topics that are dominating the eDiscovery revolution. Take a quick look at the episodes they showcase in season one:The Future is Now – AI and Analytics are Here to StayThe Truth Behind Data ReuseMicrosoft Office 365 Part 1: Microsoft’s Influence on the Next Evolution of eDiscoveryMicrosoft Office 365 Part 2: How to Leverage all the Tools in the Toolbox Moving to the Cloud Part 1: A Corporate JourneyMoving to the Cloud Part 2: A Law Firm JourneyThe episodes are short and easy to consume and each one shares key takeaways for you to take back to your team. Listen here or on a platform of your choice and follow us on Twitter for updates and to join in on the conversation.For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.ediscovery-reviewmicrosoft, cloud, self-service, spectra, ai-big-data, data-re-use, blog, ediscovery-review,microsoft; cloud; self-service, spectra; ai-big-data; data-re-use; bloglighthouse
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Legal's Balancing Act: Risk, Innovation, and Advancing Strategic Priorities
As legal teams expand their responsibilities and business impact throughout their organizations, there’s a delicate balance legal professionals must strike in their roles: be better partners and balance risk.To tease out this complex and dynamic relationship, Megan Ferraro, Associate General Counsel of eDiscovery and Information Governance at Meta, recently joined as a guest on Law & Candor.Highlights from that conversation are below.The legal function's bigger roleLegal departments are playing a more significant part in strategy and innovation because the role of in-house counsel has changed greatly in the past few decades. There's been a considerable shift in forward-thinking companies from viewing legal as a blocker to more of a strategic partner.Successful legal teams are partnering internally to ensure attorneys across their organization get early signals to address potential inquiries in litigation or investigations. Additionally, companies are now hiring in-house teams to fill roles where those legal partners can identify and assess legal risk early on.In-house counsel have become advocates for why legal deserves a seat at the table at all company levels, which contributes to the overall success of the business.A great example of how legal is partnering with other parts of their organizations to drive innovation is through the role of product counsel at technology companies. The most effective product counsel have a deep understanding of product goals early, which helps them to identify and address legal issues more quickly and accurately. By working closely with the product team through development, updates, and deployment, they also serve as a conduit between legal and product teams to help advance projects and address potential risks.Critical risks for legal teams todayOne of the most significant challenges for in-house legal teams is keeping up with the pace of their organization’s growth—whether it’s developing products and services, forging unique partnerships, or adopting new technology and software.Often, business teams do not appreciate how even the slightest difference in facts can contribute to different outcomes in the law. Managing the expectations of the business regarding the time it takes to do legal analysis is extremely important.It's normal to take the time to think about these challenging issues. An important adage for the business to remember is that the law is not “Minute Rice.”The balancing act between risk and innovationWeighing risk and innovation requires that you keep pace with changes throughout the organization, including pivots in strategic priorities, with a variety of stakeholders. Staying ahead of these developments and allowing counsel enough time to evaluate potential impacts is key to understanding if the benefits are worth the risk, and if not, how to adjust a business plan accordingly.Along with providing the guidance stakeholders need to assess risk and make decisions, legal teams also frequently manage how organizational data is stored and accessed with IT departments. If other teams throughout the business do not have the information they need, they can't move as fast to help the company innovate. How long to keep data, what format it is in, and who can access it are all questions that can have a huge impact on innovation.Cross-functional collaborationIn-house counsel are increasingly working with other leaders in their organizations to inform strategic decisions, but having a seat at the table requires listening and staying connected to “clients” within the business. Strategic priorities can change very often, especially in a fast-paced environment.Knowing not just what these priorities are but how the business interprets them and what success means to the company will contribute to the most successful legal partners for balancing risk factors and supporting innovation.To listen to the full conversation and hear more stories from the legal technology revolution, check out Law & Candor.ai-and-analytics; information-governanceblog, risk-management, ai-and-analytics, information-governanceblog; risk-managementlighthouse
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Leveraging Microsoft 365 to Reduce Your eDiscovery Spend
In the early days of electronic discovery, technologies that legal teams utilized were researched and procured by specialists independent of information technology teams. Getting IT, legal, compliance, records managers, and other stakeholders to come together to discuss and strategize as a team was almost impossible. The move to the Cloud is changing that dynamic, as corporations move to address data challenges including eDiscovery, information governance, data privacy, and cybersecurity, in a more holistic fashion. When a corporation leverages Microsoft 365 (M365), they have procured a technology that not only meets their data storage requirements but provides eDiscovery, privacy, data governance, and cybersecurity features as well.With the upside that a single platform can provide, there are also challenges including the continued growth in data and new data types that M365 presents. Most eDiscovery professionals are still working to understand how to leverage the functionality in M365 and how to incorporate it into their existing program. Teams usage, for example, has risen with the addition of 31 million new users in one month when the COVID-19 pandemic first hit. Based on that statistic, it is clear that Teams is new to many professionals and eDiscovery teams need to understand how to deal with Teams data in discovery.eDiscovery features in M365 vary based on licensing, but can include data culling, data processing, and even some high-level review. The functionality in no way is an end-to-end solution for discovery. It can achieve some basic needs and other technologies are still required to address limitations in the platform.M365 is also an incredibly dynamic program. It is a challenge to track modifications and updates to the system. Organizations need to invest in personnel to test their M365 environment proactively to identify potential issues that could occur in the discovery process, understand limitations, and capture benchmarking data on the time and effort certain tasks can take in the system. This information should be discussed with legal teams, as it can impact their discovery negotiations and should be considered for proportionality assessments. It’s vitally important to train internal and external legal teams on the capabilities and the limitations of the technologies.Keeping pace with M365 often requires multiple resources. Consider having a dedicated team to test the new tools and ensure any new updates get incorporated back into your workflows. Reach out to your peers at other organizations to learn from their experiences with the tool. Working with service providers who have deep expertise in the tool and the roadmap is extremely beneficial. Microsoft is open to receiving feedback on your experiences outside of simply support tickets. In fact, there is a formal design change request option available to M365 users. Contact your Microsoft representative to learn more about that alternative.When it comes to leveraging M365 for eDiscovery, keep these key takeaways in mind:The explosion of data, new technology, and cybersecurity risks have all led to a continual evolution of the M365 tool.Staying up to date with these continuous evolutions can be a challenge, be sure to (1) have dedicated resources to test new capabilities and report back; and (2) ensure these new updates get incorporated into training and workflow documentation.Train both your internal and external teams on your M365 needs.Collaborate with your various partners (i.e. providers, third-party vendors, outside counsel, etc.).To discuss this topic further, please feel free to continue the discussion by emailing me at PHunt@lighthouseglobal.com.microsoft-365; information-governance; chat-and-collaboration-data; legal-operationsmicrosoft, legal-ops, blog, microsoft-365, information-governance, chat-and-collaboration-data, legal-operationsmicrosoft; legal-ops; blogpaige hunt
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Legal Tech Trends to Watch
We are now past the midpoint of 2020, which means we are more than halfway through the first year of a brand new decade. This midway point is a great time to take a look at the hottest trends in the legal tech world and predict where those trends may lead us as we move further into the new decade.If we were evaluating future trends in legal tech during a normal year, there might be one or two uncertainties or prominent events from the first half of the year that we would need to take into account. Maybe a shift in global data safety laws or a change to the Federal Rules of Evidence. But, as I’m sure we’re all tired of reading, 2020 has not been a normal year (“the new normal”, “these uncertain times”, “these unprecedented events”, etc. etc. etc.). No matter how you phrase it, we can all agree that 2020 has been… unpredictable. Or to be a bit less understated: the first six months of 2020 have drastically changed how many corporations and law firms function on a day-to-day basis, and industry leaders are predicting that many of those changes will have a lasting effect. For example, a recent Gartner survey of company leaders from HR, legal and compliance, finance, and real estate industries showed that 82% of those responding plan to allow employees to continue working remotely in some capacity once employees are allowed back in the office, while close to half responded that they will allow employees to work remotely full time.So what does that mean for the legal tech industry? Well, while the world around us has changed dramatically due to the events of 2020, many of those changes actually dovetail quite nicely into where legal tech was already headed. In this article, we will look at the latest trends in legal tech and how 2020, in all its chaos, has affected those trends.SaaS self-service, spectra eDiscovery: The growing adoption of cloud services is leading us to a unique hybrid approach to managing eDiscovery programs: SaaS self-service, spectra eDiscovery solutions. This new subscription-based approach gives law firms and corporate legal teams the ability to take charge of their own fates by bringing their eDiscovery program in house, while leaving much of the security risks, costs, and IT burdens to a reputable, secure vendor that can house the data in a private cloud or within its own data centers. The benefit of controlling your own eDiscovery program in house are obvious. Legal teams would have the ability to control costs and access their data whenever and wherever they need to without the expense and hassle of having to go through a middle man. It would also give legal teams more control over their own costs, deadlines, and workflows, with the ability to fluidly scale up or down depending on case need. The self-service, spectra subscription approach is also unique in that it leaves the burden and risk of creating and managing an entire IT data storage infrastructure with the vendor. A security-minded vendor with SOC 2 and ISO 27001 security certifications can house data in a private cloud or their own data center, providing a completely secure environment without the overhead and risk of managing that data in house. A subscription service also may come with the reassurance that if a project or timeline becomes more burdensome than expected, the in-house team could easily pass off a workflow or entire project to the vendor seamlessly.In 2020, a SaaS self-service, spectra solution has the added benefit of being available in every location around the world, at any time. If a worldwide pandemic has taught us anything, it is that traveling to multiple locations throughout the world to set up data centers to handle the specific needs of a case or a client is no longer a feasible solution. Housing and accessing data in the Cloud does not require abiding by global travel restrictions or mandatory quarantines. A SaaS self-service, spectra model where data is stored in the Cloud allows for global expansion without concern for pandemics, natural disasters, or political uncertainty.Big Data Analytics: Big data analytics and technology assisted review (TAR) are certainly not new ideas to 2020. The technology and tools have existed for years and the legal industry has slowly been adopting them. (I say “slowly” in contrast to how fast these tools are developed and adopted in other areas outside of the legal field.) The need to find reliable ways to comb through massive amounts of data in the eDiscovery and compliance arenas will only grow, and we can expect that the technology will only continue to improve and become even more reliable.One could argue that the biggest hindrance to big data analytics in the legal world is not the advancement of the technology, but rather the ability and willingness of many lawyers and courts to adopt that technology as a defensible, necessary legal tool in the modern world of big data. The legal field is notoriously slow to adopt new technology. As a personal example, I clerked for a prominent, incredibly smart criminal defense attorney who still used carbon paper to make copies of important court filings. This occurred during the same year that the third season of Lost aired (or the same year that the first season of Madmen premiered - pick your reference. Either way, not that long ago). And every law firm is rife with stories of the old-school partner who holes up in the firm library (the existence of which could also be an example to my point, in and of itself) because she doesn’t believe in online legal research. While the practice of law is steeped in an awe-inspiring mix of tradition and history, it can also be frustratingly slow to expand on that tradition because it refuses to use a copier. Even Don Draper had a copier by the second season.However, if we can say one positive thing about 2020, it is that the last six months have pushed the legal world into the technological future more than any other time period to date. Almost every in-house counsel, law firm, and court across the globe has been forced to find a way to conduct its business in a completely remote environment. This means that judges, law firms, and in-house counsel are facing the reality that the legal world needs to rely on and adapt to technology in order to survive. One hopes that this new reality helps lead to a more robust adoption of technological advancement in the legal world in general, and hopefully, a shift away from the reactionary relationship the legal industry always seems to have with technology. Because data volumes will only continue to explode and there will come a time in the near future when it will not be defensible to tell a judge or a client that discovery may take years in order to allow time for a team of 200 contract attorneys to look at each individual document that hits on a search term. Analytics will eventually be a requirement for a defensible eDiscovery program, and 2020 may be the year that helps many in the legal field take a more proactive approach to its adoption.New sources of data (i.e. collaboration tools): Like big data analytics, online collaboration tools like Teams and Slack are not new to 2020, but this year has certainly helped push the use of these tools to the forefront of many companies’ day-to-day business. It seems like new collaboration tools arise every month and companies are increasingly pushing employees to utilize them. Organizations are realizing the value of these collaboration tools in a post-COVID environment, where online collaboration is not only preferable, but absolutely critical. Not to repeat some of 2020’s greatest memes, but I’m sure we’ve all seen the 2020 adage that this is the year that we all realized that not only could that meeting have been an email, that email could have been an instant message. Data actually proves that theory to be true. Microsoft for example, found that chat messages within Microsoft Teams meetings increased over 10x from March 1 to June 1.The widespread use of these types of tools, in turn, generates more and more unique data that needs to be accounted for during an eDiscovery or compliance event Going forward, organizations will need to ensure that they know which tools their employees or contractors are using, what data those tools generate, and how to defensibly collect, process, and review that data in the event of a lawsuit or investigation (or retain a vendor who can guide them through that process). Which brings us to our final 2020 trend…Continuous program update subscription services: Going hand-in-hand with the above, watch out for eDiscovery programs and solutions that can manage the continuous delivery of program updates on all of the applications and platforms that organizations use to effectively perform their work. Gone are the days when the same data collection or processing workflow could be used for years at a time and still be defensible. From iPhone iOS to Teams, systemic updates to work applications and platforms can now roll out on an almost weekly basis, and it is imperative that legal and compliance teams stay on top of those updates and adapt to them in order to ensure that company information remains secure and that any data generated can be defensibly collected and processed when needed. In 2020 and beyond, look for technologically advanced eDiscovery subscription services that give companies the ability to prepare for and stay ahead of the never-ending stream of software updates.To discuss this topic further, please feel free to reach out to me at SMoran@lighthouseglobal.com.ai-and-analytics; ediscovery-review; legal-operationscloud, ai-big-data, blog, ai-and-analytics, ediscovery-review, legal-operations,cloud; ai-big-data; blogsarah moran
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Legalweek in 2022 and Beyond: Greeting a Changed World without Fear
This year’s Legalweek conference was back to an in-person event in New York City — a significant change from the virtual format in 2021. Folks who hadn’t seen each other in person in over two years (or met for the first time in person) were able to talk and exchange ideas while sharing a hug, a meal, or a drink. Over and over again, the words, “It’s so good to see you, in person!” echoed throughout hallways and conference rooms. But as good as it feels to reconnect, it was also abundantly clear that the pandemic has fundamentally and permanently altered our world. There is no return to the “normal” we knew prior to March of 2020. The pandemic has changed us. Over the last two years, we have reprioritized what’s important in our lives, which has changed not only where we work, but how we work. And technology, as it always does, has evolved to keep up with those changes. As we emerge into this new world, our eyes blinking in the sun, these changes may fill us with anxiety. Change, after all, can be scary. But as Don Draper, the fictional Madmen character, once said when talking to a client about cultural change in 1960s New York City: “Change is neither good nor bad, it simply ‘is.’ It can be greeted with terror or joy — a tantrum that says, ‘I want it the way it was,’ or a dance that says, ‘Look, something new!’" Below, I’ve outlined some key industry changes that were discussed throughout Legalweek, as well as how legal technology companies can help law firms and organizations greet these changes as an opportunity, rather than something to be feared. The virtual workforce revolution is here to stay The massive and abrupt pivot to remote working for organizations and law firms is not a blip that will reverse itself once the pandemic “ends.” Prior to 2020, it was a trend bubbling under the surface. The pandemic simply accelerated that trend more quickly than previously anticipated, and in doing so, permanently changed the landscape of white-collar careers. Most young adults who entered the workforce over the last two years have never known a world where work had to take place solely in an office setting. Meanwhile, more experienced workers—suddenly able to reap the flexibility that remote working provides—also do not seem keen to go back to a more rigid office-based work environment. And the younger generations waiting in the wings to enter the workforce over the next five to ten years have grown up learning and socializing in much more immersive virtual settings than any previous generation. As they become consumers and employees, technology will continue to evolve to accommodate their comfort interacting in those virtual environments. With a worldwide workforce shortage that does not seem like it well ebb anytime soon, this modern workforce will have the upper hand when it comes to demanding a more flexible, remote work environment, as well as access to the technology that facilitates it. Thus, organizations will not only have to adapt to these changes—they may need to lean heavily into them to survive. We can see the harbingers of this sea change even today. More and more companies are entering the metaverse , investing in NFTs, and utilizing virtual reality (VR) technology to perform work that would have typically been done in person or on flat screens (like training new employees). Microsoft, developers of one of the world’s most heavily used cloud collaboration and work platforms (M365 and Teams), also announced plans to introduce VR technology in 2022 that will work in conjunction with their existing technology, facilitating a more immersive virtual remote working experience for workers around the world. All these potential new data sources will significantly increase challenges from a data governance, data privacy, and eDiscovery perspective. But rest assured, the work that legal technology providers are doing now to put better systems in place to handle existing cloud-based tools will help lay the framework for how we handle data from the metaverse and other new sources in the future. For example, some eDiscovery providers and lawyers are already advocating for a move away from the traditional eDiscovery “custodial” ownership framework in order to accommodate how cloud-based data is stored and interacted with in organizations. Forward-thinking eDiscovery service providers are also advocating for a more holistic view of eDiscovery, one that begins at the data source and spans the entire data lifecycle—which will be a necessity as we move into a more virtual-based workplace. Technology providers are also starting to factor eDiscovery, data privacy, and compliance issues into future roadmaps and upgrades—making it easier to manage, search, and export data from new data sources for eDiscovery and compliance purposes. There is no magic bullet—a risk balancing act The shift to a more virtual world significantly increases risk for organizations and the law firms that represent them. Utilizing cloud-based tools and newer technology to facilitate a more virtual workplace will be increasingly important for organizations. However, due to the volume of data, and the speed at which it’s created, organizations will have to accept increased risks related to data privacy, data security, compliance, eDiscovery, etc. In effect, in today’s cloud-based world, there is no magic bullet that will completely eliminate risk caused by the proliferation and speed of data. Organizations are learning to balance risk and innovation when it comes to technology, rather than take an “all or nothing” approach. To do so, stakeholders from across the company must have a seat at the table when deciding how much risk they’re willing to take on in order to keep their employees productive and customers satisfied via technology. Knowledgeable legal technology service providers are already helping organizations adapt to this balancing act. Companies that have dedicated cloud technology experts can help their clients understand the technology they are using and how it works within their own environment. They can also help their clients staying abreast of ever-evolving risks presented by cloud-based technology and provide risk mitigation strategies that fit within the priorities of the organization. An increasing need to lean on managed service providers Today’s cloud-based tools and applications are increasingly complicated and present increased risks that must be managed. Additionally, due to global workforce shortages (i.e., “the great resignation) and unpredictable economic conditions (caused not only by the pandemic but by market uncertainty around Russia’s invasion of Ukraine, increasing gas prices, supply shortages, inflation, etc.), employees are often being asked to do more work with less budget and resources. Together, these two factors have led organizations and law firms to lean more on outsourcing specific segments and technology processes to outside service providers. The benefits of partnering with a trustworthy service provider to manage segments of the organization that require specialized expertise are manifold. The right service provider will have experts on staff who are wholly dedicated to understanding and managing specific technology, processes, and risk. Offloading management to those partners allows organizations to refocus on their own underlying mission. Service providers may also be better positioned to advocate for a company’s needs with pure technology providers because they have an existing partnership with those companies. This can help organizations fill technology gaps without spending weeks or months trying to negotiate with technology providers. Partnering with service providers also allows the organization to offload risks associated with the management of specific technology or processes to a company that is much better equipped to understand and take on that risk. Outsourcing work to a service provider can also significantly lower overhead costs and allow organizations to stay leaner and nimbler — empowering them to focus on tasks that add value to the underlying business while providing relief to overworked employees. In short, a good legal technology service partner can become an extension of an organization’s own team while lowering overhead and risk. Diversity can no longer be just a numbers game Over the last few years, we saw organizations and law firms focusing more on diversity efforts. Often, this focus was merely numerical, intended to increase the headcount of diverse staff. While this effort is well-intended (and long overdue), we are now seeing more demand for a deeper commitment to diversity and inclusion that goes beyond statistics, diversity training, and simple corporate statements. Today’s workforce, spurred on in part by a new generation of employees, are demanding that organizations be truly committed to diversity and equality on a deeper level—with action that is evident across the organization, from leadership profiles, to internal and external teams, to opportunities for advancement, to vendor selection, etc. And due to labor shortages, this new workforce has the power to effect change by refusing to work for companies that can’t demonstrate this type of commitment. Both the legal and technology industries have historically suffered from a lack of diversity. This is evident from the diversity gaps we still see in the industry today. However, this lack of diversity also presents an opportunity for legal technology companies to make a more significant impact. There is no downside to leaning into diversity. In fact, studies have shown that diverse companies are more successful. Legal technology companies have an opportunity to lead the way by putting dedicated systems in place to ensure that their leadership is diverse, that diversity is represented across all teams and company segments, that annual review processes and career advancement within the company are focused on equality, and that employees from underrepresented communities feel supported and seen within the company. Legal technology companies also have a unique opportunity to support groups that are dedicated to increasing legal and technology education and training opportunities for underrepresented communities (which is often at the root of the diversity problem across both industries). In this way, legal technology companies can help lead by example for the organizations and law firms they serve — showing that truly, a more diverse company is a more innovative company. Conclusion The world we are facing in 2022 is much different than the pre-pandemic world we left behind. The changes we are encountering today can present significant challenges to organizations and law firms — but they also present unique opportunities for growth. Legal technology companies can help both segments take advantage of these opportunities and emerge into a brighter future. ediscovery-reviewmanaged-services, cloud-migration, cloud-services, blog, ediscovery-review,managed-services; cloud-migration; cloud-services; blogsarah moran
Blog
Legal Operations Efficiency Begins with a Rock-Solid Collaboration Tool
Legal departments tend to run fairly lean. This means relying on external parties to accomplish any task is the norm. But when you are managing dozens of outside counsel on different matters, it can be nearly impossible to keep abreast of email traffic, calendars, and the status of any given task. Thankfully with a little bit of technology and some organization, this issue can be solved. This blog will share some tips on how other legal departments have solved this challenge.Select a technology platform to support organization and collaboration. The technology should allow internal and external parties to edit documents, view and manage calendars, organize task lists, and make comments and/or send messages to each other. There are many technologies that organizations use, such as Microsoft Teams or Google Workspace, that work well for this type of collaboration internally, but are not necessarily set up for external collaboration. With some additional work, you can also set these tools up for external collaboration. However, given all the privacy and data management considerations for internal use, one can imagine how high the hurdles are to set this up for external use. If you are facing those hurdles, there are several third-party technologies, such as Joinder and HighQ, that work well for external collaboration. These third-party cloud technologies are fairly low cost and quick to implement. The most important thing here is to choose a single platform. You want to make sure that you are able to minimize switching platforms with every new matter and/or outside counsel. Imagine the ease with which you can get an overview of all your legal work if you can log in to one platform and see your litigation eDiscovery deadlines, patent filing deadlines, and third-party subpoena response deadlines. You can then seamlessly edit the associated documents and assign a task to the next reviewer. You can see how selecting a single platform provides greater visibility and efficiency.Ensure each third party has a person responsible for maintaining the records inside the shared technology. Although you will likely have multiple people working on any given matter, you want to make sure there is at least one person from each third party who is responsible for updating the system. This should be someone knowledgeable about the matter, the deadlines, and the tasks. This should also be someone who is highly organized and comfortable with the technology.Agree upon a common organizational structure. The hardest thing about managing hundreds of matters is staying organized across all of them. If you choose a way to organize that remains consistent, it makes it much easier to find what you are looking for quickly. For example, you may choose to folder documents and tasks by matter type or by the department of origination. Either way, make sure it is a structure that makes sense across your legal portfolio. Here are some considerations to ponder when deciding how to name your files.Write the above into your outside counsel guidelines. A third-party collaboration tool and the organizational system are only as good as the adoption. By writing a requirement to keep it updated into your outside counsel guidelines, you are increasing the chances of success. Here is some sample text for your use:[Company name] uses [software name] as its third-party collaboration tool and asks that each of its outside counsel use [software name] for all work on the matter. On at least a weekly basis, outside counsel shall update [software name] with important dates in the matter, an updated list of tasks in the matter, and any final versions of key documents in the matter.The benefits of having all your legal documents in one platform increase over time. You create a system of records that can be referenced at any time. I hope that these tips will help you implement a solution for third-party collaboration so you can reduce the time you spend searching your email for the last version of the contract.legal-operationsediscovery-process, legal-ops, blog, legal-operations,ediscovery-process; legal-ops; bloglighthouse
Blog
Legal Tech Innovation: The Future is Bright
Recently, I had the opportunity to (virtually) attend the first three days of Legalweek, the premier conference for those in the legal tech industry. Obviously, this year’s event looked much different than past years, both in structure and in content. But as I listened to legal and technology experts talk about the current state of the industry, I was happily surprised that the message conveyed was not one of doom and gloom, as you might expect to hear during a pandemic year. Instead, a more inspiring theme has emerged for our industry - one of hope through innovation.Just as we, as individuals, have learned hard lessons during this unprecedented year and are now looking towards a brighter spring, the legal industry has learned valuable lessons about how to leverage technology and harness innovation to overcome the challenges this year has brought. From working remotely in scenarios that previously would have never seemed possible, to recognizing the vital role diversity plays in the future of our industry – this year has forced legal professionals to adapt quickly, utilize new technology, and listen more to some of our most innovative leaders.Below, I have highlighted the key takeaways from the first three days of Legalweek, as well as how to leverage the lessons learned throughout this year to bring about a brighter future for your organization or law firm.“Human + Machine” not “Human vs. Machine” Almost as soon as artificial intelligence (AI) technology started playing a role within the legal industry, people began debating whether machines could (or should) eventually replace lawyers. This debate often devolves into a simple “which is better: humans or machines” argument. However, if the last year has taught us anything, it is that the answers to social debates often require nuance and introspection, rather than a “hot take.” The truth is that AI can no longer be viewed as some futuristic option that is only utilized in certain types of eDiscovery matters; nor should it be fearfully viewed as having the potential to replace lawyers in some dystopian future. Rather, AI has become essential to the work of attorneys and ultimately will be necessary to help lawyers serve their clients effectively and efficiently.1Data volumes are exponentially growing year after year, so much so that soon, even the smallest internal investigation will involve too much data to be effectively reviewed by human eyes alone. AI and analytics tools are now necessary to prioritize, cull, and categorize data in most litigations for attorneys to efficiently find and review the information they need. Moreover, advancements in AI technology now enable attorneys to quickly identify categories of information that previously required expensive linear review (for example, leveraging AI to identify privilege, protected health information (PHI), or trade secret data).Aside from finding the needle in the haystack (or simply reducing the haystack), these tools can also help attorneys make better, more strategic counseling and business decisions. For example, AI can now be utilized to understand an organization’s entire legal portfolio better, which in turn, allows attorneys to make better scoping and burden arguments as well as craft more informed litigation and compliance strategies.Thus, the age-old debate of which is better (human or machine learning) is actually an outdated one. Instead, the future of the legal industry is one where attorneys and legal professionals harness advanced technology to serve their clients proficiently and effectively.Remote Working and Cloud-Based Tools Are Here to StayOf course, one of the biggest lessons the legal industry learned over the past year is how to effectively work remotely. Almost every organization and law firm across the world was forced to quickly pivot to a more remote workforce – and most have done so successfully, albeit while facing a host of new data challenges related to the move. However, as we approach the second year of the pandemic, it has become clear that many of these changes will not be temporary. In fact, the pandemic appears to have just been an accelerator for trends that were already underway prior to 2020. For example, many organizations were already taking steps to move to a more cloud-based data architecture. The pandemic just forced that transition to happen over a much shorter time frame to facilitate the move to a remote workforce.This means that organizations and law firms must utilize the lessons learned over the last year to remain successful in the future, as well as to overcome the new challenges raised by a more remote, cloud-based work environment. For example, many organizations implemented cloud-based collaboration tools like Zoom, Slack, Microsoft Teams, and Google Workspace to help employees collaborate remotely. However, legal and IT professionals quickly learned that while these types of tools are great for collaboration, many of them are not built with data security, information governance, or legal discovery in mind. The data generated by these tools is much different than traditional e-mail – both in content and in structure. For example, audible conversations that used to happen around the water cooler or in an impromptu in-person meeting are now happening over Zoom or Microsoft Teams, and thus may be potentially discoverable during an investigation or legal dispute. Moreover, the data that is generated by these tools is structured significantly differently than data coming from traditional e-mail (think of chat data, video data, and the dynamic “attachments” created by Teams). Thus, organizations must learn to put rules in place to help govern and manage these data sources from a compliance, data security, and legal perspective, while law firms must continue to learn how to collect, review, and produce this new type of data.It will also be of growing importance in the future to have legal and IT stakeholder collaboration within organizations, so that new tools can be properly vetted and data workflows can be put in place early. Additionally, organizations will need a plan in place to stay ahead of technology changes, especially if moving to a cloud-based environment where updates and changes can roll out weekly. Attorneys should also consider technology training to stay up-to-date and educated on the various technology platforms and tools their company or client uses, so that they may continue to provide effective representation.Information Governance is Essential to a Healthy Data StrategyRelated to the above, another key theme that emerged over the last year is that good information governance is now essential to a healthy company, and that it is equally important for attorneys representing organizations to understand how data is managed within that organization.The explosion of data volumes and sources, as well as the unlimited data storage capacity of the Cloud means that it is essential to have a strong and dynamic information governance strategy in place. In-house counsel should ensure that they know how to manage and protect their company’s data, including understanding what data is being created, where that data resides, and how to preserve and collect that data when required. This is important not only from an eDiscovery and compliance perspective but also from a data security and privacy perspective. As more jurisdictions across the world enact competing data privacy legislation, it is imperative for organizations to understand what personal data they may be storing and processing, as well as how to collect it and effectively purge it in the event of a request by a data subject.Also, as noted above, the burden to understand an organization’s data storage and preservation strategy does not fall solely on in-house counsel. Outside counsel must also ensure they understand their client’s organizational data to make effective burden, scoping, and strategy decisions during litigation.A Diverse Organization is a Stronger OrganizationFinally, another key theme that has emerged is around recognizing the increasing significance that diversity plays within the legal industry. This year has reinforced the importance of representation and diversity across every industry, as well as provided increased opportunities for education about how diversity within a workforce leads to a stronger, more innovative company. Organizational leaders are increasingly vocalizing the key role diversity plays when seeking services from law firms and legal technology providers. Specifically, many companies have implemented internal diversity initiatives like women leadership programs and employee-led diversity groups and are actively seeking out law firms and service providers that provide similar opportunities to their own employees. The key takeaway here is that organizations and law firms should continue to look for ways to weave diverse representation into the fabric of their businesses.ConclusionWhile this year was plagued by unprecedented challenges and obstacles, the lessons we learned about technology and innovation over the year will help organizations and law firms survive and thrive in the future.To discuss any of these topics more, please feel free to reach out to me at SMoran@lighthouseglobal.com.1 In fact, attorneys already have an ethical duty (imposed by the Rules of Professional Conduct) to understand and utilize existing technology in order to competently represent their clients.ai-and-analytics; ediscovery-review; legal-operationscloud, information-governance, ai-big-data, blog, ai-and-analytics, ediscovery-review, legal-operations,cloud; information-governance; ai-big-data; blogsarah moran
Blog
Legal Operations Change Management: Getting Your Idea Approved At Your Organization
Legal operations change management is one of the biggest challenges that professionals face according to a poll at the most recent CLOC conference. This isn’t surprising given that organizational change management is an often analyzed topic with a plethora of opinions about ways to accomplish it. There is no magic bullet to force a change in your legal department, however, growing your influence across legal operations and your organization can certainly help. Here are five steps to grow that influence and get people to modify their behaviors.Step 1: Get Clear About the Problem & Root CauseWhether you are tired of hearing about the myriad of issues with your contract lifecycle management or e-billing tool or you have been tasked with centralizing outside counsel selection and management, the first step remains the same. You must get clear in your own mind about what it is that you’re trying to change – both the problem complained about and the root cause of said problem. When starting out you should brainstorm and be liberal with your ideas, jot down anything that comes to mind, both problem and potential causes, and then ask others for their thoughts. Getting various opinions will help you to clarify the issue in your own mind. Once you have a page or two of related ideas, review all the notes and come to a final conclusion about the problem you are trying to solve and its root cause. Write this down in a succinct 1-3 sentence statement.Step 2: Create Your HypothesisThis second step also involves brainstorming. Go through the same process as step one by jotting down any ideas to solve your succinct problem statement. Again, you may want to ask a legal operations colleague (or two) for their thoughts. You may also want to observe people completing the task(s) you’re trying to change so that you can come up with some ideas of ways to solve the problem you have identified. For example, if you are targeting changing the matter management tool, you will want to understand the nature of the matters involved, understand what people are using the tool for, and create a hypothesis around the new tool you want to implement. Once you have your list, cull it down to 1-3 potential solutions to test.Step 3: Test Your HypothesisNext, take your 1-3 potential solutions and test them out. The first way to test is to reach out to other legal operations professionals and/or service providers outside your organization to see if the solution has worked for others. Next, if you can, test it out yourself in your organization. This doesn’t necessarily mean you will implement a sample of a new tool, but that you will demoing the tool and get an understanding of what you would need to implement this solution at your organization.Step 4: Create and Deliver Your PitchNow that you are the expert on the problem and have a well thought out solution, you need to convince others. The best way to do that is to tell a story that includes the following:what you saw (the problem);how pervasive the problem is (# of people impacted);the cost of the problem (time/money);the proposed solution;the benefit of this solution;why this solution over the other 2-3 good solutions; and what is needed to implement this solution. Once you have this together, determine who you will have to convince. Start with your boss, any budget owners, and any leaders whose teams will be directly impacted. Before you share the presentation, make sure that you understand what each of these group’s reactions may be so that you can tailor your verbal commentary to address their comments. If you don’t know the attendees’ potential reactions, you should consider doing some due diligence beforehand. The most effective way I have found to do this is to start with your boss. Share the general ideas of your presentation with them and ask them how others will react. If they are not sure, you can start with a peer in legal or another department or have informal conversations with the attendees before the actual presentation. Investing time in these “pre-pitches” will ensure a successful end result. Make sure you incorporate any feedback from these pre-pitches into the ultimate presentation.Step 5: Brag About Your ResultsAfter a successful presentation, procurement, and implementation, don’t forget to share the wins of your project. Specifically, share with the same people you pitched at the outset but also share the results with anyone whose behavior you have already or are still trying to change. Sharing any wins will reinforce the new behaviors you are trying to implement. Tie those wins back to the original presentation and the results you were anticipating. This showing of success (and of credibility of your original pitch) will have a positive impact on your reputation and ability to influence future change. You will develop a reputation for getting positive results and people will be excited to try what you have up your sleeve. legal-operationslegal-ops, blog, legal-operations,legal-ops; bloglighthouse
Blog
Legal Operations: From Tactical Resource to Strategic Partner
Do you ever feel like you are spending your day firefighting and wish you could spend more time planning and executing all the great ideas you have? Do you wish the business came to you first to ask for input so they could be prepared rather than rushing in once the alarm bells are already ringing? You are not alone. These are common refrains heard from legal operations professionals. Here are some ways to change that and go from a tactical resource to a strategic partner.Make Time for Strategic PlanningEven if the majority of your role calls for real-time execution, you can still showcase your strategic side. First, make sure you are spending time thinking strategically. I would recommend blocking out time at least once a month to do this work. During each of your thinking sessions, focus on just one idea. If you have too many ideas, your sessions will not be as productive. If you have multiple ideas you need to work through simultaneously, do so in multiple sessions. Or, if you don’t have any ideas, identify a need or frustration in your department. You can focus on a broad need (i.e. how to organize the department most efficiently) or a more narrow need (i.e. how to understand the company’s legal spend). When choosing what to focus on, choose something that you would be comfortable sharing with someone else. This will ensure that you can demonstrate the great strategic thinking you have done. Once you have selected the need you are going to think about, divide your time into three parts. Spend the first part brainstorming around all of the details of the specific need. Identify the problem and the potential causes. You can also identify related problems. Jot down the impact of the issue with as much detail as possible.In the second third, brainstorm potential solutions. Jot down anything that comes to mind. If this is an issue you have already thought about, you may even be able to identify how long each solution might take and/or the potential associated cost. If you have this information, note it. If not, that is ok too. The focus of the first two-thirds of your time should be to let the ideas flow. In the last third of your time, organize your thoughts on the first two sections. I find it easiest to do my organizing in a presentation software like PowerPoint, Google Slides, or Canva. You can follow the below outline or check out more details in my prior blog on getting your ideas approved at your organization.Problem Statement – Identify the issue in 1-3 sentences.Impact Statement – Identify the impact of the issue. You want to quantify this in some way, although at the early stages you might just put a placeholder or blank in here.Cause(s) – Identify the top 3-5 causes of the problem.Potential Solutions – How much you put here will really vary, but try to at least get your top idea into writing.Next Steps – Identify the next steps. If you’re not sure here, leave this blank. When you have your first conversation (more on that below), you can add information here. If you are clear about what you want to do, spend time on this section. This is an area where you can make any asks you have.Once you have completed your strategic thinking time, decide whether you want to share this plan. You may not do so with each monthly idea but you should share at least two outputs of your strategic thinking each year if you want to demonstrate your strategic ability. When you are sharing, I recommend starting with your boss. If that feels too vulnerable, you may decide to share with a co-worker first, but you will want to go to your boss next. Make sure you make clear that the goal of the session is to get their feedback. During that presentation, ask for feedback on the idea, next steps, as well as who else’s input might be valuable. If things go well, you will likely go forward with presenting to others. If your boss feels like this idea is not viable at this time, make sure you ask if there are any other similar projects that you can get involved in? Note that it might feel like a letdown if your boss says this isn’t the right time for this project. Keep in mind, however, that your goal was to showcase your strategic thinking and you will have accomplished this goal by presenting. I would also be remiss if I didn’t mention the primary obstacles I hear from people who “want” to do such an exercise. I don’t have time. I hear you – this is not something that is necessarily part of your day job, and if you’re fighting fires, you’re likely at your maximum capacity. However, think of this as a career investment. If you want to get out of the firefighting mode, invest in this work even if it is outside of your typical work hours or job responsibilities. I can’t take on the solution I’m suggesting. You can always have this discussion with your boss. It may be that there are resources that can help you or perhaps someone else takes on driving the solution. Either way, you will be able to showcase your strategic thinking.I’m worried that I will damage my reputation because this isn’t part of “my job.” Each organization is different and values this type of work differently. I will say that if this is something you really enjoy and is important to you, and your organization or role doesn’t value this work, you should consider whether your passions align with your current role.How to Show Up as Strategic in Tactical SituationsIf you can’t take on the strategic thinking right now, or if you want to press fast forward on you being seen as a strategic resource, there are ways you can show up strategically in your day-to-day interactions. When someone comes to you with a specific request for action, pause and ask yourself these three questions:“why” are we doing this;“what” broader impact will this have; and“how” does this relate to other things going on inside the organization? Take the example of a lawyer coming to you holding their latest law firm bill – fuming! “I just heard that we are paying twice on our matter for Firm ABC than Jane is paying on her matter for similar Firm ABD. Firm ABC’s rates are ridiculous – please negotiate them down right away.” You could absolutely pick up the phone and call Firm ABC. Or, you could think about the above questions. In doing so, you may realize that we are due for an annual firm rate adjustment across all our firms and that this firm has a very specialized area of expertise. If you share with this lawyer that the department has an overall rate discussion coming up that would potentially impact all of their matters, rather than just this one, as well as positively impact other matters with this firm. You can share that your preference would be to not make a phone call now but instead work this into a broader more strategic conversation with the firm. This second response showcases how you are thinking about the bigger picture and longer-term consequences for the organization. It also shares with the lawyer that you have proactive measures that you are working on that positively impact their world.legal-operationslegal-ops, blog, legal-operations,legal-ops; bloglighthouse
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Legal Operations: Borrowing from Product Management Principles to Implement a Successful Contract Management Solution
What is the most frustrating thing when you have spent months overhauling and then launching a new contract lifecycle management (CLM) solution? Nobody using it! Or, more likely, a few people are using it but most people are hesitating to change their current processes and start using the new solution. I hear this frustration in contract management solutions as well as other large project implementations. As I sat down to think about this challenge, I read many articles about the best business practices to apply to avoid this. These articles focused on bringing business process management to this process, which is valuable, but even with those processes, your implementation could be left with very little adoption.Then I had a light bulb moment – why not pull from a discipline whose main focus is to resonate with its clients and users – product management. It wasn’t a far reach given my product management background and certification. Product managers do a lot of different things at different organizations but I think most people would agree that they play a key role in building and launching a successful product. More specifically, a product manager is tasked with knowing her or his customer base so well that he or she can speak for them and direct the development of a product into one that resonates with its users. A product that resonates with users is more highly adopted and therefore, typically seen as more successful. So what can we, in legal operations, learn from this field?1. Focus on what really matters to your users and potential usersStart by interviewing people who are directly involved with the contract management process as well as some people who are adjacent to the contract management process. Make sure to capture the views of people close to contracts (e.g. attorneys), as well as those who rely on the outputs of those contracts (e.g. finance and sales). Ask about each person’s main goal in contract management and what is preventing them from achieving that goal. Specific to CLM solutions, metadata can be critical to understand and map early, so I would recommend asking people what metadata they rely on when searching for contracts.[1]In these interviews, make sure you understand the impact of any contract management challenges raised in the interviews. You may hear a variety of complaints, but how many of those are frustrations that make the process inefficient versus just minor grumblings. When someone mentions an issue, you should always ask them to quantify, on a scale of 1-10, how big an impact that problem has in their daily life. You should also ask how pervasive the problem is, on a scale of 1-10, across their peers. This will allow you to more quickly identify the real issues that will be impactful to solve. For example, someone may be frustrated that they have to log in to a different technology to manage a contract workflow. Another person may be frustrated that they cannot tie together later revisions to contracts, such as renewals, pricing, or amendments. By asking for the impact during the interviews, you will likely learn that the technology switching challenge is a 2 out of 10 on the impact scale whereas the issue of the later revision is a 9 out of 10. You can prioritize solving for the latter and have tremendous business impact and avoid mistakes by other departments relying on outdated terms.2. Launch a beta solution for a handful of usersMost products have some sort of test user group that is able to provide feedback on releases early. Since you likely are not engineering your own CLM, I would recommend gathering a small group of “early adopters” to test your new CLM solution in three ways:First, you should map out your ideal state process. Bring this group together to talk through that ideal state and suggest any tweaks. Second, when you have narrowed your technology selection to one or two technologies, you can bring the group together to test those technologies. Finally, this group should be your first users of the final solution, the technology and process combined, once implemented.This may be self evident, but be sure to include yourself in the testing group. Often people feel like they are running the project so they should not participate in the feedback. However, given the deep immersion in the contract management process and your knowledge of the organization, your feedback is critical to shaping the right solution. 3. Use your personas in communicationsCommunicating about your solution is a critical step in any CLM solution. That communication is what gets users using the solution and what jump starts change. Making this communication effective can be daunting, but here is the product management formula. Start with the challenges that your users shared with you. When they see their voices reflected, they will immediately be interested in the message. Next, state in 1-2 sentences how you have solved the challenge. When people see that a challenge they have raised has been solved, it is highly likely that they will adopt the new solution. With this, you should have a 3 sentence “elevator pitch” that connects with your intended audience. If appropriate for your organization, you could also consider shortening those three sentences to a tagline that could be used within the legal department to give visibility to the project. A great example of a tagline was Apple’s iPod: “1,000 songs in your pocket.” This was a short statement showing how the product solved the problem. Something similar in the CLM space could be “your contracts, and revisions, in one place” or “automating the contracts that don’t need your attention.” 4. Check in on user satisfactionRemember that your job is not finished upon implementation. Continue to check in with your users to see how things are going. When checking in, the best thing to do is a survey so you can measure the response empirically. The most common question to ask in a customer satisfaction survey is how satisfied they are with the solution on a scale of 1-5. You can follow that up by asking what would improve their satisfaction. The survey can be helpful to understand how the solution is working as well as a way to gather areas of improvement. Before making any changes, however, I would recommend doing some interviews to understand the impact and pervasiveness of the issues so you can determine what changes are needed.[1] Typical fields include party name, party state, contract type, contract expiration date, notification period (to the extent different, next contract review date), contract amount (or at least a small/med/large designation), internal legal contact, department, limitation of liabilities, and early payment.legal-operationslegal-ops, blog, legal-operations,legal-ops; bloglighthouse
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Legal and AI: A Symbiotic Relationship for Modern Disclosure
The goal of Practice Direction 57AD (PD57AD, previously known as the Disclosure Pilot Scheme) is to modernise the UK’s disclosure practice. This transformation is essential because the traditional, manual, and combative approach to disclosure is unsustainable in the face of today’s massive data volumes and ever-evolving data sources. Manually collecting and reviewing millions of documents one-by-one has become prohibitively expensive, impossibly time consuming, and prone to the risk of both under and over disclosure. When you add in the combative approach between opposing parties, the traditional disclosure process becomes a recipe for skyrocketing legal costs, missed deadlines, and data issues that can derail entire matters. Conversely, a more cooperative approach that leverages AI technology can help improve the process—by allowing attorneys to focus their expertise on critical parts of the matter and refining AI tools to better handle data now and for future, related matters.Thus, PD57AD focuses on two pivotal elements to modernise disclosure: cooperation and technology. Specifically, PD57AD requires parties to “liaise and cooperate with the legal representatives of the other parties to the proceedings…so as to promote the reliable, efficient, and cost-effective conduct of disclosure, including through the use of technology.” Similarly, the Disclosure Review Document asks that each party outline how they “intend to use technology assisted review/data analytics to conduct a proportionate review of the data set” and further reminds parties of their duty to cooperate. Through PD57AD, legal teams’ relationships to each other and with technology is changing in a few crucial ways that present opportunities to work smarter, more cost effectively , and with greater agility.The duty to cooperateJudges are increasingly focusing on the language requiring cooperation between parties in PD57AD and will admonish counsel who attempt to use the disclosure process as a tool to punish an opposing party. For instance, in McParland & Partners Ltd v Whitehead, when a dispute arose involving the framing of the issues of disclosure, the judge took the opportunity to broadly remind both parties of the following: “It is clear that some parties to litigation in all areas of the Business and Property Courts have sought to use the Disclosure Pilot as a stick with which to beat their opponents. Such conduct is entirely unacceptable, and parties can expect to be met with immediately payable adverse costs orders if that is what has happened.”As data volumes grow and PD57AD becomes more cemented into the fabric of UK’s disclosure practice, there is a growing intolerance for “weaponised” disclosure practices by courts. Certainly, parties can expect that the days of “data dumping” (i.e., the strategy of over collecting and producing documents to bury the opposing party in data) or conversely, winning burden arguments related to the cost and time of manual review, are over. The duty to leverage technology Instead of this combative approach, courts will expect that parties come together cooperatively to agree on the use of technology to perform targeted disclosure that is both more cost effective and efficient. Indeed, in a cloud-based world, this symbiotic relationship between technology and legal is the only successful path forward for an effective disclosure process. Under this modern approach, the technology used to collect, cull, review, and produce data must be leveraged in such a way that results can be verified by opposing counsel and judges. This means that all workflows and processes must be transparent, defensible, and agreed upon by opposing counsel. Even prior to the implementation of the Disclosure Pilot Scheme in 2018, judges had begun to crack down on parties who attempted to “go it alone” by unilaterally leveraging technology to cull or search data in a non-transparent way, without the consent of opposing counsel and/or without implementing industry standard best practices. For example, in Triumph Controls UK Ltd., the judge explicitly admonished a party for deploying a computer assisted review (CAR) search strategy overseen by “ten paralegals and four associates” rather than a “single, senior lawyer who has mastered the issues in the case” to ensure that the criteria for relevance was consistently applied to effectively teach the CAR technology. He also rebuked the party’s CAR approach because it was not transparent and could not be independently verified. Because these technology best practices were not followed, the judge forced the producing party to go back and cooperatively agree with opposing counsel on an alternative review methodology to sample and re-review a portion of the original dataset. The future of disclosure for counsel and clients The modernisation of the disclosure process through cooperation and technology means that it will be increasingly imperative that each party has the requisite legal and technology expertise to meet the requirements of PD57AD. Specifically, each party must have a barrister who understands disclosure law and can guide them through each step of the process in a way that complies with PD57AD. Each party should also have an expert who understands how to implement technology to perform targeted, efficient, and transparent disclosure workflows. As seen from legal decisions emanating around PD57AD, parties without this expertise who attempt to “wing it” will increasingly find themselves facing delayed proceedings, hefty legal costs, and unfavourable judgements by courts. Law firms or corporations that don’t have the requisite expertise internally must look for an external partner that does. This is where an experienced managed review partner can provide a true advantage to both law firms and their clients. Parties should look for a partner who can provide a team of technology experts and experienced barristers, working in tandem and leveraging the industry’s best technology. This team should be ready to jump in at the outset of every matter to understand the nuances of the client’s data, as well as the underlying legal issues at play, so that each step of the disclosure process is performed transparently, defensibly, and efficiently. Over time, a managed review team can become a valuable extension of corporate in-house and law firm teams. This partner can use institutional knowledge, gained by working with the same clients across multiple matters, to create customised, strategic, and automated disclosure workflows. These tailored processes, designed directly for a client’s data infrastructure and technology, can save millions and achieve better outcomes. In turn, law firms can refocus their attention on the evidence that actually matters, while assuring their clients that the disclosure process is contributing to lower legal costs and better overall results.ConclusionUnder the modern approach to disclosure, parties must have someone on their team with the necessary legal and technology expertise to perform the type of targeted, cooperative, and transparent disclosure methodology now required by PD57AD. This partnership between legal and technology is truly the only path forward for a successful disclosure endeavour in the face of today’s more voluminous and complicated datasets. Parties that do not have this expertise should look for an experienced managed review partner who can provide a consistent team of legal and technology experts who can perform each step of the disclosure process efficiently, transparently, and defensibly. ai-and-analytics; ediscovery-reviewreview, ai-big-data, blog, ai-and-analytics, ediscovery-reviewreview; ai-big-data; blogjennifer cowman
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How to Overcome Common eDiscovery Challenges for Franchises
Co-authored by Hannah Fotsch, Associate, Lathrop GPM; Samuel Butler, Associate, Lathrop GPM; and Casey Van Veen, Vice President Global eDiscovery Solutions, Lighthouse2020 has been an incredibly tough year for many businesses, with companies big and small shuttering at a record pace due to COVID-19 restrictions and significant reductions in customer travel and spending. But there is one surprising business type that many people seem to want to continue to invest in despite the pandemic: the franchise business model.For example, both the U.S. Chamber of Commerce and Business.com recently highlighted franchise-model businesses that were not only surviving the pandemic and associated lockdowns, but thriving. And in fact, one of those thriving franchise business types called out by the authors was franchise consulting businesses (consultants that help match aspiring franchise owners with franchise opportunities). Apparently, the pandemic has actually increased investment interest in franchise opportunities.There may be a few different reasons why people are looking to the franchise business model during an economic downturn. Many franchise businesses have the benefit of a widely known name brand and market presence. Many have the benefit of leveraging a fully baked business model – one that has presumably already been proven successful. Many also have more support than solo businesses in a variety of key business development areas, including marketing, advertising, and training. In short, the franchise business model may have more appeal during this economic upheaval than a solo business model because people trust the support it can provide in times of economic trouble.However, there are still several common pitfalls that can drag profits down and slow economic growth, leaving the franchise model just as exposed to failure as a solo business model in this time of economic uncertainty. One of those pitfalls is litigation and internal investigations, and the resulting eDiscovery challenges those two can raise. Not only do businesses operating within a franchise model face the same types of litigation and employee workplace issues that all other businesses face – they may also have to deal with added litigation that is unique to the franchisor-franchisee relationship. All of this means increased cost and overhead, especially when it comes to preserving, collecting, reviewing, and producing the required data during the discovery phase.In this article, we discuss the legal eDiscovery challenges and the primary legal issues that we see affecting franchise businesses, large and small. We’ll also provide best-practice tips that can help keep eDiscovery costs down and enable franchise businesses to utilize their advantage and continue to survive and thrive during this trying time.Legal eDiscovery ChallengesThere are four main challenges we see affecting franchise businesses currently: (1) the explosion of data sources; (2) the increased frequency of internal investigations and compliance matters; (3) the lack of a playbook to ensure discovery is managed in a low risk, low-cost manner; and (4) big data challenges.Explosion of Data SourcesWalk through any franchise store, restaurant, or facility today and you will be amazed at the number of devices and systems that must be contemplated in discovery.Fixed systems on property: Video security, card key access, time clock, email, and desktop computersCloud-based systems: Many of the above systems can also be found in the Cloud along with M365 and Google Suite of business documents, email, collaboration tools, and backupsEmployee sources: Personal email, cell phones (video, app chat, texts), iPads, and tabletsCorporate maintained systems: Marketing documents, HR systems, Material Safety Data Sheets (MSDSs), proprietary training, and competitive analysis documentationMoreover, employees at different franchise businesses may often choose to communicate on different platforms, which can exponentially diversify data sources. This amount and variety of sources can pose a myriad of challenges from an eDiscovery perspective.The duty to preserve data begins as soon as litigation is “reasonably foreseeable.” Thus, once an allegation that may lead to litigation surfaces, the clock begins ticking, not only to effectively respond to the allegation but also to ensure that evidentiary data at issue is preserved. And once discovery begins, that preserved data will need to be collected. All of this can present challenges for the ill-prepared: How do you collect data from employees’ personal devices? What are the local state and federal rules regarding the privacy of personal devices? How does collecting the data differ from Apple device vs Android devices? The need to be aware of platforms that create data and the possibilities for collecting that data from them must be addressed before litigation begins, or businesses risk losing data that could be essential to litigation.Key takeaway: Know your data sources as a standard course of business. Make sure that you know where data resides, how it can be accessed, and what can and cannot be collected from data sources.Internal Investigations & Compliance MattersThere has been a drastic increase in internal investigations and compliance matters with franchise clients recently. Hotline and compliance phone line tips, allegations around employee theft, and suspected fraud are on the rise. The key to resolving these types of investigations quickly and cost efficiently is speed. Attorneys and company executives need to know as soon as possible: is there truly an issue, how far does it go, how long has it been happening, how many employees does this effect, and what is the exposure (financially, socially). It is important to develop workflows and tools to help decision-makers and their legal experts sift through the mountains of data quickly.To understand the importance of this, consider this example. A company sales representative leaves the business and does not disclose their next line of work. A tip line reveals they the representative may have left for a competitor. Shortly thereafter, business deals that were executed and even ones in the pipeline suddenly disappear to a competitor. The former employer quickly conducts a forensic investigation on the representative’s laptop computer. Despite their attempt to hide their activity, the investigation reveals that the representative had downloaded proprietary customer lists, price sheets, and other valuable IP during their last week of employment and had also moved large chunks of confidential information from the company’s servers to thumb drives and utilized their personal email to store work communications. Without a strategic plan in place laying out how to quickly execute a forensic internal investigation in this type of situation, the company would have lost substantial revenue to a competitor.Companies that are particularly concerned about former employees stealing proprietary information can even go further than creating an effective investigatory and remediation strategy – putting a departing employee forensic monitoring program in place can prevent this time of abuse from happening in the first place.Key takeaway: Have a program in place to certify that departing employees leave with only their personal belongings and not proprietary company information.Lack of an eDiscovery PlaybookPlaybooks come in many forms today: user manuals, company directives, cooking instructions, and recipe guides. A successful playbook for the legal department will establish a practical process to follow should a legal or compliance issue arise. Playbooks, like a checklist for a pilot about to fly a plane, ensure that everyone is following a solid process to avoid risk. These documents also prevent rogue players from recreating the wheel and going down potentially expensive rabbit holes.Repetitive litigation situations are particularly well suited for acting according to playbooks, and standardizing the response to these situations helps to ensure the predictability of both outcomes and expenses. For example, these documents can be as granular as necessary but typically include a few key topics such as:The process for responding to a 3rd party subpoena, service, or allegation of wrongdoingThe company’s systems that are typically subject to discoveryIT contacts that can help gather the information/dataA list of service providers/trusted partners to assistStandard data processing and production specifications (i.e. time zone, global deduplication, single-page TIFF images 400 dpi, text, and metadata fields)Preferred technologies to search, review, and produce documents (i.e. Relativity)Key takeaway: Playbooks can shave days off of the engagement process with outside counsel and data management companies. Having a repeatable process and plan on day one will save time and money as well as reduce risk.Big Data ChallengesFranchisors face issues in litigation that are unique to the industry, from vicarious liability claims involving the actions of franchisees or their employees to the sheer unpredictability that comes from extensive business relationships involving franchisees of a breathtaking range of sophistication. An increase in litigation leads to an increase in data. Even a run-of-the-mill dispute can lead to the need to gather (and potentially review) more than 100,000 documents. Add one or two more small disputes, and the amount of data quickly becomes unmanageable (and expensive).Fortunately, there have been impressive advances in the field of advanced legal analytical and artificial intelligence (AI). These innovative eDiscovery tools can help legal professionals analyze data to quickly identify documents that are not important to the litigation or investigation (thereby eliminating the need to review them), as well find the “story” within a data set. For example, some analytical tools can help identify code words that an employee might have used to cover up nefarious actions, or analyze communications patterns that allow attorneys to identify the bad actors in a given situation. Other tools now have the capability of analyzing all of the company’s previously collected and attorney-reviewed data, which substantially reduces the need for attorney review in the current matter.All of these tools work to reduce data burden, which in turn reduces costs and increases efficiency.Key takeaway: Take the time to learn what eDiscovery solutions are available on the market today and how you can leverage them before you are faced with a need to use them.To discuss this topic more, please feel free to reach out to me at CVanVeen@lighthouseglobal.com. ediscovery-review; ai-and-analyticscloud, ai-big-data, compliance-and-investigations, ediscovery-process, blog, ediscovery-review, ai-and-analyticscloud; ai-big-data; compliance-and-investigations; ediscovery-process; blogcasey van veen
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Legal and Compliance Should Use Chatbots to Their Advantage
Most of you are pretty familiar with using website chatbots in your daily lives – whether to assist in your online banking or to help with a product issue. But what if you went to report sexual harassment at work and you were greeted by a chatbot? That may seem a little unusual, however, there are a couple of advantages to this approach, including a better customer service experience for internal customers and allowing the compliance professionals to take on more complex work. For several years the legal and compliance industry discussions around chatbots have focused on how law firms can use chatbots. In this blog, I will focus on three ways in-house legal and compliance departments should use them to their advantage.1. As a legal intake tool.A common challenge for legal departments is how to intake matters and manage the work in the legal department. Legal operations teams are always looking for ways to understand what people are doing and how to make the process more efficient. There is a lot of discussion on how forms and/or workflow tools can be leveraged to solve this issue – and they are very helpful – but you can take this one step further with a chatbot. When someone inside your organization comes to the legal team, you can have a chatbot gather basic, or even more detailed, information about what they need. You can train a chatbot to understand the category of their need – advice, contract, patent, litigation, eDiscovery – and then take them through a series of questions to better understand the need. You can then even have the request routed through your workflow tool so it gets assigned to the right person (e.g., assigned to an attorney, a paralegal, or an eDiscovery project manager). As your chatbot gets familiar with the questions, you can have it ask deeper questions and take the request even further.2. To answer common legal questions.Legal departments tend to run lean. As a former general counsel who still speaks with a lot of legal department leaders, I know these leaders are always looking for ways to do more with less (or the same). They want to ensure their teams are spending time on substantive legal issues and not answering common questions that come up and can be handled differently. For example, answering questions about where to find the sexual harassment training or how to send over or sign a standard NDA, are questions that come into the legal department and lawyers spend their time answering them. These questions could easily be answered by a chatbot trained with common questions. This would provide a better user experience because the information is shared instantaneously with the user and it also frees up time for legal resources to spend their time on more unique issues. Finally, legal team members also feel more productive and engaged because their time isn’t being spent on more administrative tasks!3. In place of a hotline.This is one of the more unique use cases I have heard recently but it makes a lot of sense. Compliance hotlines work well because of the anonymity available but there is not an opportunity to share information back with the person reporting. For example, the person reporting an incident may want to know what the next steps might be, where they can find a certain policy, or where they can find additional resources. None of that is available via a hotline or even a form. With a chatbot, however, you can keep the anonymity but mimic a more personal conversation where additional resources can be shared. As shared on the Women in Compliance podcast, one organization has trained chatbots to be their first line of intake and support on sexual harassment complaints. The internal response has been very positive.legal-operationscompliance-and-investigations, legal-ops, blog, legal, legal-operations,compliance-and-investigations; legal-ops; blog; legallighthouse
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Law & Candor Season 8 Available Now!
The Law & Candor podcast is back for Season 8, continuing its exploration of the legal technology revolution. Our co-hosts return with a stellar slate of expert guests and captivating conversations, all striving to elevate the current state of our industry and look to the future.Bill Mariano and Rob Hellewell are back to help lead those discussions in six easily digestible episodes that cover a range of topics, including: AI and linguistics in eDiscovery, staying ahead of AI innovation, family versus four corner review, cross-matter review strategy and implementation, unindexed items in Microsoft 365, and the rise of wearable devices and health-related apps.Episode 1. Finding Lingua Franca: The Power of AI and Linguistics for Legal TechnologyEpisode 2. Staying Ahead of the AI CurveEpisode 3. eDiscovery Review: Family Vs. Four CornerEpisode 4. Achieving Cross-Matter Review Discipline, Cost Control, and EfficiencyEpisode 5. Understanding Microsoft 365 Unindexed Items Episode 6. Getting Personal—Wearable Devices, Data, and CoGetting Personal—Wearable Devices, Data, and Compliance Listen now or bookmark individual episodes to listen to them later, and be sure to follow the latest updates on Law & Candor's Twitter. And if you want to catch up on past seasons or special editions, click here.For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.ediscovery-reviewblog, podcast, ediscovery-review,blog; podcastlighthouse
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Law & Candor Season 10: New Conversations for the Legal Technology Revolution
With a new look, and new co-host, Law & Candor returns for its 10th season. Paige Hunt, Vice President of Global Discovery Solutions at Lighthouse, joins Bill Mariano for more compelling conversations with industry leaders and luminaries in the legal and technology spaces.In six brand new episodes, our guests and co-hosts explore some of the most pressing issues for the industry, including: data governance in the work-from-home era; improving mental health in legal and eDiscovery; the power of review analytics; championing diversity, equity, and inclusion; the role of AI in cross-border data transfer; and self-service, spectra solutions for internal investigations.Listen and learn more about the episodes : Episode 1: Data Governance for the BYOD AgeEpisode 2: Review Analytics for a New EraEpisode 3: Legal’s Mental Health ImperativeEpisode 4: Anonymization and AI: Critical Technologies for Moving eDiscovery Data Across Borders Episode 5: Investigative Power: Utilizing Self Service Solutions for Internal Investigations  Episode 6: A Journey from One to All in Legal with Diversity, Equity, and Inclusion   For more news and updates, follow Law & Candor on Twitter. And if you want to catch up on past seasons or special editions, click here.For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com. ediscovery-reviewblog, podcast, ediscovery-review,blog; podcastmitch montoya
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Law & Candor Season 6 is Now Available!
This eDiscovery Day, a day dedicated to educating industry professionals around growing trends and current challenges, we are excited to bring you season six of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution.Co-hosts, Bill Mariano and Rob Hellewell, are back for another riveting season of Law & Candor with six easily digestible episodes that cover a range of hot topics such as how cellular 5G increases fraud and misconduct risk to tackling modern attachment challenges in G-Suite, Slack, and Teams. This dynamic duo, alongside industry experts, discuss the latest topics and trends within the eDiscovery, compliance, and information governance space as well as share key tips for you and your team to take away. Check out season six's lineup below:Does Cellular 5G Equal 5x the Fraud and Misconduct Risk?Cross-Border Data Transfers and the EU-US Data Privacy Tug of WarReducing Cybersecurity Burdens with a Customized Data Breach WorkflowTackling Modern Attachment and Link Challenges in G-Suite, Slack, and TeamsThe Convergence of AI and Data Privacy in eDiscovery: Using AI and Analytics to Identify Personal InformationAI, Analytics, and the Benefits of TransparencyCheck them out now or bookmark them to listen to later. Follow the latest updates on Law & Candor and join in the conversation on Twitter. Catch up on past seasons by clicking the links below:Season 1Season 2Season 3Season 4Season 5Special Edition: Impacts of Covid-19For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.ediscovery-reviewmicrosoft, cybersecurity, analytics, g-suite, ai-big-data, cloud-security, cloud-migration, phi, pii, blog, ediscovery-review,microsoft; cybersecurity; analytics; g-suite; ai-big-data; cloud-security; cloud-migration; phi; pii; bloglighthouse
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Law & Candor Season 11: How Innovative Women Are Advancing eDiscovery, Legal, and AI
Individual stories can lead to collective action, innovation, and change. Throughout our celebration of Women’s History Month, this is a critical lesson that has emerged in our conversations with leading women in the eDiscovery, legal, and technology spaces. In the brand-new season of Law & Candor, we’re thrilled to share six more stories of women bringing innovation, agility, and tenacity to modern data and legal challenges. Our co-hosts Paige Hunt and Bill Mariano explore a range of key issues with our guests, including:Episode 1—Optimizing Review with Your Legal Team, AI, and Tech-Forward Mindset Episode 2—Everything Dynamic Everywhere: Managing a More Collaborative Microsoft 365Episode 3— Why Your Data is Key to Reducing Risk and Increasing Efficiency During Investigations and LitigationEpisode 4— An Expert View on the Critical Data Privacy Issues for 2023 and Beyond Episode 5— Prioritizing Information Governance and Risk Strategy for a Dynamic Economic ClimateEpisode 6— The Chat Effect: Improving eDiscovery Workflows for Modern Collaboration Data To keep up with news and updates on the podcast, follow Lighthouse on LinkedIn and Twitter. And check out previous episodes of Law & Candor at https://www.lighthouseglobal.com/law-and-candor-podcast.For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.diversity-equity-and-inclusionblog, podcast, dei, diversity-equity-and-inclusion,blog; podcast; deimitch montoya
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Law & Candor Returns for Women’s History Month, Highlighting Legal and Technology Innovators and Trailblazers
To celebrate Women’s History Month, the Law & Candor podcast returns for season nine to interview women in the legal and technology industries who are breaking bias and creating more inclusive work cultures, advancing technological innovation, and keeping a pulse on the latest issues facing corporations and law firms.Law & Candor co-hosts, Rob Hellewell and Bill Mariano, return as our guides through a variety of dynamic topics, including balancing risk and innovation, AI and HSR Second Requests, and the evolving data privacy landscape. Check out this season’s lineup belowLeading in Legal with Inclusive MentorshipLegal’s Balancing Act: Risk, Innovation, and Advancing Strategic PrioritiesMapping Updates to Data Privacy Regulations WorldwideSpring Cleaning for Legal Teams: The Cloud and Defensible Deletion of DataClosing the Deal: Deploying the Right AI Tool for HSR Second RequestsMicrosoft 365 and the Age of Automation Listen now or bookmark individual episodes, and be sure to follow the latest updates on Law & Candor’s Twitter.And if you want to catch up on past seasons or special editions, click here.For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.diversity-equity-and-inclusionblog, diversity-equity-and-inclusion,bloglighthouse
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Law & Candor Podcast Celebrates Women's History Month with Launch of Season 7
The Law & Candor podcast is back for season seven, with a special guest speaker twist! In celebration of Women’s History Month (March), this season features an all-female guest speaker lineup. Our esteemed guests will not only explore the hottest topics in legal tech, but also discuss how to champion the development and career growth of women within the space in each episode.Law & Candor co-hosts, Bill Mariano and Rob Hellewell, are back to help lead those discussions in six easily digestible episodes that cover a range of topics: from diversity within eDiscovery, to keeping up with M365 software updates, to a look at possible antitrust changes in a new presidential administration. Check out season seven's lineup below:Diversity and eDiscovery: How Diverse Hiring Practices Lead to a More Innovative Workforce Innovating the Legal Operations Model Efficiently and Defensibly Addressing Microsoft Teams Data Keeping Up with M365 Software Updates AI and Analytics for Corporations: Common Use Cases Antitrust Changes in a New Administration Listen now or bookmark individual episodes to listen to them later, and be sure to follow the latest updates on Law & Candor's Twitter. And if you want to catch up on past seasons or special editions, click here.For questions regarding this podcast and its content, please reach out to us at info@lighthouseglobal.com.diversity-equity-and-inclusionmicrosoft, ai-big-data, legal-ops, blog, antitrust, corporate-legal-ops, diversity-equity-and-inclusionmicrosoft; ai-big-data; legal-ops; blog; antitrust; corporate-legal-opslighthouse
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In Flex: Utilizing Hybrid Solutions for Today's eDiscovery Challenges
As eDiscovery becomes more complex, organizations are turning to hybrid solutions that give them the flexibility to scale projects up or down as needed. Hybrid solutions offer the best of both worlds: the ability to use self-service, spectra for small matters or full-service for large and complex matters. This flexibility is essential in today's litigation landscape, where the volume and complexity of data can change rapidly. Hybrid solutions give organizations the agility to respond quickly and effectively to changing eDiscovery needs. In a recent webinar, I discussed hybrid eDiscovery solutions with Jennifer Allen, eDiscovery Case Manager at Meta, and Justin Van Alstyne, Senior Corporate Counsel, Discovery and Information Governance at T-Mobile. We explored some of the most pressing eDiscovery challenges, including data complexity, staffing, and implementation. We also discussed scenarios that require flexible solutions, keys to implementing new technology, and the future of eDiscovery solutions. Here are my key takeaways from our conversation.Current eDiscovery challengesA hybrid approach can transition between an internally managed solution and a full-service solution, depending on the nuances and unique challenges of the matter. This type of solution can be beneficial in situations where the exact needs of the case are not known at the outset. A few challenges come into play when deciding your approach to a project:Data volume: When dealing with large data sets, being able to scale is critical. If the data for a matter balloons beyond the capacity of an internal team, having experts available is critical to avoid any disruptions in workflows or errors.Data predictability: When it comes to analyzing data, consistency and predictability can greatly inform your approach to analysis. Standard data allows for more flexibility, as there is an expectation that the results will fall within a certain range. However, to ensure accurate representation, caution must be exercised when dealing with complicated big data. It is important to consider variables, potential outliers, and how the data is compiled and presented. Internal capacity: It's important to monitor and manage the internal workload of your team closely. When everyone is already at their maximum capacity, it can be tempting to outsource various tasks to a full-service project manager. Technology can be a more cost-effective and efficient method for filling the gaps.The right talent and knowledge Finding and utilizing the right team in today's competitive labor market can be difficult. A hybrid solution can help with this by providing a scalable way to get the most out of your workforce. With a hybrid solution, you have the option to staff fewer technical positions and provide training on the data or matters your organization most frequently encounters with your existing team. But, if you have a highly complicated data source, you can still staff an expert who knows how to handle that data. An expert can shepherd the data into a solution, do extensive quality control to ensure that you marry up the family relationships correctly, and give confidence that you're not making a mistake.To assuage concerns about the solution being misused, technology partners can provide training and education, and limit access to who can create, edit, or delete projects within the tool. This training helps to upskill your team by teaching them more advanced technology, which leads to more efficient and sophisticated approaches to matters.Flexible solutions for different mattersA hybrid solution can be a great option for a variety of matters, including internal investigations, enforcement matters, third-party subpoenas, and case assessments. These matters can benefit from the flexibility and scalability provided by a hybrid approach.When determining if a matter needs full-service treatment, it's important to consider the specific requirements at hand. Questions around the volume and frequency of data production, the types of data involved, and the necessary metadata and tagging all play a role in determining if a self-service, spectra approach will suffice or if full-service support is needed. It's always important to consider the timeline and potential challenges during the transition. Using experience with similar cases can provide valuable insight into what might work best in your situation.Keys for implementing eDiscovery solutionsThere are a few critical components to keep in mind when evaluating which eDiscovery solutions and tools are right for your business now, and as it grows.Training team: With any new solution or product there may be some trepidation around learning and adoption. Leverage vendor support to answer your questions and help train your team. Keep them involved in your communications with outside counsel and internal teams so you can receive suggestions and assistance if needed. As users get more experience with the software, they will begin to feel empowered and understand how the tool can be used most effectively. Scalability: One of the most significant hurdles to scaling big eDiscovery projects is the amount of data that needs to be processed. With new data sources, tighter deadlines, and more urgency, it can be difficult to keep up with the demand. Using a fully manual process or a project management solution has a greater chance for error or increased cost. A flexible solution can help your team keep up with increasing data volumes while reducing costs and errors. Automation: Automating repetitive tasks and workflows can dramatically speed up data collection and analysis. This can be a huge advantage when investigating large, complex cases. Additionally, automation can help to ensure that data is collected and parsed consistently.Cost-benefit analysis: Through support and training with a self-service, spectra tool, you can work to reduce the number of support requests. This can minimize the time your team spends on each request and ultimately lowers the cost of providing support. The cost reduction of self-service, spectra tools is often substantial, and it can have a positive snowball effect as your team becomes more skilled at the task. You can reinvest those savings into other business areas with less need for oversight and fewer mistakes. The future state of eDiscovery solutionsThe proliferation of DIY eDiscovery solutions has made it easier for organizations to take control of their data and manage their cases in-house. As AI technology, including continuous active learning (CAL) and technology-assisted review (TAR), continues to evolve, teams will better understand how to handle the growing demands of data and implement hybrid tools. As we move into the future of eDiscovery and legal technology, DIY models will play an increasingly important role in supporting business needs.ediscovery-review; ai-and-analytics; lighting-the-path-to-better-ediscoveryself-service, spectra, blog, ediscovery-review, ai-and-analyticsself-service, spectra; blogself-service, spectrapaige hunt
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Illuminating eDiscovery in 2021: Top Six Reads
Complexity, resiliency, adaptability are some of the defining traits from the past year, with good reason. From navigating hybrid workplaces and new collaboration platforms to weathering economic uncertainty and new regulatory postures, the legal industry, and workforce overall, have faced extraordinary challenges. But, with the adversity came great innovation and problem solving. Developments in communications, artificial intelligence (AI), and data have opened new, and often unexpected, possibilities for years to come.With these dynamics in mind, below we've compiled some of our best thinking from 2021, covering critical topics in eDiscovery such as data privacy, AI, information governance, analytics, privilege, and big data. Explore the posts below for some fresh thinking to enter a new year:Navigating the Intersections of Data, Artificial Intelligence, and PrivacyMaking the Case for Information Governance and Why You Should Address it Now Is Your AI Algorithm Admissible in Court? Some Things to ConsiderBig Data Challenges in eDiscovery (and How AI-Based Analytics Can Help)Privilege Mishaps and eDiscovery: Lessons LearnedFour Ways a SaaS Solution Can Make In-House Counsel Life Easierediscovery-reviewblog, ediscovery-reviewbloglighthouse
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Is Your Workflow Working? Finding Facts in Healthcare Litigation and Investigations
Are you a healthcare provider or payor with any of these concerns?Your company is trying to manage its budget for litigation and investigations but can’t find the most effective approachYou’re concerned that you may be missing critical insights because you can only review a small subset of your document population to stay within your budgetYou’re subject to an investigation and you want to quickly understand if the government or opposing party has any “gotcha” informationYou want to proactively perform a risk assessment to monitor for fraudulent activitiesIf so, you’re not alone. These are challenges that depend on finding pertinent facts, many of which are buried in the volumes of electronic information most companies now have, quickly and efficiently. In the healthcare industry especially, where litigation and investigation risks are common, complex data environments can pose confounding obstacles to finding key information quickly.In the case of any litigation or investigation, it pays to be able to hit the ground running. Early and effective fact-finding can provide valuable insights for both company and counsel, enabling cost-effective resource alignment based on the strength of the case and faster development of the narrative.Since most insight comes from an assessment of facts that lie within electronically-stored information (ESI), advance preparation for data preservation and collection is critical. So is having the right methodology, tools and expertise in place to find key information once you’ve identified the most important data to explore. Here’s how to optimize those efforts.It's all about data. Plan accordingly.In today’s complex healthcare data landscape, knowing (and finding) the key documents and other information located within massive data collections is no mean feat. Although many data repositories in an enterprise are contained and accessible, today’s myriad data sources, from mobile devices to billing systems to sensor data, are growing in size and complexity every day. Advance planning can speed up the process and enable straightforward and beneficial negotiations with the opposing counsel or regulatory agency.What to do? In advance of litigation or investigation, make sure the enterprise maintains an inventory of data systems that includes descriptions of business owners, users, locations, functionality, backups, data types, possible PII/PHI, and a potential preservation/collection approach. Counsel and in-house legal teams should work with IT to organize this information in a format that can be useful for eDiscovery to enable an expeditious and organized response to a matter.Then make sure that you have the right experts to preserve/collect data from the implicated sources. You may need forensic collections or different ways to extract relevant information from certain data stores. Databases and other structured data sources may require reporting rather than collection techniques, for example, and it’s best to know that early, when you can inform and negotiate with the requesting agency or other side, setting expectations and mitigating potential conflict.Finding key documents quickly is essential. Scrap an out-of-date workflow and explore new methods and tools. There are complex needs involved in a litigation or investigation response and a dizzying array of service providers, tools and technologies to choose from, with new ones being offered every day. The traditional workflow of finding key documents—developing keyword search terms to cull the documents then performing a manual review—is just not efficient. New data analytics and machine learning tools (not to mention the experts that provide them) have opened up a whole new fact-finding horizon. Imagine a team of linguists and search experts with experience in the healthcare domain attacking a complex data population with advanced search and analytics tools going after key documents right from the very start. Actually experiencing how experts leverage such tools to accelerate time to critical insights may be eye-opening for any legal teams who have had to spend weeks and months trying to piece the facts together.What to do? If you haven’t explored new ways to find key documents, you’re probably bogged down with an out-of-date workflow. Pairing advanced analytics tools with the right expertise can accelerate fact-finding and document review, but you may have to try it to believe it. You could discover that having the right expertise on hand in advance of the need will expedite response efforts, reduce cost and risk, and lead to the best possible outcome.Learn more about finding facts fast with Key Document Identification. ediscovery-reviewblog, -investigations, key-document-identification, fact-finding, healthcare-litigation, healthcare-investigations, ediscovery-review,blog; key-document-identification; fact-finding; healthcare-litigation; healthcare-investigationslighthouse
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How the Right Legal Team, AI, and a Tech-Forward Mindset Can Optimize Review
To keep up with the big data challenges in modern review, adopting a technology-enabled approach is critical. Modern technology like AI can help case teams defensibly cull datasets and gain unprecedented early insight into their data. But if downstream document review teams are unable to optimize technology within their workflows and review tasks, many of the early benefits gained by technology can quickly be lost.In a recent episode of Law & Candor, I was happy to discuss the ongoing evolution of document review—including the challenges of incorporating available technologies. We explored some of the most pressing eDiscovery challenges, including today’s data complexity, and how to break through the barriers that keep document review stuck in the manual, linear review model. We also discussed the value of expertise and where it may be applied to optimize review in various phases of a project. Here are my key takeaways from our conversation.Increasing data complexity challenges and entrenched manual review paradigms Today’s digital data—a wellspring of languages, emojis, videos, memes, and unique abbreviations—looks nothing like the early days of electronic information, and it is certainly a universe away from the paper world where legal teams had to plow through documents with paper cuts, redaction tape, and all. Yet, that “paper process” thinking—the manual, linear review model—still has a firm hold in the legal community and presents an unfortunate barrier to optimizing review. The evolution is telling. As digital data began to take over, the early AI adopters and the “humans need to look at everything” review camps staked their ground. Although the two are moving closer together as time goes on, the use of technology is not as highly leveraged as it could be, leaving clients to pay the high costs of siloed review when technology-enabled processes could enhance accuracy and reduce costs. There are a variety of factors that can contribute to this resistance, but it may also be simply a matter of comfort; it’s always easier to do what you already know in the face of changes that may seem too difficult or complex to contemplate. For the best result, know when and where to leverage available technologies in the review process Human beings are certainly a core component of the document review process, and they always will be, but thinking about the entire review lifecycle strategically, from collection through trial preparation, is critical when it comes to understanding where you can gain value from technology. Technology should be considered a supplement to—not a substitute for—human assessment and knowing where to use it effectively is important. When considering the overall document review process, two key questions are: Where can you get more value by using technology? And where are the potential areas of either nuanced or high-risk communications that may require a more individualized assessment? The goal, after all, isn’t to replace humans with technology, but rather to replace outmoded contract review factories with smarter alternatives that leverage the strengths of both technology and human expertise. A smaller review team, coupled with experts who can effectively apply machine learning and linguistic modeling techniques in the right place, is a much more efficient and cost-effective approach than simply using a stable of reviewers. Technology buyers need to understand what a given tech does, how it differs from other products, and what expertise should be deployed to optimize its use Ironically, the profusion of viable tech options that can applied to expedite document review may be off-putting, but this is a “many shades of gray” situation. Many products do similar things and it is important to understand what the differences are—they may be significant. Today’s tools are quite powerful and layering them alongside the TAR tools that document review teams have become more familiar with is what allows for the true optimization of the review process. These tools are not plug-and-play, however. You need to know what you’re doing. It takes specific expertise to be able to assess the needs of the matter, the nature of the data, the efficacy of the appropriate tools, and whether they’re providing the expected result. Collaboration is still the critical core component of document reviewAnd let’s not forget that document review is a collaborative process between client counsel, project managers, and the review team. Within this crucial collaboration, specific expertise at various points in the process ensures the best result, including: • Expertise in review consulting to assess the right options for both the data that’s been collected and the project goals.• Individualized experts in both the out-of-the-box TAR technology as well as any proprietary technology being used so that the tech can be fine-tuned to optimize the benefits.• A core team of expert human reviewers with the appropriate skills.Experimentation with technology can help bridge the divideWith so many products available to enhance the document review workflow, it makes sense to test potential options. Running a parallel process for a particular aspect of the review to get comfortable with a new product can be very helpful. For example, privilege review, which is an expensive part of the review process, could be a good place to test an alternate workflow. An integrated approach works bestThe bottom line is that an integrated approach, advanced technology, and human expertise, is the best solution. The technology to increase the efficiency and effectiveness of document review is out there and most of it has been shown to be low risk and high value. The cost-effectiveness of an integrated approach has been shown over and over again: In using the appropriate technology, budgets can be reduced, and savings reinvested in new matters. It is up to the client and their legal and technology teams to work together in deciding what combination of tools makes the most sense for their organization and matter types. Just make sure to call upon those with the appropriate expertise to provide guidance. For more examples of how AI and human expertise are optimizing review, check out our review solutions page. ai-and-analytics; ediscovery-reviewai-big-data, blog, managed-review, ai-and-analytics, ediscovery-reviewai-big-data; blog; managed-reviewmary newman
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How Name Normalization Accelerates Privilege Review
A time-saving tool that consolidates different names for the same entity can make all the difference. One of the many challenges of electronic information and messaging rests in ascertaining the actual identity of the message creator or recipient. Even when only one name is associated with a specific document or communication, the identity journey may have only just begun.The many forms our monikers take as they weave in and out of the digital realm may hold no import for most exchanges, but they can be critical when it comes to eDiscovery and privilege review, where accurate identification of individuals and/or organizations is key.It’s difficult enough when common names are shared among many individuals (hello, John Smith?), but the compilation of our own singular name variations and aliases as they live in the realm of digital text and metadata make life no less complicated. In addition, the electronic format of names and email addresses as they appear in headers or other communications can also make a difference. Attempts to consolidate these variations when undertaking document review is painstaking and error-prone.Not metadata — people. Enter “name normalization.” Automated name normalization tools come to the rescue by isolating and consolidating information found in the top-level and sub-level email headers. Automated name normalization is designed to scan, identify, and associate the full set of name variants, aliases, and email addresses for any individual referenced in the data set, making it easier to review documents related to a particular individual during a responsive review.The mindset shift from email sender and recipient information as simply metadata to profiles of individuals is a subtle but compelling one, encouraging case teams and reviewers to consider people-centric ways to engage with data. This is especially helpful when it comes to identifying what may be—and just as importantly what is not—a potentially privileged communication.Early normalization of names can optimize the privilege workflow.When and how name normalization is done can make a big difference, especially when it comes to accelerating privilege review. Name normalization has historically been a process executed at the end of a review for the purpose of populating information into a privilege log or a names key. However, performing this analysis early in the workflow can be hugely beneficial.Normalizing names at the outset of review or during the pre-review stage as data is being processed enables a team to gain crucial intelligence about their data by identifying exactly who is included in the correspondence and what organizations they may be affiliated with. With a set of easy-to-decipher names to work with instead of a mix of full names, nicknames, initials without context, and other random information that may be even more confusing, reviewers don’t have to rely on guesswork to identify people of interest or those whose legally-affiliated or adversarial status may trigger (or break) a privilege call.Name normalization tools vary, and so do their benefits. Not all name normalization tools are created equal, so it is important to understand the features and benefits of the one being used. Ideally, the algorithm in use maximizes the display name and email address associations as well as the quality and legibility of normalized name values, with as little cleanup required as possible. Granular fielded output options, including top level and sub-header participants is also helpful, as are simple tools for categorizing normalized name entities based on their function, such as privilege actors (e.g., in-house counsel, outside counsel, legal agent) and privilege-breaking third parties (e.g., opposing counsel, government agencies). The ability to automatically identify and classify organizations as well as people (e.g., government agencies, educational institutions, etc.) is also a timesaver.Identification of privilege-breaking third parties is important: although some third parties are acting as agents of either the corporation or the law firms in ways that would not break privilege, others likely would. Knowing the difference can allow a team to triage their privilege review by either eliminating documents that include the privilege breakers from the review entirely, significantly reducing the potential privilege pile, or organizing the review with this likelihood in mind, helping to prevent any embarrassing privilege claims that could be rejected by the courts.Products with such features can provide better privilege identification than is currently the norm, resulting in less volume to manage for privilege log review work later on and curtailing the re-reviews that sometimes occur when new privilege actors or breakers come to light later in the workflow. This information enables a better understanding of any outside firms and attorneys that may not have been included in a list of initial privilege terms and assists in prioritizing the review of documents that include explicit or implied interaction with in-house or outside counsel.Other privilege review and logging optimizers. Other analytics features that can accelerate the privilege review process are coming on the scene as AI tools become more accepted for document review. Privilege Analytics from within Lighthouse Matter Analytics can help review teams with this challenging workflow, streamlining and prioritizing second pass review with pre-built classifiers to automate identification of law firms and legal concepts, tag and tier potentially privileged documents, detect privilege waivers, create privilege reasons, and much more.Interested in how Name Normalization works in Privilege Analytics? Let us show you!ediscovery-review; ai-and-analyticsblog, name-normalization, privilege-review, ediscovery-review, ai-and-analyticsblog; name-normalization; privilege-reviewlighthouse
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Getting on the Same Page…of the Dictionary
Have you ever had this scenario – multiple team members from different groups come to you frustrated because the working relationship between their groups is “broken?” Legal is saying they aren’t getting what they need, IT says they are providing what’s asked, and finance doesn’t understand why we are paying our outside vendor for something that the internal IT and legal teams are “supposed to do.” You are responsible for process improvement among these groups so the questions and frustration lands on your desk! This is a common issue. So common, in fact, that this was a big part of a recent Legal Operators webinar I attended. The good news is that the solution may be simple.Often times, the issue revolves around language and how different departments are using the words differently. Let’s explore the above scenario a bit further. The legal team member says they asked IT to gather all data from a certain “custodian.” The IT team took that to mean all “user-created data” on the network from one certain employee, so that is what they provided. They didn’t, however, gather the items on the person’s desktop nor did they gather records that the person created in third-party systems such as the HR and sales systems that the company uses. The legal team, therefore, asked the outside vendor to collect the “missing” data and that vendor sent a bill for their services. Finance is now wondering why we are paying for collecting data when we have an IT team that does that. The issue is that different teams have slightly different interpretations of the request. Although this scenario is eDiscovery specific, this can happen in any interaction between departments. As legal operations is often responsible for process improvement as well as the way legal functions with other departments, the professionals in that group find themselves trying to navigate the terminology. To prevent such misunderstandings in the future, you can proactively solve this problem through a dictionary.Creating a dictionary can be really simple. It is something I have seen one person start on their own just by jotting down words they hear from different groups. From there, you can share that document and ask people to add to it. If you already have a dictionary of your company acronyms, you can either add to it or you can create a specific “data dictionary” for the purposes of legal and IT working together. Another option is to create a simple word document for a single use at the outset of a project. Which solution you select will vary based on the need you are trying to solve. Here are some considerations when you are building out your dictionary.What is the goal of the data dictionary? Most commonly I have seen the goal to be to improve the working relationship of specific teams long term. However, you may have a specific project (e.g., creation of a data map or implementation of Microsoft 365) that would benefit from a project-specific dictionary.Where should it live? This will depend on the goal, but make sure you choose a system that is easy to access for everyone and that doesn’t have a high administrative burden. Choosing a system that the teams are using for other purposes in their daily work will increase the chances of people leveraging this dictionary.Who will keep it updated? This is ideally a group effort with one accountable person who will make any final decisions on the definitions and own updating in the future. There will be an initial effort to populate many terms and you may want a committee of 2 or 3 people to edit definitions. After this initial effort, you can allow access to everyone to edit the document or you can have representatives from each team. The former allows the document to be a living, breathing document and encourages updating, however, may require more frequent oversight by the master administrator. The latter allows each group to have its own oversight but increases the burden of updating. Whichever method you choose, the ultimate owner of the dictionary should review it quarterly to ensure it is staying up to date.Who will have access? I recommend broader access over more limited access, especially for the main groups involved. The more people understand each other’s vocabulary, the easier it is for teams to work together. However, you should consider your company’s access policies when making this decision.What should it include? All department-specific business terms. It is often hard to remember what vernacular in your department is specific to your department as you are so steeped in that language. One easy way to identify these terms is to assign a “listener” from another department in each cross-functional meeting you have for a period. For example, for the next 3 weeks, in each meeting that involves another department, ask one person from that other department to write down any words they hear that are not commonly used in their department. This will give you a good starting point for the dictionary.Note that. although I am talking about a cross-functional effort in the above, this dictionary can also be leveraged within a department. I have found it very effective to create a legal ops dictionary that includes terms from all other departments that you pick up in your work with those other departments. This can still help your goal of resolving confusion and will allow you to get to a common understanding quickly as you are then better equipped with the language that will make your ask clear to the other team.legal-operationsediscovery-process, legal-ops, blog, legal-operations,ediscovery-process; legal-ops; bloglighthouse
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How GDPR and DSARs are Driving a New, Proactive Approach to eDiscovery
Executive SummaryThe GDPR and Data Subject Access Requests (DSARs) are a key reason why companies are starting to focus their attention on information governance strategically, as opposed to simply reacting each time they get a request. With GDPR, companies have seen a significant increase in DSARs and the resulting requirement to look inwardly at their data landscape is timed perfectly with advances in cloud computing.Inconsistent NeedOver the last 20 years, I have assisted clients in responding to triggering events such as litigation and investigations by helping to identify where their data is and how to retrieve, preserve, and filter it for legal review. Rarely have those same clients been interested in proactively implementing information governance frameworks and policies without a consistent need to do so. A General Counsel once told me they face an investigation about as often as every Olympic cycle, so they don’t prioritise resources to prepare for such an infrequent event.The GDPR and associated DSAR obligations have provided exactly this motivation. However, this stick has combined with the carrot of cloud computing to provide the right mix of requirement and capability, not just to make compliance a token project stream within a company, but an enterprise-wide strategic initiative to focus on how data is generated, accessed, managed, and deleted. Common and Civil Law EnvironmentsThroughout my career, I have worked closely with companies in mainland Europe and the Middle East on cross-border litigation and investigations. In my experience, companies operating in civil law jurisdictions are not as familiar with the eDiscovery process as their common law counterparts unless they have faced regulatory scrutiny (such as companies in the financial services or technology industry). This is because they and their counsel do not face the same discovery obligations and thus have not traditionally focused on gathering evidence to produce to a court or third party. The result is inadequate retention procedures and disconnected strategies regarding data management.However, one thing all companies have in common is that using technology to make data management more efficient has become essential as data volumes grow. For example, DSAR responses may not be as ‘normal’ in mainland Europe as they are in the US or UK, but they have universally added motivation to those tasked with managing data within the company.Information Governance Buy-InNow that awareness has increased on the significant consequences of holding certain data longer than you need, senior leadership is prioritising (even at board level) how to effectively manage data within the company. This comes at a time when most companies have moved or are moving to the Cloud. According to Microsoft, “97% of Fortune 500 and 95% of Fortune 1000 companies have Office 365.” Notably, these companies are not moving to the Cloud for compliance or eDiscovery reasons, they are doing so for overall enterprise reasons including streamlining IT operations by moving off premise, giving employees access to modern workplace tools, and for security purposes. But as a bonus, when it comes to comprehensive cloud platforms such as Office 365, information governance, compliance, and eDiscovery tools are already included.Cloud Relevance for Legal TeamsNow that companies are shifting their focus to information governance, what can legal teams do to utilise the investment they’ve made in cloud computing? Since business efficiencies are important but not what legal is primarily concerned about, risk management is the key and to that end, data management is the order of the day. With increased GDPR penalties looming and cloud capabilities at their disposal, lawyers are now turning to the central pillars of information governance – document retention, categorisation, preservation, defensible deletion, identification, collection, and, depending on cloud maturity, data migration.For example, utilising functionality within Office 365, a company has a fighting chance to develop very effective and granular document retention policies that actually work and are dynamic (rather than a dusty document no one ever refers to). Categorising a document (or having it automatically categorised) when it is created, as well as determining, based on its content, when it will be deleted, is a very powerful capability. Setting email and chat message retention based on a defined policy is a significant achievement that goes a long way to limiting what data is kept and for how long.Not Just TechnologyAs GDPR and the Cloud have revolutionised information governance and provided the motivation and capability to address new and existing risks and inefficiencies, for these technology solutions to work in the long term, there needs to be a strong focus on people and processes. Change management has always been the Achilles heel of technology implementation and it is no different for Office 365 when it comes to effective information governance. First and foremost, understanding who in the company has responsibility for various processes needs to be determined. For example, who will respond to a DSAR? Who will create the data searches, preserve the data, and retrieve it for review? When it comes to labelling a document, what is the criteria for determining what qualifies as personal data? How does the technology assist in the decision making? How can a remediation exercise tie into an ongoing retention policy?Overall ComplianceIt is very hard for a multinational company to become 100% GDPR compliant. However, the Cloud offers significant capability for a company to take very reasonable and appropriate measures that go a long way. It’s better to be in the middle of the sheep pack than on the outside when the wolf is close and modern cloud technology allows companies to develop enterprise-wide frameworks to better manage their data. Let the regulators worry about companies with no demonstrable plans, not those who have made comprehensive changes to their data landscape. Even for companies that are not used to the fraught discovery world of US or even UK discovery, information governance has become a key priority due to GDPR and increasingly complex data environments that can now be managed in an effective and coordinated manner.More on this topic can be found in this article, Three Steps to Tackling Data Privacy Compliance Post GDPR. To discuss this article further, please feel free to reach out to me at MBrown@lighthouseglobal.com. data-privacycloud, gdpr, dsars, blog, data-privacy,cloud; gdpr; dsars; blogmichael brown
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How to Get Started with TAR in eDiscovery
In a recent post, we discussed that requesting parties often demand more transparency with a Technology Assisted Review (TAR) process than they do with a process involving keyword search and manual review. So, how do you get started using (and understanding) TAR without having to defend it? A fairly simple approach: start with some use cases that don’t require you to defend your use of TAR to outside parties.Getting Comfortable with the TAR WorkflowIt’s difficult to use TAR for the first time in a case for which you have production deadlines and demands from requesting parties. One way to become comfortable with the TAR workflow is to conduct it on a case you’ve already completed, using the same document set with which you worked in that prior case. Doing so can accomplish two goals: You develop a better understanding of how the TAR algorithm learns to identify potentially responsive documents: Based on documents that you classify as responsive (or non-responsive), you will see the algorithm begin to rank other documents in the collection as likely to be responsive as well. Assuming your review team was accurate in classifying responsive documents manually, you will see how those same documents are identified as likely to be responsive by the algorithm, which engenders confidence in the algorithm’s ability to accurately classify documents. You learn how the TAR algorithm may identify potentially responsive documents that were missed by the review team: Human reviewers are only human, and they sometimes misclassify documents. In fact, many studies would say they misclassify them regularly. Assuming that the TAR algorithm is properly trained, it will often more accurately classify documents (that are responsive and non-responsive) than the human reviewers, enabling you to learn how the TAR algorithm can catch mistakes that your human reviewers have made.Other Use Cases for TAREven if you don’t have the time to use TAR on a case you’ve already completed, you can use TAR for other use cases that don’t require a level of transparency with opposing counsel, such as: Internal Investigations: When an internal investigation dictates review of a document set that is conducive to using TAR, this is a terrific opportunity to conduct and refine your TAR process without outside review or transparency requirements to uphold. Review Data Produced to You: Turnabout is fair play, right? There is no reason you can’t use TAR to save costs reviewing the documents produced to you to while determining whether the producing party engaged in a document dump. Prioritizing Your Document Set for Review: Even if you plan to review the entire set of potentially responsive documents, using TAR can help you prioritize the set for review, pushing documents less likely to be responsive to the end of the queue. This can be useful in rolling production scenarios, or if you think that eventual settlement could obviate the need to reduce the entire collection.Combining TAR technology with efficient workflows that maximize the effectiveness of the technology takes time and expertise. Working with experts who understand how to get the most out of the TAR algorithm is important. But it can still be daunting to use TAR for the first time in a case where you must meet a stringent level of defensibility and transparency with opposing counsel. Applying TAR to use cases first where that level of transparency is not required enables your company to get to that efficient and effective workflow—before you have to prove its efficacy to an outside party.ediscovery-review; ai-and-analyticstar-predictive-coding, ediscovery-review, ai-and-analyticstar-predictive-codingmitch montoya
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Five Common Mistakes In Keyword Search: How Many Do You Make?
When you’re a kid, you love easy games to learn and play, whether they’re interactive games, board games or card games. One of the first card games many kids learn how to play is “Go Fish.” It’s easy to learn because you simply ask the other player if they have any cards of a certain kind (e.g., “got any Kings?”) – if they do, you collect those cards from them; if they don’t, they say “Go Fish” and you have to draw a card from the deck and your turn ends. Easy, right?Conducting keyword searching without a planned, controlled process that includes testing and verifying the results is somewhat like playing “Go Fish” – you might get lucky and retrieve the documents you need to support your case (without retrieving too many others) and you might not. Yet many lawyers and legal professionals think they “get” keyword searching. Why? Because they learned keyword searching in law school using Westlaw and Lexis? Or they understand how to use “Google” to locate web pages related to their topics? But these examples are designed to identify a single item (or handful of items) related to one topic that you seek.Keyword searching for electronic discovery is about balancing recall and precision to produce a proportional volume of electronically-stored information (ESI) that is responsive to the case, which could be thousands or even millions of responsive documents, depending on the issues of the case.Five Common Keyword Searching MistakesWith that in mind, here are five common mistakes that lawyers and legal professionals make when conducting keyword searches:1. Poor Use of Wildcards: Wildcard characters can be helpful in expanding the scope of the search, but only if you use them well — and understand how they are applied by the search engine you’re using (warning: don’t use Google’s search engine as an exemplar). Poorly placed or ill-advised wildcard character(s) can completely blow up a search. A few years ago, there was a case where one of the goals was to identify documents that related to apps on devices (mobile and PC), so the legal team decided to use a search term “app*” to retrieve words like “app”, “application”, “apps”, etc. Great, right? Not when that same term also retrieves terms like “appear”, “apparent”, “applied”, “appraise”, etc. A better search in this case would have been (app or apps or application*). Make sure to think through word variability and consider word formulations that could be hit by the search. Also consider whether wildcard operators are attached at the appropriate place in the stem of a word so that all of the variants are hit. If not, the search might target too many unrelated words or omit words you want to capture.2. Use of Noise or Stop Words: To keep retrieval responsive even in large databases, most platforms don’t index certain common words that appear regularly (defined as “noise” or “stop” words), yet many legal professionals fail to exclude these noise words in the searches they conduct – yielding unexpected results. Search terms such as “management did” or “counseled out” won’t work if “did” and “out” are noise words that can’t be retrieved. There are typically 100 or more words that are not indexed by a typical platform, so it’s important to understand what they are and plan around them in creating searches that can get you as close as possible to your desired result.3. Starting with Searches That Are Too Broad: Another common mistake is to start with searches that are too broad, assuming that you’ll get a result that will be easy to narrow down through additional search. In fact, you may get a result that makes it nearly impossible to determine what might be causing your search to retrieve unexpected results. Keyword search works best when the hard work has been done up front, either by working with subject matter experts who have provided insight into likely vocabulary used (e.g., shorthand, code words, slang) or via a targeted exploration of the document population. That knowledge, coupled with the effective use of Boolean operators like AND, OR, and NOT, should enable you to craft initial searches that put targeted words in the appropriate context, increasing the likelihood that relevant material will be found at the outset. That result will provide the necessary fodder for developing additional searches that are more precise.4. Failing to Test What’s Retrieved: Many legal professionals create a search, perform that search and then proceed to review without testing the results. Performing a random sample on the results could quickly identify a search that is considerably overbroad and would result in a low prevalence rate of responsive documents, driving up costs for review and production. Testing the result set to ensure the search is properly scoped is well worth the time and effort to take that extra step in terms of potential cost savings. Better to review an extra few hundred documents than an extra hundred thousand documents.5. Failing to Test What’s Not Retrieved: It’s just as important to test the documents that were not retrieved in a search to identify areas that were potentially missed. Not only does a random sample of the “null set” help identify searches that were too narrow in scope, they also are important in addressing defensibility concerns related to your search process if it is challenged by opposing counsel.The ”Go Fish” analogy isn’t an original one – then New York Magistrate Judge Andrew J. Peck used it in his article Search, Forward over nine years ago (October 2011) when he observed that “many counsel still use the “Go Fish” model of keyword search.” If you’re making some of the mistakes listed above, you might be doing so as well. Proper keyword searching is an expert planned and managed process that avoids these mistakes to maximize the proportionality and defensibility of your discovery process. It’s not a kid’s game, so make sure you don’t treat it like one.ediscovery-reviewblog, -keyword-search, ediscovery-review,blog; keyword-searchlighthouse
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From A to Ziti: Finding Hidden Meaning and Intent in Large Datasets
Investigators experienced in interrogating data know that there may be more to a communication than meets the eye. Whether from intentional or unconscious behavior, clues abound.When key facts are conveyed in nuanced or disguised language, it is important to explore the available collection of documents and communications with a linguistic and forensic sensibility. Although a difficult endeavor, the payoff is high when previously hidden meaning and intent surfaces in your investigation. In the process, individual finds often lead to a larger set of findings providing you a deeper understanding of who exactly knew or did what, and how they felt about it.Follow the ScentUnlike for a typical discovery request, searching for hidden meaning and intent in large data sets requires an ability to pinpoint nuanced — and often indirect — textual cues. This capability is distinct from relevance-based classification techniques such as TAR, which are optimized to ensure consistent coverage for a topic across a large data set. When looking for possible subterfuge or heightened emotion, for example, the task is more akin to incremental detective work than it is batch or prioritized classification. As such, it is useful to frame your efforts within an iterative search workflow that brings you into contact with potentially interesting content and communications, while also allowing you an ability to pivot off your search to explore particular key people, events, and timelines where interesting content appears to be clustered. Make a ListAn important first step in searching for key content you might otherwise be missing is to develop or tailor pre-existing lists of keywords and phrases targeting the types of behaviors and sentiments you are interested in uncovering.For example, if you are investigating possible fraud, you may want to focus part of your search on isolating communications in which there are textual traces suggesting concealment. Some concealment-related phrases to add to a keyword list for a fraud investigation could include “do not share this,” “take off line,” or “delete email,” to name just a few.Additionally, if you are interested in isolating internal chatter conveying strong concern or worry, you could include items like “atrocious,” “huge mistake,” “ill advised,” or “ordeal.” Ziti? Or Fraud?Apart from language expressing worry or concealment, other language worth targeting to get at hidden meaning and intent could include profanity and slang. Also, keep in mind the cultural context in which the communications and documents you are searching through were produced. For example, in a recent bribery and corruption case in NY state involving NY state government officials and private business executives, “ziti” (or “zitti”) was used as a code word to refer to bribes and extortion money. This particular code word in this context was borrowed from the language used by organized crime in New York and surrounding states.Stay on TopicGiven the richness of language and culture, keyword lists targeting hidden figurative meaning can grow to hundreds, even thousands, of words and phrases. To avoid a deluge of hits, it is useful to pair these special keywords with broad issue indicators to make sure you are targeting not only figurative language, but also potentially relevant content. For example, if you are interested in isolating potential fraud around billing practices, one possible tactic would be to leverage proximity search by pairing fraud-related terms like “unusual” with a broad topical keyword term “billing” (e.g., unusual /50 bill[s,ed,ing]). Using this tactic in a systematic way across targeted sentiments and topics will get you a richer result set to focus your in-depth review on.Prepare Ahead of TimeAs with any search effort, setting up your data by threading email conversations and identifying near-duplicate sets of documents are two of the many approaches available to winnow down and prioritize the set of documents you perform targeted searches on. Techniques such as name normalization can also be especially helpful when your aim is to understand who is communicating with whom on a consistent basis.Keep Smiling It is also useful to explore how best to tailor the indexing of your data for searching — for instance, emojis are often used in key relevant conversations, yet they are rarely indexed automatically for search in review platforms. From both a discovery and investigative perspective, this can be a big blind spot. Preliminary research on the topic shows an increase in the number of US cases referring to emoji as evidence increased from 33 in 2017 to 53 in 2018.Searching for key content conveyed through nuanced language is a complex task that is substantively distinct from relevance and topic classification. With the right mindset, workflow, and tools, you will be able to structure and manage this effort in order to isolate key facts otherwise left hidden that are relevant to your case.ai-and-analyticsblog, key-document-identification, fraud-detection, ai-and-analytics,blog; key-document-identification; fraud-detectionlighthouse
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Finding the Needles Faster – Speeding up the Second Request Process
Facing a second request can be painful, kind of like searching for a needle in a haystack exacerbated by a strict deadline looming above it all. And, as volumes of data continue to grow and types of data become increasingly complex, these matters are often inefficient and costly, while getting to the key documents (needles) quickly can feel like an insurmountable challenge.In the 2019 Antitrust Leadership Panel, I gathered together a group of top antitrust experts to discuss the grueling challenges, the role of technology and emerging trends, and a few concrete recommendations for progress to make second requests more efficient and less costly. The video series of the panel was very well received and I have since been asked by several viewers, “So, Bill, how do I apply these ideas to my current antitrust practice or process? How do I find the needles in the haystack?”In this blog, I will answer just that and distill the key takeaways from the panel to share with your team so that you can be better equipped to tackle a second request and find the critical needle in that giant, ever-evolving haystack of data.Lesson 1: Technology is a must, but so is trust.Our expert panelists all agreed that although the usage of technology can be challenging to negotiate with the DOJ and the FTC, its application is paramount in getting to key documents quickly. With that in mind, the first phase in preparing for your next second request and conquering the haystack of data is to leverage technology. Here are some simple steps to get you started:It’s critical to understand what technology is out there and what it can do (i.e. AI, predictive coding, email threading, deduplication, etc.). Ensure you and your team stay on top of what each of these tools does and how you can leverage them in second requests. Understanding and educating yourself on all aspects of the technology is key to increasing the government’s trust and acceptance of new tools they may not be familiar with…more on that in the next step.Once you understand what technology options are available and have the best probability for success in your specific case, select the tool or tools that make the most sense for your team and secure them (i.e. by leveraging your vendor’s tools or procuring them in house). Work with your vendor or in-house team to develop sound evidence that will persuade the DOJ and FTC to accept technology so that it can be more broadly used and leveraged within your matters. This will allow you to save significant time and money and, who knows, if we all did it the DOJ and FTC may be more likely to accept itLesson 2: Proportionality can save you time and money, leverage it.The panel also discussed that although the DOJ and FTC sometimes don’t seem to make proportionality a priority in second requests and may intentionally request broader swaths of data to buy more time outside of the strict statutory guidelines, it’s clear that proportionality should be a primary focus for both parties to limit the burdensome amount of data that must be collected and reviewed. Consider this next set of steps as another way to potentially save time and money when trying to dig through the haystack of second request data.When faced with a second request, first discuss amongst your team what arguments for proportionality can be made.Ensure your arguments for proportionality are based on compelling evidence and bring them to the DOJ and FTC at the onset of the second request.If your argument is not accepted on one matter, work with your vendor to focus on building more evidence to get the DOJ and FTC on the side of proportionality in your next matter.Lesson 3: Privilege review tools can be a privilege in the long run.According to the panelists, having better and more user-friendly privilege review tools would result in a significantly improved second request process for everyone involved. So, how do you take concrete action on that? Here are a few additional steps to improve the privilege review process and break down one of the most burdensome parts of tackling the haystack.Reach out to your vendor and ask what tools and solutions they have around privilege review.Test out their privilege tools on your next matter and provide feedback for continuous process improvement.Work with your vendor to develop customized privilege tools using advanced analytics to find privileged documents more quickly and easily.When leveraging privilege tools, be sure to track solid metrics and develop new evidence to showcase to the DOJ and FTC why they can trust the advanced technology.Share these takeaways within your team and apply the steps that make sense for your practice so that the next time you’re faced with a daunting second request and a seemingly insurmountable amount of data, you’ll be well positioned to tackle the challenge and find the right needles in the haystack from the onset.Want to discuss this topic more? Feel free to reach out to me at BMariano@lighthouseglobal.com.To explore related content, click the links below:Antitrust Leadership Panel: Time and CostAntitrust Leadership Panel: The Role of TechnologyAntitrust Leadership Panel: Evolving for the Futureai-and-analytics; antitrustanalytics, hsr-second-requests, blog, ai-and-analytics, antitrustanalytics; hsr-second-requests; blogbill mariano
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Featured Females of International Women's Day 2019
In honor of International Women’s Day 2019, Lighthouse highlighted a few female thought leaders who are changing the game in the eDiscovery, compliance, and information governance space. Check out our featured ladies below and discover what they are doing to lead change as well as some of their key tips for success: Take a look at our 2020 International Women's Day Campaign!diversity-equity-and-inclusionediscovery-process, blog, diversity-equity-and-inclusion,ediscovery-process; bloglighthouse
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Four Ways a SaaS Solution Can Make In-House Counsel Life Easier
Your team is facing a wall of mounting compliance requirements and internal investigations, as well as a few larger litigations you fear you may not be able to handle given internal resource constraints. Each case involves unwieldy amounts of data to wade through, and that data must be collected from constantly-evolving data sources—from iPhones to Microsoft Teams to Skype chats. You’re working with your IT team to ensure your company’s most sensitive data is protected throughout the course of all those matters.All of this considered, your team is faced with vetting eDiscovery vendors to handle the large litigation matters and ensuring those vendors can effectively protect your company’s data. Simultaneously, you are shouldering the burden of hosting a separate eDiscovery platform for internal investigations with a legal budget that is already stretched thin. Does this sound familiar? Welcome to the life of a modern in-house attorney. Now more than ever, in-house counsel need to identify cost-effective ways to improve the effectiveness and efficiency of their eDiscovery matters and investigations with attention to the security of their company’s data. This is where adopting a cloud-based self-service, spectra eDiscovery platform can help. Below, I’ve outlined how moving to this type of model can ease many of the burdens faced by corporate legal departments.1. The Added Benefit of On-Demand Scalability‍A cloud-based, self-service, spectra platform provides your team the ability to quickly transfer case data into a cutting-edge review platform and access it from any web browser. You’re no longer waiting days for a vendor to take on the task with no insight into when the data will be ready. With a self-service, spectra solution, your team holds the reigns and can make strategic decisions based on what works best for your budget and organization. If your team has the bandwidth to handle smaller internal investigations but needs help handling large litigations, a scalable self-service, spectra model can provide that solution. If you want your team to handle all matters, large and small, but you worry about collecting from unique sources like Microsoft Teams or need help defensibly culling a large amount of data in a particular case, a quality self-service, spectra provider can handle those issues and leave the rest to you. In short, a self-service, spectra solution gives you the ability to control your own fate and leverage the eDiscovery tools and expertise you need, when you need them. 2. Access to the Best eDiscovery Tools – Without the Overhead Costs A robust self-service, spectra eDiscovery solution gives your team access to the industry’s best eDiscovery tools, enabling you to achieve the best outcome on every matter for the most efficient cost. Whether you want to analyze your organization’s entire legal portfolio to see where you can improve review efficiency across matters, or you simply want to leverage the best tools from collection to production, the right solution will deliver. And with a self-service, spectra model, your team will have access to these tools without the burden of infrastructure maintenance or software licensing. A quality self-service, spectra provider will shoulder these costs, as well as the load of continuously evaluating and updating technology. Your team is free to do what it is does best: legal work.3. The Peace of Mind of Reliable Data Security In a self-service, spectra eDiscovery model, your service provider shoulders the data security risk with state-of-the-art infrastructure and dedicated IT and security teams capable of remaining attentive to cybersecurity threats and evolving regulatory standards. This not only allows you to lower your own costs and free up valuable internal IT resources, but also provides something even more valuable than cost savings—the peace of mind that comes with knowing your company’s data is being managed and protected by IT experts.4. Flexible, Predictable Pricing and Lower Overall Costsself-service, spectra pricing models can be designed around your team’s expectations for utilization—meaning you can select a pricing structure that fits your organization’s unique needs. From pay-as-you-go models to a subscription-based approach, self-service, spectra pricing often differs from traditional eDiscovery pricing in that it is clear and predictable. This means you won’t be blindsided at the close of the month with hidden charges or unexpected hourly fees from a law firm or vendor. Add this type of transparent pricing to the fact that you will no longer be shouldering technology costs or paying for vendor services you don’t need, and the result is a significantly lower eDiscovery overhead that can fit within any legal budget. These four benefits can help corporations and in-house counsel teams significantly improve eDiscovery efficiency and reduce costs. For more information on how to move your organization to a self-service, spectra eDiscovery model, be sure to check out our other articles related to the self-service, spectra eDiscovery revolution – including tips for overcoming self-service, spectra objections and building a self-service, spectra business case.ediscovery-review; ai-and-analyticsself-service, spectra, blog, ediscovery-review, ai-and-analyticsself-service, spectra; bloglighthouse
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Featured Females of International Women's Day 2020
In honor of International Women’s Day 2020, Lighthouse is featuring female leaders within the industry who actively choose to challenge stereotypes, fight bias, broaden perceptions, improve situations, and celebrate women's achievements. Below are spotlights on each of our 2020 featured females helping to make a gender equal world. Check them out!1. What does a gender-equal world mean to you? It means a meritocracy where everyone with skill, hard work, and imagination may aspire to, and actually can achieve, the highest level regardless of gender. It means the elimination of explicit and implicit biases that can skew professional relationships and result in disparate opportunities. It means having a voice and a seat at the table earned through performance and not being sidelined because of gender.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I was raised in a counter-stereotypical environment. My mother was the primary breadwinner and a full-time working professional, while my father took on most of the childcare responsibilities after a full work day of physical labor that began at 5 a.m. I grew up playing backyard tackle football with my brother and male family friends in mud, ice, and rain, and they did not go easy on me. I then joined the Marine Corps. Until a few years ago, I never had the perception that there were limits on what I could achieve because I am female.Unfortunately, I am now intimately aware of the ugly reality of gender discrimination. My experiences allow me to better understand the elements that contribute to disparate treatment and what can be done to address them. Raising awareness of these issues in a more vocal way is in the works. I have never been afraid to challenge the status quo (like using predictive coding in 2012) and I will continue to do so to effectuate positive change.When faced with bias in the past, I researched and gathered information regarding best practices to address such issues. I presented recommendations to leadership and organized events to build community and provide training. I continue to provide mentorship and support to other women. And, I challenge stereotypes by persevering as a working mom in big law.3. How do you celebrate other women's achievements? I like to spread awareness of other women’s achievements and provide other women opportunities to shine. I go out of my way to ensure key decision makers know about the accomplishments of other women.4. What recommendations do you have for others looking to ensure a gender equal workplace? For those trying to establish best practices internally, there are a myriad of resources available. For example, the Center for Worklife Law, spearheaded by the Professor Joan Williams, provides an array of practical tools, model policies, training, and best practice guides. Vote with your feet and dollars. If efforts to effectuate change internally fall on deaf ears, go somewhere else where there is a demonstrated commitment to providing a level playing field. Dentons is truly invested in supporting women, as apparent through their review processes, bias training and safeguards, development and authentic leadership diversity. Support vendors and consultants who demonstrate gender equality. Be cognizant of who you work with and keep busy. Build community.1. What does a gender-equal world mean to you? To me a gender-equal world means not having to over analyze each piece of my daily life to assure my value is recognized by all participants. It means not having to change my approach, tone, or demeanor to be heard by my male colleagues. It means I can be ME.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I personally challenge stereotypes at my firm by being a strong leader, volunteering for important projects, speaking up in meetings, offering feedback to my colleagues equally, male and female. Importantly, I recognize my value to the firm. I am BRAVE. I am CONFIDENT.3. How do you celebrate other women's achievements? Through my leadership in the GOIC Lean In Circle and membership in the Diversity and Inclusion Committee at Orrick, I help host events and provide a forum for women’s accomplishments to be recognized. When working with my colleagues and teams I assure that credit earned is given.4. What recommendations do you have for others looking to ensure a gender equal workplace? Be persistent! Be ambitious! Don’t settle. Recognize your value. People live up to expectations. Make your value known, expect credit. If you don’t get it, seek it out. If you don’t expect to get the next big project, you may never get it. Volunteer and make your voice heard.1. What does a gender-equal world mean to you? A human is recognized for "their" personality and knowledge in all capacities. Mental and physical health are supported and provided for without bias. "We" are respected for virtues both positive and negative.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? Initially and always, listening. What's the reason for the bias? Challenging the responses with actions, calmness, and, ultimately, calling out the unbalanced views. Empathy to all is the sincerest way to "fight" and remove bias.3. How do you celebrate other women's achievements? I like to send notes or cards to congratulate as a small but personal article of celebration. Telling women how fantastic the achievements are and discussing them in other communities. Sharing the knowledge equates to opening new conversations or relighting old topics.4. What recommendations do you have for others looking to ensure a gender equal workplace? Develop an altruistic culture focusing on team dynamics, envelop clients into team and workspace initiatives, and, importantly, talk about it! Publicise the how, the who, and the why.1. What does a gender-equal world mean to you? It means fair treatment across the gender identity spectrum. It does not mean we have to look, talk, or act the same. We all bring something unique to the conversation and should be celebrated equally for our contributions. Rights, opportunities, obligations, and pay should not take gender into consideration. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? My workplace makes diversity a priority. That being said bias still exists, often when you least expect it. When you experience bias, gather your thoughts, speak up, and don’t tolerate bad behavior. Set an example by never apologizing for being at the table. Your opinion matters so speak with authority. 3. How do you celebrate other women's achievements? We’re often bad at celebrating our own achievements, making it more important that we celebrate each other. Words of encouragement when things don’t go as expected and notes of recognition when they do. Use your organization's award, bonus, and feedback structure, especially if achievements were missed by the broader group. 4. What recommendations do you have for others looking to ensure a gender equal workplace? Begin with the end in mind. My organization works hard to expand our candidate pool, rethink our interview process so that a diverse panel interviews candidates, and set up mentor and onboarding programs that match diverse candidates. For my team, work life balance, flexibility, and open communication have been key.1. What does a gender-equal world mean to you? I aspire to a world where we equally value the attributes of all genders and celebrate the power of teams of people with different experiences, perspectives, and strengths. It may seem funny, but when traveling for business, I am often struck by the fact that I am the only woman in the hotel restaurant at breakfast. It would be inspiring to see that change. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? My career path and non-partner role defy stereotypes. In my role, I strive to create an environment where it is safe to disagree and challenge the status quo. The success of my team shows that when you refuse to do things as they have always been done by the same people who have always done them, great things can happen. But, most of all, I love what I do contrary to stereotypes!3. How do you celebrate other women's achievements? As a team we foster meaningful relationships and connections among women so that we can lift each other up and challenge one another. We are active in Women in eDiscovery and She Breaks the Law, and recently nominated 16 women to the ABA Women in Tech list. When selecting vendors, technology solutions, and making investments via our legal tech fund, we look at whether the company has women in senior leadership roles. 4. What recommendations do you have for others looking to ensure a gender equal workplace? Re-imagine the skill set and talent profiles for new hires. Women are under-represented in senior leadership positions in the legal and technology industries. To expand your talent pool, look for candidates in other industries and value innate ability over previous titles and years of experience. Give early opportunities and invest in creating the next generation of women leaders. 1. What does a gender-equal world mean to you? At a basic level, gender equality means having gender never enter into the equation. However, for my everyday reality, it means a workplace where being a working mother that values and prioritizes time with her family does not count against me and is actually celebrated. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? As a manager, I promote an environment that has open and honest communication and treats everyone equally. As a mother, I am raising my two young boys to think of women as not just equals, but as powerful forces. 3. How do you celebrate other women's achievements? As the world comes closer to gender equality, it is important that we reward all individuals in a way that does not create a greater divide. At a basic level, this means rewarding people for the quality of work they do and not just the number of hours they put in. 4. What recommendations do you have for others looking to ensure a gender equal workplace? There are a number of actions companies and individuals can take to help ensure gender equality in the workplace. These can be as simple as removing names from resumes to make them gender neutral, create pay bands based on position and not previous salary, and using gender neutral leave policies. 1. What does a gender-equal world mean to you? A world where gender is no longer a barrier to equal opportunity. A world free of the biases and prejudice currently associated with gender, both overtly and unconsciously, where everyone has a chance to develop their potential. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I support diversity in groups and teams, both during the hiring phase and after hiring. When hiring, I work with recruiters to ensure a diverse applicant pool. When managing, I encourage inclusion and collaboration, thereby allowing for a wide range of perspectives and opinions from which everyone will benefit.3. How do you celebrate other women’s achievements? Whenever a female colleague accomplishes something important, I take the time to recognize, support and encourage her. Where possible, I do so in person. In addition, and where necessary, I also use one of the other myriad avenues for such recognition, including email, phone, text, social media, company intranet.4. What recommendations do you have for others looking to ensure a gender equal workplace? Use best efforts to support and encourage diversity, and celebrate important accomplishments. Start during hiring, working with recruiters to ensure it includes both women and men. When managing, encourage inclusion and collaboration, encourage everyone to develop their potential, and take the time to celebrate the successes.1. What does a gender-equal world mean to you? Girls are often encouraged to believe they can do anything they set out to do, as long as they aren’t too loud about it, because, after all, they must behave like proper young ladies. In a gender-equal world, girls should be as brash as they wish and women should tout their accomplishments.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I lead by example, making sure my voice is heard. When I run meetings, I ensure that every participant has the opportunity to contribute if they wish. I acknowledge great ideas put forth by women when their male counterparts try to co-opt them.3. How do you celebrate other women’s achievements? I choose words carefully when describing women’s achievements to ensure they are gender-neutral and give credit that is deserved. I use active voice to indicate a female team member has worked for her accomplishments, rather than phrases that seem to imply she was lucky to have something happen for her.4. What recommendations do you have for others looking to ensure a gender equal workplace? If you feel overlooked in the workplace, develop allies and mentors. Allies are female and male counterparts who will amplify your voice. Mentors can help navigate workplace politics and educate male-dominated leadership on the importance of gender equality.1. What does a gender-equal world mean to you? A gender-equal world is on in which all people, regardless of their sex, have the same opportunities and receive equal compensation.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I definitely lead by example. As a leader in my organization, I also have a responsibility to identify and correct when stereotypes or biases surface. I find one-on-one conversations with a person who has articulated the stereotype or bias is effective. Some people don't even realize that they have biases. It is important to me that I am known for cultivating a fair work environment for everyone.3. How do you celebrate other women’s achievements? Women need more professional mentors. I seek mentors out myself and I have served as a mentor for many other women in my career. I celebrate the achievements of the women I have mentored with a personal note or even a quick text. I have close professional female counterparts at other organizations. We are intentional about staying connected. Congregations with these ladies at industry events often turn into think tanks of sorts and we are always celebrating someone's latest accomplishment. Women have to hold up and support other women.4. What recommendations do you have for others looking to ensure a gender equal workplace? If you are in the job market, look at the leadership of the organization. That will speak volumes about their efforts to ensure a gender equal workplace. Ask about their commitments to gender quality and any corporate programs they have in place to support those efforts. If you are in a company that lacks in this area, take the initiative to raise it and spearhead a proposal to help them elevate their efforts.A big shout out to the women who participated in our International Women's Day Campaign focused on #EachforEqual! Take a look at our 2019 International Women's Day Campaign. diversity-equity-and-inclusionediscovery-process, blog, diversity-equity-and-inclusion,ediscovery-process; bloglighthouse
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Fact-finding for a litigation or investigation? Plan ahead before diving in
Planning the best ways to find key documents will pay off in the long run. Getting to the bottom of alleged claims is often a high-stakes race to find critical information amidst an avalanche of data. Regardless of whether you are conducting an internal investigation, early case assessment, or preparing for depositions, there is no time to waste. Although it’s surely tempting to dive right into document reviews to find the key documents that will shed light on the matter at hand, litigators and investigators know that good preparation leads to a better result.Conducting fact-finding in a reactive manner by skipping upfront preparation diminishes the ability to systematically investigate the full set of allegations and compromises the development of a comprehensive factual narrative. Here are a few things to keep in mind as you prepare.Consider the source(s).To conduct efficient fact-finding through key document identification, you need to first take stock of the various sources of data available for review and then map them to the type of evidence they may contain.Is the evidence you are looking for likely to reside in reports, communications, or memos? Are there particular sets of custodial data that are likely more important to understanding the case than others? Are inbound consumer marketing solicitations to employees, or bulk email news alerts likely to contain important information for the case? Taking the time to consider these questions and articulate hypotheses about where important evidence may reside allows you to effectively prioritize which data sets to search through first.What are the targets?In addition to prioritizing the data, it’s critically important to articulate the array of evidence you are looking for based on the set of allegations at issue. Your understanding of the case will certainly evolve as fact-finding progresses, but defining evidentiary targets in advance better enables you to assess later on whether you have diligently investigated all possible angles. Moreover, defining discrete targets for fact-finding allows you to articulate searches at a more granular level. Rather than leveraging one fully encompassing crude keyword search to hunt for key documents, creating a net of many targeted searches will lead to more comprehensive results in a more efficient manner.What tools should you use?Another key to efficient and successful fact-finding is selecting the right data analytics tools that will help reduce the noise and boost the signal. For example, threading email conversations and identifying near-duplicate sets of documents are two of the many approaches available to winnow down and prioritize the set of documents you perform targeted searches on. Techniques such as name normalization can also be especially helpful when your aim is to understand who is communicating with whom about which underlying facts. It might even be worth investigating how to best tailor the way the data is indexed for searching — for instance, emojis are often used in key conversations useful in investigations yet they are rarely indexed for search in review platforms unless you explicitly specify them to be.Understanding the data, articulating an evidentiary approach, and equipping yourself with the right data analytics helps ensure that critical facts do go undiscovered. Although it’s natural to want to get right into the thick of it, skilled counsel know that high-stakes fact-finding is a complex affair requiring forethought and preparation. And once in place, a well-informed search strategy can be quickly executed allowing your team to spend more time understanding the significance of key documents, and less time re-evaluating and tinkering with approaches for finding them.Want to know more? Watch “Winning the Race for the Facts: Case Studies on How to Leverage Technology and Search Expertise for Investigations and Case Preparation,” a joint webinar with H5 and Covington & Burling, for further tips on finding key documents for investigations.ediscovery-reviewblog, -key-document-identification, kdi, ediscovery-review,blog; key-document-identification; kdilighthouse
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eDiscovery, Ethics, and the Case for AI
Ever since ABA Model Rule of Professional Conduct 1.1 [1] was modified in 2012 to include an ethical obligation for attorneys to “keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology [2]” (emphasis added), attorneys in almost every state have had a duty to stay abreast of how technology can both help and harm clients. In other words, most attorneys practicing law in the United States have an ethical obligation to not only understand the risks created by the technology we use in our practice (think data breaches, data security, etc.), but also to keep abreast of technology that may benefit our practice.Nowhere is this obligation more implicated than within the eDiscovery realm. We live in a digital world and our communications and workplaces reflect that. Almost any discovery request today will involve preserving, collecting, reviewing, and producing electronically stored information (ESI) – emails, text messages, video footage, Word documents, Excels, PowerPoints, social media posts, collaboration tool data – the list is endless. To respond to ESI discovery requests, attorneys need to use (or in many cases, hire someone who can use) technology for every step of the eDiscovery process – from preservation to production. Under Model Rule 1.1, that means that we must stay abreast of that technology, as well as any other technology that may be beneficial to completing those tasks more effectively for our clients (whether we are providing legal advice to an organization as in-house counsel or externally through a law firm).In this post, I posit that in the very near future, this ethical obligation should include a duty to understand and evaluate the benefits of leveraging Artificial Intelligence (AI) during almost any eDiscovery matter, for a variety of different use cases.AI in eDiscoveryFirst, let’s level set by defining the type of technology I’m referring to when I use the term “AI,” as well as take a brief look at how AI technology is currently being used within the eDiscovery space. Broadly speaking, AI refers to the capability of a machine to imitate intelligent human behavior. Within eDiscovery, the term is often also used broadly to refer to any technology that can perform document review tasks that would normally require human analysis and/or review.There is a wide range of AI technology that can help perform document review tasks. These include everything from older forms of machine learning technology that can analyze the text of a document and compare it to the decisions made about that document by a human to predict what the human decision would be on other documents to newer generations of analytics technology that can analyze metadata and language used within documents to identify complicated concepts, like the sentiment and tone of the author. This broad spectrum of technology can be incredibly beneficial in a number of important document review use cases – the most common of which I have outlined below: Culling Data - One of the most common use cases for AI technology within eDiscovery is leveraging it to identify documents that are relevant to the discovery request and need to be produced. Or, conversely, identify documents that are irrelevant to the matter at hand and do not need to be produced. AI technology is especially proficient at identifying documents that are highly unlikely to be responsive to the discovery request. In turn, this helps attorneys and legal technologists “cull” datasets, essentially eliminating the need to have a human review every document in the dataset. Newer AI technology is also better at identifying documents that would never be responsive to any document request (i.e., “junk” documents) so that these documents can be quickly removed from the review queue. More advanced AI technology can do this by aggregating previously collected data from within an organization as well as the attorney decisions made about that data, and then use advanced algorithms to analyze the language, text, metadata, and previous attorney decisions to identify objectively non-responsive junk documents that are pulled into discovery request collections time and time again. Prioritizing and Categorizing Data - Apart from culling data, AI can also be used to simply make human review more efficient. Advanced AI technology can be used to identify specific concepts and issues that attorneys are looking for within a dataset and group them to expedite and prioritize attorney review. For example, if a litigation involves an employee accused of stealing company information, advanced AI technology can analyze all the employee’s communications and digital activities and identify any anomalies, such as an activity that occurred during abnormal work hours or communications with other employees with whom they normally would not have reason to interact. The machine can then group those documents so that attorneys can review them first. This identification and prioritization can be critical in evaluating the matter as a whole, as well as helping attorneys make better strategic decisions about the matter. Review prioritization can also simply help meet court-imposed production deadlines on time by enabling human reviewers to focus on data that can go out the door quickly (i.e., documents that the machine identified as highly likely to be responsive but also highly unlikely to involve issues that would require more in-depth human review like privilege, confidentiality, etc.). Identifying Sensitive Information - On the same note, AI technology is now more adept at identifying issues that usually require more in-depth human review. Newer AI technology that uses advanced Natural Language Processing (NLP) and analyzes both the metadata and text of a document is much better at identifying documents that contain sensitive information, like attorney-client privileged communications, company trade secrets, or personally identifiable information (PII). This is because more advanced NLP can take context into account and, therefore, more accurately identify when an internal attorney is chatting with other employees over email about the company fantasy football rankings vs. when they are providing actual legal advice about a work-related matter. It can do this by analyzing not only the language being used within the data, but also how attorneys are using that language and with whom. In turn, this helps attorneys conducting eDiscovery reviews prioritize documents for review, expedite productions, and protect privileged information.Attorneys’ Ethical Obligation to Consider the Benefits of AI in eDiscovery The benefits of AI in eDiscovery should now be clear. It is already infeasible to conduct a solely human linear review of terabytes of data without the help of AI technology to cull and/or prioritize data. A review of that amount of data (performed by humans reviewing one document at a time) can require months and even years, a virtual army of human reviewers (all being paid at an hourly rate), as well as the training, resources, and technology necessary for those reviewers to perform the work proficiently. Because of this, AI technology (via technology assisted review (TAR)) has been widely accepted by courts and used by counsel to cull and prioritize large sets for almost a decade.However, while big datasets involving terabytes of data were once the outliers in the eDiscovery world, they are now quickly becoming the norm for organizations and litigations of all sizes due to exploding data volumes. To put the growing size of organizational data in context, the total volume of data being generated and consumed has increased from 33 zettabytes worldwide in 2018 to a predicted 175 zettabytes in 2025[3]. This means that soon, even the smallest litigation or investigation may involve terabytes of data to review. In turn, that means that AI technology will be critical for almost any litigation involving a discovery component.And that means that we as attorneys will have an ethical duty to keep abreast of AI technology to competently represent our clients in matters involving eDiscovery. As we have seen above, there is just no way to conduct massive document reviews without the help of AI technology. Moreover, the imperative task of protecting sensitive client data like attorney-client privilege, trade secret information, and PII (which all can be hidden and hard to find amongst massive amounts of data) also benefits from leveraging AI technology. If there is technology readily available that can lower attorney costs and client risk, while ensuring a more consistent and accurate work product, we have a duty to our clients to stay aware of that technology and understand how and when to leverage it.But this ethical obligation should not scare us as attorneys and it doesn’t mean that every attorney will need to become a data scientist in order to ethically practice law in the future. Rather, it just means that we, as attorneys, will just need to develop a baseline knowledge of AI technology when conducting eDiscovery so that we can effectively evaluate when and how to leverage it for our clients, as well as when and how to partner with appropriate eDiscovery providers that can provide the requisite training and assist with leveraging the best technology for each eDiscovery task.ConclusionAs attorneys, we have all adapted to new technology as our world and our clients have evolved. In the last decade or so, we have moved from Xerox and fax machines to e-filings and Zoom court hearings. The same ethic that drives us to evolve with our clients and competently represent them to the best of our ability will continue to drive us to stay abreast of the exciting changes happening around AI technology within the eDiscovery space.To discuss this topic more, feel free to connect with me at smoran@lighthouseglobal.com.‍[1] “Client-Lawyer Relationship: A lawyer shall provide competent representation to a client. Competent representation requires the legal knowledge, skill, thoroughness and preparation reasonably necessary for the representation.” ABA Model Rules of Professional Conduct, Rule 1.1.[2] See Comment 8, Model Rules of Professional Conduct Rule 1.1 (Competence)[3] Reinsel, David; Gantz, John; Rydning, John. “The Digitization of the World From Edge to Core.” November 2018. Retrieved from https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf. An IDC White Paper, Sponsored by SEAGATE.ai-and-analyticsanalytics, ai-big-data, ediscovery-process, red-flag-reporting, departing-onboarding-employee, prism, blog, focus-discovery, ai-and-analytics,analytics; ai-big-data; ediscovery-process; red-flag-reporting; departing-onboarding-employee; prism; blog; focus-discoverysarah moran
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Delivering Value: Sharing Legal Department Metrics that Move the Core Business
Below is a copy of a featured blog written by Debora Motyka Jones for CLOC's Legal Operations Blog.One of the most common complaints I hear from General Counsels and Chief Legal Officers is that they are not able to sit at a table full of their executive peers and provide metrics on how legal is impacting the core business. Sure, they are able to show their own department’s spending, tasks, and resource allocation. But wouldn’t it be nice to tell the business when revenue will hit? Or insights about what organizational behaviors are leading to inefficiency and, if changed, will impact spending. More specifically, as the legal operations team member responsible for metrics, wouldn’t it be great to share these key insights with your GC as well as your finance, sales, IT, and other department counterparts? Good news! Legal has this type of information, it is just a matter of identifying and mining it!Keeping metrics has become table stakes in today’s legal department and it often falls on the shoulders of legal operations to track and share those metrics. In fact, CLOC highlights business intelligence as a core competency for the legal operations function. Identifying metrics, cleansing those metrics, and putting them forth can be quite a lift, but once you have the right metrics in place, you are able to make data-driven decisions about how to staff your team, what external resources you need, and drive efficiencies. If you are still at the early stages of figuring out which metrics you should track for your department, there are many good resources out there including a checklist of potential metrics by Thompson Reuters, and a blog by CLOC on where to start. HBR also conducts a survey so you can see what other departments are seeing – this can be helpful for setting targets and/or seeing how you compare. When you analyze these and other resources, you will notice that many of the metrics are legal department centric. Though they are helpful for the department, they are not very meaningful when they are sitting around the table with executives doing strategic business planning for the business as a whole. So what types of metrics can legal provide in those settings and how do you capture them? There are many ways to go about this, but I have highlighted a few that can provide a robust discussion at the executive table.Leading Indicators of RevenueMost companies are reviewing the top line with some frequency and in many industries it is a challenge to predict the timing of that revenue. Given its position at the end of the sales cycle, in the contracting phase, legal has excellent access to information about revenue and the timing thereof. Here are the most common statistics your legal department can provide in that area:New Customer Acquisition: Number of Customer Contracts Signed this Month – Signing up paying customers is a direct tie to revenue and the legal department holds the keys to one of the last steps pre-revenue: contract signing. By identifying the type of contract that leads to revenue, the legal department is able to share with the business how many new customers are coming online. The metric is typically a raw number and can be compared against the number of contracts in a prior period. If not all customers who sign this contract lead to revenue, you will want to report (or at least know) the ratio of contracts to paying customers in order to give an accurate picture. Once you have been tracking this metric, you may want to take it a step further and identify and contracts that come earlier in the process. For example, in some companies, prospective clients sign NDAs earlier in the sales cycle. By reporting on the number of NDAs signed, you will start to see a ratio of the number of NDA to the number of MSAs and can give even earlier visibility into the customer acquisition pipeline.Expected New Customers: Contracts in Negotiation and Contract Negotiation Length – If your company has negotiated contracts then reporting on the number of contracts in negotiation can also help with revenue planning. Knowing the typical length of that negotiation will give an indication as to the timing of that revenue.Expected Revenue: Timing – The final piece of the revenue puzzle is when the above revenue will hit. You can work with the finance team to get the typical time between contract signing and revenue. This will often vary by contract size so layering in the contract size is helpful. If contract size if not available in the contract itself, that is likely information that sales keep so they can report that metrics if legal cannot.The two departments most interested in all three the above metrics are likely to be sales and finance but depending on the detail reported at the executive level, these may be executive-level metrics. If the above seems like a lot, know that many contract management tools and/or contract artificial intelligence tools can mine your contracts for the above information.Efficiency in Business OperationsLegal operations also has a unique ability to look back and reflect on the efficiency in some areas of business operations. More specifically, in the course of litigation and investigations, cross sections of the business are examined with hindsight and as we all know, hindsight is 20/20. Providing that look back information to the business can help in overall business efficiency. In addition, legal has access to payment clauses, in contracts, that can ensure efficiency in cash management. Here are some helpful statistics your legal department can provide on the state of legal operations.Early Payment Discount Usage: Number of Contracts with Early Payment and Percentage of Early Payment Discounts Used – When signing vendor contracts, there are often provisions allowing for discounts if certain terms – e.g. payment within a short timeframe, are met. Although this may be fresh on everyone’s mind at the time of negotiation, this often gets lost over time. Using current technologies, the legal operations team can identify these contracts and provide the number of contracts in which such provisions exist. You can then work with finance to determine how many of these provisions are being leveraged – e.g. is the business actually paying early and taking the percentage reduction. The savings for the business can be material by just providing visibility into this area.Data Storage: How Much Data to Keep – A common IT pain point is storage management and having to add servers in order to keep up with the business needs. With cloud technologies, IT often knows how much space they have allocated to each user’s mail or individual drives but what is unknown is how much data users are keeping on their machines or in collaborations tools and shared drives. With data collections for litigation or regulatory matters, the legal team has access to this information. This information can help IT understand its storage needs and put in place technologies to minimize storage per person thereby saving on storage costs.Business Intelligence from Active Matters – This one isn’t a specific metric. Instead, this is more focused on the business intelligence that comes out of the legal department’s unique position as a reviewer of sets of documents. In litigation or investigations, the legal department has access to a cross section of data that the business doesn’t pull together in the regular course of business. Technology is now advanced enough to be able to provide business insights from this data that can be shared with the business as a whole.Example #1: Artificial intelligence can be used to create compliance models that show correlations between expense reports, trade journals, and sales behavior to identify bad behaviors. Sharing these types of learnings from matters can open up discussions among executives as to which learnings deserve a deeper dive. As an aside, you could also imagine a scenario where this same logic can also be used inversely – when combined with revenue it could identify effective sales behaviors – although this is something that would be a bigger lift and I would expect the sales department to drive this type of work.Example #2: The amount of duplicative data is a common metric reported in litigations or investigations. Sharing this with your IT team can highlight an easy storage win and legal can help craft a plan of how to attack duplicative data thereby leading to lower storage costsI would be remiss if I didn’t mention that there are opportunities for the legal department in these metrics as well. By using these metrics, as well as the artificial intelligence mentioned above, legal operations can resource plan and drive savings within the legal department. For example, the number of NDAs and sales contracts can inform staffing. Technology can identify contracts or other documents that are repetitive and automate the handling of those documents. Within litigation and investigations, technology can identify objectively non-responsive data so that it does not need to be collected as well as identify sources that are lower risk which don’t require outside counsel review and previously collected data that can be re-used.I hope that with the above metrics, you’re able to participate in some great business discussions and show how your legal department is not only effective in its own right but how integral a unit it is to driving the core business.ai-and-analytics; legal-operationsreporting, legal-ops, blog, ai-and-analytics, legal-operationsreporting; legal-ops; bloglighthouse
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eDiscovery Analytics Use Cases You May Not Know About
Evolving analytics tools and methods can help expedite review.Analyze this! No, we’re not talking about the 1999 movie starring Robert DeNiro and Billy Crystal, but rather analytics mechanisms that many organizations are using today to streamline discovery. As these mechanisms become more sophisticated, it pays to keep abreast of the ways in which they can impact a review, including how data can be organized, visualized, identified and reduced.For example, conceptual clustering can identify groups of topics that might be clearly responsive or non-responsive. Communication visualization maps can identify communication patterns of key parties within a data collection And, of course, predictive coding can train a supervised machine learning algorithm to identify potentially responsive and non-responsive documents based on classifications of other documents.But there are other use cases for eDiscovery analytics many organizations aren’t taking advantage of that make eDiscovery workflows even more efficient and more cost effective. To improve the efficiency of eDiscovery workflows, organizations can now implement technology with the following analytics features.Email Threading and Near Duplicate IdentificationYou may have heard the famous phrase “Insanity is doing the same thing over and over again expecting a different result.” But, in document review, insanity is simply doing the same thing over and over again. De-duplication using hash values identifies documents that are exact duplicates in content and format, but there is considerable additional content within document collections that is also duplicated within documents that aren’t exact matches. Email conversation threads contain considerable duplicative information, but conversations between multiple people can branch off, so you can’t just assume that the last message for the thread contains the entire thread discussion.Documents converted to PDF may be identical in content but not format, so they have different hash values and are not “de-duped.” ESI collections often include multiple drafts of documents that have both duplicative and unique content. To avoid over-capture of duplicates and gain visibility into email branches, organizations can now employ advanced analytics that can help in the following ways:Utilize advanced algorithms to identify email thread relationships and individual emails in a thread with unique contentGroup similar documents with flexible near-duplicate identification to easily review and compare to determine whether the differences are significantIdentify exact content duplicates with only formatting differences that hash de-duplication would not catch.Name Normalization and Entity AnalysisWhat’s in a name? Potentially, a whole lot of options! If the sixth US president were alive today and sending emails, here are some ways that you might see him represented within the collection:John AdamsJohnny AdamsJohn Q. AdamsQ. AdamsQuincy AdamsAdams, JohnAdams, John Q.Adams, J.Q.Adams, J. Quincyjadams@xyzcorp.com/O=XYZCORP/OU=EXCHANGE ADMINISTRATIVE GROUP (FYDIBOHF23SPDLT)/CN=RECIPIENTS/CN=jadamsAdams@gmail.comAnd potentially more…That’s a lot of variation – just for one person! Case teams often waste significant time and energy sorting through the numerous variations of names and email addresses for individuals in a matter. Advanced analytics solutions can be used to automated name normalization algorithms to link different name variations and email addresses to a single individual, format those names uniformly and aggregate the normalized participants that appear across an entire email thread group. The result? Refined results that streamline processes such as privilege logging without the intensive manual cleanup typically associated with the process.Metadata AnalyticsAI-driven analytics applied to the metadata can streamline eDiscovery by:a) identifying mass email communications so that reviewers can focus on more likely responsive emails;b) filtering email signature images and other extraneous embedded objects; andc) remediating data populations with missing or incomplete metadata by auto-detecting and populating email metadata fields on inbound productions.Privilege AnalyticsAutomated categorization and classification powered by advanced analytics can also be applied to privilege review to weed out non-responsive and non-privileged material early and rapidly identify, elevate and prioritize potentially privileged information. Customizable rules to exclude disclaimers and boilerplate language can also improve the accuracy of that identification process by eliminating many false positives.As most privilege determinations involve considerations of nuance and context, human judgments are a necessary part of the process. Pre-built and customized linguistic models, name normalization and email thread identification can extend those automated privilege determinations more quickly through the collection, with automated identification of legal concepts, privilege actors and law firms and a reusable asset with consistent propagation of privilege designations across matters.And clean name normalization outputs, along with automated and customizable privilege reasons assigned to each document expedite privilege log creation, significantly decreasing the manual cleanup often associated with this time-consuming task.Personal Identifiable Information (PII) DetectionFinally, with all of the data privacy requirements associated with recent regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), identifying and protecting PII has become a requirement within every phase of the eDiscovery lifecycle. Using analytics and pattern matching through regular expressions (RegEx) to identify common format numbers such as passport IDs, social security numbers, drivers license numbers and credit card numbers, as well as identification of common form types that often contain PII (such as loan applications or IRS forms) will help flag those documents so that they can be adequately protected throughout the process.Newer, more advanced AI-driven analytics solutions go a step further by utilizing highly precise classifiers to model the way in which different forms of supported personal data appear in data populations. These automated solutions provide rapid identification of likely and potential PII, resulting in rapid insights and immediate access to the most relevant documents first.ConclusionYou may be using analytics to streamline parts of your eDiscovery process, but there are always new use cases being identified to leverage analytics to make your eDiscovery workflows more efficient. Even Analyze This had a sequel!For more information on ways H5 Matter Analytics® can assist your organization in creating efficiencies and expediting eDiscovery workflows, click here.ediscovery-reviewblog, -ediscovery, data-analytics, document-review, ediscovery-review, aiandanalyticsblog; ediscovery; data-analytics; document-reviewlighthouse
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Deploying Modern Analytics for Today’s Critical Data Challenges in eDiscovery
Artificial intelligence (AI) has proliferated across industries, in popular culture, and in the legal space. But what does AI really mean? One way to look at it is in reference to technology that lets lawyers and organizations efficiently manage massive quantities of data that no one’s been able to analyze and understand before.While AI tools are no longer brand new, they’re still evolving, and so is the industry’s comfort and trust in them. To look deeper into the technology available and how lawyers can use it Lighthouse hosted a panel featuring experts Mark Noel, Director of Advanced Client Data Solutions at Hogan Lovells, Sam Sessler, Assistant Director of Global eDiscovery Services at Norton Rose Fulbright, Bradley Johnston, Senior Counsel eDiscovery at Cardinal Health, and Paige Hunt, Lighthouse’s VP of Global Discovery Solutions.Some of the key themes and ideas that emerged from the discussion include:Defining AIMeeting client expectationsUnderstanding attorneys’ duty of competenceIdentifying critical factors in choosing an AI toolAssessing AI’s impact on process and strategyThe future of AI in the legal industryDefining AIThe term “AI” can be misleading. It’s important to recognize that, right now, it’s an umbrella term encompassing many different techniques. The most common form of AI in the legal space is machine learning, and the earliest tools were document review technologies in the eDiscovery space. Other forms of AI include deep learning, continuous active learning (CAL), neural networks, and natural language processing (NLP).While eDiscovery was a proving ground for these solutions, the legal industry now sees more prebuilt and portable algorithms used in a wide range of use cases, including data privacy, cyber security, and internal investigations.Clients’ Expectations and Lawyers’ DutiesThe broad adoption of AI technologies has been slow, which comes as no surprise to the legal industry. Lawyers tend to be wary of change, particularly when it comes at the hands of techniques that can be difficult to understand. But our panel of experts agreed that barriers to entry were less of an issue at this point, and now many lawyers and clients expect to use AI.Lawyers and clients have widely adopted AI techniques in eDiscovery and other privacy and security matters. However, the emphasis from clients is less about the technology and more about efficiency. They want their law firms and vendors to provide as much value as possible for their budgets.Another client expectation is reducing risk to the greatest extent possible. For example, many AI technologies offer the consistency and accuracy needed to reduce the risk of inadvertent disclosures.Mingled with client expectations is a lawyer’s duty to be familiar with technology from a competency standpoint. We aren’t to the point in the legal industry where lawyers violate their duty of competence if they don’t use AI tools. However, the technology may mature to the point where it becomes an ethical issue for lawyers not to use AI.Choosing the Right AI ToolDecide Based on the Search TaskThere’s always the question of which AI technology to deploy and when. While less experienced lawyers might assume the right tool depends on the practice area, the panelists all focused on the search task. Many of the same search tasks occur across practice areas and enterprises.Lawyers should choose an AI technology that will give them the information they need. For example, Technology-assisted review (TAR) is well-suited to classifying documents, whereas clustering is helpful for exploration.Focus More on FeaturesTeams should consider the various options’ features and insights when purchasing AI for eDiscovery. They also must consider the training protocol, process, and workflow. At the end of the day, the results must be repeatable and defensible. Several solutions may be suitable as long as the team can apply a scientific approach to the process and perform early data assessment. Additional factors include connectivity with the organization’s other technology and cost.The process and results matter most. Lawyers are better off looking at the system as a whole and its features in deciding which AI tech to deploy instead of focusing on the algorithm itself.Although not strictly necessary, it can be helpful to choose a solution the team can apply to multiple problems and tasks. Some tools are more flexible than others, so reuse is something to consider.Some Use Cases Allow for ExperimentationThere’s also the choice between a well-established solution versus a lesser-known technology. Again, defensibility may push a team toward a well-known and respected tool. However, teams can take calculated risks with newer technologies when dealing with exploratory and internal tasks.A Custom Solution Isn’t NecessaryThe participants noted the rise in premade, portable AI solutions more than once. Rarely will it benefit a team to create a custom AI solution from scratch. There’s no need to reinvent the wheel. Instead, lawyers should always try an off-the-shelve system first, even if it requires fine-tuning or adjustments.AI’s Impact on ProcessThe process and workflow are critical no matter which solution a team chooses. Whether for eDiscovery, an internal investigation, or a cyber security incident, lawyers need accurate and defensible results.Some AI tools allow teams to track and document the process better than others. However, whatever the tool’s features, the lawyers must prioritize documentation. It’s up to them to thoughtfully train the chosen system, create a defensible workflow, and log their progress.As the adage goes: garbage in, garbage out. The effort and information the team inputs into the AI tool will influence the validity of the results. The tool itself may slightly influence the team’s approach. However, any approach should flow from a scientific process and evidence-based decisions.AI’s Influence on StrategyThere’s a lot of potential for AI to help organizations more strategically manage their documents, data, and approach to cases. Consider privileged communications and redactions. AI tools enable organizations to review and classify documents as their employees create them—long before litigation or another matter. Classification coding can travel with the document, from one legal matter to another and even across vendors, saving organizations time and money.Consistency is relevant, too. Organizations can use AI tools to improve the accuracy and uniformity of identifying, classifying, and redacting information. A well-trained AI tool can offer better results than people who may be inconsistently trained, biased, or distracted.Another factor is reusing AI technology for multiple search tasks. Depending on the tool, an organization can use it repeatedly. Or it can use the results from one project to the next. That may look like knowing which documents are privileged ahead of time or an ongoing redaction log. It can also look like using a set of documents to better train the algorithm for the next task.The Future of AIThe panelists wrapped the webinar by discussing what they expect for the future of AI in the legal space. They agreed that being able to reuse work products and the concept of data lakes will become even greater focuses. Reuse can significantly impact tasks that have traditionally had a huge cost burden, such as privilege reviews and logs, sensitive data identification, and data breach and cyber incidents.Another likelihood is AI technology expanding to more use cases. While lawyers tend to use these tools for similar search tasks, the technology itself has potential for many other legal matters, both adversarial and transactional. To hear more of what the experts had to say, watch the webinar, “Deploying Modern Analytics for Today’s Critical Data Challenges.” ai-and-analytics; ediscovery-review; lighting-the-path-to-better-ediscoveryai-big-data, blog, data-reuse, project-management, ai-and-analytics, ediscovery-reviewai-big-data; blog; data-reuse; project-managementai-analyticslighthouse
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Document Review: It’s Not Location, Location, Location. It’s Process, Process, Process.
Much of the workforce has been forced into remote work due to social distancing requirements because of the pandemic, and that includes the workforce conducting services related to electronic discovery. Many providers have been forced into remote work for services including collection and review. Other providers have been already conducting those services remotely for years, so they were well prepared to continue to provide those services remotely during the pandemic.Make no mistake, it’s important to select a review provider that has considerable experience conducting remote reviews which extends well before the pandemic. Not all providers have that level of experience. But the success of your reviews isn’t about location, location, location; it’s about process, process, process — and the ability to manage the review effectively regardless of where it’s conducted. Here are four best practices to make your document reviews more efficient and cost effective, regardless of where they’re conducted:Maximize culling and filtering techniques up front: Successful reviews begin with identifying the documents that shouldn’t be reviewed in the first place and removing them from the document collection before starting review. Techniques for culling the document collection include de-duplication and de-nisting and identification of irrelevant domains. But it’s also important to craft a search that maximizes the balance between recall and precision to exclude thousands of additional documents that might otherwise be needlessly reviewed, saving time and money during document review.Combine subject matter and best practice expertise: Counsel understands the issues associated with the case, but they often don’t understand how to implement sophisticated discovery workflows that incorporate the latest technological approaches (such as linguistic search) to maximize efficiency. It’s important to select the provider that knows the right questions to ask to combine subject matter expertise with eDiscovery best practices to ensure an efficient and cost-effective review process. It’s also important to continue to communicate and adjust workflows during the case as you learn more about the document collection and how it relates to the issues of the case.Conduct search and review iteratively: Many people think of eDiscovery document review as a linear process, but the most effective reviews today are those that implement an iterative process that that interweave search and review to continue to refine the review corpus. The use of AI algorithms and expert-designed linguistic models to test, measure and refine searches is important to achieve a high accuracy rate during review, so remember the mantra of “test, measure, refine, repeat” for search and review to maximize the quality of your search and review process.Consider producing iteratively, as well: Discovery is a deadline driven process, but that doesn’t mean you have to wait for the deadline to provide your entire production to opposing counsel. Rolling productions are common today to enable producing parties to meet their discovery obligations over time, establishing goodwill with opposing counsel and demonstrating to the court that you have been meeting your obligations in good faith along the way if disputes occur. Include discussion of rolling productions in your Rule 26(f) meet and confer with opposing counsel to enable you to manage the production more effectively over the life of the project.You’re probably familiar with the famous quote from The Art of War by Sun Tzu that “every battle is won or lost before it is ever fought,” which emphasizes the importance of preparation before proceeding with the task or process you plan to perform. Regardless where your review is being conducted, it’s not the location, location, location that will determine the success of your review, but the process, process, process. After all, it’s called “managed review” for a reason!ediscovery-reviewblog, -document-review, ediscovery-review,blog; document-reviewlighthouse
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Data Reuse – Small Changes for Big Benefits
What is data reuse? There are many different flavors and not everyone thinks about it the same way. In the context of eDiscovery, subject-matter specific work product in the form of responsiveness or issue coding often comes to mind and is then immediately dismissed as untenable given that the definitions for these can change from matter to matter. This is just one tiny piece of what’s possible, however. We need to consider the entire EDRM from end to end. What else has already been done, and what can be gained from it?First, there’s the source data itself. The underlying electronically stored information (ESI) is foundational to the reuse of data as a whole. Many corporations deal with frequent litigation and investigations, and those matters often include the same or at least overlapping players, i.e. the “frequent flier” custodians. This means the same data is relevant to multiple matters, which means it can be reused. There’s the potential for a one-to-many relationship here. In other words, instead of starting from scratch with each new project by going back to the same sources to collect the same data, why not take stock of what has been collected already? Compare the previously collected inventory to what is required for each specific matter, and then return to the well for the difference as needed. It may be as simple as a “refresh” to capture a more recent date range, or, even better, there’s no new collection to be done at all.Next up is the processed data. Once it’s collected, a lot of time, effort, and money are spent transforming ESI into a more consumable format. Extracting and indexing the metadata such that it can easily be searched and reviewed in your platform of choice takes real effort. Considering the lift, utilizing data that has already undergone processing makes a lot of sense. Depending on volume, significant savings in terms of timeline and fees are often realized, and this is not a one-time thing. The same data often comes up over and over across multiple matters, compounding savings over time.Finally, after processing comes review, which is where reusing existing work product comes in. This isn’t limited to relevance calls, which may or may not consistently apply across matters. There’s limited application for the reuse of subject-matter specific work product as mentioned earlier. The real treasure trove is all the different types of static work product – the ones that remain the same across matters regardless of the relevance criteria – and there are so many! One valuable step that is often overlooked is the ability to dismiss portions of the data population upfront. Often there is some chunk of data that will simply never be of interest. These are the “junk” or “objectively non-relevant” files that can clog a review. For example, automatic notifications, spam advertisements, and other mass mailings can contribute a lot of volume and rarely have any chance of including relevant content. Also, think about redactions and what often drives them: PII, PHI, trade secret, IP, etc. These are a pain to deal with, so why force the need to do so repeatedly? And, what about privilege? Identifying it is one thing, and then there are the incredibly time intensive privilege log entries that follow. These don’t change, and the cost to handle them can be steep. On top of that, they are incredibly sensitive, so ensuring accuracy and consistency is key. That’s pretty difficult to accomplish from matter to matter if you rely on different reviewers starting over each time.At the end of the day, no one wants to waste time and effort on unnecessary tasks, especially considering how often intense deadlines loom right out of the gate. The key is understanding what has already been done that overlaps with the matter at hand and leveraging it accordingly. In other words, know what you have and use it to avoid performing the same task twice wherever possible.ai-and-analytics; ediscovery-reviewediscovery-process, data-re-use, blog, ai-and-analytics, ediscovery-reviewediscovery-process; data-re-use; bloglighthouse
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Cybersecurity Defense: Recommendations for Companies Impacted by the Biden Administration Executive Order
As summarized in the first installment of our two-part blog series, President Biden recently issued a sweeping Executive Order aimed at improving the nation’s cybersecurity defense. The Order is a reaction to increased cybersecurity attacks that have severely impacted both the public and private sectors. These recent attacks have evolved to a point that industry solutions have a much more difficult time detecting encryption and file state changes in a reasonable timeframe to prevent an actual compromise. The consequence is that new and evolving ransomware and malware attacks are now getting past even the biggest solution providers and leading scanners in the industry.Thus, while on its face, many of the new requirements within the Order are aimed at federal agencies and government subcontractors, the ultimate goal appears to be to create a more unified national cybersecurity defense across all sectors. In this installment of our blog series, I will outline recommended steps for private sector organizations to prepare for compliance with the Order, as well as general best-practice tips for adopting a more preemptive approach to cybersecurity. 1. Conduct a Third-Party AssessmentFirst and foremost, organizations must understand their current cybersecurity posture. Given the severity and volume of recent cyberattacks, third-party in-depth or red-team assessments should be done that would include not only the organization’s IT assets, but also include solutions providers, vendors, and suppliers. Red teaming is the process of providing a fact-driven adversary perspective as an input to solving or addressing a problem. In the cybersecurity space, it has become a best practice wherein the cyber resilience of an organization is challenged by an adversary or a threat actor’s perspective.[1] Red-team testing is very useful to test organizational policies, procedures, and reactions against defined, intended standards.A third-party assessment must include a comprehensive remote network scan and a comprehensive internal scan with internal access provided or gained with the intent to detect and expose potential vulnerabilities, exploits, and attack vectors for red-team testing. Internal comprehensive discovery includes scanning and running tools with the intent to detect deeper levels of vulnerabilities and areas of compromise. Physical intrusion tests during red-team testing should be conducted on the facility, networks, and systems to test readiness, defined policies, and procedures.The assessment will evaluate the ability to preserve the confidentiality, integrity, and availability of the information maintained and used by the organization and will test the use of security controls and procedures used to secure sensitive data.2. Integrate Solution Providers and IT Service Companies into Plans to Address Above Executive Order StepsTo accurately assess your organization’s risk, you first have to know who your vendors, partners, and suppliers are with whom you share critical data. Many organizations rely on a complex and interconnected supply chain to provide solutions or share data. As noted above, this is exactly why the Order will eventually broadly impact the private sector. While on its face, the Order only seems to impact federal government and subcontractor entities, those entities’ data infrastructures (like most today) are interconnected environments composed of many different organizations with complex layers of outsourcing partners, diverse distribution routes, and various technologies to provide products and services – all of whom will have to live up to the Order’s cybersecurity standards. In short, the federal government is recognizing that its vendors, partners, and suppliers’ cybersecurity vulnerabilities are also its own. The sooner all organizations realize this the better. According to recent NIST guidance, “Managing cyber supply chain risk requires ensuring the integrity, security, quality, and resilience of the supply chain and its products and services.” NIST recommends focusing on foundational practices, enterprise-wide practices, risk management processes, and critical systems. “Cost-effective supply chain risk mitigation requires organizations to identify systems and components that are most vulnerable and will cause the largest organizational impact if compromised.[2]In the recent attacks, hackers inserted malicious code into Orion software, and around 18,000 SolarWinds customers, including government and corporate entities, installed the tainted update onto their systems. The compromised update has had a sweeping impact, the scale of which keeps growing as new information emerges. Locking down your networks, systems, and data is just the beginning! Inquiring how your supply chain implements a Zero Trust strategy and secures their environment as well as your shared data is vitally important. A cyber-weak or compromised company can lead to exfiltration of data, which a bad actor can exploit or use to compromise your organization.3. Develop Plan to Address Most Critical Vulnerabilities and Threats Right AwayThird-party assessors should deliver a comprehensive report of their findings that includes the descriptions of the vulnerabilities, risks found in the environment, and recommendations to properly secure the data center assets, which will help companies stay ahead of the Order’s mandates. The reports typically include specific data obtained from the network, any information regarding exploitation of exposures, and the attempts to gain access to sensitive data.A superior assessment report will contain documented and detailed findings as a result of performing the service and will convey the assessor’s opinion of how best to remedy vulnerabilities. These will be prioritized for immediate action, depending upon the level of risk. Risks are often prioritized as critical, high, medium, and low risk to the environment, and a plan can be developed based upon these prioritizations for remediation.4. Develop A Zero Trust StrategyAs outlined in Section 3 of the Order, a Zero Trust strategy is critical to addressing the above steps, and must include establishing policy, training the organization, and assigning accountability for updating the policy. Defined by the National Security Agency (NSA)’s “Guidance on the Zero Trust Security Model”: “The Zero Trust model eliminates trust in any one element, node, or service by assuming that a breach is inevitable or has already occurred. The data-centric security model constantly limits access while also looking for anomalous or malicious activity.”[3]Properly implemented Zero Trust is not a set of access controls to be “checked,” but rather an assessment and implementation of security solutions that provide proper network and hardware segmentation as well as platform micro-segmentation and are implemented at all layers of the OSI (Open Systems Interconnection) model. A good position to take is that Zero Trust should be implemented using a design where all of the solutions assume they exist in a hostile environment. The solutions operate as if other layers in a company’s protections have been compromised. This allows isolation of the different layers to improve protection by combining the Zero Trust principles throughout the environment from perimeters to VPNs, remote access to Web Servers, and applications. For a true Zero Trust enabled environment, focus on cybersecurity solution providers that qualify as “Advanced” in the NSA’s Zero Trust Maturity Model; as defined in NSA’s Cybersecurity Paper, “Embracing a Zero Trust Security Model.”[4] This means that these solution providers will be able to deploy advanced protections and controls with robust analytics and orchestration.5. Evaluate Solutions that Pre-emptively Protect Through Defense-In-DepthIn order to further modernize your organization’s cybersecurity protection, consider full integration and/or replacement of some existing cybersecurity systems with ones that understand the complete end-to-end threats across the network. How can an organization implement confidentiality and integrity for breach prevention? Leverage automated, preemptive cybersecurity solutions, as they possess the greatest potential in thwarting attacks and rapidly identifying any security breaches to reduce time and cost. Use a Defense-in-Depth blueprint for cybersecurity to establish outer and inner perimeters, enable a Zero Trust environment, establish proper security boundaries, provide confidentiality for proper access into the data center, and support capabilities that prevent data exfiltration inside sensitive networks. Implement a solution to continuously scan and detect ransomware, malware, and unauthorized encryption that does NOT rely on API calls, file extensions, or signatures for data integrity.Solutions must have built-in protections leveraging multiple automated defense techniques, deep zero-day intelligence, revolutionary honeypot sensors, and revolutionary state technologies working together to preemptively protect the environment. ConclusionAs noted above, Cyemptive recommends the above steps in order to take a preemptive, holistic approach to cybersecurity defense. Cyemptive recommends initiating the above process as soon as possible – not only to comply with potential government mandates brought about due to President Biden’s Executive Order, but also to ensure that organizations are better prepared for the increased cybersecurity threat activity we are seeing throughout the private sector. ‍[1]“Red Teaming for Cybersecurity”. ISACA Journal. October 18, 2018. https://www.isaca.org/resources/isaca-journal/issues/2018/volume-5/red-teaming-for-cybersecurity#1 [2] “NIST Cybersecurity & Privacy Program” May 2021. Cyber Supply Chain Risk Management C-SCRM” https://csrc.nist.gov/CSRC/media/Projects/cyber-supply-chain-risk-management/documents/C-SCRM_Fact_Sheet_Draft_May_10.pdf [3] “NSA Issues Guidance on Zero Trust Security Model”. NSA. February 25, 2021. https://www.nsa.gov/Press-Room/News-Highlights/Article/Article/2515176/nsa-issues-guidance-on-zero-trust-security-model/[4] “Embracing a Zero Trust Security Model.” NSA Cybersecurity Information. February 2021. https://media.defense.gov/2021/Feb/25/2002588479/-1/-1/0/CSI_EMBRACING_ZT_SECURITY_MODEL_UOO115131-21.PDFdata-privacy; information-governancecloud, cybersecurity, blog, corporate, data-privacy, information-governancecloud; cybersecurity; blog; corporatelighthouse
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Cybersecurity in eDiscovery: Protecting Your Data from Preservation through Production
Now more than ever, data security has become priority number one, especially in the context of litigation and eDiscovery. And as the worlds of eDiscovery, information governance, and cybersecurity continue to rapidly converge, cybersecurity incidents are alarmingly on the rise, showcasing all of the weaknesses in an organization’s information governance system. Addressing cybersecurity continues to be a top challenge in eDiscovery. Many are unsure if their own internal processes are safe, not to mention those of the vendors who manage their outsourced eDiscovery.So, how can you protect your ESI all the way from preservation and collection to review and production? In a Law and Candor podcast episode, special guest David Kessler, Head of Data and Information Risk at Norton Rose Fulbright US LLP, discussed with our hosts the diverse set of challenges that arise with data security at each stage of the EDRM. Most understand the right methods start with implementing the fundamentals of cybersecurity, but some have learned the hard way that you can’t fix a house built on a shaky foundation after a cybersecurity disaster strikes. With the protection of client ESI first and foremost top of mind, here are the some of the most pressing cybersecurity challenges in eDiscovery as well as actionable solutions.Cybersecurity Challenges in eDiscoveryThe intersection of information governance, eDiscovery, and data security: The nature of data has evolved such that eDiscovery and information governance naturally intersect with data privacy and security. We’ve learned that issues around data access are very similar to eDiscovery issues and the next challenge is learning how to operate the areas together cohesively. In addition, with the shift to scrutiny on privacy and what can be done with personal data, now we know almost all cases that involve ESI have tremendous privacy concerns.The important role eDiscovery plays in cybersecurity: No longer are the days where confidential data relevant to litigation is primarily found in email and simply on computers. Now, data is created and stored across a wide variety of mediums and the amount of data continues to grow at an exponential rate. For cybersecurity criminals, this is a gold mine of confidential data available to steal and access.The outstanding security gaps throughout the EDRM: Historically, we’ve been focused on the responding parties’ obligations to securely undertake discovery. The business process of eDiscovery is primarily about collecting, copying, and transferring data outside of an organization, which creates concerns about securing that information at every stage of the process. Both the responding and requesting parties need to find a way to collaboratively and cooperatively work together at the beginning of a case to ensure data is protected through the entire EDRM lifecycle.The weakest part of the cybersecurity chain is when you hand over sensitive data: How do we help clients make sure their data isn’t accidentally or intentionally taken from them during the eDiscovery process? Everyone from eDiscovery vendors to law firms has an obligation to shore up their security and organizations have a responsibility to thoroughly vet those partners as they hand over their most sensitive data. In the EDRM, attention has shifted to making sure cybersecurity protections span the entire EDRM and the last step that hasn’t received much attention is making sure the requesting party is taking the appropriate steps to secure the data once they receive it.Cybersecurity Solutions in eDiscoveryShore up cybersecurity contracts and repurpose existing security riders: When an organization engages law firms and eDiscovery vendors to handle discovery, it’s important they work closely with their data security IT team. These teams can help to repurpose some of the standard security riders from other contracts and use it to create new contracts with the appropriate protections in place.Establish comprehensive protective orders at the beginning of cases: With respect to the requesting party, who you will ultimately be producing the data to, ensure that early in the case you’ve negotiated a comprehensive protective order that includes reasonable and proportionate requirements for the protection of data. In that protection order (and a step that’s often forgotten), follow up and confirm the data you produced has been deleted after a case is over.Keep open lines of communication with law firms and eDiscovery vendors: Your discovery partners understand and have a significant stake in their security reputations. They have a strong motivation to work with you to execute risk assessments and other agreements that contain the necessary security provisions to ensure your data is safe at every step of the process. Also, include a breach notification order if data is accidentally lost or there’s an attack.Focus on things you can do to strengthen your productions: Think about the most efficient ways to reduce the number of copies involved in productions where appropriate. For example, use redaction as much as possible and consequently less copies of data. Don’t produce sensitive and irrelevant portions of data – redact it instead.Ultimately, most people have become acutely aware of the vulnerabilities that exist in data security as it travels through the EDRM, and as law firms and eDiscovery vendors become accustomed to deeper vetting, it’s at the production stage where the biggest security vulnerabilities seem to remain. To get ahead of all aspects of potential cybersecurity failures, the use of well-written protective orders will get you a long way. Requirements in protective orders can ensure all parties take reasonable steps to protect data from third-party hackers and unauthorized access, as well as include protections based on encryption, access controls, passwords, etc.data-privacy; information-governance; ediscovery-reviewcybersecurity, cloud-security, ediscovery-process, preservation-and-collection, blog, data-privacy, information-governance, ediscovery-review,cybersecurity; cloud-security; ediscovery-process; preservation-and-collection; bloglighthouse
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Cloud Security and Costs: How to Mitigate Risks Within the Cloud
When it comes to storing organizational data in the Cloud, a few phrases come to mind: the train has left the station; the ship has sailed; the horse is out of the barn, etc. No matter how you phrase it, the meaning is the same – the world is moving to the Cloud, with or without you. It is no longer an oncoming revolution. The revolution is here and your organization needs to prepare for dealing with data in the Cloud, if it hasn’t already. With that in mind, let’s talk cloud logistics – namely, security and cost.First up to the Plate – Cloud Security You might have heard the analogy circulating in technology forums recently that storing your data within the Cloud is akin to storing data on someone else’s hard drive. Unfortunately, from a security perspective, that’s not quite an accurate analogy (although life would be much easier if it were true).Don’t get me wrong - a significant benefit of moving to the Cloud is that it allows an organization to transfer much of the day-to-day security management to a technology company with the resources and expertise to handle that risk. Thus, if you are moving to a private cloud (i.e., renting data center space for your equipment), you can ease security concerns by ensuring that the hosting company maintains widely recognized security attestations/certifications and has a demonstrated commitment to data center security in accordance with strict vendor management risk processes. And of course, there’s always the reassurance when moving to a public cloud (Microsoft’s Azure or Amazon’s AWS) that you’re entrusting your data to companies with seemingly infinite security resources and expertise. That all certainly helps me sleep better at night.However, working within the Cloud still poses unique internal security challenges that will only amplify any of your existing security weaknesses if you’re not prepared for them. To put it another way: ISO certifications from cloud service providers cannot protect you from yourself. Risk, governance, and compliance teams will need to identify, plan for and adapt to internal security challenges. To do so, be sure to have a change management and review approval process in place (ideally before moving to the Cloud, but if not, as soon as possible once you’ve migrated). Also, ensure that your company has someone on hand (either through a vendor or within your IT staff) with the expertise needed to manage your internal cloud security who can stay abreast of all updates and changes.Next up – CostTo plan for a cloud migration, all stakeholders (including Legal Operations, Finance, DevOps, Security, and IT) should have a seat at the table and a plan in place for scaling up in the Cloud. Each team should understand the plan and process, as well as the role their team plays in controlling cost and risk for the company.Cloud Security and Costs Best PracticesTo plan for security risk in the Cloud, companies should ensure that:All cloud service providers are fully vetted, security certified, and have the requisite posture in place to fully protect your data.Company internal processes are evaluated for security risks and gaps. Have a change management and review approval process in place and ensure that you have the experts on hand to manage your cloud security practices and stay abreast of all updates and changes.To plan for costs, companies should ensure that:All stakeholders (including Legal Operations, Finance, DevOps, Security, and IT) collaborate and have a plan in place for scaling up within the Cloud when needed.Each team understands the plan and process, as well as the role their team plays in controlling cost and risk for the company.data-privacy; information-governancecloud-security, cloud-migration, blog, data-privacy, information-governancecloud-security; cloud-migration; blogmarcelino hoyla
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Cybersecurity Defense: Biden Administration Executive Order a Great Start Towards a More Robust National Framework
On May 12, President Biden issued a landmark Executive Order (“the Order”) aimed at improving the country’s cybersecurity threat defense. This Order is an attempt to create a “whole of government” response to increasingly frequent cybersecurity incidents that have wreaked havoc in the United States in recent months, affecting everything from energy supplies to healthcare systems to IT infrastructure systems. In addition to becoming more frequent, recent cyberattacks have also become increasingly more sophisticated – and even somewhat professional. In response to these attacks, the Biden administration seeks to build a national security framework that aligns the Federal government with private sector businesses in order to “modernize our cyber defenses and enhance the nation’s ability to quickly and effectively respond to significant cybersecurity incidents.” Prior to this Order, there has been no unified system to report or respond to cybersecurity threats and breach incidents. Instead, there is currently a patchwork of state legislation and separate federal government agency protocols, all with differing reporting, notification, and response requirements.In the first of this two-part blog series, I will broadly outline the details of this Order and what it will mean for private sector companies in the coming years. In the second installment, Rob Pike (CEO and Founder of Cyemptive Technologies) will provide guidance on how to set up your organization for compliance with the Order, as well as general best-practice tips for adopting a preemptive cybersecurity approach. What is in President Biden’s Executive Order on Improving the Nation’s CybersecurityThere are nine main sections to the Order, which are summarized below.Section 1: PolicyThis section outlines the overall goal of the Order – namely that, with this Order, the Federal government is intent on making “bold changes and significant investments in order to defend the vital institutions that underpin the American way of life.” To do so, the Order states that the government must improve its efforts to “identify, deter, protect against, detect, and respond to” cybersecurity attacks. While this may sound like a purely governmental task, the Order specifically states that this defense will require partnership with the private sector. Section 2: Removing Barriers to Sharing Threat Information As noted above, prior to this Order, there was no unified system for sharing information regarding threats and data breaches. In fact, separate agency procurement contract terms may actually prevent private companies from sharing that type of information with federal agencies, including the FBI. This section of the Order responds to those challenges by requiring the government to update federal contract language with IT service providers (including cloud service providers) to require the collection and sharing of threat information with the appropriate government agencies. While the Order currently only speaks to federal subcontractors, it is expected that this information-sharing requirement will have a trickle-down effect across the private sector, with purely private companies falling in line to share threat information once federal subcontractors are required to do so. Section 3: Modernizing Federal Government CybersecurityThis section calls for the federal government to adopt security best practices – and is specifically aimed at adopting Zero Trust Architecture and pushing a move to secure cloud services, including “Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).” It requires that each government agency update plans to prioritize the adoption and use of cloud technology and develop a plan to implement Zero Trust Architecture, in part by incorporating the migrations steps outlined by the National Institute of Standards and Technology (NIST).Section 4: Enhancing Software Supply Chain SecurityThis section deals with increasing the cybersecurity standards of software sold to the government. It specifically calls out the fact that the development of commercial software “often lacks transparency, sufficient focus on the ability of the software to resist attack, and adequate controls to prevent tampering by malicious actors.” It, therefore, calls for “more rigorous and predictable mechanisms for ensuring that products function securely.” Thus, this section calls for NIST to issue new security guidelines for software used by the government. These new guidelines will include encryption requirements, multi-factor and risk-based authentication requirements, vulnerability detection and disclosure programs, and trust relationship audits, among others.Section 5: Establishing a Cyber Safety Review BoardThis section establishes a federal Cyber Safety Review Board, which will convene following significant cyber incidents, providing recommendations to the Secretary of Homeland Security for improving cybersecurity and incident response practices. It will be made up of federal officials, as well as representatives from private sector entities.Section 6: Standardizing the Federal Government’s Playbook for Responding to Cybersecurity Vulnerabilities and IncidentsThis section again speaks to the patchwork of differing vulnerability and incident response procedures that currently exists across multiple federal agencies. The goal here is to create a standard set of operational procedures (or a playbook) for cybersecurity vulnerability and incident response activity. The playbook will have to incorporate all appropriate NIST standards, be used by all Federal Civilian Executive Branch (FCEB) Agencies, and spell out all phases of incident response.Sections 7 and 8: Improving Detection, Investigation, and Remediations of Cybersecurity Vulnerabilities and Incidents on Federal Government NetworksThese two sections focus on creating a unified approach to the detection, investigation, and remediation of cybersecurity vulnerabilities and incidents. Section 7 focuses on improving detection – mandating that all FCEB agencies deploy an “Endpoint Detection and Response (EDR)” initiative to support proactive detection of cybersecurity incidents and establishes a procedure for the implementation of threat hunting and detection, as well as inter-agency information sharing around threat detection. Section 8 is focused on improving the government’s investigative and remediation capabilities – namely, by establishing requirements for agencies and their IT service providers to collect, maintain, and share specified information from Federal Information System network logs.Section 9: National Security SystemsThis section requires the Secretary of Defense to adopt National Security System requirements that are at least equivalent to the requirements spelled out by the above sections in the Order.Who Will This Impact?As noted above, while the Executive Order is aimed at shoring up the federal government’s cybersecurity detection and response systems – its impacts will be felt throughout much of the private sector. That isn’t a bad thing! A patchwork cybersecurity system is clearly not the best way to respond to the increasingly sophisticated cybersecurity incidents currently threatening both the United States government and the private sector. Responding to these threats requires a robust, unified national cybersecurity system, which in turn requires updated and unified cybersecurity standards across both government agencies and private sector companies. This Executive Order is a great stepping stone towards that goal.As far as timing for private sector impacts: the first impacts will be felt by software companies and other organizations that directly contract with the federal government, as there are direct requirements and implications for those entities spelled out within the Order. Many of those requirements come into play within 60 days to a year after the date of the Order, so there may be a quick turnaround to comply with any new standards for those organizations. Impacts are then expected to trickle down to other private sector organizations: as government subcontractors update policies and systems to comply with the Order, they will in turn require the companies that they do business with to comply with the new cybersecurity standards. In this way, the Order actually creates an opportunity for the federal government to create a cybersecurity floor above which most companies in the US will eventually have to comply.ConclusionDetecting and defending against cybersecurity threats is an increasingly difficult worldwide challenge – a challenge to which, currently, no perfect defense exists. However, with this Order, the United States is taking a step in the right direction by creating a more unified cybersecurity standard and network that will encourage better detection, investigation, and mitigation.Check out the second installment of this blog series, where Rob Pike, CEO and Founder of Cyemptive Technologies, provides guidance on how to set up your organization for compliance with the Executive Order, as well as general best-practice tips for adopting a preemptive cybersecurity approach. If you would like to discuss this topic further, please reach out to me at erubenstein@lighthouseglobal.com.data-privacy; information-governancecloud, cybersecurity, blog, corporate, data-privacy, information-governancecloud; cybersecurity; blog; corporateerin rubenstein
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Cloud Adaptation: How Legal Teams Can Implement Better Information Governance Structures for Evolving Software
There is much out there about cloud solutions and how they improve the lives of users, offer flexibility for expansion and contraction of business, and can lighten the lift for IT. There is even a lot of specific commentary about how cloud can help legal teams and enable change management for the department. But what about the day-to-day tasks? How does the cloud change the legal team’s work and what new governance and skills are necessary to handle that change? This blog will tackle these questions so you can be more prepared and agile as cloud technology advances.Why does a shift to the cloud matter for legal teams?From a practical perspective, it means having to be reactive in areas where legal has traditionally been more proactive. Things like data storage timelines and locations, internal access permissions, and document history are now ever-changing with software updates being automatically pushed to corporate software environments. Many organizations that manage on-premises software have historically had an effective software governance structure in place. They can meet, discuss upcoming upgrades and their impacts, and make decisions about when to execute a software upgrade. Now, in an agile cloud approach, upgrades come frequently, without much notice, and sometimes have highly impactful changes. Traditional governance structures are no longer sustainable given the new timing and volume of updates – sometimes hundreds in a week. Legal and IT teams now need to collaborate more often to quickly analyze any impacts updates will have on the organization and what, if anything, needs to be done to mitigate cloud security risks.Given this, how should corporate legal teams adapt?A typical legal department is organized around areas of expertise – you may have employment, litigation, business advice, and contracts, for example. The department may also have a legal operations function, or a member of the team assigned to certain process improvement and/or corporate programs. One of these programs covers technology changes at an organization. It is this latter set of responsibilities that become much more important, and more voluminous, in an agile software environment. Analyzing the potential risks of cloud updates, advising the business on how to mitigate those risks, and changing any associated legal workflows can become a full-time or close to full-time set of responsibilities. In addition, the culture of the department must change to one that embraces frequent change, understands change management, and is consistently updating and improving processes and procedures.Traditionally, in an on-premises environment, an IT organization would typically manage an upgrade governance structure. They would plan for a software upgrade every six months, outline the changes that are due with each upgrade, and analyze what departments it impacts and the risks of those impacts. Finally, they would present this information to a cross-functional committee who would discuss when the upgrade can be made and what kind of work needs to precede the upgrade. Legal was typically part of that committee. Now, in a cloud environment dozens (or even hundreds) of changes get pushed out weekly and, although there may be some advanced warning, the timing isn’t as flexible, it isn’t uniform across users, and there is usually less time to prepare. In addition, changes may be pushed out, rolled back, and potentially reversed. Updates may also occur without any warning, which can contribute to the cloud challenges for corporate legal departments[1]. To minimize risk in this agile environment some specific steps can be helpful: a similar governance committee needs to meet more frequently, the analysis of impact and risk needs to be done very quickly, and changes need to be made almost immediately to ensure you get ahead of any potential impacts. Due to the frequent nature of these changes, and supervising process updates to mitigate risk associated with the changes, managing cloud updates can be more time-consumingWithout structure, these cloud updates can add stress and increase reactive work. However, with some structure and clearly delineated oversight, they can be managed more efficiently. Although many organizations may not have a structure in place, those that do pull together a committee for each enterprise technology. This committee has IT, legal, compliance, and business-focused representation. It may have multiple representatives from some of these groups, depending on the perspectives needed. The goal is for the business representative to advocate for users of the technology, the legal and compliance representatives to mitigate risk and take into account regulatory, litigation and privacy considerations, and the IT team to represent management of the platform and be a voice for the platform provider. The committee should have access to a sandbox-type environment where they can test changes and should be empowered to lead companywide changes – or at least be able to work with a project management office or other resource to make these changes.Most legal departments run pretty lean so creating a new governance structure can be a significant challenge, but there are ways to make the process easier. First, you can hire outside support to handle all, or some, of this work. For example, outsourcing the creation of the governance structure to manage software updates and staffing that group with your own resources or have your external partner staff and manage it until a time when you are ready to take it over. Second, instead of hiring outside support, you can share your risk concerns with IT and rely on them to raise any potential impact that upgrades may have on risk and legal processes. For example, when IT receives an email from a software provider outlining updates, they would analyze them for potential impact to legal workflows, retention policies, or any other issues you have flagged. They would then test the updates and remediate any negative impacts. Finally, you can rotate governance committee membership so that the work is being shared across your team. Whatever approach you choose, keep in mind that changes in the cloud environment are happening frequently and having someone within your company watching from a legal perspective will pay dividends when it comes to accessing data for legal, compliance, investigative, or other reasons down the line.[1] Victoria Hudgins, “Big Adjustment: Legal Departments Struggle with Lack of Control Over Cloud Technology,” Legaltech news, November 29, 2021, law.com information-governance; microsoft-365; lighting-the-path-to-better-information-governancecloud-security, cloud-migration, blog, risk-management, information-governance, microsoft-365cloud-security; cloud-migration; blog; risk-managementlighthouse
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Case Preparation - Thinking out Loud! Summarized…
Long gone are days when the majority of discovery records were kept in paper format. Documents, invoices, and other related evidence needed to be scanned and printed in the tens (if not hundreds) of thousands. Today, a huge number of discovery efforts (internal or external) revolve around digital content. Ergo, this article will highlight the collection of digital evidence and how to best prepare your case when it comes to preservation and collections as well as processing and filtering.But, before we get into that, one of the core factors to keep in mind here is time, which will always be there irrespective of what we have at hand. It is especially complicated if multiple parties are involved, such as vendors, multiple data locations, outside counsels, reviewers, and more. For the purposes of this blog, I have divided everything into the following actionable groups - preservation and collection as well as processing and filtering.Preservation and CollectionIn an investigation or litigation there could be a number of custodians involved, for example, people who have or had access to data. Whenever there are more than a handful of custodians the location may vary. It is imperative to consider where and what methods to use for data collection. Sometimes an in-person collection is more feasible than a remote collection. Other times, a remote collection is the preferred method for all those concerned. A concise questionnaire along with answers too frequently asked questions is the best approach to educate the custodian. Any consultative service provider must ensure samples are readily available to distribute that will facilitate the collection efforts.Irrespective of how large the collection is, or how many custodians there are, it is best to have a designated coordinator. This will make the communication throughout the project manageable. They can arrange the local technicians for remote collections and ship and track the equipment.The exponential growth in technology presents new challenges in terms of where the data can reside. An average person, in today’s world, can have a plethora of potential devices. Desktops and laptops are not the only media where data can be stored. Mobile devices like phones and tablets, accessories such as smartwatches, the IoT (everything connected to the internet), cars, doorbells, locks, lights…you name it. Each item presents a new challenge and must be considered when scoping the project.User-generated data is routinely stored and shared on the Cloud using a variety of platforms. From something as ancient as email servers to “new” rudimentary storage locations, such as OneDrive, Google Drive, Dropbox, and Box.com. Others include collaborative applications, such as SharePoint, Confluence, and the like.Corporate environments also heavily rely on some sort of common exchange medium like Slack, Microsoft Teams, and email servers. These applications also present their own set of challenges. We have to consider, not just what and how to collect, but equally important is how to present the data collected from these new venues.The amount of data collected for any litigation can be overwhelming. It is imperative to have a scope defined based on the need. Be warned, there are some caveats to setting limitations beforehand, and it will vary based on what the filters are. The most common and widely acceptable limitation is a date range. In most situations, a period is known and it helps to set these parameters ahead of time. In doing so, only the obvious date metadata will be used to filter the contents. For example, in the case of emails, you are limited to either the sent or received date. The attachment's metadata will be ignored completely. Each cloud storage presents its own challenges when it comes to dates.Data can be pre-filtered with keywords that are relevant to the matter at hand. It can greatly reduce the amount of data collected. However, it is solely dependent on indexing capabilities of the host, which could be non-existent. The graphical contents and other non-indexable items could be excluded unintentionally, even if they are relevant.The least favored type of filter among the digital-forensics community is a targeted collection, where the user is allowed to guide where data is stored and only those targeted locations are preserved. This may not be cost effective, however, it can restrict the amount of data being collected. This scope should always be expected to be challenged by other parties and may require a redo.Processing and FilteringOnce the data collected goes through the processing engine the contents get fully exposed. This allows the most thorough, consistent, and repetitive filtering of data. In this stage, filtering relies on the application vetted by the vendor and accompanied by a process that is tested, proven, and updated (when needed).The most common filtering in eDiscovery matters is de-NIST-ing, which excludes the known “system” files from the population. Alternatively, an inclusion filter can be applied, which only pushes forward contents that typically a user would have created, such as office documents, emails, graphic files, etc. In most cases, both de-NIST-ing and inclusion filters are applied.Once the data is sent through the meat grinder (the core processing engine) further culling can be done. At this stage, the content is fully indexed and extensive searches and filters will help limit the data population even further to a more manageable quantity. The processing engine will mark potentially corrupt items, which are likely irrelevant. It will also identify and remove any duplicate items from all collected media from the entire matter data population. Experts can then apply relevant keyword searches on the final product and select the population that will be reviewed and potentially produced.I hope this article has shed some light on how to best prepare your case when it comes to preservation and collections as well as processing and filtering. To discuss this topic further, please feel free to reach out to me at MMir@lighthouseglobal.com.digital-forensics; information-governance; chat-and-collaboration-datacollections, ediscovery-process, preservation-and-collection, processing, blog, digital-forensics, information-governance, chat-and-collaboration-data,collections; ediscovery-process; preservation-and-collection; processing; blogmahmood mir
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Cloud Based Collaboration Tools are not Just Desirable, but Necessary for Keeping Workforces Productive
Below is a copy of a featured article written by Denisa Luchian for The Lawyer.com, where she interviews Lighthouse's Matt Bicknell. Lighthouse business development director EMEA Matt Bicknell talks to The Lawyer about how in today’s remote environment, cloud based collaboration tools are not just desirable but a necessity – but also the challenges they pose for eDiscovery processes.What is the driving force behind the massive migration to cloud-based environments over the last few years?There are a few factors at play here. Prior to the Covid-19 pandemic, companies were already moving their data to the Cloud (both public and private) in droves, in order to take advantage of unlimited data capacities and drastically lower IT overhead. The move to the Cloud is also being driven by a younger workforce that feels at home working with cloud-based chat and collaboration tools, like M365 or G-Suite. However, the worldwide shift to remote work due to the pandemic really broke the dam when it comes to cloud migration. We’ve seen a seismic shift to cloud-based tools and environments since March of 2020. In a completely remote environment, cloud-based collaboration tools are not just desirable, they are necessary to keep workforces productive. Migrating to the Cloud can greatly reduce the need for workers to be physically present in an office building.What are some of the challenges that cloud migration can pose to the eDiscovery process?Unlimited storage capacity at low cost can be a great thing for an organisation’s bottom line, but can definitely cause issues when it comes time to find and collect data that is needed for a litigation or investigation. Search functions built for cloud-based tools are often built for business use, rather than for the functionality that legal and compliance teams require in order to find relevant information. In addition, collecting and producing from collaboration tools like Teams or Slack can be much more complicated than a traditional email collection. Relevant communications that previously would have happened over email now happen over chat, through emoticon reactions, or through collaboratively editing a document. All of this relevant data may be stored in several different places, in a variety of formats within the Cloud. Even attachments are handled differently in cloud-based applications – instead of sending a static document as an attachment via email, Teams defaults to sending a link to the document in Teams. This means that the document could look significantly different at the time of collection than it did when the link was sent. Collecting from those types of sources, producing them in a format that makes sense to a reviewer/opposing counsel, and accounting for all the dynamic variables can be a difficult hurdle to overcome if the organisation hasn’t planned for it.How can companies prepare for eDiscovery challenges in a cloud environment?First, make sure compliance, legal and IT all have a seat at the table and have input into decisions that may affect their workflows and processes. Understand where your data resides and have effective retention, data governance, and compliance policies in place. Your policies should spell out which cloud-based applications employees may use and also have rules in place regarding how they can be used and where work product should be stored. Understand your legal hold policy and what type of data it encompasses. Make sure you have the right talent (either within your organisation or through a vendor) who understands the underlying architecture behind Teams, G-Suite, or any other cloud-based tool your organisation uses and also knows how to collect relevant information when needed. Ensure that your IT team or vendor has a system in place to monitor application and system updates. Cloud-based updates can roll out on a weekly basis; those changes may significantly impact the efficacy of your data retention and collection policies and workflows.As cloud technology continues to evolve, what does the future hold for eDiscovery? Because of the near endless storage capacity of the Cloud, the amount of data companies generate will just continue to exponentially expand. As a result, the technology behind AI and analytics will continue to improve, and those tools will eventually be less of an option to use in certain matters and more of a necessity to use for most matters. I also think as more companies feel comfortable moving their data to the Cloud, we will start to see more and more of these companies bring their eDiscovery programs in house. Vendors are already beginning to offer subscription-based, self-service, spectra eDiscovery programs which hand over the eDiscovery reigns to the organisation, while the vendor stores and manages the data in the Cloud (both public and private). This type of service allows companies to eliminate the middleman, control their own eDiscovery costs, and easily scale up or down to meet their own needs, while leaving the burden of data storage security and maintenance with the vendor. Finally, look for vendors to start offering subscription-based services to help organisations manage the near-constant stream of application and system updates for cloud-based services.microsoft-365; chat-and-collaboration-data; information-governancemicrosoft, cloud, g-suite, blog, microsoft-365, chat-and-collaboration-data, information-governance,microsoft; cloud; g-suite; blogthe lawyer
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Charting the Path to Progress: A Conversation with Economic Forecaster Marci Rossell and Lighthouse CEO Brian McManus
In 2021, corporations and law firms alike grappled with yet another year of disruption and unpredictability caused by economic volatility, a lingering global pandemic, increased regulation, and inequality within the workforce. To help our clients prepare for whatever 2022 may have in store, Lighthouse CEO Brian McManus welcomed economic forecaster and former CNBC chief economist and Squawk Box co-host Marci Rossell for a lively discussion centered around these current global macroeconomic trends, with a focus on their effect on the legal industry.Their conversation was wide-ranging and informative, touching on impacts, causes, and forecasts related to inflation, global workforce shortages, inequality in the workplace, technology adoption, and increased regulatory and data privacy restrictions. The key takeaways from this discussion are outlined below.Economic InflationAs of January 2022, the inflation rate was hovering around 7% in the United States (US), and around 5% in the European Union (EU). These are the highest inflation rates both countries have seen in decades. Rossell explained that one of the major contributing factors for this increase is the speed at which the overall economy recovered from the abrupt halt in economic activity in the spring of 2020 due to the COVID-19 pandemic. The sharp economic recovery drove a surge in demand for services and goods, at a time when supply around the world was at an all-time low due to pandemic-related shutdowns. This tension led to the current sustained inflation rates we’re seeing today, and those rates can be expected to remain high for the foreseeable future in markets where production is not expected to meet demand any time soon (such as the energy and oil industries).Within the legal industry, specifically, law firms and organizations have not only been impacted by the typical “cost of goods” inflation described above – they have also been impacted by inflation related to labor shortages and rising wages, as well as costs related to regulation and compliance. “The Great Resignation” and Its Impact on the Legal IndustryOver the last two years, droves of workers have switched employers, changed careers, or left the workforce all together, in what pundits and economists have deemed, “The Great Resignation.” Rossell explained that this global phenomenon may have roots in the financial crises of 2008 – 2009, when the economy contracted dramatically, leaving millennials struggling to enter a workforce plagued by an unemployment rate that had soared into the double digits. In the wake of this recession and for years afterward, the balance of power between employers and employees was weighted heavily in favor of employers, with overqualified workers applying to the same jobs, giving employers their pick of quality candidates. Now, this same generation of millennials have been confronted with a pandemic that has caused millions of people to suddenly sever their connections to jobs, employers, and/or geography. Many of these workers may not have felt very connected to where they worked or lived in the first place, but stayed because of their previous experience in a job market that was heavily influenced by the last recession. The pandemic suddenly forced this generation of workers into a situation that ultimately enabled them to make different career choices. And we are certainly seeing them making those choices. As Rossell noted, in addition to this trend among the millennial generation, the pandemic also escalated early retirements for an older generation, while an overall decrease in population growth has led to 400,000 fewer young people entering the labor force every year. These three factors are a perfect labor-shortage storm, with fewer experienced workers, fewer young people entering the labor market, and a generation of mid-career millennials reevaluating their careers and/or employers.McManus pointed out that labor shortage has also had a significant effect on the legal industry generally, and the eDiscovery industry specifically. eDiscovery is a niche industry, which makes it harder to find and retain experienced talent in general. But over the last twelve months, the tighter labor market has significantly exacerbated those issues. There is now a shortage of talent within eDiscovery and the cost of retaining valuable talent has sharply increased over the last nine months, with experienced employees being offered 20% to 40% more in compensation.This trend also affects the broader legal industry. Attrition of associates at law firms was at an unprecedented level in 2021 and the cost of retaining associates skyrocketed. For example, law firm associate compensation grew 11% in November of 2021, year over year, according to a state of the legal market report from the Thomson Reuters Institute. This trend can be expected to continue over the next few years due to the economic factors at play.To combat the worker shortage, McManus warned that employers should expect to not only offer higher compensation, but also include benefits like flexible work arrangements, in order to recruit and retain talented employees. Even prior to the pandemic, Rossell noted, studies showed that flexible work arrangement benefits were worth about 8% of a salary to younger employees. This trend is expected to sustain well into the future, as housing market trends indicate that 30-somethings are moving to larger homes away from large corporate offices and cities.Diversity, Equity, and Inclusion in the WorkforceThere has been a significant emphasis placed on diversity, equity, and inclusion (DE&I) over the past few years across many markets, including the legal industry. Rossell provided a historical perspective, explaining that thirty years ago the consensus from economists was that the labor market was rational and profit-maximizing and thus, discrimination in the labor force could not exist. The theory was that for-profit companies would always be incentivized to hire the best individual for the job, regardless of gender, race, ethnicity, sexual orientation, etc. But in 2004, a groundbreaking economic study on race in the labor market found that people with white-sounding names were 50% more likely to get a call back from an HR professional. This study was the beginning of a sea-change in economics, where organizations slowly realized the economic need for, and importance of, DE&I. In effect, organizations began to slowly understand that there was an economic cost to not hiring the best candidates, and that focusing on DE&I increases profitability, productivity, and growth.This sea-change is represented across the globe. European countries were initially on the forefront of this movement, as evidenced by the 2003 emphasis in Norway to have gender equity represented on corporate boards within the country. The US is now moving even further in that direction. Last year, Nasdaq proposed new board diversity rules and disclosure guidance, including that listed companies should have at least one board member who identifies as a woman, as well as one board member who self-identifies as an underrepresented minority or LGBTQ+.As McManus pointed out, this trend is also represented across the legal industry. There is a continued expectation for more diversity, equity, and inclusion within organizations, law firms, and legal technology supply vendors. Clients want to see diversity, equity, and inclusion represented in the teams they work with on a daily basis. Additionally, the next generation of talented employees is also demanding an equitable environment in which to work. Thus, legal and eDiscovery employers should expect that going forward, they will need to track, measure, and demonstrate an inclusive, equitable, and diverse environment in order to attract and retain the best workers.As Rossell pointed out: “(DE&I) matters to the next generation. As talent becomes scarcer and the balance of power shifts away from employers to employees, [the next generation of workers] is going to demand not only a flexible workforce but a diverse and inclusive environment to work in.”As DE&I programs advance, eDiscovery and legal teams will see how diverse hiring contributes to greater innovation and success.AI and Its Role in the Legal IndustryRossell also provided a historical view of technology innovation and its effect on worldwide economies. She noted that artificial Intelligence (AI) technology is the next step in a 200-year-old process that began with the industrial revolution – when advances in machine automation allowed simple machines to perform manufacturing related processes, enabling humans to migrate towards more service-related work. This has now evolved into machines that can now perform some of the work in the service sector, thanks to advancements in AI technology.McManus noted that within the legal industry, lawyers (who are trained to be risk-averse) have traditionally been much slower to adopt this emerging technology. However, the legal industry is also quickly becoming submerged in “big data,” and AI is one of the most effective tools to combat the labor shortages and increased costs that exacerbate the problems caused by massive data volumes. Nowhere is this more evident than in the document review process performed during eDiscovery.“The industry still follows a traditional approach [to document review] with large groups of lawyers reviewing massive volumes of text and that approach is just untenable,” McManus said.The impracticality of that traditional approach is not only due to the increased volume and complexity of data, but also due to labor shortages and increased labor costs. Advancements in AI give newer legal technology tools the capability to help automate and expedite the document review process. This should lead to AI adoption at a much faster pace than we’ve traditionally seen in the legal industry, McManus noted.The Global Regulatory Landscape, Anti-Trust Activity, and What to Look for in the Coming YearsRossell also provided an insightful overview of the dynamic and shifting regulatory landscape from an economist’s perspective. Increased governmental regulation is raising costs in almost every industry and is one of the driving forces behind higher inflation rates. In the United States, the increase in government regulation may be due to the fact that the government’s governing functions have been slowly shifting from the legislative branch to the executive branch. In turn, this shift means that every four years, companies may deal with a complete shift in the regulatory landscape depending on which political party wins the presidential office. These abrupt swings make compliance very costly and put pressure on smaller organizations. Often the only companies that can survive this type of volatility are those big enough to support a department solely dedicated to compliance. Thus, in some ways, increased government regulation is driving the consolidation of companies.At the same time, we are seeing a shift in antitrust policy from an economics perspective. Whereas previously, anti-competition policy was centered around whether consolidation would harm consumers, we’re now seeing a shift to assessing a broader range of harm. Prior to this shift, a merger would be blocked if it would cause higher prices for consumers (i.e., if the merger would cause consumers harm by giving them less choices and therefore raise consumer prices). Now, mergers are blocked for a much broader range of issues that are not just centered solely around consumers, but around society as a whole. For example, a merger might now be blocked if it would be harmful to the environment, to workers, would cause a decline in future competition, etc. This more aggressive governmental regulation worldwide is expected to continue in the coming years. In short, expect anti-competition scrutiny to continue to be broad and aggressive, regardless of changes in political parties and offices.The Future of the Global Data Privacy LandscapeFinally, McManus provided a helpful overview of recent changes to the data privacy landscape, and what to expect in the 2022. Another area where government regulation is expected to continue to increase globally is around data privacy rights and protections for consumers. The EU’s GDPR legislation in 2018 paved the way for data privacy rights, providing a template for governments on how to regulate and protect consumer data privacy. Within a few years, California followed suit, as did a plethora of other governments around the world. This trend is only expected to continue as we move into an increasingly digital world.In the US in 2021 alone, two more states passed comprehensive GDPR-like laws (Virigina and Colorado), while at least 25 other states introduced or had data privacy laws somewhere within the state legislative consideration process. And the US federal government also looks to be increasingly active in this area – with the U.S. House Energy and Commerce Committee voting to give the Federal Trade Commission $1 billion to set up a data privacy bureau. Even China passed a GDPR-like law in 2021, the Personal Information Protection Law, which included not only the risk of huge fines for non-compliance, but also the risk of companies being black-listed by the Chinese government.This focus on data privacy regulation will certainly increase costs for businesses in the coming years, as companies work to stay compliant with a patchwork of global and local data privacy laws and regulations.ediscovery-reviewccpa, gdpr, review, ai-big-data, blog, ediscovery-review,ccpa; gdpr; review; ai-big-data; bloglighthouse
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Challenging 3 Myths About Document Review During Second Requests
Legal teams approaching a Hart-Scott-Rodino (HSR) Second Request may hold false assumptions about what is and isn’t possible with document review. Often these appear as necessary evils—compromises in efficiency and precision are inevitable given the unique demands of Second Requests. But, in fact, these compromises are only necessary in the context of legacy technology and tools. Using more current tools, legal teams can transcend many of these compromises and do more with document review than they thought possible.Document review during an HSR Second Request is notoriously arduous. Legal teams must review potentially millions of documents in a very short timeframe, as well as negotiate with regulators about custodians and other parameters that could change the scope of the data under review.Up until recently, legal teams’ ability to meet these demands was limited by technology. It wasn’t possible to be precise and thorough while also being extremely quick. As a result, attorneys adopted certain conventions and concessions around the timing of review steps and how much risk to accept.Technology has evolved since then. For example, tools powered by advanced artificial intelligence (AI) utilize deep learning models and big data algorithms that make review much faster, more precise, and more resilient than legacy tools. However, legacy thinking around how to prepare for Second Requests remains. Many attorneys and teams remain beholden to the constraints imposed on them by tools of the past. New review tools enable new approaches and benefits, eliminating these constraints. Here’s a look at three of the most common myths surrounding document review during Second Requests and how they’re proven false by modern review tools.Myth 1: Privilege review must come after responsive reviewThe classic approach to reviewing documents during a Second Request is to start by creating a responsive set and then review that set for privileged documents. This takes time— an extremely precious commodity during a Second Request—but these steps are unavoidable with legacy tools. The linear nature of legacy review models requires responsive review to happen first because supporting privilege review over an entire dataset simply is not a feasible task over potentially millions of records. Tools leveraging advanced AI, however, are well suited to support scalable privilege analysis with big data. Rather than save privilege review for later, legal teams can conduct privilege review simultaneously with responsive review. This puts documents in front of human reviewers sooner and shaves invaluable hours off the timeline as a whole.Myth 2: Producing privileged documents to regulators is inevitableInadvertently disclosing privilege documents to federal agencies is so common the Federal Rules of Civil Procedure give parties some latitude to do so without penalty. Even so, the risk remains of inadvertent disclosure during a Second Request that will invite additional questions and scrutiny from regulators and undermine the deal.Although advanced AI tools cannot eliminate the possibility of inadvertent disclosure, these automated solutions can vastly reduce it. In one recent Second Request, a tool using advanced AI was able to identify and withhold 200,000 privilege documents that a legacy tool had failed to catch. This spared the client from costly exposure and clawbacks.Myth 3: There’s no time to know the details of what you’re producingWith massive datasets and very little time to review, legal teams get used to producing documents without fully knowing what’s in them. This can cause surprise and pain down the line when regulators ask for clarification about information the team isn’t prepared to address.With advances in technology, teams can gain more clarity using tools that identify key documents. These tools conduct powerful searches of both text and document attributes, using complex and dynamic search strings managed by linguistic experts. Out of a million or more documents, key document identification can surface the one or two thousand that speak precisely to attorneys’ priorities, efficiently helping counsel prepare for testimony and other proceedings.What’s your Second Request strategy?Second Requests will always be intense. Advancements in eDiscovery technology prove the limits of the past don’t apply today. With technology moving beyond legacy tools, it is time for teams to move beyond legacy thinking as well.For more detail about how advancements in technology help teams meet the demands of Second Requests, download our eBook.antitrust; ediscovery-review; ai-and-analyticsreview, hsr-second-requests, blog, antitrust, ediscovery-review, ai-and-analytics,review; hsr-second-requests; blogkamika brown
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California’s New Discovery Rules too Costly? Technology is the Answer
Last year, California passed legislation that alters civil discovery procedures and significantly impacts discovery for all litigants in state court. This change in the state court rules of civil procedure essentially makes it mandatory for the producing party to identify the specific discovery request to which each and every document is responsive. Many fear this new rule will exponentially increase the cost and burden of discovery requests. The good news is there’s a simple solution: use technology to easily automate the process. In this blog, I’ll discuss a brief overview of the rule, the potential impact, and how technology can save the day and provide an automated and cost-effective solution.The RuleBeginning on January 1, 2020, California’s Code of Civil Procedure § 2031.280 was amended by legislation S.B. 370 to make it a requirement that documents planned for production identify “the specific request number to which the documents respond.” Prior to this rule (and as is the case in the majority of jurisdictions both in federal and state courts), documents could either be produced as they are maintained in the usual course of business, or organized to correlate with the categories in the discovery demand. By mandating this new way of organizing and labeling documents, S.B. 370 marks the establishment of a major new requirement for document productions and impacts all pending and active cases that are subject to California’s Civil Discovery Act. Of note, the new rule is vague on the procedural front and fails to identify how exactly litigants should fulfill the requirements, leaving open questions that courts will likely need to address in the future.Potential ImpactThe rule change is weighted towards the goal of saving the requesting party time and streamlining reviews so that large quantities of documents aren’t received without any indication of which discovery request they relate to. Litigants are also concerned, however, that a heavy burden in terms of time and cost is created by S.B. 370 for producing parties. Imagine a case involving a large-scale ESI production with thousands upon thousands of documents where the producing party must go through and manually identify every document and exactly which request it is responsive to. The time it would take to manually organize a large production at this level would almost certainly greatly increase the length of the review due to the challenge that is involved with manually determining how each document correlates to a specific discovery demand. Ultimately, the biggest potential impact of S.B. 370 is higher litigation costs as a result of a lengthened review if a manual process is left in place.The SolutionWhen contemplating the bigger burden this new rule might place on producing parties, there’s also a unique opportunity that presents itself. With the use of technology, large reviews can be managed with an automated solution that would decrease the time from review to production and reduce costs. At a high level, the solution would entail:Identify the Issues - Identifying a comprehensive list of issues involved in the review.Map the Issues - Once the issues are understood, they would be mapped to a numbered list of specific discovery requests.Review and Tag - Armed with that organizational structure, the reviewers would conduct their document review and tag the documents by issue as per usual. At the completion of the review, the solution would automatically link the documents to each category based on the original map we created at the commencement of the review.Report Back - A report could also be generated to be provided with the final production set. That list could be produced in a sortable spreadsheet or it could be automated to connect to separate tags within the review database so it could be searched as contemplated. With S.B. 370 now in effect, it’s important to set up an automated process that will address the changes and potentially create a better organized and more cost-effective review. ediscovery-reviewediscovery-process, blog, ediscovery-review,ediscovery-process; bloglighthouse
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Building Your Case for Cutting-Edge AI and Analytics in Five Easy Steps
As the amount of data generated by companies exponentially increases each year, leveraging artificial intelligence (AI), analytics, and machine learning is becoming less of an option and more of a necessity for those in the eDiscovery industry. However, some organizations and law firms are still reluctant to utilize more advanced AI technology. There are different reasons for the reluctance to embrace AI, including fear of the learning curve, uncertainty around cost, and unknown return on investment. But where this is uncertainty, there is often great opportunity. Adopting AI provides an excellent opportunity for ambitious legal professionals to act as the catalysts for revitalizing their organization’s or law firm’s outdated eDiscovery model. Below, I’ve outlined a simple, five-step process that can help you build a business case for bringing on cutting-edge AI solutions to reduce cost, lower risk, and improve win rates for both organizations and law firms.Step 1: Find the Right Test CaseYou will want to choose the best possible test case that highlights all the advantages that newer, cutting-edge AI solutions can provide to your eDiscovery program.One of the benefits of newer solutions is that they can be utilized in a much wider variety of cases than older tools. However, when developing a business case to convince reluctant stakeholders – bigger is better. If possible, select a case with a large volume of data. This will enable you to show how effectively your preferred AI solution can cull large volumes of data quickly compared to your current tools and workflows.Also try to select a case with multiple review issues, like privilege, confidentiality, and protected health information(PHI)/personally identifiable information (PII) concerns. Newer tools hitting the market today have a much higher degree of efficiency and accuracy because they are able to run multiple algorithms and search within metadata. This means they are much better at quickly and correctly identifying types of information that would need be withheld or redacted than older AI models that only use a single algorithm to search text alone.Finally, if possible, choose a case that has some connection to, or overlap with, older cases in your (or your client’s) legal portfolio. For a law firm, this means selecting a case where you have access to older, previously reviewed data from the same client (preferably in the same realm of litigation). For a corporation, this just means choosing a case, if possible, that shares a common legal nexus, or overlapping data/custodians with past matters. This way, you can leverage the ability that new technology has to re-use and analyze past attorney work product on previously collected data.Step 2: Aggregate the Data Once you’ve selected the best test case, as well as any previous matters from which you want to analyze data, the AI solution vendor will collect the respective data and aggregate it into a big data environment. A quality vendor should be able to aggregate all data, prior coding, and other key information, including text and metadata into a single database, even if the previously reviewed data was hosted by different providers in different databases and reviewed by different counsel.Step 3: Analyze the Data Once all data is aggregated, it’s time for the fun to begin. Cutting-edge AI and machine learning will analyze all prior attorney decisions from previous data, along with metadata and text features found within all the data. Using this data analysis, it can then identify key trends and provide a holistic view of the data you are analyzing. This type of powerful technology is completely new to the eDiscovery field and something that will certainly catch the eye of your organization or your clients.Step 4: Showcase the Analytical ResultsOnce the data has been analyzed, it’s time to showcase the results to key decision makers, whether that is your clients, partners, or in-house eDiscovery stakeholders. Create a presentation that drills down to the most compelling results, and clearly illustrates how the tool will create efficiency, lower costs, and mitigate risk, such as:Large numbers of identical documents that had been previously collected, reviewed, and coded non-responsive multiple times across multiple mattersLarge percentages of identical documents picked up by your privilege screen (and thus, thrust into costly privilege re-review) that have actually never been coded privilege in any matterLarge numbers of identical documents that were previously tagged as containing privilege or PII information in past matters (thus eliminating the need for review for those issues in the current test case).Large percentages of documents that have been re-collected and re-reviewed across many mattersStep 5: Present the Cost ReductionYour closing argument should always focus on the bottom line: how much money will this tool be able to save your firm, client, or company? This should be as easy as taking the compelling analytical results above and calculating their monetary value:What is the monetary difference between conducting a privilege review in your test case using your traditional privilege screen vs. re-using privilege coding and redactions from previous matters?What is the monetary difference between conducting an extensive search for PII or PHI in your test case, vs. re-using the PII/PHI coding and redactions from previous matters?How much money would you save by cutting out a large percent of manual review in the test case due to culling non-responsive documents identified by the tool?How much money would you save by eliminating a large percentage of privilege “false positives” that the tool identified by analyzing previous attorney work product?How much money will you (or your client) save in the future if able to continue to re-use attorney work product, case after case?In the end, if you’ve selected the right AI solution, there will be no question that bringing on best-of-breed AI technology will result in a better, more streamlined, and more cost-effective eDiscovery program.ai-and-analyticsanalytics, ai-big-data, data-re-use, phi, pii, blog, ai-and-analytics,analytics; ai-big-data; data-re-use; phi; pii; bloglighthouse
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Breaking the Bias: Strategies from Top Women Leaders in Legal Technology
This year’s International Women’s Day theme revolves around “breaking the bias” and imagining a more gender-equal world. This topic seems particularly relevant for the legal and technology fields, which both have long histories of being male-dominated industries. In 1980, just 8% of attorneys were women, with that number growing to 37% percent by 2021. While the number of women in the technology field has actually declined over the last 40 years, from 37% in 1985, to 33% in 2022.But cold statistics, while helpful, don’t tell the full story. Numbers can be helpful to get a 10,000-foot view of how far we’ve come and how far we still need to go—but they can’t tell us how to get to that gender-equal world or what it’s like to live those statistics. For that, we need to listen to women in the legal and technology space.We need to understand the perseverance of the women who broke through the glass ceiling when they were one of a few in the profession. Like when Supreme Court Justice Ruth Bader Ginsburg explained how they had to install a women’s bathroom in the justices’ robing room after her appointment to the Supreme Court in 1993. We need to hear the stories of the women who broke barriers while dealing with the intersectionality of gender and racial bias. Like Loretta Lynch, the first African-American woman and second woman to be confirmed as United States Attorney General in 2015, recounting the story of a client who directed all of his questions to Lynch’s co-worker – a young male associate – who had nothing to do with what Lynch was presenting.And we need to listen to the women leading our industry today and paving the way for the next generation. In that vein, Lighthouse is honored to feature seven women who are innovators, champions of equity, and models of leadership in the legal technology field:Vanessa Quaciari, eDiscovery Counsel, Baker Botts L.L.P.Kim Foster, Discovery Services Manager, Lane PowellKelly Clay, Assistant General Counsel and Global eDiscovery Counsel, GSKJani Grantz, eDiscovery Manager, DaVitaMarilyn Caldwell, eDiscovery Director, SiemensMoira Errick, Litigation Support Manager, StripeMargaret Dolson, Global Head eDiscovery Services and Archiving Technology, Deutsche Bank USAWe had the honor of interviewing these women about their experiences in the legal technology field and asking them their thoughts on breaking down biases within the industry. Their perspectives and advice can serve as a helpful guide for all people who strive for equality.Recognize the achievements and contributions of women Recognizing the achievements of women is a simple but powerful tool in the fight to break down bias. When women’s achievements, contributions, and ideas are recognized within a firm or organization, it helps dismantle harmful stereotypes that women are not as present in the workplace, or that they don’t achieve as much as men.Talking other women up is so important. When you have a seat at the table and an opportunity to promote another talented woman – you should always do so. —Margaret DolsonFrom a cultural perspective, you have to be intentional and lead by example. Elevate female voices by echoing their comments and ideas while ensuring they receive full credit for their contributions. Seek out their counsel in front of others, and do it often, so that it becomes the norm within your culture. —Kim FosterHowever, for a variety of reasons, women may not feel comfortable recognizing their own achievements. They may also be more reticent to accept recognition or downplay their contributions. Many of the women we spoke to mentioned that accepting recognition was just as important as giving it, because recognition of one woman serves to amplify the voices of others.Women are far too often dismissive of their own achievements. We don't want to be seen as someone who brags or calls attention to ourselves. Frequently, we fall into the societal trappings of even going so far as to be dismissive of our own accomplishments – if we even make them publicly known. I strive to normalize being proud of ourselves, to share what we have achieved, and know that even if it may seem small to our own eyes, it's an accomplishment. I encourage a safe and supportive environment where everyone can feel free to share in their own way, through their own voice, or through the help of another. We all deserve recognition for what we do. —Moira ErrickI remind women that your achievements may seem like just doing your job, but they are so much more for each of us, and it is important to accept and recognize the appreciation. —Kelly ClayI’ve joined organizations to get my name, knowledge, and experience out there to show what women are capable of and be encouraging to women and other genders. —Jani GrantzTo help facilitate and encourage this recognition, it’s important for firms, organizations, departments, and teams to have a dedicated method for acknowledging achievements, wins, and contributions for all employees. This can be as simple as an email chain, or as formal as a dedicated system.My company as a whole strives for equality in all areas, be it gender, race, or any other identifying factor, and that allows my team the ability to recognize accomplishments from everyone including women. In my department, we do Friday emails where people get shout-outs for their contributions and wins, all inclusive of genders, as everyone’s achievements are important to the growth of the village. —Jani GrantzWe are proud to have extremely talented women throughout our firm and are constantly making sure we help raise their visibility. —Vanessa QuaciariWe celebrate achievements both formally and informally, including day-to-day support and recognition in broader team meetings, postings, and events. —Marilyn CaldwellWork to increase representation Both the legal and technology fields have been historically male-dominated. While the statistics are improving incrementally, there is still a way to go before there is equity in the legal technology industry.Many times in my career, I have been the only woman in the room, in the meeting, in the planning session. —Marilyn CaldwellGenerally speaking, both the legal and technology fields have up to now been male-dominated. Even in the eDiscovery niche, the technological knowhow is typically something that is provided by men. This likely is the result of the relatively low number of women historically graduating with science, technology, engineering, and mathematics (STEM)-related degrees. —Vanessa QuaciariHistorically, there has been a perception that women are not as technically inclined or analytical as men. This is simply not true, evidenced by the many exceptional women in eDiscovery at all levels. The legal and technology fields both suffer from stereotypes of having fewer women in them than many other fields. While more women have been entering law school and the legal field generally, there are fewer women at the higher levels of ownership (partners) and leadership. Women want equitable opportunities for growth and development, and they want to be considered for leadership roles. —Kim FosterOver the years I’ve seen men get bigger matters, better pay, and faster promotions because “historically men know more about technology” and they support their own first. —Jani GrantzThus, the importance of women representation in the industry cannot be understated. A more diverse team is stronger and more innovative. Representation also breaks down barriers and moves organizations toward gender equality.When there are more of us in the room, more women who have a seat at the table and have the ability to influence decision-making, it puts us in a better position to recognize the potential of other women and help move them forward. —Margaret DolsonMore women in leadership positions bring a more well-rounded, balanced, and holistic perspective to business. —Marilyn CaldwellThere are a variety of ways to increase representation of women, both on a small scale and across the entire industry. On a micro level, team members can ensure that there is diversity across projects, matters, and teams. Co-workers can prioritize diversity of thought when setting important meetings. Outside of work, people can strive to improve representation by getting involved in technology and legal education programs or join industry groups dedicated to diversity, equity, and inclusion in the field. On a macro level, organizations should develop systems to ensure their hiring, pay, and career development practices are driving diversity. Companies and firms can also support organizations that are dedicated to increasing diversity in technology and legal education.We get to increased representation in the industry by listening, by intentional discourse, and, most importantly, by supporting and identifying women with talent to fill these roles.—Marilyn CaldwellBreaking gender biases starts at home. I have two daughters and a son, and I try to instill in them all an interest in science and technology, rather than perpetuate the misguided notion that those fields are only appropriate for boys. —Vanessa QuaciariTake stock of your current compensation program (i.e., how are people paid, do we have consistent methodologies to establish pay ranges for a specific role, provide pay increases, etc.). Develop hiring and recruiting protocols that evaluate individuals based on observable skills, measurable outcomes, etc. In hiring, this may entail ensuring that recruiters use similar questions for each candidate, improve validity and reliability within the candidate selection process, and give weight to candidate attributes that actually count and ensure that scorers are consistent. —Kim FosterI personally have worked to change that gender stereotype by increasing my eDiscovery tech knowledge, learning the front and back end of relevant software, getting my RCA, and staying current with legal tech updates. —Jani GrantzBefore implementing these systems at the organizational level, however, decision-makers may need to be trained to understand their own implicit biases to ensure they are not unintentionally hampering diversity efforts. Educate your decision-makers about bias and implicit bias. Decision-makers could include, but are not limited to, your organization’s recruiting team, hiring managers, supervisors, those in leadership roles who hire individuals, including positions responsible for ongoing professional development. —Kim FosterOne of the things I’ve championed within our organization is unconscious bias training and exposure – because I think the awareness of that is what can really lead to change. Discussing unconscious bias and its effects is not about assigning blame. It’s about talking through the things that may cause us to be inherently biased against others, and even ourselves, within the workplace. And that discussion can lead us to shift those perceptions so that everyone feels comfortable expressing their thoughts and opinions. —Margaret DolsonBoldly be yourself… and then don’t be afraid to use your voice loudlyMany high-achieving women often speak about facing “imposter syndrome” – the feeling of doubting your own ability in a role while feeling like a fraud masquerading as a leader. This experience may be exacerbated for women in a male-dominated industry because other leaders and experts in the industry are predominantly men, and therefore, don’t look or sound like they do.One way to overcome this feeling is to recognize the implicit bias you may have around what an “expert” or “leader” looks or sounds like – and then working to stop trying to fit into that mold. In other words, strive to be your authentic self.Imposter syndrome is a very real issue because we may never fit into the template of what a “leader” has traditionally looked and sounded like within the legal and technology industries. So, we end up trying to fit into a mold of someone who is not remotely like us. But when we are able to be our authentic selves, and we know our subject matter – we can show up as competent, charismatic, and confident even when we don’t fit into a blueprint. However, it can take a lot of courage to do that. —Margaret DolsonOnce you are not afraid to use your own voice, you can then start using it loudly – not only to demonstrate your own expertise and knowledge, but also as a voice for others.Present yourself as you are, focusing on your skills and abilities rather than your appearance. Do not be afraid to put yourself “out there” for technical positions or projects, and never let anyone tell you that you are not capable. —Kim FosterContinue to stand up for gender equality and don’t back down whether you’re a woman who is being treated unfairly or someone who is witnessing acts of inequality toward women and other genders. Don’t be afraid to voice your opinion and bring notice to the bias. Even if it’s unintentional, it’s important that people see the affects bias has so that behaviors can be changed. —Jani GrantzDon’t let inertia get you. Speak up, advocate for yourself the way you would for others. Take up more space than you need and keep moving forward. —Kelly ClayThere are very brilliant women who are leading the charge both on the legal and the technological side as well as the judicial side. Day in and day out they are demonstrating through case law, articles, and innovative technology expansion that the traits we prize in the workforce are equal opportunity characteristics that any human can demonstrate passionately. —Moira ErrickLean in. Gather perspective. Be clear. Be diplomatic AND assertive. Be an example. Take a seat at the table. Be brave. Be candid. Listen to understand. —Marilyn CaldwellFind your tribeIt’s important to find your “tribe” – a group of people who support each other and can provide knowledgeable advice and an ear to listen when needed. When women have a support system and feel accepted as they are, they feel comfortable using their voice to advocate for themselves and for others. In this way, women can empower each other to break through barriers and bias.I strongly urge all women to find their tribe. Find a mentor, be a mentor. Be active in both your professional and personal communities in whatever way you can. We don't have to network through these organized functions to be supported. We can support one another on the sidelines of the soccer field, at 3 a.m. on a group text as we cram in one more rewrite of that summary, or at 8 a.m. as we take a moment to ourselves. Find your tribe who will give you the support and respect we all deserve. —Moira ErrickWithin the workplace, I recommend women align themselves with similarly-minded professionals, not only women in leadership positions, but people whose careers and knowledge are worth emulating and understanding. I think this helps break gender biases while creating goodwill with people with similar career paths. —Vanessa QuaciariRecognize the historic challenges women are facing today – and work to overcome thoseCovid-19 has had a dramatic effect on the workforce. But it has had a disproportionate effect on women. For instance, a 2021 policy brief from the International Labour Organization found that globally, women’s employment dropped by 4.2% between 2019 and 2020, compared with 3% for men. And a January 2021 report from the National Women’s Law Center showed that when the economy lost 140,000 net jobs in December of 2020, all of those losses fell on women (with women losing 156,000 jobs and men gaining 16,000). This disproportionate effect is because women are often the primary caregivers in family structures.Covid has impacted all of us profoundly. For caregivers in a family its impact is amplified. I don’t want to assume that all caregivers are women, but many are the primary caregivers and also have full time jobs. —Kelly ClayAs a mother, I am aware of how the pandemic has impacted not only women lawyers with children, but parents in general, who now have their usual load of professional responsibilities plus the added duties related to having their children at home all of the time. —Vanessa QuaciariI have seen many working women, especially those who also act as caregivers, facing a lot of added stress due to biased thinking. I have seen many women who have had to make life altering choices...family or career. Near and dear friends have had to step away from their roles because they are not afforded the trust by their employers to get their jobs done outside of the “correct” hours of the day. Covid has exacerbated that, but by the same token it has brought this issue to the forefront. It's not a problem that is unique to any one company, it is endemic in our nation. —Moira ErrickIndeed, while these hardships were felt most acutely during pandemic-related lockdowns, the pandemic simply highlighted and exacerbated inequities that already existed for women. Moving forward, this can be addressed by looking more holistically at the root cause and working to remedy from the ground up. In terms of how to curb the disproportionate impact of the pandemic as we move forward – we need to shift our focus to include men in this analysis. Rather than solely asking women what they need, we also need to ask men, “What do you need in order to be equal participants in running a household?” Because running a household is very similar to running a business and when we focus only on women, we are saying that it’s solely on a woman to keep that business running. The disproportionate burden on women can’t just be addressed by trying to accommodate women, we need to also bring men into the equation. —Margaret DolsonCorporations that support work life balance, in whatever terms the employee sets, are still unicorns. We have to recognize, as a nation, that the mindset that work can only be done in one location during set hours is simply not true in today's business world and given the disparate impact such restrictions have on women, it should not be tolerated anymore. We cannot close the door to half of the workforce because they are left with no other options due to inability to access childcare, lack of school, partners who also are beholden to unforgiving work schedules, and the many other hurdles that are out there. We need to recognize that work is work, whether it is done between 9 a.m. and 5 p.m. or 7 p.m. to 2 a.m. or any combination thereof, so long as it meets the overarching needs of the business. —Moira ErrickConclusionThe stories and advice of these women leaders can serve as a guide, helping to lead us to become a more gender-equal industry and world. Lighthouse is proud to amplify their voices.diversity-equity-and-inclusionblog, diversity-equity-and-inclusion,bloglighthouse
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Building a Business Case for Upgrading Your eDiscovery Self-Service Practices in Six Simple Steps
self-service, spectra models are becoming increasingly more popular within the eDiscovery space. The ability to easily manage matters using in house teams, not only saves time and money, but it also allows companies to scale and maintain control in the ever-growing data landscape we live in today, without having to make the investment in infrastructure or additional headcount. It is no wonder so many firms and corporations are making the shift to a technology on-demand model and upgrading their internal processes.However, whether you are hoping to move away from a legacy platform or looking to upgrade your current self-service, spectra tool-kit, the process can seem intimidating and may take some convincing for those not completely on board. Below I outline some key steps to help you build a business case to propose to your teams and get the ball rolling when it comes to onboarding or upgrading your self-service, spectra practice.1. Assess the Interests of the Decision Makers – This is the first key step to getting started and will help you build your business case moving forward. To get started, list the current challenges your key decision makers are facing and whether they can be addressed with an upgraded self-service, spectra model. If folks are unsure, review the key benefits of modern self-service, spectra solutions and explore if any of them resonate.2. Outline the Goal – Once you understand the interests of your decision makers, the next step is to identify their key needs and requirements. For example, what matters most to your team? Is it accessibility, speed, data analytics, scalability, cost recovery, all-in-one tool, ease of use, low maintenance, controlled access, limited professional service hours, etc.? Define their top requirements and overall goals, and keep those top of mind while executing the next few steps.3. Do the Research – Next, dig into those challenges and key requirements and how an upgraded self-service, spectra model may meet those needs. Why will this model be of value to your team, and more specifically what are the top benefits and how do those overlap with the decision maker’s needs? Are there any client success stories that are relatable to your team’s situation? Stats?4. Develop the Pitch – Once you have conducted your research and have a solid list of key findings and benefits, outline them in a digestible manner. Think competitive matrices, tables, and PowerPoint. Feel free to leverage this Excel or PDF self-service, spectra selection matrix template. Lay out the key reasons why an upgrade makes sense and how it will meet the needs of your team.5. Present the Findings – Prior to presenting, get a meeting invite on the books with details and expectations (i.e. looking for decision maker’s feedback and preferences). It is also a good idea to preview the findings with your leader or a trusted colleague who can weigh in and provide ideas to enhance your presentation. Present your findings, any key client success stories you uncovered, as well as the benefits that matter most to your team.6. Continue the Communication – After the presentation, be sure to follow up and address any concerns or questions that came up in the meeting. If needed, set another meeting to hone in on some of those questions. Ask for feedback and continue the conversation.Building a business case to upgrade your self-service, spectra practices can require upfront research and tough conversations, but this simple six-step guide should ease that process. To discuss these steps further or for assistance developing your business case, feel free to reach out to me at bthompson@lighthouseglobal.com.ediscovery-reviewcloud, self-service, spectra, blog, ediscovery-review,cloud; self-service, spectra; blogbrooks thompson
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Big Data Challenges in eDiscovery (and How AI-Based Analytics Can Help)
It’s no secret that big data can mean big challenges in the eDiscovery world. Data volumes and sources are exploding year after year, in part due to a global shift to digital forms of communication in working environments (think emails, chat messages, and cloud-based collaboration tools vs. phone calls, in-person meetings, and paper memorandums, etc.) as well as the rise of the Cloud (which provides cheaper, more flexible, and virtually limitless data storage capabilities).This means that with every new litigation or investigation requiring discovery, counsel must collect massive amounts of potentially relevant digital evidence, host it, process it, identify the relevant information within it (as well as pinpoint any sensitive or protected information within that relevant data) and then produce that relevant data to the opposing side. Traditionally, this process then starts all over again with the next litigation – often beginning back at square one in a vacuum by collecting the exact same data for the new matter, without any of the insights or attorney work product gained from the previous matter.This endless cycle is not sustainable as data volumes continue to grow exponentially. Fortunately, just as advances in technology have led to increasing data volumes, advances in artificial intelligence (AI) technology can help tackle big data challenges. Newer analytics technology can now use multiple algorithms to analyze millions of data points across an organization’s entire legal portfolio (including metadata, text, past attorney work product, etc.) and provide counsel with insights that can improve efficiency and curb the endless cycle of re-inventing the wheel on each new matter. In this post, I’ll outline the four main challenges big data can pose in an eDiscovery environment (also called “The Four Vs”) and explain how cutting-edge big data analytics tools can help tackle them.The “Four Vs” of Big Data Challenges in eDiscovery 1. The volume, or scale of dataAs noted above, a primary challenge in matters involving discovery is the sheer amount of data generated by employees and organizations as a whole. For reference, most companies in the U.S. currently have at least 100 terabytes of data stored, and it is estimated that by 2025, worldwide data will grow 61 percent to 175 zettabytes.As organizations and individuals create more data, data volumes for even routine or small eDiscovery matters are exploding in correlation. Unfortunately, court discovery deadlines and opposing counsel production expectations rarely adjust to accommodate this ever-growing surge in data. This can put organizations and outside counsel in an impossible position if they don’t have a defensible and efficient method to cull irrelevant data and/or accurately identify important categories of data within large, complex data sets. Being forced to manually review vast amounts of information within an unrealistic time period can quickly become a pressure cooker for critical mistakes – where review teams miss important information within a dataset and thereby either produce damaging or sensitive information to the opposing side (e.g., attorney-client privilege, protected health information, trade secrets, non-relevant information, etc.) or in the inverse, fail to find and produce requested relevant information.To overcome this challenge, counsel (both in-house and outside counsel) need better ways to retain and analyze data – which is exactly where newer AI-enabled analytics technology (which can better manage large volumes of data) can help. The AI-based analytics technology being built right now is developed for scale, meaning new technology can handle large caseloads, easily add data, and create feedback loops that run in real time. Each document that is reviewed feeds into the algorithm to make the analysis even more precise moving forward. This differs from older analytics platforms, which were not engineered to meet the challenges of data volumes today – resulting in review delays or worse, inaccurate output that leads to critical mistakes.2. The variety, or different forms of dataIn addition to the volume of data increasing today, the diversity of data sources is also increasing. This also presents significant challenges as technologists and attorneys continually work to learn how to process, search, and produce newer and increasingly complicated cloud-based data sources. The good news is that advanced analytics platforms can also help manage new data types in an efficient and cost-effective manner. Some newer AI-based analytics platforms can provide a holistic view of an organization’s entire legal data portfolio and identify broad trends and insights – inclusive of every variety of data present within it. These insights can help reduce cost and risk and sometimes enable organizations to upgrade their entire eDiscovery program. A holistic view of organizational data can also be helpful for outside counsel because it also enables better and more strategic legal decisions for individual matters and investigations.3. The velocity, or the speed of dataWithin eDiscovery, the velocity of data not only refers to the speed at which new data is generated, but also the speed at which data can be processed and analyzed. With smaller data volumes, it was manageable to put all collected data into a database and analyze it later. However, as data volumes increase, this method is expensive, time consuming, and may lead to errors and data gaps. Once again, a big data analytics product can help overcome this challenge because it is capable of rapidly processing and analyzing iterative volumes of collected data on an ongoing basis. By processing data into a big data analytics platform at the outset of a matter, counsel can quickly gain insights into that data, identifying relevant information and potential data gaps much earlier in the processes. In turn, this can mean lower data hosting costs as objectively non-responsive data can be jettisoned prior to data hosting. The ability of big data analytics platforms to support the velocity of data change also enables counsel and reviewers to be more agile and evolve alongside the constantly changing landscape of the discovery itself (e.g., changes in scope, custodians, responsive criteria, court deadlines).4. The veracity, or uncertainty of dataWithin the eDiscovery realm, the veracity of data refers to the quality of the data (i.e., whether the data that a party collects, processes, and produces is accurate and defensible and will satisfy a discovery request or subpoena). The veracity of the data produced to the opposing side in a litigation or investigation is therefore of the utmost importance, which is why data quality control steps are key at every discovery stage. At the preservation and collection stages, counsel must verify which custodians and data sources may have relevant information. Once that data is collected and processed, the data must then be checked again for accuracy to ensure that the collection and processing were performed correctly and there is no missing data. Then, as data is culled, reviewed, and prepared for production, multiple quality control steps must take place to ensure that the data slated to be produced is relevant to the discovery request and categorized correctly with all sensitive information appropriately identified and handled. As data volumes grow, ensuring the veracity of data only becomes more daunting.Thankfully, big data analytics technology can also help safeguard the veracity of data. Cutting-edge AI technology can provide a big-picture view of an organization’s entire legal portfolio, enabling counsel to see which custodians and data sources contain data that is consistently produced as relevant (or, in the alternative, has never been produced as relevant) across all matters. It can also help identify missing data by providing counsel with a holistic view of what was collected in past matters from data sources. AI-based analytics tools can also help ensure data veracity on the review side within a single matter by identifying the inevitable inconsistencies that happen when humans review and categorize documents within large volumes of data (i.e., one reviewer may categorize a document differently than another reviewer who reviewed an identical or very similar document, leading to inconsistent work product). Newer analytics technology can more efficiently and accurately identify those inconsistencies during the review process so that they can be remedied early on before they cause problems. Big Data Analytics-Based MethodologiesAs shown above, AI-based big data analytics platforms can help counsel manage growing data volumes in eDiscovery.For a more in-depth look at how a cutting-edge analytics platform and big data methodology can be applied to every step of the eDiscovery process in a real-world environment, please see Lighthouse’s white paper titled “The Challenge with Big Data.” And, if you are interested in this topic or would like to talk about big data and analytics, feel free to reach out to me at KSobylak@lighthouseglobal.com.ai-and-analytics; ediscovery-reviewcloud, analytics, ai-big-data, ediscovery-process, prism, blog, ai-and-analytics, ediscovery-reviewcloud; analytics; ai-big-data; ediscovery-process; prism; blogkarl sobylak
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Big Data and Analytics in eDiscovery: Unlock the Value of Your Data
The current state of eDiscovery is complex, inefficient, and cost prohibitive as data types and volumes continue to explode without bounds. Organizations of all sizes are bogged down in enormous amounts of unresponsive and duplicative electronically stored information (ESI) that still make it to the review stage, persistently the most expensive phase of eDiscovery.Data is at the center of this conundrum and it presents itself in a number of forms including:Scale of Data - In the era of big data, the volume, or amount of data generated, is a significant issue for large-scale eDiscovery cases. By 2025, IDC predicts that 49 percent of the world’s stored data will reside in public cloud environments and worldwide data will grow 61 percent to 175 zettabytes.Different Forms of Data - While the volume of ESI is dramatically expanding, the diversity and variety are also greatly increasing, and a big piece of the challenge involved with managing big data is the varying kinds of data the world is now generating. Gone are the days in eDiscovery where the biggest challenge was processing and reviewing structured, computer-based data like email, spreadsheets, and documents.Analysis of Data - Contending with large amounts of data creates another significant issue around the velocity or speed of the data that’s generated, as well as the rate at which that data is processed for collection and analysis. The old approach is to put everything into a database and try to analyze it later. But, in the era of big data, the old ways are expensive and time-consuming, and the much smarter method is to analyze in real time as the data is generated.Uncertainty of Data - Of course, with data, whether it’s big or small, it must be accurate. If you’re regularly collecting, processing, and generally amassing large amounts of data, none of it will matter if your data is unreliable or untrustworthy. The quality of data to be analyzed must first be accurate and untainted.When you combine all of these aspects of data, it is clear that eDiscovery is actually a big data and analytics challenge!While big data and analytics has been historically considered too complex and elaborate, the good news is that massive progress has been made in these fields over the past decade. Access to the right people, process, and technology in the form of packaged platforms is more accessible than ever.Effective utilization of a robust and intelligent big data and analytics platforms enable organizations to revamp their inefficient and non-repeatable eDiscovery workflows by intelligently learning from past cases. A powerful big data and analytics tool utilizes artificial intelligence (AI) and machine learning to create customized data solutions by harvesting data from all of a client’s cases and ultimately creating a master knowledge base in one big data and analytics environment.In particular, the most effective big data and analytical technology solution should provide:Comprehensive Analysis – The ability to integrate disparate data sources into a single holistic view. This view gives you actionable insights, leading to better decision making and more favorable case outcomes.Insightful Access – Overall and detailed visibility into your data landscape in a manner that empowers your legal team to make data-driven decisions.Intelligent Learnings – The ability to learn as you go through a powerful analytics and machine learning platform that enables you to make sense of vast amounts of data on demand.One of the biggest mistakes organizations make in eDiscovery is forgoing big data and analytics to drive greater efficiency and cost savings. Most organizations hold enormous amounts of untapped knowledge currently locked away in archived or inactive matters. With big data and analytics platforms more accessible than ever, the opportunity to learn from the past to optimize the future is paramount.If you are interested in this topic or just love to talk about big data and analytics, feel free to reach out to me at KSobylak@lighthouseglobal.com.ai-and-analytics; ediscovery-reviewai-big-data, blog, ai-and-analytics, ediscovery-reviewai-big-data; blogkarl sobylak
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Best Practices for Embracing the SaaS eDiscovery Revolution
It’s an exciting time in the world of legal tech as SaaS eDiscovery solutions, and cloud computing in general, represent an enormous amount of potential with nearly unlimited capacity of storage, power, and scalability, whether you’re handling small or very large matters. Once seen as something only big firms need to deal with for large cases, we’ve seen electronic communication in the workplace (like email and chat) become the norm and consequently eDiscovery become a typical domain for law firms of all shapes and sizes. It makes perfect sense that the proliferation of an easy-to-use, cost-effective solution is the future for an industry right on the cusp of its next iteration.So you’re ready to embrace this next era of eDiscovery and you’ve decided to adopt a SaaS, self-service, spectra tool within your firm? In my previous blog, I outlined three top reasons why SaaS makes the most sense for law firms in the age of cloud storage, especially as new and improved self-service, spectra tools incorporate the latest technology, are easy to use, and have significantly improved the efficiency of the typically arduous and expensive on-prem eDiscovery process.But transitioning even some of your firm’s in-house eDiscovery process to a SaaS solution requires careful thought around the complexities involved with security, solution support, and business continuity. To make the transition to SaaS as smooth as possible, it’s important to tailor your solution to your specific environment and create an implementation plan that will set you up for success. Here are a few suggestions for best practices to consider when you’re ready to embrace the self-service, spectra, SaaS eDiscovery revolution and leave your cumbersome on-prem environment behind.Eliminate your on-prem applications and infrastructure. Many firms have a patchwork of on-prem tools that they use for different phases of their eDiscovery workflow. A great starting point to eradicating the expense, headache, and risk that comes with maintaining your own infrastructure is to get rid of those old on-prem applications altogether and start fresh with a SaaS tool that will handle your entire workflow. That means choosing one comprehensive tool that allows you to create, upload, and process matters while also enabling you to manage your users across matters and locations from a single place. You’ll not only eliminate administrative headaches, you’ll no longer have to worry about managing data and will be free to concentrate on analyzing data while your SaaS solution provider takes on the security and infrastructure management for you.Leverage best-of-breed tools. A common problem for consumers of on-prem eDiscovery software has been needing to pull together multiple technologies to process, review, perform analytics, and produce data. While you’ve been working with that complicated patchwork of tools you’ve licensed and tried to maintain within your own IT environment, new versions of best-of-breed tools have evolved for everything from processing to analytics to review and production. Now that you’ve chosen one SaaS tool that can handle your full eDiscovery workflow, your new tool should provide you with access to the most updated and advanced tools across the EDRM without any maintenance or upgrades ever needing to be managed on your end.Ensure your solution is supported. Once you’re on board with a streamlined eDiscovery workflow with no infrastructure risks or administrative headaches and access to the most modern and best available eDiscovery tools, what happens when a matter becomes too large or unwieldy or you simply need access to a more traditional full-service support model? In this case, make sure you’re set up with a SaaS tool that is supported by a solution provider who can easily transition you from that self-service, spectra, on-demand eDiscovery model to one where they can take over when you need them to. In addition, speed to implementation is something to consider. While on-prem systems can take months to actually install and implement, a self-service, spectra, SaaS tool can literally be up and ready to use within days.Now that you’ve made the smart decision to modernize your eDiscovery program and implement a self-service, spectra, SaaS solution, it’s time to use these best practices to eliminate your expensive and risky infrastructure, streamline your workflow, adopt the most advanced best-in-breed tools, and benefit from a self-service, spectra tool that’s also backed with the peace of mind of full support from your solution provider. ediscovery-review; ai-and-analyticscloud, self-service, spectra, blog, ediscovery-review, ai-and-analyticscloud; self-service, spectra; bloglighthouse
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Automation of In-House Legal Tasks: How and Where to Begin
Legal operations departments aim to support the delivery of legal services in an efficient manner. To that end, resource management and solving problems through technology are core responsibilities of the department. But, the tasks of a legal department vary from answering legal phone calls, filing patents, reviewing and approving contracts, and litigating, just to name a few. With such a varied workload, what to automate can be difficult to identify. To help, I have put together a brief overview of where to start.Step 1: IdentificationStart by identifying the tasks that are repetitive. One of the best ways I have found to do this is to set up a quick 15-minute discussion with 3-5 representatives from different functional areas of your legal team, and from different levels (e.g. individual contributor, manager, function head). In that meeting, ask them one or all of the following questions:What tasks do you wish your team no longer had to do?What tasks do you want to be replaced by robots in the future?What tasks are low value but your team still spends a lot of time on?You should not spend too much time here – the goal is to identify a pretty quick list that is top of mind for people. From these interviews, create a list for further vetting. Just in case you come up empty handed or aren’t able to get time with people within legal, here is a list of items that are commonly automated and we would expect to come up:Contract Automation Self service retrieval of boilerplate contracts (e.g., NDAs) Self service building common contracts (e.g., clause selection for vendor contracts, developer agreements)Request for review, negotiation, and signature of other contractsLegal Team Approvals Marketing document approvals Budget approval for any legal team spend Legal Assistance Requests (Intake) Legal research request Legal advice on an issue neededNeed for outside counselPatent Management Alerts for filing and renewal deadlines Automatically manage workflow for submissionsSelect one or two items from your list and then validate it with your boss and/or general counsel. You want to understand whether others agree on the impact automation will make and identify any potential concerns.Step 2: Build vs. BuyWhether to purchase third-party software or build your own internally is always a good question to start with. Building your own tool gives you exactly what you want with, oftentimes, very little need to change your process. But, it is more resource-intensive both for the build and the maintenance. Buying off the shelf software limits you in what’s commercially available but it takes all the load off your development resources.For some, build or buy may be an easy question as they may not have access to development resources. For others, they may not have any budget for an external tool and/or may be required to use internal teams. For most, however, they fall in the middle and have some access to resources and some budget (but usually not enough of either – that’s a whole other topic).If you fall into this latter category, you will have to analyze your options. Your organizational culture will dictate what depth of analysis is needed. Regardless of the level of detail, the process is the same. The easiest place to start is by surveying what is commercially available. Even if you decide to build, knowing what software is out there, what features are available, and the general costs is helpful. Next, it is helpful to get an approximate cost of the build and maintenance if done internally. This can be a rough order of magnitude based on estimates from other internal tools developed or can be a more detailed estimate developed with the engineering team. Once you have the costs, you will want to add some information about the pros and cons of each solution – e.g., time to build and implement, technology dependencies (if known), other considerations (e.g., we are moving to the cloud in 6 months and we don’t know impact). Once you have this analysis, you can put forth a recommendation to your boss and whomever else is required to decide on how to proceed.Step 3: DesignNow that you have a decision, you can move on to design. This is the most critical stage as this is where you are determining exactly what results your automation will produce. The first thing to do here is to map out your current internal process including who does what. You want to make sure you have a representative of each group take a look at the process diagram and validate it.Once you have the process in place, you’re ready to work with the development team. If you are buying a solution for automation, you should be working closely with the software provider’s onboarding team to overlay your current process with the capabilities of the software. You will want to note where the software does not support your process and where changes will need to be made. If you adjust your process, be sure to involve the same representatives that helped with the initial diagram to provide feedback on any proposed changes in the process.If you are building the solution, you will meet with your internal product resource. This person (or people) will want to understand the process diagram and may even want to watch people go through the process so they can understand user behavior. They will then likely convert your diagram into user stories that developers will develop against. Make sure to be as specific as possible in this process. This resource will be the one representing your voice with the developers so you want them to really understand the nuances of the process.Expect some iteration back and forth during this stage and although I have simplified it here, this will be a long stage and the most important.Step 4: ImplementationThe final stage of the process is implementation. Start with a pilot of the automation. Either select a small use case or a small group of users and validate that your automation functions as planned. During this pilot project, it is really helpful to have resources from your software providers or from the development team readily available to make changes and help answer questions. During this pilot, you should also keep track of how the automation is performing versus your expectations. For example, if you expected it to save time, create a way to track the time it saves and report on that metric.After a successful pilot and necessary refinement, you can move on to your full rollout. Create a plan that includes the deployment of the technology, training, feedback, and adjustment. Make sure to also identify the longer-term maintenance strategy that includes continuing to gather feedback and ways to improve the automation over time.There are lots of great publications that go into further detail about each of the steps above, but hopefully this points you in the right direction. Once deployed, automation can be a very powerful tool that augments your team without adding additional FTEs.To discuss this topic more, please feel free to reach out to me at DJones@lighthouseglobal.com.legal-operations; ai-and-analyticslegal-ops, blog, legal-operations, ai-and-analyticslegal-ops; bloglighthouse
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Beyond HIPAA: Protecting Private Data in Healthcare Fraud Matters
When it comes to data privacy in healthcare fraud investigations and litigation, there is more than HIPAA to consider. Fraud investigations and litigation in the healthcare industry are growing. Whether these matters are handled internally or involve external parties to produce to, increased regulatory scrutiny — coupled with vast amounts of data generated by healthcare organizations — has created a pressing need for such organizations to become more adept at comprehensively inventorying, accessing, and reviewing internal data sources for potential fraud.A perennially tricky issue, and one that is just getting thornier, concerns how to treat sensitive, private data in a healthcare context. Healthcare organizations need to be mindful not only of carefully managing protected health information (PHI) subject to the Health Insurance Portability and Accountability Act (HIPAA), but also protected consumer information, which is now subject to regulations such as the California Consumer Privacy Act. Challenges and costs related to being compliant with these regulations are growing and setting themselves up to be just as substantial as managing privilege in litigation.Healthcare data: What privacy rules apply?To make sure these new compliance requirements do not inadvertently extend timelines or burn through budgets, those managing healthcare fraud matters need to proactively take stock of which regulatory regimes concerning personal data are applicable in their case and what data sets being reviewed in their matter could potentially have personal data subject to regulation.Now there is certainly a gray area in distinguishing between protected health information and protected consumer information in a healthcare context. Technically, information is PHI (and therefore subject to HIPAA) if it is created or received by a healthcare provider or health plan. But in today’s data-driven environment, there are a variety of touchpoints between consumers and healthcare services (e.g., marketing data analytics, customer service records, fitness app logs, fringe benefit tracking) that defy traditional understandings of what exactly differentiates PHI from a broader pool of potentially protected consumer data.So, whether subject to HIPAA or CCPA or other privacy mandates, healthcare companies nowadays need to be able to track potentially protected information across all of their data sources, including those not traditionally considered sensitive in that they do not contain information such as health histories, lab test results, or medical bill information.Healthcare fraud: Muddying the data privacy watersThe nature of healthcare fraud further complicates an approach to identifying and appropriately treating sensitive personal data. Matters related to false claims, physician self-referral, Medicaid/Medicare fraud, improper kick-backs, or non-compliant contract and billing practices (to name a few), most often require delving into internal email communications to understand to what extent a fraudulent pattern exists within the organization under investigation, thus enlarging the data pool subject to privacy mandates.The internal work of sorting out billing and coding issues is a messy affair that involves relaying a variety of details of specific patient treatment across multiple related emails. Methodically tracking how these questions get resolved internally over time is at the heart of good healthcare fraud investigation and litigation practice. And carefully treating the sensitive data involved in these conversations is a responsibility that comes with it. If, for instance, you are relying on techniques to extract personal data that have only been tested on structured electronic medical records, you will be missing data that is potentially protected in relevant email discussions.Similar to the task of finding potentially privileged information in large document sets, identifying and treating personal data in healthcare fraud requires its own dedicated workflow, leveraging a mix of tools and methods. The key to successful identification and treatment of protected personal data is being deliberate about the process you design and implement, and specific about the tools you are integrating into it.data-privacyblog, data-privacybloglighthouse
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Biden Administration Executive Order on Promoting Competition: What Does it Mean and How to Prepare
On July 9, 2021, President Biden signed a sweeping new Executive Order (“the Order”) with the stated goal of increasing competition in American markets. Like the recently issued Executive Order on Improving the Nation’s Cybersecurity, the Executive Order on Promoting Competition in the American Economy is meant to establish “a whole-of-government” approach to tackle an issue that is typically handled by numerous federal agencies. As such, the Order includes 72 initiatives touching more than a dozen federal agencies and numerous industries, including healthcare, transportation, agriculture, internet service providers, technology, beer and wine manufacturing, and banking and consumer finance.Notably, the Order calls on the Department of Justice (DOJ) and Federal Trade Commission (FTC) to “vigorously” enforce antitrust laws and “reaffirms” the government’s authority to challenge past transactions that may have been in violation of antitrust laws and regulations (even if they were not challenged by previous Administrations). The remainder of this blog will broadly outline the contents of the Order and conclude with a brief summary on possible ramifications for organizations undergoing merger and acquisition activity (as well as the law firms that counsel them) and how to prepare for them.What is in the Executive Order on Promoting Competition in the American EconomySection 1: PolicyThis section broadly outlines the benefits of “robust competition” to America’s economy and asserts the U.S policy of promoting “competition and innovation” as an answer to the rise of foreign monopolies and cartels. This section also announces the Administration’s policy of supporting “aggressive legislative reforms” to lower prescription drug prices and supports the enactment of a public health insurance option.Sec. 2: The Statutory Basis of a Whole-of-Government Competition Policy This section outlines the antitrust laws which form the Administration’s whole-of-government anti-competition policy, including the Sherman Act, the Clayton Act, and the Federal Trade Commission Act, as well as fair competition and anti-monopolization laws, including Packers and Stockyards Act, Federal Alcohol Administration Act, the Bank Merger Act, and others.Sect 3: Agency Cooperation in Oversight, Investigation, and RemediesThis section outlines the Administration’s policy of cooperation between agencies on anti-competition issues, stating that when there is overlapping jurisdiction over anticompetitive conduct and mergers, the involved agencies should “endeavor to cooperate fully in the exercise of their oversight authority” to benefit from the respective expertise of the agencies and to improve Government efficiency.Section 4: The White House Competition Council This section establishes a White House Competition Council to “coordinate, promote, and advance” government efforts to address monopolies and unfair competition. The section also mandates that the Council should work across agencies to provide a coordinated response to monopolization and unfair competition and outlines the Council make up and meeting cadence.Section 5: Further Agency Responsibilities This section mandates that the heads of all agencies must “consider using their authorities” to further the anti-competition policies outlined within the Order, and “encourages” relevant positions and heads of agencies (including the Attorney General, Chair of the Federal Trade Commission (FTC), Secretary of Commerce, and others) to enforce existing antitrust laws “vigorously,” as well as review and consider revisions to other laws and powers, including encouragement to:Enforce the Clayton Act and other antitrust laws “fairly and vigorously.Review merger guidelines to consider whether they should be revised.Revise positions on the intersection of intellectual property and antitrust laws.Review current practices and adopt a plan for the revitalization of merger oversight under the Bank Merger Act and the Bank Holding Company Act of 1956.Consider whether to revise the Antitrust Guidance for Human Resource Professionals of October 2016.Consider curtailing the unfair use of non-compete clauses that may unfairly limit worker mobility.Consider rulemaking in other areas such as: Unfair data collection and surveillance practices that may damage competition, consumer autonomy, and consumer privacy; Unfair anticompetitive restrictions on third-party repair or self-repair of items (aimed at restrictions that prevent farmers from repairing their own equipment);Unfair anticompetitive conduct or agreements in the prescription drug industries;Unfair competition in major Internet marketplaces;Unfair occupational licensing restrictions;Unfair exclusionary practices in the brokerage or listing of real estate; andAny other unfair industry-specific practices that substantially inhibit competition.The section also calls upon the Secretary of Agriculture to address the unfair treatment of farmers and improve competition in the markets for farm products, and for the Secretary of the Treasury to assess the conditions of competition around the American markets for beer, wine, and spirits (including improving the market for smaller, independent operations).Notably, this section also calls for the Chair of the Federal Communications Commission to consider adopting “Net Neutrality” rules and other avenues to promote competition and lower prices across the telecommunications ecosystem.Finally, the section also calls for the Secretary of Transportation to protect consumers and improve competition in the aviation industry, including enhancing consumer access to airline flight information, providing consumers with more flight options at better prices, promoting rulemaking around requiring airlines to refund baggage fees, and address the failure of airlines to provide timely refunds for flight cancellations resulting from the COVID-10 pandemic.ConclusionAs a whole, the result of this Order will be that organizations undergoing mergers and acquisition activity can expect to face more scrutiny from the government – and that law firms that provide counsel for those types of transactions can expect that government investigations of those activities (like HSR Second Requests) will be more in-depth and meticulous. Accordingly, any law firms and organizations preparing for those types of investigations would do well to evaluate their eDiscovery technology now, in order to ensure that they are using the best and most up-to-date legal technology and workflows to help locate the data requested by the government more accurately and efficiently.antitrustprism, blog, antitrustprism; blog; antitrustsarah moran
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Is 2023 the Tipping Point for AI Adoption in Legal?
Generative AI. Bard. Bing AI. Large language models. Artificial intelligence continues to dominate headlines and workplace chats across every industry since OpenAI’s public release of ChatGPT in November of 2022. Nowhere was this more evident than at this year’s Legalweek event. The annual conference, which gathers thousands of attorneys, legal practitioners, and eDiscovery providers together in New York City, was dominated by discussions of ChatGPT and AI. This makes sense, of course. Attorneys must understand how major technology shifts will impact their clients or companies—especially those in eDiscovery and information governance who deal with corporate data and its challenges. But there was a slight twist to the discussions about ChatGPT. In addition to the possible impacts and risks to clients who use the technology, there was just as much, if not more, focus on how it could be used to streamline eDiscovery.The idea of using a tool released to the public less than four months ago seems almost ironic in an industry with a reputation for slowly adopting technology. Indeed, a 2022 ABA survey showed that as few as 19.2% of lawyers use predictive coding technology (i.e., technology assisted review or TAR) for document review, up from just 12% in 2018. Even surveys dominated by eDiscovery software providers showed TAR was being used on less than 30% of matters in 2022. Given that the technology behind traditional TAR tools has existed since the 1970s and the use of TAR has been widely accepted (and even encouraged) by court systems around the world for over a decade, these statistics are strikingly low.So, what is driving this recent enthusiasm in the industry around AI? The accessibility and generative results of ChatGPT is certainly a factor. After all, even a child can quickly learn how to use ChatGPT to generate new content from a simple query. But the recent excitement in eDiscovery also seems to be driven by the significant challenges attorneys are encountering:Macroeconomic volatility and unpredictability have been a near constant stressor for both corporate legal departments and law firms. Legal budgets are shrinking, and layoffs have plagued almost every industry, leaving legal teams to do the same volume of work with fewer resources.Corporate legal teams are being pressured to evolve from a cost center to one that generates revenue and savings, while attorneys at law firms are expected to add value and expertise to all sectors of a company’s business, beyond the litigation and legal sectors they’ve traditionally operated in. And all attorneys are facing increasing demand to become experts in the risks and challenges of the ever-evolving list of new technology used by their clients and companies.New technology is generating unprecedented volumes of corporate data in new formats, while eDiscovery teams are still grappling with better ways to collect, review, and produce older data formats (modern attachments, collaboration data, text messages, etc.) In short, even the most technology-shy attorneys may be finding themselves at a technology “tipping point,” realizing that it is impossible to overcome some of these challenges without leveraging AI and other forms of advanced technology. But while the challenges may seem grim, there is an inherent hopefulness in this moment. The legal industry’s tendency to adopt AI technology more slowly than other sectors means there’s ample opportunity for growth. Some forward-thinking legal teams, with the help of eDiscovery providers, have already been leveraging advanced AI technology to substantially increase the efficiency and accuracy of eDiscovery workflows. This includes tools that utilize the technology behind ChatGPT, including large language models and natural language processing (NLP). And unlike ChatGPT, where privacy concerns have already been flagged regarding its use, existing AI solutions for eDiscovery were developed specifically to meet the stricter requirements of the legal industry—with some already overcoming tough scrutiny from regulators, opposing counsel, and courts. In other words, the big eDiscovery question of 2023 may not be, “Can ChatGPT revolutionize eDiscovery in the future?” but rather, “What can advanced AI and analytic tools do for eDiscovery practitioners right now?” While the former is up for debate, there are definitive answers to the latter threaded throughout many of the other major industry discussions happening now. Some of those discussions include:If you want to go far, go together Today’s larger and more complicated data volumes often make the traditional eDiscovery model feel like the proverbial round hole that the square (data) peg was not designed to fit into. And it’s becoming increasingly expensive for legal teams to try to do so. To operate in this new era, it’s essential to work with partners who can help you meet your data needs and align with your goals. A good example is when an in-house legal team partners with a technology-forward law firm and eDiscovery provider to build a more streamlined and modern eDiscovery program. This kind of partnership provides the resources, expertise, and technology needed to take a more holistic approach to eDiscovery—breaking away from the traditional model of starting each new matter from scratch. These teams can work together to create and deploy tools and expertise that reduce costs and improve review outcomes across all matters. For example, customized AI classifiers built with data and work product from the company’s past matters, cross-matter analytics that identify review and data trends, and tailored review workflows to increase efficiency and accuracy for specific use cases. This partnership approach is a microcosm of how different organizations and teams can work together to overcome common industry challenges. Technology that meets us where we areDespite all the chatter around ChatGPT, there is currently no “easy AI button” to automate the document review process. However, modern eDiscovery technology (including advanced AI) can be integrated into almost every stage of the document review process in different ways, depending on a case team’s goals. This technology-integrated approach to eDiscovery workflows can help case teams achieve unprecedented efficiency and review accuracy, mitigate risks of inadvertently producing sensitive documents, minimize review redundancy across matters, and quickly pull out key themes, timelines, and documents hidden within large data volumes. Technology-forward law firms and managed review partners can help case teams integrate advanced technology and specialized expertise to achieve these goals in a defensible way that works with each company’s existing data and workflows. The only constant is change The days of a static, rarely updated information governance program are gone. The nature of cloud data, the speed of technology evolution and adoption, and the increasingly complex patchwork of data privacy and security regulations mean that legal and compliance teams need to be nimble and ready for the next new data challenge. New generative AI tools like ChatGPT may only add to this complexity. While this type of technology may be largely off limits in the near future for eDiscovery providers and law firms due to client confidentiality, data privacy, and AI transparency issues, companies in other industries have already begun using it. Legal and compliance teams will need to ensure that any new data created by generative AI tools follow applicable data retention guidelines and regulations and begin to think through how this new data will impact eDiscovery workflows.The furor and excitement over the potential use cases for ChatGPT in eDiscovery are a hopeful sign that more legal practitioners are realizing the potential of AI and advanced analytic technology. This change will help push the industry forward, as more in-house teams, outside counsel, and eDiscovery providers partner together to overcome some of the industry’s toughest data challenges with advanced technology.For other stories on practical applications of AI and analytics in eDiscovery, check out more Lighthouse content. lighting-the-way-for-review; ai-and-analytics; lighting-the-path-to-better-reviewai-big-data, blog, ai-and-analytics,ai-big-data; blogsarah moran
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IT at the Helm: Change Management for Cloud-Based SaaS is Key to Minimizing Risk
Cloud computing dates to the mid-1990s – so why is this relatively old concept still such a hot topic? Haven’t we figured it all out by now? And isn’t the benefit of today’s SaaS cloud environments that someone else, namely the SaaS provider, handles software management? What else is there to figure out? Having spent the last several months talking to legal, compliance, and IT professionals about their Microsoft 365 environments, I am confident that there is still a lot that corporate IT departments are grappling with. In fact, a recent survey conducted by Lighthouse of 106 IT managers and executives found that although most organizations had a change management process in place for on-premises feature updates and upgrades, and most organizations planned to have change management in place for enterprise-wide SaaS technology updates in the next five years, only 16% had something in place today.[1] To better harness this technology as it continues to evolve and to minimize risks along the way, it’s important to understand why these change management gaps exist, what their impact is, and how legal and IT teams can work together in new ways to close them.Managing the Evolution of SaaSThe adoption of enterprise SaaS cloud technologies has only become prevalent in the last decade and growth has skyrocketed over the last couple of years. In fact, Microsoft 365 had 23.1 million consumer subscribers five years ago (Fiscal Year 2016) and that number has grown to 58.4 million. As such, IT organizations have not had to support SaaS enterprise offerings at scale until very recently and today most IT departments are supporting both on-premises and SaaS cloud environments. The first priority in supporting this explosive adoption was to implement and migrate over to the new system. It is only recently that focus has shifted toward governance and processes around these systems.Even with a newer focus on process, one of the touted benefits of SaaS cloud technology is less maintenance and software support by the in-house IT team. Of course, there is the need to set up process to resolve user questions and to ensure systems have been set up to facilitate the business running properly. But, planning and executing hardware or software upgrades is mostly managed by a third-party provider so there is not an urgent need to set up robust change management. In addition, the old change management process where major developments are analyzed, tested, and timed for deployment to desktops still applies to Microsoft 365.However, using the old process for new applications can have drawbacks. First, not all updates that Microsoft or others make are configurable updates where there is a choice on how, and whether, to implement. Second, if users are logging into a web environment (as opposed to desktop apps), IT teams don’t necessarily have control over the version their users are utilizing. Finally, given that most organizations have differing levels of IT permissions, meaning some groups are upgraded sooner than others, teams must move quickly to handle unpredictable and varied update schedules. With the speed and variability of new feature updates, the old process may not be agile enough to handle them. The differences between SaaS and on-premises environments (where you have full control of the upgrade schedule) can leave some gaps even when organizations review, analyze, and test the roadmap and updates from the Microsoft Message center.The old process often fails to prepare the business for these changes because IT, legal, and other teams are not always communicating about the broader risk or implementation implications. Because the IT team is focused on availability and scalability, it often misses how certain changes can introduce business risks outside of their ken. Solely relying on IT professionals to determine the broader impact of updates can mean that business, regulatory, and other risks outside of IT’s awareness are overlooked.Measuring the Impact of UpdatesWhether these management gaps are tolerable is a risk decision that each organization must make—one that can put the user experience in tension with a developed IT process. In discussions with legal, compliance, and information governance professionals that focus on SaaS services, handling the cadence and speed of these updates is a concern that keeps them up at night. But, quickly providing users new features has considerable benefits for the business too. It’s important for IT to prioritize ensuring that users can access their business data and that the business can continue without interruption over cumbersome update management.When weighing these risks and benefits it’s important to fully appreciate their potential impacts. An example of where these priorities conflict is highlighted in a change around Microsoft Teams meeting transcripts. In March 2021, Microsoft made an update that allows for a live transcript of certain Teams meetings. In November 2021, Microsoft expanded that functionality to Teams Channel meetings and upgraded the features of live transcripts to include name attribution to the speaker. This is helpful functionality for users and, given that it is an automatic upgrade, there may be little to do from an IT perspective. From a risk and legal perspective, however, there are a couple of key considerations. First, where is the transcript stored after the meeting and do retention policies apply? Second, is the data subject to ongoing regulatory or litigation requests and how is it accessed? The answers to those questions are complicated by the fact that the location of the data depends on whether a user downloaded the transcript after the meeting. Many IT organizations caught this change by reviewing the Microsoft Message center for updates—and in doing their own testing they determined that disabling the functionality was the best course of action. This was an update with obvious data ramifications that outweighed the potential benefits in a risk assessment from both IT and legal. For updates that are less obvious, IT may not have consulted legal. For updates where the value to users may seem to outweigh the risk, where the risks aren’t initially apparent, or when there are no configuration options—IT may have a more challenging decision to make.Reimagining a Change Management ProcessHaving a cross-functional framework in place to discuss and implement these types of updates is key to managing changes. Many organizations have some sort of accountability in place around updates—an individual or group of people are responsible for reviewing the Microsoft Message center. Although this structure is lower in cost and requires fewer resources, it has a few drawbacks. First, if only IT is involved, you may have only one perspective on the impacts of updates and that can be too narrow to determine the effects on the broader business. Second, many organizations do not have a tracking mechanism to determine what Microsoft updates they have read, evaluated, tested, and taken action against. With dozens of messages, many of which don’t need action, it is easy to lose track of what has been evaluated. Finally, if there isn’t clear accountability with dedicated resources the process can lose legitimacy and fail. Organizations who choose to minimize their business risk do not have to put in place a heavy structure to manage updates. In fact, the process around on-premises software upgrades can easily be adapted to the cloud situation.The single most important thing that an IT team can do for an effective SaaS support practice is to adapt and enforce existing change management and organizational controls. More specifically, IT organizations should consider:Dedicating a resource to track and review changes from service and cloud providers to ensure updates and changes are properly evaluated for risk and business continuity.Relying on a robust change management system with stakeholders throughout the organization to provide clearly articulated approval, risk identification, testing, and risk management.Partnering with your compliance team to ensure adherence to governance frameworks, organizational commitments, and client requirements. The compliance function is trained to manage risk and is uniquely chartered with authority and independence with a company’s governing body.Collaborating with legal. Lawyers are trained to spot issues and manage risk for the entire business. Often times, individual departmental stakeholders are responding to team-level incentives. Legal teams are also learning to adapt their governance structures to evolving cloud solutions.Leveraging the Project Management Office to ensure that stakeholders and risks are identified at the start of any specific project (i.e., measure twice, cut once).One of the most effective ways to get the right stakeholders’ input is to create a Change Approval Board (“CAB”) with subject matter experts from every business group to meet on a periodic basis. The CAB provides a framework that ensures IT has input from across the business while still giving it the opportunity to own and manage the support of the software.One of the benefits of SaaS technologies is the ability to utilize and optimize with the newest features and to take some of the hardware management burden off IT. By putting in place a cross-functional team to review and manage the update process, you can mitigate your organizational risk while allowing users take full advantage of the benefits.[1] In February 2022, Lighthouse surveyed 106 IT managers or above who had Microsoft on-premises and now have Microsoft 365. The survey found that only 16% had implemented a change management process for M365 and 62% of organizations planned to implement one in the next 5 years.microsoft-365; chat-and-collaboration-data; information-governancemicrosoft, cloud-migration, cloud-services, blog, microsoft-365, chat-and-collaboration-data, information-governance,bloglighthouse
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All Aboard! Best Practices for Standardizing and Socializing Your eDiscovery Program
Standardizing your eDiscovery program can be a huge benefit to you and your team. With a well-rounded program, you are able to pressure test and layer in repeatable and trackable processes at each stage of the EDRM. This will result in a lower overall cost of eDiscovery and the ability to more accurately forecast spend from matter to matter. Your program will reduce risk, and increase quality, efficiency, and consistency. You will also have the advantage of program-wide metrics and analysis, leading to knowledge that will empower you to make better and more informed litigation and investigation decisions early on, which in turn leads to better outcomes and greater defensibility. Finally, with your program-wide data tracking you will be able to showcase true ROI and other key metrics. It sounds pretty good, right? So, why doesn’t everyone standardize their eDiscovery program? It can be a challenge. There are several hurdles that one may face when trying to socialize and drive the adoption of their program. For example, lack of alignment across key stakeholders and the challenges of trying to build a program while also managing the pressures of ongoing litigation deadlines. You may also have to invest more time and potentially more cost upfront, which can be a resourcing challenge, and you may have to redefine efficiency across multiple teams. Managing expectations across key stakeholders is critical to building a successful program. Change doesn’t happen overnight.How do you go about overcoming these challenges and standardizing your program? I’ve summarized some tips and best practices below for socializing, implementing, and getting your eDiscovery program to be accepted as the standard both within your organization and beyond.Getting StartedTo begin, build one thing at a time. It is important not to bite off more than you can chew. Start with one project, implement it, and carefully review the results. If it is successful, drive adoption internally, and once it is adopted you can get started on the next project or piece of the program. Be sure all of your key stakeholders are involved early on and set up weekly or even monthly strategy sessions with these stakeholders to ensure that everyone has a seat at the table and a voice in program development decisions. Finally, documentation is your single source of truth. Be sure to think about what you are documenting, where you are storing it, when it should be evaluated for updates, and how it will be circulated after these updates are made. More on driving a successful eDiscovery project can be found in this article, Staying on Pointe: Key Lessons eDiscovery Professionals can Learn from Ballet.Ensuring the Right AudienceAs I mentioned above, you need to be sure to involve all key stakeholders when driving the standardization of your eDiscovery program, but how do you make sure you have the right audience? It is different for everyone and will depend on your organization. Typically, I would recommend that you involve your legal operations and finance teams, as well as any other teams with eDiscovery stakeholders. Once you have these folks identified, set up that recurring strategy meeting.Showing ROIWhen it comes to showing ROI you want to be sure to pick what will make an impact within your company. Whether that be risk reduction, cost reduction, efficiency gains, or something else, you want to focus on what matters at your organization. This is where the documentation I mentioned above comes into play. Be sure you are tracking the metrics and results you would like to report on and format them in graphs, charts, and high-level stats that your key stakeholders can take away and share with their teams. Lean on your providers to help you pull metrics and come up with creative ways to display ROI across your program. It is also important to note that your ROI focus may shift over time, so be sure to remain flexible and check-in with leaders on a bi-annual or annual cadence.Socializing & Driving AdoptionSo, you know how to get started, who to involve, and how to show ROI, but how do you socialize and drive adoption? This is the hardest part and will require flexibility. It is important not to design and drop. You have to continue to reiterate the program and processes consistently. Document your processes, track your results, and make sure you build in a regular feedback loop. Ensure you have support from the right people. This can include your internal teams, outside counsel, vendor(s), etc., and can vary depending on your organization. Be open to feedback and revisions as they come along, document those updates, and share them out.To summarize, when looking to standardize and socialize your eDiscovery program, remember to:involve the right folks early on;build one thing at a time;document the processes;show meaningful ROI; andbe open to feedback - a successful program evolves!To discuss this topic further, please feel free to continue the discussion by emailing me at SBarsky-Harlan@lighthouseglobal.com.ediscovery-review; legal-operationsediscovery-process, blog, ediscovery-review, legal-operationsediscovery-process; blogsarah barsky harlan
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AI and Analytics: Reinventing the Privilege-Review Model
Identifying attorney-client privilege is one of the most costly and time-consuming processes in eDiscovery. Since the dawn of the workplace email, responding to discovery requests has had legal teams spending countless hours painstakingly searching through millions of documents to pinpoint attorney-client and other privileged information in order to protect it from production to opposing parties. As technology has improved, legal professionals have gained more tools to help in this process, but inevitably, it still often entails costly human review of massive amounts of documents.What if there was a better way? Recently, I had the opportunity to gather a panel of eDiscovery experts to discuss how advances in AI and analytics technology now allow attorneys to identify privilege more efficiently and accurately than previously possible. Below, I have summarized our discussion and outlined how legal teams can leverage advanced AI technology to reinvent the model for detecting attorney-client privilege.Current Methods of Privilege Identification Result in Over IdentificationCurrently, the search for privileged information includes a hodgepodge of different technology and workflows. Unfortunately, none of them are a magic bullet and all have their own drawbacks. Some of these methods include:Privilege Search Terms: The foundational block of most privilege reviews involves using common privilege search terms (“legal,” “attorney,” etc.) and known attorney names to identify documents that may be privileged, and then having a review team painstakingly re-review those documents to see if they do, in fact, contain privileged information.‍Complex Queries or Scripts: This method builds on the search term method by weighting the potential privilege document population into ‘tiers’ for prioritized privilege review. It sometimes uses search term frequency to weigh the perceived risk that a document is privileged.‍Technology Assisted Review (TAR): The latest iteration of privilege identification methodologies involves using the TAR process to try to further rank potential privilege populations for prioritized review, allowing legal teams to cut off review once the statistical likelihood of a document containing privilege information reaches a certain percentage.Even applied together, all these methodologies are only just slightly more accurate than a basic privilege search term application. TAR, for example, may flag 1 out of every 4 documents as privilege, instead of the 1 out of every 5 typically identified by common privilege search term screens. This result means that review teams are still forced to re-review massive amounts of documents for privilege.The current methods tend to over-identify privilege for two very important reasons: (1) they rely on a “bag of words” approach to privilege classification, which removes all context from the communication; (2) they cannot leverage non-text document features, like metadata, to evaluate patterns within the documents that often provide key contextual insights indicating a privileged communication.How Can Advances in AI Technology Improve Privilege Identification MethodsAdvances in AI technology over the last two years can now make privilege classification more effective in a few different ways:Leveraging Past Work Product: Newer technology can pull in and analyze the privilege coding that was applied on previous reviews, without disrupting the current review process. This helps reduce the amount of attorney review needed from the start, as the analytics technology can use this past work product rather than training a model from scratch based on review work in the current matter. Often companies have tens or even hundreds of thousands of prior privilege calls sitting in inactive or archived databases that can be leveraged to train a privilege model. This approach additionally allows legal teams to immediately eliminate documents that were identified as privileged in previous reviews.Analyzing More Than Text: Newer technology is also more effective because it now can analyze more than just the simple text of a document. It can also analyze patterns in metadata and other properties of documents, like participants, participant accounts, and domain names. For example, documents with a large number of participants are much less likely to contain information protected by attorney-client privilege, and newer technology can immediately de-prioritize these documents as needing privilege review.Taking Context into Account: Newer technology also has the ability to perform a more complicated analysis of text through algorithms that can better assess the context of a document. For example, Natural Language Processing (NLP) can much more effectively understand context within documents than methods that focus more on simple term frequency. Analyzing for context is critical in identifying privilege, particularly when an attorney may just be generally discussing business issues vs. when an attorney is specifically providing legal advice.Benefits of Leveraging Advances in AI and Analytics in Privilege ReviewsLeveraging the advances in AI outlined above to identify privilege means that legal teams will have more confidence in the accuracy of their privilege screening and review process. This technology also makes it much easier to assemble privilege logs and apply privilege redactions, not only to increase efficiency and accuracy, but also because of the ability to better analyze metadata and context. This in turn helps with privilege log document descriptions and justifications and ensuring consistency. But, by far the biggest gain, is the ability to significantly reduce costly and time-intensive manual review and re-review required by legal teams using older search terms and TAR methodologies.ConclusionLeveraging advances in AI and analytics technology enables review teams to identify privileged information more accurately and efficiently. This in turn allows for a more consistent work product, more efficient reviews, and ultimately, lower eDiscovery costs.If you’re interested in learning more about AI and analytics advancements, check out my other articles on how this technology can also help detect personal information within large datasets, as well as how to build a business case for AI and win over AI naysayers within your organization.To discuss this topic more or to learn how we can help you make an apples-to-apples comparison, feel free to reach out to me at RHellewell@lighthouseglobal.com.ai-and-analytics; chat-and-collaboration-data; ediscovery-reviewprivilege, analytics, ai-big-data, blog, ai-and-analytics, chat-and-collaboration-data, ediscovery-review,privilege; analytics; ai-big-data; bloglighthouse
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Automating Legal Operations - A DIY Model
Legal department automation may be top of mind for you like several other legal operations professionals, however, you might be dependent on IT or engineering resources to be able to execute. Or perhaps you are struggling with change management and not able to implement something new. You are not alone. These were the top two blockers to building out an efficient process within legal departments as shared by recent CLOC conference attendees. The good news is that off-the-shelf technologies have advanced to the point where you may not need any time from those resources and may be able to manage automation without needing to change user behavior. With “no code” automation, you can execute end-to-end automation for your legal operations department, yourself!What is “No Code” Automation?As recently highlighted in Forbes magazine, “no-code platforms feature prebuilt drag-and-drop activities and tasks that facilitate integration at the business user level.” This is not “low code” automation that has been around for decades. Low code refers to using existing code, whether from open source or from other internal development, to lower the need to create new code. Low code allows you to build faster but still requires the knowledge of code. In “no code,” however, you do not need to have an understanding of coding. What this really means is that no code platforms are so user-friendly that even a lawyer, or legal operations professional, can create automated actions…I know because I am a lawyer that has successfully done this!But, How Does this Apply in Legal Operations?The short answer is that it lets you, the legal operations professional, automate workflows with little external help. There are some legal departments already taking advantage of this technology. At a recent CLOC conference, Google shared how they had leveraged “no code” automation to remove the change management process for ethics and compliance in the code of conduct, conflict of interest, and anti-bribery and corruption areas. With respect to outside counsel management, Google was similarly able to remove IT/engineering dependencies for conflict waiver approvals, outside counsel engagements, and matter creation. For more details, watch Google describe their no-code automation use cases.Google’s workflow automation is impressive and more mature than those of us who are just starting, so I wanted to share a simple example. A commonplace challenge for smaller legal teams is to manage tasks – ensuring all legal requests are captured and assigned to someone on the legal team. Many teams are dealing with dozens, or hundreds, of emails and it can be cumbersome to look through those to determine who is working on what. Inevitably some of those requests get missed. It is also challenging to then later report on legal requests – e.g., what types of requests the legal team receives daily, how long they take to resolve, and how many requests each person can work on. A “no code” platform can help. For example, you can connect your email to a shared Excel spreadsheet that captures all legal tasks. You would do this by creating a process that has the tool log each email sent to a certain address (e.g. legal@insertconame.com) on an Excel spreadsheet in a shared location (e.g. LegalTasks.xls). You would “map” parts of the email to columns in the spreadsheet. For example, you would want to capture the sender, the date, the time, the subject, and the body. You can even ask users who are sending requests into that email to put the type of request in the subject line. Your legal team can then check the shared spreadsheet daily and “check out” tasks by putting their initials in another column. Once complete, they would also mark that on the spreadsheet. Capturing all this information will allow you to see who is working on what, ensure that all requests are being worked on, and use pivot reporting on all legal tasks later on. Although this is a really simple use case with basic tools, it is also one that takes only a few minutes to set up and can measurably improve organization among legal team members.You can use “no code” automation in most areas of legal operations department automation. Some of the most common things to automate with “no code” are as follows:Legal ApprovalsDocument GenerationsEvidence CollectionTracking of Policy AcceptanceMany “no code” companies work with legal departments, so they may have experience with legal operations use cases. Be sure to ask how they have seen their technologies deployed in other legal departments.Can I Really Do This Without Other Departments?About 90% of the work can be done by you or your team, and in some cases, even 100%. However, sometimes connecting the tools or even installing the software has to be done by your IT and development teams. This is particularly true if you are connecting to proprietary software or have a complex infrastructure. This 10% of work required by these teams, however, is much smaller than if you were asking for those resources to create the automations from scratch. In addition, you often do not have to change user behavior so change management is removed as a blocker.I encourage you to explore using “no code” automation in your legal department. Once you start, you’ll be glad you tried. I would be excited to hear your experiences with “no code” in legal operations. If you are using it, drop me a line at djones@lighthouseglobal.com and tell me how.legal-operations; ediscovery-reviewediscovery-process, legal-ops, blog, legal-operations, ediscovery-reviewediscovery-process; legal-ops; bloglighthouse
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Analytics and Predictive Coding Technology for Corporate Attorneys: Six Use Cases
Below is a copy of a featured article written by Jennifer Swanton of Medtronic, Shannon Capone Kirk of Ropes & Gray, and John Del Piero of Lighthouse for Legaltech News.This is the second article in a two-part series, designed to help create a better relationship between corporate attorneys and advanced technology. In our first article, we worked to demystify the language technology providers tend to use around AI and analytics technology.With the terminology now defined, we will now focus on six specific ways that corporate legal teams can put this type of technology to work in the eDiscovery and compliance space to improve cost, outcome, efficiencies.1. Document Review and Data Prioritization: The earliest example of how to maximize the value of analytics in eDiscovery was the introduction of TAR (technology-assisted review). CAL (or continuous active learning) allows counsel to see the most likely to be relevant documents much earlier on in the process than if they had been simply looking at search term results, which are not categorized or prioritized and are often overbroad. Plainly put, it is the difference between an organized review and a disorganized review.Data prioritization offers strategic value to the case team, enabling them to get to the crux of a case earlier in the process and ultimately develop a better strategic plan for cost and outcomes. This process also offers the ability to get to a point of review where the likelihood of additional relevant information is so low, no new review is needed. This will save time and money on large document review projects. Such prioritization is critical for time-sensitive internal investigations, as well.To dive further into the Pandora analogy we used above: if you were to listen to a random shuffle of songs on Pandora without giving feedback on what you like and don’t like, you’d likely listen for days to encounter several songs you love. Whereas, if you give Pandora feedback, it learns and you’re likely to hear several songs you love within hours. So why suffer days of listening to show tunes and harp solos when what you really love is the brilliant artistry found in songs by the likes of Ray LaMontagne?2. Custodian and Data Source Identification: Advanced analytics that can analyze complex concepts within data can be a powerful tool to clearly identify your relevant data custodians, where that data lives, and other data sources worth considering. Most conceptual analytics technology can now provide real-time visibility into information about custodians, including the date range of the data collected and the data types delivered. More advanced technology that also analyzes metadata can provide you with a deeper understanding of how custodians interact with other people, including the ability to analyze patterns in timing and speech, and even the sentiment and tone of those interactions.All of this information can be used to help quickly determine whether or not a prospective custodian has information relevant to the case that needs to be collected, or if any supplemental collections are required to close a gap in the date range collected. This, in turn, will help reduce the amount of collections required and minimize processing time in fast-paced cases. These tools also help determine which data sources are likely to hold your most relevant information and where supplemental collections may be warranted.Above: Brainspace display of communication networks, which enable users to identify custodians of interest, as well as related people and conversations.3. Identifying Privileged and Personal Information: Another powerful way to leverage analytics in the eDiscovery workflow is to identify privileged documents in a far more cost-effective way than we could in the past. New privilege categorization software creates significant efficiencies by analyzing the text, metadata, and previous coding of documents in order to categorize documents according to the likelihood that they are actually privileged.More advanced analytics tools can now identify documents that have been flagged as privileged by traditional privilege term screens, but have a high likelihood of not containing privileged communications. For example, the technology identifies that the document was sent to a third-party (thus breaking the privilege attorney-client privilege) or because the only privilege term within the document is contained within a boilerplate footer.These more advanced analytics tools can be much more effective at identifying privileged documents than a privilege search term list, and can help case teams successfully meet rolling production deadlines by pushing the documents that are less likely to be privileged (i.e. those that require less privilege review) to the front of the review line. When integrated with other eDiscovery applications, you can also create a defensible privilege log that can be produced for the litigation team.Additionally, flagging potential PII and protected intellectual property (IP) caught up in a large data set can be challenging, but analytics technology provides in-house legal teams with an important ally for automating those processes. Advanced analytics can streamline the process of locating and isolating this sensitive data, which is often hiding in a variety of different systems, folders, and other information silos. Tools allow you to flag Health Insurance Portability and Accountability Act (HIPAA) protected information based on common format and structure to help quickly move through documents and accurately identify and redact needed information.4. Information Governance: One of the high-stakes elements of large data collections is the importance of parsing out highly sensitive records, such as those that contain PII and protected IP. This information is incredibly important to protect company data and also to comply with the growing number of data privacy regulations worldwide, including Europe’s General Data Protection Regulation (GDPR), the California Consumer Protection Act (CCPA), and HIPAA. Analytics can help identify and flag documents per their appropriate document classification. This can be helpful for both the business in their day-to-day operations as well as the legal team in responding to requests.5. Data Re-Use: One of the largest potentials with the use of analytics is the ability to save time and money on your next matter. Technologically advanced companies are now starting to use analytics technology to integrate previous attorney work product, case information, and documents across all organization matters. On a micro level, recycling and analyzing previous work product allows companies to stop re-inventing the wheel on each case and aids in much faster identification of privilege, personal information, and non-responsive documents.For example, organizations often pay to store documents that contain previous privilege tagging from past matters in inactive or archived databases. Those documents, sitting unused in storage, can be separately re-ingested and used to train a privilege model in the new matter, allowing legal teams to immediately eliminate documents that were identified as privileged in previous reviews—even prior to any human coding in the new matter.On a macro level, this type of advanced capability enables organizations to make data-driven decisions across their entire eDiscovery landscape. Rather than looking at each new matter on an individual basis in a singular lens, legal teams can use advanced analytics to analyze previously coded data across the organization’s entire legal portfolio. This can provide previously unheard of insights, like which custodians often contain the most privileged documents matter over matter, or if a data source rarely produces responsive documents. Data re-use can also come in handy in portfolio matters that have overlapping custodians and data sets and need common production. The overall results are more strategic legal and data decisions, more favorable case outcomes, and increased cost efficiency.6. Accuracy: Finally, and potentially the most important reason to use analytics tools, is to increase accuracy and have a better work product. Studies have shown that tools like predictive coding are more accurate than human work product. That, coupled with the potential for cost savings, should be all one needs to utilize these technologies.As useful as these new analytics tools are to in-house legal teams in their efforts to manage eDiscovery today, it is important to understand that the great promise of these technologies is the fact that they are in a state of continuous improvement. Because analytics tools learn, they refine and “get smarter” as they review more data sets. We all know that we’re on just the cusp of what analytics will bring to our profession—but we believe the future of this technology in the area of eDiscovery management is here now.ai-and-analyticstar-predictive-coding, blog, corporate, ai, ai-and-analytics,tar-predictive-coding; blog; corporate; aijohn del piero
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As Employees Move, Keeping Data in All the Right Places Is Crucial
As the corporate workplace continues to evolve—encompassing hybrid work environments, bring your own device policies, and cloud-based storage—companies are well-advised to consider areas of increased vulnerability and whether their policies, procedures, and forensic tools are keeping pace with reality. A hybrid or remote workforce and a more collaborative data infrastructure only exacerbate data risks that were easier to manage when employees were comfortably situated at their desks. Adding even more complexity to these risks are broader labor trends, including “the Great Resignation and Reshuffle” and an aging work force, which are changing staffing and recruiting strategies and impacting knowledge transfer and IP creation.Employee intake and departure: crucial points of data security Two areas likely needing renewed attention are the moments of employee onboarding and offboarding, when a company’s most prized assets—people and data—are on the move. Departing employees present a particular risk as the potential for data exfiltration of IP and other sensitive information, whether intentional or not, is high. Often, employees take corporate IP with them inadvertently, a situation bound to get worse as turnover rates grow (Gartner anticipates a 20% jump in turnover from the pre-pandemic national average).Since people usually take jobs similar to the ones they leave (and often with competitors), taking company data along with their coffee mug and potted plant may seem justified (I wrote this stuff, so it’s mine)—or simply inconsequential. Cloud storage services such as Dropbox, Box, or Google Drive, and collaborative apps such as Microsoft Teams or Slack make it all the easier to appropriate files, lending credence to a feeling of personal data ownership. No matter how it happens, the escape into the wild of proprietary items such as source code, strategy documents, contact lists, and financial information exposes the company to untold risk, including the danger of running afoul of any number of privacy regulations if personal data is exfiltrated from its protected environment—an additional headache for the company if things go south. Are current entry and exit protocols enough? Although most companies have entrance and exit protocols usually siloed as HR and IT functions, the recent surge in employee turnover has put those very teams under pressure as they face their own personnel and budget deficits. Further, responsibilities have become less defined at a time when offboarding tasks—many now carried out at a distance—should be fortified to include proactive data monitoring and oversight, activities such teams may not be equipped to handle. The challenge, of course, is the growing complexity of the data landscape. Knowing what information is where, who accesses it, and for what purpose becomes more difficult to track as software and storage options grow, yet this is key to keeping important data protected. Data security: start training early and reinforce often Onboarding procedures can play a key role in keeping data where it belongs and helping employees navigate through and understand their responsibilities in this increasingly intricate data terrain. First, a sound onboarding protocol can ensure that new employees aren’t bringing troublesome data into the environment. No company wants to deal with the fallout of being in possession of some other company’s IP or sensitive information. More importantly, onboarding offers the most opportune time to clearly communicate expectations regarding data management and safety—information that should be reinforced with frequent (and up to date) training that emphasizes data protection and ownership. It's easy to forget as time goes on what data may be confidential or sensitive, and even easier to forget that data belongs to the business, not the employee. In short, data awareness should be instilled as part of the company culture right from the start. Seize the moment: identify and monitor offboarding risksThe recent and ongoing workplace disruption calls for a hard look at offboarding data risks and an evaluation of potential vulnerabilities to protect data before an employee leaves the company, bolster the exit protocols to have in place when they do, and have the proper forensic and analytic tools to handle data monitoring and address potential wrongdoing. Most companies do have standard offboarding checklists that address employee assets, data access, and preservation obligations as they leave the company. But there’s more to data protection at this crucial moment than ticking off boxes. Expand and optimize the offboarding checklistSavvy companies implement a more proactive, programmatic approach that begins earlier, with monitoring procedures that include defensible and repeatable processes to guard against the exfiltration of company data while helping to fortify the company’s position in case of a breach. A few important things to consider as part of the offboarding process:Know which employees warrant departure attention. Develop risk profiles with business stakeholders to identify which classes of employees, whether based on role, circumstance of departure, seniority, or access to sensitive information could present an exfiltration risk.Understand the company’s data landscape. Make sure there are mechanisms in place for tracking where sensitive data and IP may reside and when such data has been accessed.Explore activity and assets with the employee prior to their departure. An expert, friendly review of a departing employee’s recent computer activity with the employee, including an audit of their recent network activities, use of peripherals, cloud uploads, and email sends, can reveal and help mitigate potential trouble.Preserve employee devices and data as warranted with state-of-the-art forensic tools. Forensic preservation is critical to ensuring valid evidence down the line, especially since investigations today regularly involve new and novel devices, data sources, and artifacts that must be diagnosed and understood.Document all offboarding information. A paper trail of findings during the exit procedure is important if further analysis is recommended or necessary and will be crucial for subsequent investigation, if it comes to that. Have a plan if there is evidence of wrongdoing. Part of any data security effort is having an action plan to execute if there are signs of a breach. Preservation, collection, and a forensic analysis may be required should legal action ensue. ConclusionThe recent upheaval in employee turnover along with more collaboration tools and storage options present increasing risk for today’s enterprise. Companies that acknowledge new vulnerabilities and leverage opportunities to revamp outdated policies and protocols are better positioned to stop data exfiltration before it becomes a problem. The best solution: Implement robust onboarding and offboarding solutions that include data monitoring, reporting, and forensic analysis to enable a quick pivot to actionable remediation steps if trouble is brewing. digital-forensics; information-governancedeparting-onboarding-employee, blog, risk-management, digital-forensics, information-governancedeparting-onboarding-employee; blog; risk-managementdaniel black
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An Introduction to Managing Microsoft 365 Updates that Present Legal and Compliance Considerations
Increasingly, opportunities for cloud-based collaboration and efficiencies, and challenges presented by the rapid proliferation of complex data, are incentivizing organizations to transform their corporate data governance and eDiscovery operations from traditional self-managed infrastructure to the Microsoft 365 (M365) Cloud. Benefits in terms of convenience, security, robust functionality, and native capabilities related to eDiscovery and compliance are the primary drivers of this move.While there are many benefits to moving into the M365 ecosystem, it requires legal and compliance teams to take on new considerations regarding the constant evolution that characterizes cloud software. With continually changing applications, establishing static workflows for eDiscovery, legal holds, data dispositions, and other legal operations is not enough. As the M365 software and functionality changes, workflows must be constantly evaluated to ensure their validity, relevance, and defensibility.Exacerbating this challenge is the reality that the traditional IT change management paradigm designed to preemptively address cross-organizational considerations (including impacts to legal, compliance, and eDiscovery operations) does not fit the Cloud/SaaS framework. Organizations must now rethink their change management approach as they modernize with M365.This is the first in a series of blog posts devoted to highlighting key changes that have been released into the M365 production environments. One of the biggest challenges for organizations is identifying which of the myriad of updates pose potential risks to eDiscovery operations. Distinguishing the changes that do and do not pose a significant eDiscovery impact can be extremely difficult unless the reviewer has some level of subject-matter expertise and understands the specific workflows deployed within the organization. Here are some common scenarios with potential eDiscovery impact that could easily go unnoticed by the untrained eye:Updates that create a new data sourceUpdates that change a backend data storage locationUpdates altering the risk profile of features that were previously disabled due to legal / privacy riskUpdates that render an existing eDiscovery process obsoleteEach subsequent blog post in this series will highlight an example of a software update related to our key software scenarios, detailing the nature of the change, the potential impact, as well as when and why organizations should care.microsoft-365; chat-and-collaboration-data; information-governancemicrosoft, compliance-and-investigations, blog, cloudcompass, advisory-services, microsoft-365, chat-and-collaboration-data, information-governance,microsoft; compliance-and-investigations; blog; cloudcompass; advisory-serviceslighthouse
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Analytics and Predictive Coding Technology for Corporate Attorneys: Demystifying the Jargon
Below is a copy of a featured article written by Jennifer Swanton of Medtronic, Shannon Capone Kirk of Ropes & Gray, and John Del Piero of Lighthouse for Legaltech News.Despite the traditional narrative that lawyers are hesitant to embrace technology, many in-house legal departments and their outside service providers are embracing the use of what is generally referred to as artificial intelligence (AI). In terms of litigation and internal investigations, this translates more specifically into conceptual analytics and predictive coding (also referred to as continuous active learning, or CAL), which are two of the more advanced technological innovations in the litigation space and corporate America.This adoption, in part, seems to be driven by an expectation from corporate leaders that their in-house counsel must be able to identify and utilize the best available technology in order to drive cost efficiency, while also reducing risk and increasing effective and defensible litigation positions. For instance, in a 2019 survey of 163 legal professionals conducted by ALM Intelligence and LexisNexis, 92% of attorneys surveyed planned to increase their use of legal analytics in the upcoming 12 months. The reasoning behind that expected increase in adoption was two-fold, with lawyers indicating that it was driven both by competitive pressure to win cases (57%), as well as client expectation (56%).Given that the above survey took place right before the COVID-19 pandemic hit, it stands to reason that the 92% of attorneys that expected to increase their use of analytics tools in 2020 may actually be even higher now. With a divisive election and receding pandemic only recently behind us, and an already unpredictable market, many corporations are tightening budgets and looking to further reduce unnecessary spend. Conceptual analytics and CAL are easy (yes, really) and effective ways to manage ballooning datasets and significantly reduce discovery, litigation and internal investigation costs.With that in mind, we would like to help create a better relationship between corporate attorneys and advanced technology with the following two step approach—which we will outline in a series of two articles.This first installment will help demystify the language technology providers tend to use around AI and analytics technology so that in-house teams feel more comfortable with adoption. In our second article, we will provide examples of some great use cases where corporate legal teams can easily leverage technology to help improve workflows. Together, we hope this approach can help in-house legal teams adopt technology that drives efficiency, lowers cost, and improves the quality of their work.Demystifying AI JargonIf you have ever discussed AI or analytics technology with a technology provider, you are probably more than aware that tech folks have a tendency to forget that the majority of their clients don’t live in the world of developing and evaluating new technology, day in and day out. Thus, they may use terms that are often confusing to their legal counterparts (and sometimes use terms that don’t match what the technology is capable of in the legal world). For this reason, it is helpful to level set with some common terminology and definitions, so that in-house attorneys are prepared to have better, more practical real-world discussions with technology providers.Analytics Technology: Within the eDiscovery and compliance space, analytics technology is the ability of a machine to recognize patterns, structures, concepts, terminology, and/or the people interacting within data, and then present that analysis in a visual representation so that attorneys have a better overview of their data. As with AI, not all analytics tools have the same capabilities. Vendors may label everything from email threading identification to more advanced technology that can identify complex concepts and human sentiment as “analytics” tools.Within these articles, when we reference this term, we are referring to the more advanced technology that can analyze not only the text within data but also the metadata and any previous coding applied by subject matter experts. This is an important distinction because this type of technology can greatly improve the accuracy of the analysis compared to older tools. For example, analytics technology that can analyze metadata as well as text is much better at identifying concepts like attorney-client privilege because it can analyze not only the language being used but who is using that language and the circumstances in which they use it.Artificial Intelligence (AI): Probably the most broadly recognized term due to its prevalence outside of the eDiscovery space, AI is technically defined as the ability of a computer to complete tasks that usually would require human intelligence. Within the eDiscovery and compliance world, vendors often use the term broadly to refer to a variety of technologies that can perform tasks that previously would require completely human review.It is important to remember though that the term AI can refer to a broad range of technology with very different capabilities. “AI” in the legal world is currently being used as a generalized term and legal consumers of such technologies should press for specifics—not all “AI” is the same, or, in several cases, even AI at all.Machine Learning: Machine learning is a category of algorithms used in AI that can analyze statistics and find patterns in large volumes of data. The algorithms improve with experience—meaning that as documents are coded in a consistent fashion by humans, the better and more accurate the algorithms should become at identifying specific data types. Note here that there is a common misunderstanding that machine learning requires large amounts of data from which to learn. That is not necessarily true—all that is required for machine learning to work well is that the input it learns from (i.e., document coding for eDiscovery purposes) is consistent and accurate.Natural Language Processing (NLP): NLP is a subset of AI that uses machine learning to process and analyze the natural language humans use within large amounts of data. The result is technology that can “understand” the contents of documents, including the context in which language is used within them. Within eDiscovery, NLP is used within more advanced forms of analytics technology to help identify specific content or sentiments within large datasets.For example, NLP can be used to more accurately identify sensitive information, like personally identifiable information (PII), within datasets. NLP is better at this task than older AI technology because older models relied on “regular expressions” (a sequence of characters to define a search pattern) to identify information. When a “regular expression” (or regex) is used by an algorithm to find, for example, VISA account numbers—it will be able to identify the correct number pattern (i.e., any number that starts with the number 4 and has 16 digits) within a dataset but will be unable to differentiate other numbers that have the same pattern (for example, employee identification numbers). Thus, the results returned by legacy technology using regex may be overbroad and include false positives.NLP can return more accurate results for that same task because it is able to identify not only the number pattern, but can also analyze the language used around the pattern. In this way, NLP will understand the context in which VISA account numbers are communicated within that dataset compared to how employee identification numbers are communicated, and only return the VISA numbers.Predictive Coding (also referred to as Technology-Assisted Review or TAR): Predictive coding is not the same as conceptual analytics. Also, predictive coding is a bit of a misnomer, as the tools don’t predict or code anything. A human reviewer is very much involved. Simply put, it refers to a form of machine learning, wherein humans review documents and make binary coding calls: what is responsive and what is non-responsive. This is similar in concept to selecting thumbs up or down in Pandora so as to teach the app what songs you like and don’t like. After some human coding and calibrations between the human and the tool, the technology uses the human’s coding selections to score how the remaining documents should be coded, enabling the human to review the high scored documents first.In the most current versions of predictive coding, this technology continually improves and refreshes as the human reviews, which reduces or eliminates the need for surgical precision on coding at the start (which was a concern in the former version of predictive coding and why providers and parties spent a considerable amount of time concerned with “seed sets”). This improved and self-improving prioritization of large document sets based on high-scored documents is usually a more efficient and organized manner in which to review documents.Because of this evolution in predictive coding, it is often referred to in a host of different ways, such as TAR 1.0 (which requires “seed sets” to learn from at the start) and TAR 2.0 (which is able to continually refresh as the human codes—and is thus also referred to as Continuous Active Learning or CAL). Some providers continue to use the old terminology, or explain their advancements by walking through the differences between TAR 1.0 and TAR 2.0, and so on. But, speaking plainly, in this day and age, providers and legal teams should really only be concerned with the latest version of TAR, which utilizes CAL, and significantly reduces or totally eliminates the previous concern with surgical precision on coding an initial “seed set.” With our examples in the next installment, we hope to illustrate this point. In a word, walking through the technological evolution around predictive coding and all of the associated terminology can cause unnecessary intimidation, and can cause confusion between providers, parties and the court.The key takeaway from these definitions is that even though all the technology described above may technically fall into the “AI” bucket, there is an important distinction between predictive coding/TAR technology and advanced analytics technology that uses AI and NLP. The distinction is that predictive coding/TAR is a much more technologically-limited method of ranking documents based on binary human decisions, while advanced analytics technology is capable of analyzing the context of human language used within documents to accurately identify a wide variety of concepts and sentiment within a dataset. Both tools still require a good amount of interaction with human reviewers and both are not mutually exclusive. In fact, on many investigations in particular, it is often very efficient to employ both conceptual analytics and TAR, simultaneously, in a review.Please stay tuned for our next installment in this series, “Analytics and Predictive Coding Technology for Corporate Attorneys: Six Use Cases”, where we will outline six specific ways that corporate legal teams can put this type of technology to work in the eDiscovery and compliance space to improve cost, outcome, efficiencies.ai-and-analyticstar-predictive-coding, blog, corporate, ai, ai-and-analytics,tar-predictive-coding; blog; corporate; ailegaltech news
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Advanced Analytics – The Key to Mitigating Big Data Risks
Big data sets are the “new normal” of discovery and bring with them six sinister large data set challenges, as recently detailed in my colleague Nick’s article. These challenges range from classics like overly broad privileged screens, to newer risks in ensuring sensitive information (such as personally identifiable information (PII) or proprietary information such as source code) does not inadvertently make its way into the hands of opposing parties or government regulators. While these challenges may seem insurmountable due to ever-increasing data volumes (and also tend to keep discovery program managers and counsel up at night) there are new solutions that can help mitigate these risks and optimize workflows.As I previously wrote, eDiscovery is actually a big data challenge. Advances in AI and machine learning, when applied to eDiscovery big data, can help mitigate and reduce these sinister risks by breaking down the silos of individual cases, learning from a wealth of prior case data, and then transferring these learnings to new cases. Having the capability to analyze and understand large data sets at scale combined with state-of-the-art methods provides a number of benefits, five of which I have outlined below.Pinpointing Sensitive Information - Advances in deep learning and natural language processing has now made pinpointing sensitive content achievable. A company’s most confidential content could be laying in plain sight within their electronic data and yet be completely undetected. Imagine a spreadsheet listing customers, dates of birth, and social security numbers attached to an email between sales reps. What if you are a technology company and two developers are emailing each other snippets of your company’s source code? Now that digital medium is the dominant form of communication within workplaces, situations like this are becoming ever-present and it is very challenging for review teams to effectively identify and triage this content. To solve this challenge, advanced analytics can learn from massive amounts of publically available and computer-generated data and then fine tuned to specific data sets using a recent breakthrough innovation in natural language processing (NLP) called “transfer learning.” In addition, at the core of big data is the capability to process text at scale. Combining these two techniques enables precise algorithms to evaluate massive amounts of discovery data, pinpoint sensitive data elements, and elevate them to review teams for a targeted review workflow.Prioritizing the Right Documents - Advanced analytics can learn both key trends and deep insights about your documents and review criteria. A normal search term based approach to identify potentially responsive or privileged content provides a binary output. Documents either hit on a search term or they do not. Document review workflows are predicated on this concept, often leading to suboptimal review workflows that both over-identify documents that are out of scope and miss documents that should be reviewed. Advanced analytics provide a range of outcomes that enable review teams to create targeted workflow streams tailored to the risk at hand. Descriptive analysis on data can generate human interpretable rules that help organize documents, such as “all documents with more than X number of recipients is never privileged” or “99.9% of the time, documents coming from the following domains are never responsive”. Deep learning-based classifiers, again using transfer learning, can generalize language on open source content and then fine-tune models to specific review data sets. Having a combination of analytics, both descriptive and predictive, provides a range of options and gives review teams the ability to prioritize the right content, rather than just the next random document. Review teams can now concentrate on the most important material while deprioritizing the less important content for a later effort.Achieving Work-Product Consistency - Big data and advanced analytics approaches can ensure the same document or similar documents are treated consistently across cases. Corporations regularly collect, process, and review the same data across cases over and over again, even when cases are not related. Keeping document treatment consistent across these matters can obviously be extremely important when dealing with privilege content – but is also important when it comes to responsiveness across related cases, such as a multi-district litigation. With the standard approach, cases are in siloes without any connectivity between them to enable consistent approaches. A big data approach enables connectivity between cases using hub-and-spoke techniques to communicate and transit learnings and work-product between cases. Work product from other cases, such as coding calls, redactions, and even production information can be utilized to inform workflows on the next case. For big data, activities like this are table stakes.Mitigating Risk - What do all of these approaches have in common? At its core, big data and analytics is an engine for mitigating risk. Having the ability to pinpoint sensitive data, prioritize what you look at, and ensure consistency across your cases is a no-brainer. This all may sound like a big change, but in reality, it’s pretty seamless to implement. Instead of simply batching out documents that hit on an outdated privilege screen for privilege review, review managers can instead use a combination of analytics and fine-tuned privilege screen hits. Review then occurs from there largely as it does today, just with the right analytics to inform reviewers with the context needed to make the best decision.Reducing Cost - The other side of the coin is cost savings. Every case has a different cost and risk profile and advanced analytics should provide a range of options to support your decision making process on where to set the lever. Do you really need to review each of these categories in full, or would an alternative scenario based on sampling high-volume and low-risk documents be a more cost-effective and defensible approach? The point is that having a better and more holistic view of your data provides an opportunity to make these data-driven decisions to reduce costs.One key tip to remember - you do not need to try to implement this all at once! Start by identifying a key area where you want to make improvements, determine how you can measure the current performance of the process, then apply some of these methods and measure the results. Innovation is about getting a win in order to perpetuate the next.If you are interested in this topic or just love to talk about big data and analytics, feel free to reach out to me at KSobylak@lighthouseglobal.com.ai-and-analyticsdigital-forensics, ai-and-analyticsanalytics; ai-big-data; data-re-use; blogkarl sobylak
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Achieving Information Governance through a Transformative Cloud Migration
Recently, I had the pleasure of appearing as a guest on Season 5, Episode 1 of the Law & Candor podcast, hosted by Lighthouse’s Rob Hellewell and Bill Mariano. The three of us discussed cloud migrations and how that process can provide a real opportunity for an organization to transform its approach to information governance. Below is a summary of our conversation, including best practices for organizations that are ready to take on this digital and cultural cloud transformation process.Because it is difficult to wrap your head around the idea of a cloud transformation, it can be helpful to visualize the individual processes involved on a much smaller scale. Imagine you are simply preparing to upgrade to a new computer. Over the years, you have developed bad habits around how you store data on your old computer, in part because the tools on that computer have become outdated. Now that you’re upgrading, you have the opportunity to evaluate your old stored data to identify what is worth moving to your new computer. You also have the opportunity to re-evaluate your data storage practice as a whole and come up with a more efficient plan that utilizes the advanced tools on your new computer. Similarly, the cloud migration process is the best opportunity an organization has to reassess what data should be migrated, how employees interact with that data, and how that data flows through the organization before building a brand new paradigm in the Cloud.You can think of this new paradigm as the organization’s information architecture. Just like a physical architecture where the architect designs a physical space for things, an organization’s information architecture is the infrastructure wherein the organization’s data will reside. To create this architecture effectively, you first must analyze how data flows throughout the company. To visualize this process, imagine the flow of information as a content pipeline: you’ve got a pile of papers and files on your desk that you want to assess, retain what is useful to you, and then pass on to the next person down the pipe. First, you would identify the files you no longer need and discard those. Next, you would identify what files you need for your work and put those aside for yourself. Then you would pass the remaining pile down to the next person in the pipeline, who has a different role in the organization (say, accountant). The accountant will pull out the files that are relevant to their accounting work, and pass the files down to the next person (say, a lawyer). The lawyer performs the same exercise for files that are relevant to their legal role, and so on until all the files have a “home.”In this way, information architecture is about clearly defining roles (accounting role, legal role, etc.) and how those roles interact with data, so that there is a place in the pipeline for the data they utilize. This allows information to flow down the pipeline and end up where it belongs. Note how different this system is from the old information governance model, where organizations would try to classify information by what it was in order to determine where it should be stored. In this new paradigm, we try to classify information by how it is used – because the same piece of content can be used in multiple ways (a vendor contract, for example, can be useful to both legal and accountant roles). The trick to structuring this new architecture is to place data where it is the most useful. Going hand-in-hand with the creation of a new information architecture, cloud migrations can (and should) also be an opportunity for a business culture transformation. Employees may have to re-wire themselves to work within this new digital environment and change the way they interact with data. This cultural transformation can be kicked off by gathering all the key players together and having a conversation about how each currently interacts with data. I often recommend conducting a multi-day workshop where every stakeholder shares what data they use, how they use it, and how they store it. For example, an accountant may explain that when he works on a vendor contract, he pulls the financial information from it and saves it under a different title in a specific location. A lawyer then may explain that when she works on the same vendor contract, she reviews and edits the contract language, and saves it under a different title to a different location. This collaborative conversation is necessary because, without it, no one in the organization would be able to see the full picture of how information moves through the organization. But equally important, what emerges from this kind of workshop is the seeds of culture transformation: a greater awareness from every individual about the role they play in the overall flow of information throughout the company and the importance of their role in the information governance of the organization. Best Practices for Organizations: Involve someone from every relevant role in the organization in the transformation process (i.e. everyone who interacts with data). If you involve frontline workers, the entire organization can embrace the idea that the cloud migration process will be a complete business culture transformation.Once all key players are involved, begin the conversation about how each role interacts with data. This step is key not only for the business cultural transformation, but also for the organization to understand the importance of doing the architecture work.These best practices can help organizations leverage their cloud migration process to achieve an efficient and effective information governance program. To discuss this topic further, please feel free to reach out to me at JHolliday@lighthouseglobal.com. information-governancemicrosoft-365, legal-operationscloud; information-governance; cloud-migration; bloglighthouse
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AI and Analytics: New Ways to Guard Personal Information
Big data can mean big problems in the ediscovery and compliance world – and those problems can be exponentially more complicated when personal data is involved. Sifting through terabytes of data to ensure that all personal information is identified and protected is becoming an increasingly more painstaking and costly process for attorneys today.Fortunately, advances in artificial intelligence (AI) and analytics technology are changing the landscape and enabling more efficient and accurate detection of personal information within data. Recently, I was fortunate enough to gather a panel of experts together to discuss how AI is enabling legal professionals in the ediscovery, information governance, and compliance arenas to identify personal protected information (PII) and personal health information (PHI) more quickly within large datasets. Below is a summary of our discussion, along with some helpful tips for leveraging AI to detect personal information.Current Methods of Personal Data Identification Similar to the slower adoption of AI and analytics to help with the protection of attorney-client privilege information (compared to the broader adoption of machine learning to identify matter relevant documents), the legal profession has also been slow to leverage technology to help identify and protect personal data. Thus, the identification of personal data remains a very manual and reactive process, where legal professionals review documents one-by-one on each new matter or investigation to find personal information that must be protected from disclosure.This process can be especially burdensome for pharmaceutical and healthcare industries, as there is often much more personal information within the data generated by those organizations, while the risk for failing to protect that information may be higher due to healthcare-specific patient privacy regulations like HIPAA.How Advances in AI Technology Can Improve Personal Data Identification There are a few ways in which AI has advanced over the last few years that make new technology much more effective at identifying personal data:Analyzing More Than Text: AI technology is now capable of analyzing more than just the simple text of a document. It can now also analyze patterns in metadata and other properties of documents, like participants, participant accounts, and domain names. This results in technology that is much more accurate and efficient at identifying data more likely to contain personal information.Leveraging Past Work Product: Newer technology can now also pull in and analyze the coding applied on previous reviews without disrupting workflows in the current matter. This can add incredible efficiency, as documents previously flagged or redacted for personal information can be quickly removed from personal information identification workflows, thus reducing the need for human review. The technology can also help further reduce the amount of attorney review needed at the outset of each matter, as it can use many examples of past work product to train the algorithms (rather than training a model from scratch based on review work in the current matter).Taking Context into Account: Newer technology can now also perform a more complicated analysis of text through algorithms that can better assess the context of a document. For example, advances in Natural Language Processing (NLP) and machine learning can now identify the context in which personal data is often communicated, which helps eliminate previously common false hits like mistakenly flagging phone numbers as social security numbers, etc.Benefits of Leveraging AI and Analytics when Detecting Sensitive DataArguably the biggest benefit to leveraging new AI and analytics technology to detect personal information is cost savings. The manual process of personal information identification is not only slower, but it can also be incredibly expensive. AI can significantly reduce the number of documents legal professionals would need to look through, sometimes by millions of documents. This can translate into millions of dollars in review savings because this work is often performed by legal professionals who are billed at an hourly rate.Not only can AI utilization save money on a specific matter, but it can also be used to analyze an entire legal portfolio so that legal professionals have an accurate sense of where (and how much) personal information resides within an organization’s data. This knowledge can be invaluable when crafting burden arguments for upcoming matters, as well as to better understand the potential costs for new matters (and thus help attorneys make more strategic case decisions).Another key benefit of leveraging AI technology is the accuracy with which this technology can now pinpoint personal data. Not only is human review much less efficient, but it can also lead to mistakes and missed information. This increases the risk for healthcare and pharmaceutical organizations especially, who may face severe penalties for inadvertently producing PHI or PII (particularly if that information ends up in the hands of malevolent actors). Conducting quality control (QC) with the assistance of AI can greatly increase the accuracy of human review and ensure that organizations are not inadvertently producing individuals’ personal information. Best Practices for Utilizing AI and Analytics to Identify Personal DataPrepare in Advance: AI technology should not be an afterthought. Before you are faced with a massive document production on a tight deadline, make sure you understand how AI and analytics tools work and how they can be leveraged for personal data identification. Have technology providers perform proof of concept (POC) analyses with the tools on your data and demonstrate exactly how the tools work. Performing POCs on your data is critical, as every provider’s technology demos well on generic data sets. Once you have settled on the tools you want to use within your organization, ensure your team is trained well and is ready to hit the ground running. This will also help ensure that the technology you choose fits with your internal systems and platforms.Take a Global Team Approach: Prior to leveraging AI and analytics, spend some time working with the right people to define what PII and PHI you have an obligation to identify, redact, or anonymize. Not all personal information will need to be located or redacted on every matter or in every jurisdiction, but defining that scope early will help you leverage the technology for the best use cases.Practice Information Governance: Make sure your organization is maintaining proper control of networks, keeping asset lists up to date, and tracking who the business and technical leads are for each type of asset. Also, make sure that document retention policies are enforced and that your organization is maintaining controls around unstructured data. In short, becoming a captain of your content and running a tight ship will make the entire process of identifying personal information much more efficient.Think Outside the Box: AI and analytics tools are incredibly versatile and can be useful in a myriad of different scenarios that require protecting personal information from disclosure. From data breach remediation to compliance matters, there is no shortage of circumstances that could benefit from the efficiency and accuracy that AI can provide. When analyzing a new AI tool, bring security, IT, and legal groups to the table so they can see the benefits and possibilities for their own teams. Also, investigate your legal spend and have other teams do the same. This will give you a sense of how much money you are currently spending on identifying personal information and what areas can benefit from AI efficiency the most.If you’re interested in learning more about how to leverage AI and analytic technology within your organization or law firm, please see my previous articles on how to build a business case for AI and win over AI naysayers within your organization.To discuss this topic more or to learn how we can help you make an apples-to-apples comparison, feel free to reach out to me at RHellewell@lighthouseglobal.com.data-privacy; ai-and-analyticsai-and-analytics, microsoft-365analytics; data-privacy; ai-big-data; bloglighthouse
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Adopting a Compliant & Defensible Remote Collections Strategy
One of the unanticipated consequences of the COVID-19 pandemic and the ensuing shift of office employees being forced to work from home, is the impact on counsel who must continue to direct forensically defensible collections for eDiscovery, investigations, and regulatory response scenarios. As employees adjust to remote work, they are increasingly commingling personal data sources, home networks, and corporate data, which in turn creates a wealth of new data sources that will need to be collected as potentially-relevant ESI.In my recent webinar, I discussed this significant shift to the “new normal” of digital digital-forensics and how information governance policies and IT security practices should be proactively extended to remote employees, as well as ways to mitigate future complications around forensic collections that will now need to be almost exclusively remote. Here are a few of the most important aspects to consider on how working from home impacts digital digital-forensics, and practical workflow strategies for handling remote ESI collections.Working from Home: The Digital digital-forensics ImpactThere’s a behavioral impact that automatically comes with working entirely from home, with less delineation between the workday and home life, and subsequently more temptation to use your work laptop for personal reasons. This behavioral impact is also mirrored in the reverse scenario where personal devices become more convenient to use for work. Although we were already seeing quite a bit of intermingling of data pre-COVID-19, this habit is dramatically increasing as home has quickly become the only workplace and there hasn’t been time for organizations to adopt new IT policies to tackle these issues.With the advent of this new remote workplace era, data (mis)management will remain with us for future matters and there will be a permanent impact on collections going forward. Among the top adjustments that need to be made is custodian questionnaires must be enhanced to scrutinize whether any relevant work-related data or communications reside on the custodians’ home devices. The same scrutiny will need to be applied to personal data potentially residing on work laptops as the opportunities for this type of data intermingling or “contamination” will undoubtedly continue to increase.ESI Collections: Practical Workflow StrategiesEven though we’re currently not able to travel onsite to acquire device and data source evidence, we can continue collections by relying on sound and defensible forensic remote strategies that are already in place. Collections from the Cloud are status quo and conducted remotely by definition, but for other ESI sources, we will favor targeted and logical collections over full physical forensic images.For remote collections on premise at an office that’s closed, if there’s a skeleton IT crew in place, screen sharing can be utilized to mimic the exact scenario of a digital-forensics professional being onsite to help load a hard drive or provide access into a server. For custodians sitting at home, the same process can apply and technical guidance can be provided remotely. If shipping is a safety concern, data can be uploaded by secure encrypted file transfer protocol (FTP) using software that can resume broken uploads or by utilizing fast data transfer solutions such as Aspera. Whether figuring out a safe way to transport encrypted hard drives back and forth or using remote data transfer technology, we’ll need to plan for increased turnaround times due to varying upload speeds from home and/or decontamination procedures that are implemented for shipping protocols.Key TakeawaysAs company and personal custodian data commingling grows during COVID-19, a permanent shift is happening in digital digital-forensics and eDiscovery. From a legal standpoint, it’s settled that company-related communication on personal devices is subject to discovery, thus custodian interviews and other information-gathering techniques to identify the relevant scope of a collections effort must be enhanced. And although data preservation and evidence acquisition tasks may take longer to conduct when onsite collections is not an option, the technology is already in place to ensure forensically sound and defensible remote collections now and in the future.To discuss this topic further, please feel free to reach out to me at JBui@lighthouseglobal.com.digital-forensics; information-governancelegal-operations, digital-forensics, information-governancecloud; collections; cloud-security; bloglighthouse
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A New Deal: Tackling HSR Second Requests with Key Documents
Among data challenges that businesses and their law firms face, those surrounding mergers and acquisitions are arguably some of the most daunting. Fast-paced and demanding, the high-stakes M&A process is like an amped-up litigation and investigation combined, with specific M&A data requirements, massive document productions, fact-finding imperatives, and more.To add a bit of drama, inflationary pressure and fears of a recession could cool M&A activity, while the impacts of the pandemic continue to make regulatory reaction to the M&A landscape unpredictable, especially as to whether an HSR Second Request will be in the offing. If there is Second Request, document requirements ramp up and so does heightened scrutiny from regulatory agencies, especially in light of the 2021 Executive Order on Promoting Competition in the American Economy. “Providing heightened scrutiny to a broader range of relevant market realities is core to fulfilling our statutory obligations under the law.” – FTC, 2021Know as much as you can, as soon as you canIn a Second Request (as with any legal matter), the more you know and the sooner you know it, the better. Since technology assisted review (TAR), continuous active learning (CAL), and other eDiscovery technology has largely usurped a linear responsive review process, there is often less need for attorneys to review the majority of the documents that get produced to the government. This is good news for attorneys, who are faced with ever-growing data volumes that would be nearly impossible to tackle using a linear document review process, while still meeting the tight substantial compliance timeframe in a typical Second Request. However, less human review during the eDiscovery process elevates the need for counsel to find a way to uncover key information within the documents for fact development, witness kits, or expert support.From a data standpoint, what fact-finding can be done early using human expertise, technology, and a specific search workflow? The sophisticated analytics tools available today make any number of assessments possible, even before data is collected. Basic data characteristics gleaned from metadata can reveal important information: email domains, recipients, BCCs, timestamps—such metadata is fodder for data analytics tools that can reveal custodians, relationships, timelines, communications patterns and more, all necessary information in regulatory matters. Companies that have found a way to have previously-assessed characteristics live with a document (think privilege, PII, confidentiality status) are really ahead of the game.Let’s also not forget that evidence of anti-competitive behavior is really what Second Requests are all about. Although there are plenty of market facts and figures to be scrutinized, communications among people who are knowledgeable about the proposed deal could tell an “interesting” story. Common words and phrases casually bandied about (“dominant player,” “sticky customers”) can be laden with meaning to regulators or attorneys, throwing up red flags for further investigation. Company data stores can thus either be a gold mine or a land mine—and it helps counsel tremendously if they have the information on hand to prepare for either circumstance. Finding key documents: a surgical strike, not a data dumpIdentifying key information requires a precise approach and assessment —it’s not something that can be accomplished with a keyword list created during a brainstorming session. Keywords can’t help much if you don’t know exactly what you’re looking for. Rather, finding key documents today can be an elevated process—one that is technology-enabled and executed by a nimble team that can leverage linguistic expertise, proven search algorithms and processes, and proprietary technology to quickly pinpoint and deliver a highly-curated set of documents on target topics. As key information is uncovered, further fact-finding can be curtailed or expanded. A team can adapt to any change in priorities, custodians, subjects, and/or time frames as a regulator changes the focus of the review. This reduces the amount of time counsel must spend going through documents, keeping costs in check, and providing the best ROI.Between the initial filing and receipt of a Second Request, especially when there is little doubt that the Second Request will be issued, a team executing key document identification can help kick off the fact-finding and development process with whatever data is available—before any responsiveness review has even begun.And even when no Second Request is issued, a team of experts executing key document identification can play a significant role. In support of an initial filing, they can help identify 4(c) and 4(d) documents that are required as part of the disclosure and get the best instance or latest version of important documents. This is especially helpful in situations where executives or others involved in the deal have massive data populations and don’t know where the relevant documents are. ConclusionIdentifying key documents is a critical part of a Second Request. If client and counsel are well-prepared—armed with the ability to leverage expertise and advanced technology to find key documents from the get-go—the most challenging hurdles can often be overcome, enabling timely compliance, and avoiding potential complications that could delay resolution—or even kill the deal. antitrust; ediscovery-reviewantitrust, ediscovery-reviewhsr-second-requests; bloglighthouse
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A Dynamic HSR Landscape Spells Uncertainty for Second Requests
A Second Request for a Hart-Scott-Rodino (HSR) filing thrusts companies and their counsel into a high-stakes race against time, complicated by massive data volumes and strict requirements. Policy and enforcement shifts by the Federal Trade Commission (FTC) and Department of Justice Antitrust Division (DOJ), brought on by a change in presidential administrations, complicate the landscape even further.In early 2022, Lighthouse analyzed the data and recent history of Second Requests in our whitepaper, the 2021 Second Request Trends Report, to help predict activity this year and beyond.Now, as we approach the halfway point of the Biden administration’s inaugural term, it seems a pertinent time to check in on the agencies’ attitudes and actions thus far, and what they mean for mergers and acquisitions — both today and in the future. To grasp the shifts in HSR Second Requests over the past two years, Lighthouse's Bill Mariano interviewed Corey Roush, a partner at Akin Gump who leads their antitrust and competition practice, and is head of their FTC-facing consumer protection practice. Below is an excerpt from their conversation.The Biden administration has now had more than a year and a half to shape its approach to mergers and acquisitions. How do you view the landscape at this point?I see outward signs of moderate hostility towards mergers that have created general uncertainty. This owes mostly to statements by leadership at both agencies rather than unexpected actions. For the most part, we are seeing Second Requests issued when one would traditionally expect them, and we are also seeing some high-profile public transactions like Elon Musk/Twitter and PMI/Swedish Match avoiding Second Requests.What have regulatory agencies done to create this atmosphere?A handful of things, from making specific policy changes to expressing general disdain for consolidation. The discourse coming from regulators is guided largely by a July 2021 Executive Order from President Biden. Inspired by that order, FTC Chair Lina Khan told Congress that “significant consolidation has undermined open and competitive markets” so it’s her agency’s responsibility “to redouble [its] commitment to policing mergers.” That attitude was echoed by Assistant Attorney General Jonathan Kanter, head of the Antitrust Division at DOJ, who said mergers “can harm downstream consumers and upstream workers at the same time that they foster coordination or exclusion in adjacent markets. Everyone loses, except extractive powerful firms in the middle.”Disdain for consolidation, at least among the largest companies, is an increasingly bipartisan posture, by the way. Last spring Senator Josh Hawley (R-Mo.) introduced the Trust-Busting for the Twenty-First Century Act, complaining that a small group of “woke mega-corporations control the products Americans can buy, the information Americans can receive” and so on. The legislation would help regulators “crack down on mergers and acquisitions by monopoly companies” and even “pursue the breakup of dominant, anticompetitive firms.”There’s the hostility you mentioned. What about enforcement? How are they following through on this rhetoric?Overall, by expecting companies to accommodate the agencies. You see cases where companies agree to delay consummation until three or four months after complying with a Second Request, so that agencies have more time to review. And even when companies agree to delay consummation under a timing agreement, the agencies may ask for even more time. Last year, 7-Eleven was three days away from closing an acquisition when the FTC asked for more time — and this was after the company had already given the Commission more time on four separate occasions. The company was able to close the deal as planned and without a Commission vote because it had already negotiated a consent decree approved by the FTC staff. Two Commissioners responded with a public threat stating, “The parties have closed their transaction at their own risk. The Commission will continue to investigate to determine an appropriate path forward to address the anticompetitive harm and will also continue to work with State Attorneys General.” After all that, a “new” consent order was issued that was almost identical to the one that the company had previously agreed to and was approved by the Commission on a 4-0 vote two months later.It seems like “close at your own risk” is becoming a trend now?It is. The FTC has been issuing letters since the fall of 2021 warning parties whose regulatory review periods had expired or were about to expire that the agency was continuing to investigate the transaction, so parties who decided to close on their planned date would do so at their own risk. By early 2022, the DOJ joined the fray, issuing at least one warning letter that I’m aware of. So far, though, it appears to be a red herring. First, parties have always closed with some risk of a post-closing challenge. For instance, the FTC is currently challenging Facebook’s acquisition of WhatsApp and Instagram—deals that were consummated eight and ten years ago, respectively. Second, in the current landscape, companies have been closing despite receiving the letters, and we haven’t seen any efforts to unwind those deals. Nor have we seen many investigations actually continue. What other policy changes have altered the landscape for HSR and Second Requests?The big one in my mind affects prior approval. In July of 2021, the FTC — by a 3-2 party-line vote — adopted a new policy that requires “buyers of divested assets in Commission merger consent orders to agree to a prior approval for any future sale of the assets they acquire in divestiture orders.” This rescinds a nearly 30-year-old policy and creates real complications in the divestiture process. To state the obvious, an asset is less attractive if it comes with a restriction on its sale and a requirement that the divestiture buyer sign a consent decree with the FTC. We now see these agreements in consent orders regularly. That said, we have also seen at least one consent order that did not require the divestiture buyer to sign on. What distinguished that case from the others is unclear.What does this all mean going forward? What should parties expect from regulators?Longer reviews, with unpredictable engagement. Some deals that do not present clear competition problems are taking longer than one might traditionally expect. At the same time, we have avoided Second Requests even though, at first glance, there were competitive overlaps and/or vertical relationships. In those cases, along with competitive analysis proving the transaction wasn’t troublesome, our early engagement with the agencies appeared to be key. The uncertainty applies mostly to certain high-profile, high-scrutiny areas like tech, pharma, and agriculture. Deals outside of those areas appear to be more predictable and consistent with past scrutiny. So, will 2023 be more of the same?Most likely. Legislation like the American Innovation and Choice Online Act and Open App Markets Act have bipartisan support. Alvaro Bedoya was confirmed as the third Democrat Commissioner in May. And the antitrust agencies are working on new merger guidelines that could replace the current Horizontal Merger guideline and provide more guidance on vertical merger enforcement (the FTC rescinded the existing vertical guidelines last year). Given all this, we expect the trends of hostility and uncertainty to magnify in the near future.Hear from other experts and dive into the numbers in the 2021 Second Request Trends Report.antitrust; ediscovery-reviewediscovery-review, digital-forensics, antitrusthsr-second-requests; blog; mergersbill mariano
Blog
2021 Data Privacy Overview: New Regulations and Guidance
While everyone hoped that 2021 would be less tumultuous than 2020, it certainly did not turn out that way in the end. The same was true in the world of data privacy – with sweeping new data protection regulations and guidance issued throughout the year that made significant ripples. Below is a summary of some of the most important data privacy changes that will impact companies operating in the United States, Europe, and China in 2022 and beyond.US Regulation ChangesVirginia Consumer Data Protection Act (VCDPA)What it Does: Similar to the California Consumer Privacy Act (CCPA) and California Privacy Rights Act (CPRA) (jointly, the first GDPR-like data protection regulations passed within the US), the new Virginia regulation is a comprehensive data protection law that bestows certain rights and protections to Virginia residents regarding the use of their personal data, including:The right to opt out of having their data sold or used for targeted advertising, as well as the right to opt out of having their data used for “profiling” (i.e., using a person’s personal data to evaluate, analyze, or predict aspects of their economic situation, health, personal preferences, interests, reliability, behavior, location, or movements).The right to request that companies provide information about the personal data they have collected from them, and have it corrected or deleted.The right to request a free copy of their personal data in a portable, readily usable format.The law also requires companies to gain permission from citizens before collecting certain classes of highly sensitive personal data, including racial or ethnic origin, genetic data, and geolocation. The new law does not provide for a private right of action (i.e., it does not allow individuals to bring lawsuits against companies for data privacy rights violations). Instead, the law will be enforced by the state’s Attorney General.Who it applies to: All Virginia residents have rights under the VCDPA. Any company or organization that conducts business in Virginia and meets either of the following two criteria must comply with its requirements:Controls or processes personal data of at least 100,000 consumers; orDerives over 50 percent of gross revenue from the sale of personal data and control or process personal data of at least 25,000 consumers.Note that there are broad exemptions for financial institutions, as well as organizations or businesses that are governed by HIPAA or HITECH. Other exemptions include non-profit organizations and higher education institutions.When it takes effect: Jan. 1, 2023When it was passed: March 2, 2021Other notes: Tech industry trade groups and businesses heavily supported the VCDPA. Colorado Privacy Act (CPA)What it Does: Following in the footsteps of California and Virginia, Colorado was the third state to pass a comprehensive GDPR-like data privacy law. The new law conveys data privacy rights to Colorado residents that are nearly identical to the VCDPA, including:The right to opt out of the use of their personal data for sale or targeted advertising, as well as for the use in profiling decisions that would have legal or significant effects to the consumer (such as the use of personal data that may affect decisions regarding consumer lending, financial, housing, and insurance decisions).The right to request that companies provide information about the personal data they have collected from them, and request that it either be corrected or deleted.The right to obtain their personal data from a company in a free “portable” and readily usable format.Similar to Virginia and California, the law also classifies “sensitive data” as a separate category of personal data that requires additional protection, including: personal data that reveals racial or ethnic origin, religious beliefs, a mental or physical health condition or diagnosis, sex life or sexual orientation, or citizenship or citizenship status; genetic or biometric data that may be processed for the purpose of uniquely identifying an individual; or personal data from a known child under the age of 13. Note that Colorado’s definition of sensitive data does not include precise geolocation data, whereas Virginia and California’s data protection laws do.Who it applies to: All Colorado residents have rights under the CPA. Any company or organization that conducts business or produces commercial products or services that are intentionally targeted to Colorado residents and meet either of the following two criteria must comply with its requirements: Controls or processes personal data of at least 100,000 consumers in a calendar year; orDerives revenue from the sale of personal data and control or process the personal data of at least 25,000 consumers.The law specifically does not apply to state and local governments, state institutions of higher education, personal data governed by certain state and federal laws, and employment records.When it takes effect: July 1, 2023When it was passed: July 7, 2021Other notes: Similar to the VCDPA and to the CCPA, the CPA does not create a private right of action. Enforcement is exclusively with the state’s Attorney General and District Attorneys. Additionally, the act specifically states that a violation of its requirements is a deceptive trade practice for purposes of enforcement. Utah Cybersecurity Affirmative Defense ActWhat it does: Utah’s Cybersecurity Affirmative Defense Act provides new affirmative defenses that businesses in Utah can use to defend themselves against lawsuits arising out of a data security breach. The law states that an organization can affirmatively defend itself against a data security breach lawsuit that alleges that the organization failed to implement reasonable information security controls, so long as that organization maintained and complied with a written cybersecurity program that meets certain requirements spelled out within the law.The new law also allows an organization to defend itself against claims that it failed to appropriately respond to a cybersecurity breach, so long as its cybersecurity program had reasonable protocols in place for responding to breaches.Additionally, an organization can defend itself against claims that it failed to appropriately notify individuals effected by a data breach if the organization’s cybersecurity program had reasonable protocols in place for notifying individuals about breaches and those protocols were followed after the breach.In this way, the law provides an incentive for Utah businesses to implement updated cybersecurity programs to protect Utah residents’ personal data more effectively, by providing defenses to data breach lawsuits if such programs are implemented and followed.Who it applies to: Any person (which the law defines as an individual and most business organizations) that creates, maintains, and reasonably complies with a written cybersecurity program that meets the requirements spelled out within the act, and is in place during the relevant cybersecurity breach.When it takes effect: May 5, 2021When it was passed: March 11, 2021Other notes: The affirmative defenses are not available where the organization had advanced notice of a cybersecurity threat or risk. The law also states that it does not provide for a private right of action for failing to comply (thus private citizens may not sue organizations who don’t implement cybersecurity programs that meet the requirements spelled out within the law). California Consumer Privacy Act AmendmentsWhat it does: The amendments update the California Consumer Privacy Act (passed in 2018) to include three general changes relating to a consumer’s right to opt out of the selling of their personal information, and one change to authorized agent requests for information related to a consumer’s personal information.The three changes relating to a consumer’s right to opt out of the selling of their information include the following:Any business that sells personal information that it collected offline must now inform consumers in an offline method of their right to opt out, including instructions on how to do so.Authorizes the use of a specific “opt-out” icon that can be used in addition to posting the notice of the right to opt out (but not in lieu of that notice).Mandates that a business’s method for consumer request submissions to opt out must be easy to execute, require minimal steps, and not designed in a way that purposefully or substantially subverts or impairs a consumer’s choice to opt out.The change regarding authorized agent requests to a business on behalf of a consumer related to the consumer’s personal information includes the following:When a consumer uses an authorized agent to submit a request for information about the personal data a company has collected from the consumer (or requests to change or delete that personal data), the responding business may now require the authorized agent to provide proof that the consumer gave the agent signed permission to submit the request. The business may also require the consumer to do either of the following:(1) Verify their own identity directly with the business.(2) Directly confirm with the business that they provided the authorized agent permission to submit the request.This is a change from the previous version of the law, which mandated that the consumer provide the authorized agent’s signed permission, in addition to the other two requirements listed above.Who it applies to: All California residents have rights under the CCPA. Any for-profit business that does business in California and meets any of the following criteria must comply with the CCPA:Has a gross annual revenue of over $25 million.Buys, receives, or sells the personal information of 50,000 or more California residents, households, or devices; orDerives 50% or more of their annual revenue from selling California residents’ personal information.When it takes effect: March 15, 2021When it was passed: March 15, 2021 GDPR ChangesNew Standard Contractual Clauses (SCCs) Issued by the European CommissionWhat it Does: The SCCs are a contractual device used to help ensure that personal data transferred outside the EU is kept secure and complies with GDPR requirements, wherein the entity receiving the data contractually agrees to protect the transferred personal data according to stringent GDPR requirements. After the 2020 invalidation of the EU-US Privacy Shield, SCCs are now one of the only viable GDPR-compliant methods for entities within the US to receive personal data from entities in Europe.The new SCCs take into account the decision-making behind the invalidation of the EU-US Privacy Shield. Whereas the old SCCs were rigid, the new SCCs provide a bit more flexibility. They are now “modular,” meaning entities can now choose from a selection of four different models, depending on the type of transaction: controller to controller; controller to processor; processor to sub-processor; and processor to controller. They also expand the rights given to data subjects, including the right to enforce SCC provisions against both the data exporter and data importer. Additionally, the SCCs mandate that data importers must agree to EU jurisdiction (including EU courts as well as compliance with applicable EU data protection laws). There is also a new optional clause (Clause 7) that allows new parties to be added to the SCCs, as well as new Annexes that must be customized for each transaction.Who it applies to: A data importer located in a country without an EU adequacy decision (like the US) that is not itself subject to the GDPR should utilize the new SCCs to transfer personal data from the EU – unless exceptions apply (i.e., the parties are able to rely on an alternate transfer mechanism, etc.). However, Recital 7 of the new SCCs appears to state that when the data importer is itself subject to the GDPR (for example, because the company provides services or goods to individuals living in the EU), the new SCCs cannot be used. This language has left open questions around what transfer mechanism companies should use in that situation (see below for a summary of additional guidance issued by the European Data Protection Board surrounding this issue).Additionally, due to Brexit, the new SCCs do not apply in the UK. The UK Information Commissioner’s Office (ICO) has launched a public consultation on drafting a new set of SCCs for use within the UK.When it takes effect: The new SCCs became effective on June 27, 2021. Any new contracts and processing transactions taking place after September 27, 2021 must use the new SCCs. Any contracts entered into prior to September 27th, 2021 must be updated with the new SCCs by December 27, 2022.When it was issued: June 4, 2021 New Guidance for Cross-Border Data Transfers Issued by the European Data Protection Board ("EDPB")What it Does: The invalidation of EU-US Privacy Sheild in 2020, along with the new SCCs (above), has led to uncertainty around how to comply with the GPDR when transferring data between the EU and countries such as the US that do not have an adequacy decision (i.e., a decision by the European Commission that a country outside the EU offers adequate levels of data protection to safely protect EU personal data that is transferred there). In particular, language within the Recitals of the SCCs states that the new SCCs only apply to data transfers between a data exporter and a data importer who itself is not subject to GDPR. This language has left open questions around what type of transfer mechanism (if any) is needed for a transfer of data to an importer that is already subject to the GDPR.New guidance issued by the EDPB provides some concrete answers to a few of these questions, as well as resolved some other long-standing murkiness about cross-border transfers (even if the guidance does not resolve all uncertainty).For example, the guidance now definitively states that data transfers from an EU-based data exporter to a data importer based outside the EU is, in fact, a transfer within the meaning of Article 44 of the GDPR and therefore would require the importer to enter into an SCC (or possibly adopt Binding Corporate Rules). However, as noted above, if the importer is itself subject to the GDPR, Recital 7 of the new 2021 SCCs state that the new SCCs cannot be used, leaving open the question of what SCC should be used in that situation. Note that the minutes to the European Data Protection Board plenary meeting held in September of 2021 mention that the EU Commission will issue a new set of SCC to govern this type of data transfer.The guidance also settled some long-standing questions around other types of transactions that are not considered transfers of data under Article 44 of the GDPR. For example, the new guidance affirmatively states that “direct collections” of personal data from individuals located within the EU does not constitute a transfer of data (because when the information is collected directly, there is no transfer between controller and processor). It also clarified that “intra-company” data transfers are not considered a transfer of data under Article 44 because a transfer requires two parties. However, note that while these transactions are not considered “transfers” under Article 44, all other applicable GDPR protections still apply and must be followed.Who it applies to: The guidance will be particularly useful for any non-EU organization that needs to transfer or collect data from within the EU. When it takes effect: November 19, 2021When it was issued: November 19, 2021 Other New RegulationsChina’s Personal Information Protection Law (PIPL)What it does: China’s new Personal Information Protection Law is a GDPR-like comprehensive data protection law aimed at protecting the personal information of “natural persons” located within China. It governs how companies collect, process, and transfer personal data of people within China and like the GDPR, is exterritorial in its reach – meaning it applies to companies outside of China that handle the personal data of someone located in China. Also like the GDPR, it allows individuals in China to request access to their personal data that a company has collected and ask for it to be corrected or deleted. And like the GDPR, the regulation includes the risk of large fines against companies that fail to comply with its mandates – including up to five percent of a company’s annual revenue. However, unlike the GDPR, failure to comply also includes the risk of being “blacklisted” by the Chinese government, as well as possible criminal penalties.Multinational organizations with Chinese employees should also be aware that the law contains specific regulations regarding transferring the personal information of Chinese employees across the country’s borders. This means that companies cannot transfer internal employee information (including typical information routinely handled by a company’s HR department) outside of China’s borders without the consent of the employee and meeting other specifications spelled out within the law.Who it applies to: The PIPL protects the personal data of people located in China. It applies to companies operating in China, as well as organizations outside of China that process the personal data of people within China for any of the following reasons:(1) To provide products or services to people in China;(2) To analyze or assess the behavior of people in China; or(3) Any other circumstances that falls under unspecified Chinese laws and regulations.When it takes effect: November 1, 2021When it was issued: August 20, 2021data-privacydata-privacyblog; data-protectionsarah moran
Case Study
The Challenge A national healthcare provider faced 14 related matters across 9 jurisdictions, with 11M documents dispersed across multiple vendors, databases, and case teams.Redundant Review Is a Data Problem, Not a Legal OneWith a traditional eDiscovery model, each matter would have required reprocessing, rehosting, and/or rereviewing large portions of the same data. Data insights and work product would be siloed inside individual matters and within disparate legal teams. This would severely escalate costs and drive inconsistent outcomes and operational drag.The SolutionLighthouse recognized that the problem wasn’t just data volume. It was the absence of a system that could learn across matters and apply that intelligence forward. With LighthouseIQ, counsel could take a fundamentally different approach—using a centralized, AI-backed data system guided by expert judgment, where decisions, insights, and work product flow seamlessly between matters and legal teams.AI-Backed ResultsReduced 11M documents to 90K requiring reviewReused 100K coding decisions across 14 related mattersAvoided duplicate hosting, processing, and review of 1.2M documentsEnabled instant productions from a national database with LighthouseIQ$650K in cost savings delivered with consistency and defensibility built in, not traded offBuilding Human-Guided AI at Multidistrict ScaleStep 1: An AI-Powered Data Repository, Expertly DesignedLighthouse migrated all 11M documents (from both Relativity and non-Relativity sources) into a single LighthouseIQ hosting environment. Lighthouse experts designed the repository architecture upfront to support cross-matter reuse and long-term litigation strategy.Lighthouse eliminated duplicate hosting, processing, and review of 1.2M documents.Step 2: AI Normalization and Cross-Matter MatchingWithin the repository, LighthouseIQ normalized documents and applied proprietary hashing to identify duplicates, near-duplicates, and previously reviewed content across matters. Lighthouse experts validated how matches and inherited decisions were applied, ensuring accuracy, consistency, and defensibility across jurisdictions.Lighthouse reused 100K coding decisions across matters.Step 3: AI-Guided Prioritization, Expert Review StrategyLighthouse review experts designed one strategic review plan for all 14 matters that lowered costs and maximized data reuse and cross-matter insights. Using cross-matter intelligence, IQ Review identified 150K documents (from within the 11M housed in the repository) that were most likely to be responsive across jurisdictions.This dataset was published to the national review database and fully reviewed by an experienced Lighthouse review team (trained by Lighthouse review managers) to categorize each document for both national and jurisdictional responsiveness. After review, Lighthouse copied this strategic production set to each jurisdictional database. This approach kept hosting costs drastically lower for each individual matter, while providing all local case teams with an immediate first production, well ahead of production deadlines.Out of 11M documents, just 90K required human review.Step 4: Continuous Learning Through a Human-in-the-Loop Feedback CycleAfter production, expert-approved coding decisions were fed back into the repository. LighthouseIQ automatically matched those decisions to corresponding documents across matters, creating immediate efficiencies while preserving expert intent. With every matter, the system became: more informed, more consistent, more cost-effective.The Results: A System That Gets Smarter Over TimeBy using LighthouseIQ, a sprawling, multidistrict litigation environment was transformed into a reusable intelligence system. The client achieved significant cost savings and faster productions, without sacrificing judgment, consistency, or defensibility.In the process, LighthouseIQ delivered $650K in cost savings.
Turning 11M Docs Into a Cross-Matter Intelligence System with LighthouseIQ
Case Study
The ClientThe client operates at the forefront of AI innovation while simultaneously navigating heightened regulatory oversight and increasingly complex civil litigation.The Legal ChallengeOver the past two years, this client has faced a sharp increase in high-profile, high-stakes litigation and regulatory investigations. Matters often involve novel technologies, modern collaboration and messaging platforms, and compressed response timelines.This was creating sustained pressure on traditional eDiscovery models and legacy discovery tools, which proved to be inefficient and difficult to scale at the speed required. Repeated data recollection, redundant review, and inconsistent issue identification also introduced unnecessary costs and risks. The client needed an approach that could apply intelligence across matters, learn from prior work, and deliver defensible results quickly.The Lighthouse SolutionWe implemented a LighthouseIQ-driven eDiscovery program capable of scaling across the client’s litigation and investigative portfolio, prioritizing the client’s need for speed, consistency, and defensibility. Through the rapid design and deployment of this framework, Lighthouse has helped the client:Meet aggressive discovery and regulatory obligationsReduce eDiscovery risk across multiple concurrent mattersSave hundreds of thousands of dollars in just a few monthsMaintain consistency, defensibility, and institutional knowledge across a growing litigation portfolioAs new matters arise, the program continues to scale, leveraging prior AI-driven insights rather than restarting the discovery process with each engagement.Pillars of the LighthouseIQ eDiscovery ProgramIn 2024, Lighthouse launched a programmatic eDiscovery initiative for this client that was grounded in what would become the LighthouseIQ platform and application suite. The objective was to move beyond point solutions and instead create an adaptive framework that continuously improves as new matters arise. The pillars of this framework and the results achieved in just the first year are below.Reusing Work Product at Scale with LLM-Backed TechnologyLighthouse built a centralized data repository designed specifically to support work product reuse across litigation. Each matter is maintained in its own siloed workspace, where LighthouseIQ is used to:Identify when prior work product is relevant to new mattersReuse review decisions, key documents, and privilege determinationsControl reuse across matters while maintaining strict, matter-level silos for privilege and confidentialityThe result:Reduced unnecessary recollection and reprocessing across litigation by over 10 terabytesSaved tens of thousands of dollars by minimizing duplicative attorney review while improving cross-matter consistencyAccelerating Fact Development Under Regulatory DeadlinesThe impact of LighthouseIQ has also been pronounced in matters requiring rapid issue and document identification under regulatory pressure. In a recent regulatory inquiry, outside counsel had only days to identify critical facts from hundreds of thousands of documents. This timeline would have been impossible to achieve using traditional search and review technology.Lighthouse deployed IQ Case Strategy to:Rapidly analyze hundreds of thousands of documentsSurface the key documents tied to three core legal issuesPrioritize results for attorney review within daysThe result:Reduced review costs by more than $100,000Completed the regulatory response within two weeksDelivered the documents attorneys needed within days (vs. the months it would have taken with traditional search tools), giving them more time to work on data-backed legal analysisBuilding a Defensible Forensics FoundationLighthouse also designed and implemented a centralized forensics collection program spanning all of the client’s major data sources, including:Google Vault and Google DriveSlackMobile devicesNon-standard messaging and social applicationsThe forensic program addressed nuanced challenges that arise in modern data environments, including the preservation, collection, and treatment of hyperlinked attachments, particularly where contemporaneous versions are unavailable. Lighthouse’s forensic team improved collection efficiency and defensibility by:Developing a core forensics playbook to standardize data retrieval across mattersDesigning targeted collection workflows that leverage usage and access patterns to prioritize files actually accessed by custodians, significantly reducing over-collectionThe result:Improved collection consistency across matters while minimizing unnecessary data processing and review via a repeatable forensic program
LighthouseIQ Saves Hundreds of Thousands in Months
Case Study
Background Regulators issued a sweeping investigation tied to a global company’s high-profile acquisition. The scope and timeline were demanding: more than 30TB of data required analysis, risk assessment, and production in less than 30 days. A defensible, scalable approach that met regulatory requirements while controlling cost, mitigating risk, and ensuring flawless execution was non-negotiable. The Lighthouse Approach LighthouseIQ eliminated unnecessary human review, decreased scope early, surfaced risk faster, and executed at scale without errors. Key elements included: IQ Review used AI to surface only what truly required human judgement. In parallel, a 300-person managed review team was rapidly ramped to handle the doc volume. IQ Priv accelerated privilege identification and used generative AI for privilege log drafting and names list creation. Key documents identified via modeling in parallel to review. Cross-matter analytics and work-product reuse across a parallel antitrust litigation Custom operational workflows, including M365 cloud attachment linking and secure reuse repositories All of it executed in parallel. No bottlenecks. No rework. Results 10TB, including 20M images were produced with M365 cloud attachments as required by regulators in under 60 days. This delivery boasted an 100% error-free production result and $20M in total cost savings. Cost avoided:
$20M in Savings in a High-Stakes, Fast-Paced Matter
Case Study
When an engineering partner suddenly pulled out of a major project, a global manufacturer needed answers fast. Was the termination allowed under the contract, or had the partner crossed a line that could lead to litigation? The company’s law firm had to move quickly. A deadline was approaching to file a termination claim, but that was only the first step. Once the partner responded, the firm expected tough follow-up discovery. To be ready, they needed to understand the full story before the dispute escalated. The firm identified and collected more than one million documents across fifteen custodians, most in the United States. While this is a large but not uncommon volume of data for such a complex investigation, the real challenge was determining how to interrogate it quickly without iterating dozens of times on keywords as is the case with traditional keyword search. As one attorney explained, “Most of the time, we don’t know the exact words people used and everyone uses different language anyway.” Every guess costs time, and every missed variation risks overlooking critical evidence. The Lighthouse ApproachLooking for a faster and more reliable approach, the firm used Lighthouse IQ Answers directly inside their Relativity environment, starting with Microsoft 365 data from the U.S. custodians. IQ Answers is not a general-purpose chatbot. It’s an enterprise AI tool that leverages large language models and other AI and ML models to answer questions but is grounded solely in the documents in your case. Instead of building complex keyword searches, attorneys simply asked questions and received clear, document-backed answers. Using this approach, the team conducted an early case assessment without relying on months of manual review. Once all documents were loaded, they used the AI to explore the data directly. Over the course of less than two months, the team asked 182 natural-language questions. That process captured 6,325 documents, of which the team flagged 835 as potentially important. To confirm the results, the firm conducted a second-level manual review of those documents. Attorneys validated 190 documents as key evidence and identified another 130 as potentially key. Notably, 832 of the 835 documents directly related to the 14 issues identified for the case. By combining AI-driven discovery with focused human review, the team turned an overwhelming volume of data into clear, actionable insight—delivering results in a fraction of the time required by traditional methods. Based on the intelligence IQ Answers delivered, the firm made a critical strategic decision: they opted against a full review. What would have been months of traditional document review and significant expense became a targeted, AI-driven investigation that gave them exactly what they needed in pre-litigation.
AI-Powered Search Speeds Time to Answers in Contract Dispute
Case Study
BackgroundThe client faced a high-stakes Hart Scott Rodino (HSR) Second Request with tight compliance deadlines under FTC oversight:7.5M documents (7.8TB) were collected in 2 phases from 28 custodians collected across email, collaboration platforms, mobile data, and hard copy sources.Differentiated responsiveness standards between groups of custodians, requiring tailored review strategies.The matter was re-opened months later and additional documents requested.The Lighthouse ApproachThe team implemented both IQ Review and IQ Priv, combining AI analysis with disciplined managed review execution. Key elements included: AI-supported relevance review and a team of 30 contract attorneys for documents that required eyes-on review Privilege review, privilege log and names legend automation via AIAI image analysis for visual and scanned contentTwo separate AI models were trained to address differing responsiveness criteria across custodial groups, ensuring precision without sacrificing defensibility.ResultsLighthouse successfully processed 7.5M total documents across both collections. Because our AI models remain largely stable even with new documents, analysis of the second phase of collection was able to start immediately. LighthouseIQ powered analysis meant that only 2,500 contract review hours were needed in total. Using AI insights, our contract review attorneys maintained high review velocity across responsiveness, privilege, and PII review streams. The approach delivered FTC-ready defensibility under close regulatory scrutiny while enabling rapid adaptation to an evolving regulatory scope. Through expert coordination across legal, technical, and review teams, the engagement delivered predictable, consistent performance even under compressed timelines and shifting requirements.
Scaling Review with AI for FTC Compliance
Case Study
Key Events and OutcomesClient initiated an internal investigation into executive misconduct, requiring high-precision document discovery and behavioral analysis.Multiple workstreams delivered: thematic overviews, interview prep kits, and targeted behavioral evidence.Lighthouse Expert Search team employed across multiple time zones enabled seamless adaptation to shifting priorities.The Expert Search team delivered 160 total key documents over four days in three deliveries to accelerate the time to knowledge and minimize the risk of missing critical evidence.Enabled counsel to prepare targeted witness interviews by surfacing behavioral evidence and operational insights.What Was NeededA large retailer launched an internal investigation after receiving whistleblower allegations of misconduct. The project required rapid, high-precision document discovery and behavioral analysis across a substantial volume of internal communications. The client needed thematic overviews of key communications, curated document sets to support interview preparation, and targeted behavioral insights to inform legal and internal review. All work had to be completed within a single week to enable critical witness interviews and support preparation of a summary report for outside counsel.ProcessThe first step in triaging the needs related to the matter involved outside counsel conducting initial research using Lighthouse AI Search. This early facts assessment confirmed that the central concerns of the investigation were reflected in the data, and helped refine the goals and targets for a hand-off to the Lighthouse Expert Search team.Leveraging insights from counsel’s initial use of AI Search, the Expert Search team used advanced techniques developed within Lighthouse’s proprietary systems to support Key Document Identification workflows. These methods, combined with tagging and document filtering workflows for compliance and legal review, targeted queries of linguistic patterns, indicators of tone and behavior, and other expressions of language.In parallel, Lighthouse AI Search powered conceptual and semantic queries, surfacing nuanced patterns and sentiment indicators across a voluminous set of 300,000 documents. The combined technology and workflow approach allowed the Expert Search team to precisely identify the documents of highest importance and potential impact for the investigative team. Volume-reduction methodologies were applied to isolate the most likely relevant, non-duplicative content. Linguistic and behavioral searches focused on topics prioritized by counsel, with results delivered on a rolling basis to support interview preparation and legal review.Throughout the project, the Expert Search team worked in close coordination with the matter team, leaning on global coverage to provide seamless support and incorporating feedback into iterative search cycles.Expert Search ResultsThe Lighthouse Expert Search team delivered three waves of curated document sets totaling approximately 160 records, each tagged with Expert Search topics and annotation fields to support rapid review. This enabled highly targeted interview preparation by surfacing behavioral indicators, communication patterns, and operational insights relevant to the investigation. The outputs integrated into client workflows, including saved searches and coding layouts within the review platform.By combining multiple information retrieval, analysis, and synthesis technologies and augmenting with human expertise, the team surfaced unique documents responsive to similar lines of inquiry—providing broader and more comprehensive information coverage in a shorter time frame than any single approach could have achieved alone.
Lighthouse AI Plus Expert Search Accelerates Internal Investigation Needs
Case Study
A global consumer products company with a distributed workforce needed to strengthen its information security posture. With sensitive intellectual property, regulatory obligations across multiple jurisdictions, and increasing use of Microsoft 365 collaboration tools, the security team sought a more resilient approach to protecting critical data against leakage, misuse, or unauthorized access.
Challenge
The existing environment lacked unified policies for sensitivity labeling, retention, and data loss prevention, making it difficult to enforce consistent governance across all business units.
The client faced significant risks around:
Data leakage from collaboration data in Microsoft Teams, SharePoint, and OneDrive.
Lack of consistent data classification leading to overexposed sensitive content.
Insufficient DLP controls for email and cloud-based sharing, creating regulatory and reputational risks.
Growing compliance pressure across global operations, requiring alignment with GDPR, CCPA, and industry-specific regulations. Solution
Lighthouse partnered with the client to design a comprehensive Microsoft Purview Information Protection and Data Loss Prevention (DLP) framework pilot that could scale globally. The solution included:
This design provided the foundation for both proactive risk reduction and reactive incident handling.
Results
Through this engagement, the client achieved:
Reduced risk of data exposure by applying consistent labeling and DLP rules across collaboration platforms.
Improved regulatory compliance by aligning information protection policies with global privacy and industry frameworks.
Enhanced incident visibility with reporting dashboards and adaptive policies that alerted security teams to high-risk events.
Sustainable governance model enabling scalability as new collaboration tools and AI-driven workflows are adopted.
Why It Matters
As global enterprises accelerate digital collaboration, data security gaps in Microsoft 365 environments can create regulatory, financial, and reputational risk. By implementing a comprehensive governance and DLP framework, organizations can protect their most valuable assets: intellectual property, customer data, and regulated records, while enabling employees to work securely across borders.
This project highlights how a well-designed information protection program, supported by Microsoft Purview, can simultaneously strengthen security and simplify compliance for multinational companies.
Enhancing Data Security and Compliance with Microsoft 365 Information Protection & DLP
Case Study
Lighthouse Governance Support Services Prepare Clients for Microsoft Purview eDiscovery Changes
Case Study
Challenge Antitrust regulators issued a broad, high-stakes HSR Second Request to investigate a global company’s high-profile acquisition. To comply, the company and their outside counsel were faced with analyzing 30+ TB of data in less than a month.Solution Lighthouse developed an AI driven approach powered by Lighthouse’s proprietary Large Language Models (LLMs) to eliminate relevance review, substantially reduce privilege review, perform privilege logging and assemble the names list, and identify key documents to mitigate risk without linear review.Simultaneously, Lighthouse operational teams executed multiple custom workflows to process and produce over 10TB+ of data and 20M+ images in 3 weeks—flawlessly.Their work included building a custom linking workflow for M365 cloud attachments and a secure data repository for work product reuse in a related antitrust litigation, while ramping a 300-person linear review team via Lighthouse’s Managed Review solution to meet the aggressive production deadline.Lighthouse AI Savings & ROI Breakdown Overall, using Lighthouse AI saved $20M+ with the following workflows: TAR powered by Lighthouses AI proprietary LLMsPrivilege identification powered by Lighthouse AI proprietary LLMsPrivilege log and names list generation via Lighthouse AI proprietary LLMsKey document identification powered by linguistic modeling and AIJunk file analysisCross matter analyticsHighlights of each of these workflows and the associated ROI are below. Lighthouse’s Proprietary Predictive AI for Relevance: 40% Narrower Responsive Set Than Other TAR Tools Counsel only needed to review around 4,000 documents to stabilize and validate a TAR model backed by Lighthouse’s predictive LLMs that measured 85.91% precision at 76.49% recall. Lighthouse’s predictive AI model for relevance is shown to deliver a 30-40% smaller and more accurate R-set based upon comparative bake-offs. Had Lighthouse implemented a Second Request workflow using commercially available TAR tools, we would have likely seen a much broader responsive set, thereby requiring additional privilege review and production.Specifically, if Lighthouse had used traditional TAR tools, it would have resulted in an estimated additional 2M documents in scope for production, translating into approximately $5.8M in additional privilege review costs and $400,000 in added production expenses—costs avoided by using Lighthouse Responsive AI.Separately, Lighthouse’s Review Management team performed Junk File analysis and identified that around 95,000 documents out of the more than 860,000 non-TAR eligible documents were highly likely to be junk and could undergo a sampling workflow instead of a full linear review.Privilege Review: 45%+ Reduction Lighthouse built an AI model for privilege that both removed documents from privilege review and accelerated the remainder. Using a tiered approach, counsel determined that around 780,000 documents (out of the more than 1.7M eligible for privilege review) could be removed from privilege review without linear review because they fell below the cutoff score and were unlikely to be privileged.Once the privileged documents were identified, Lighthouse’s generative AI was used to create first-pass privilege descriptions for the more than 100,000 documents on the privilege log. This removed the need for human drafting of log lines. As a result, the log required an investment of mere hours as opposed to days and the heavy expensive of a full contract attorney review and outside counsel QC.Lighthouse also used generative AI to build the names list for the privilege log. Lighthouse’s AI model quickly analyzed around 130,000 documents to identify and provide close to 15,000 normalized names with titles for the privilege log. Key Document Identification The Lighthouse AI team used modeling to quickly surface documents that could pose an antitrust risk to the company. This process eliminated the need for the more dated approach of search+linear review for key documents and issues tags. Out of an initial tranche of 4.4M documents, the Lighthouse team identified roughly 270 documents of the greatest interest and sensitivity and delivered them to counsel in 5 deliveries over the course of just 3 weeks.To provide additional support to counsel, the Lighthouse AI team also categorized the final Responsive document set based on risk profile—classifying a broad set of documents as Likely Risky and Likely Safe over the course of just 1.5 weeks.Work Product Reuse for Cross-Matter EfficiencyThe Second Request had a large set of overlapping data with a concurrent antitrust litigation. To ensure there was no duplicative review and to drive consistency, Lighthouse built a secure data repository that enabled work product reuse between this Second Request and that concurrent litigation and used Lighthouse AI to drive cross matter analytics. With Lighthouse AI, Lighthouse repurposed calls for around 680,000 documents, resulting in a savings of $3.5M between first pass review, 1L QC, and outside counsel QC.Speed, Quality, and Operational Delivery The scale and complexity of this Second Request required an extraordinary cross-functional effort across several Lighthouse Client Services and Operational teams who worked tirelessly to deliver a seamless, high-quality result under immense time constraints. The core of this matter was completed in under 60 days, demonstrating an exceptional level of execution.Key highlights of the operational delivery include: High-Volume Processing and Custom Workflows: Lighthouse processed over 30TBs of data, ensuring rapid ingestion, indexing, and AI-powered classification. A custom workflow was implemented to link M365 cloud attachments, meeting regulatory requirements.Flawless Data Production at Scale: Within 3 weeks, the Lighthouse team produced over 10TBs of data and more than 20M images, achieving a 100% error-free production result. This ensured compliance without delay or rework.Scalable Review Team for Complex Work Streams: Leveraging our Managed Review capabilities, Lighthouse rapidly scaled a linear review team to 300 professionals. The team expertly navigated multiple complex work streams, dynamically segmenting data to mitigate risk while accelerating the review process to meet the production deadline. The bulk of review ramped and concluded in a mere 4 weeks. This work showcases the coordination, detail, operational excellence and sheer dedication of the Lighthouse team in delivering a timely, high-quality outcome in an intense regulatory investigation.
Lighthouse Delivers $20M Savings in Fast Paced Second Request
Case Study
Client: Global academic medical system Stakeholders: CISO, Information Governance, Legal Tech stack: Microsoft 365 + Microsoft Purview (SharePoint, OneDrive, Exchange, Teams) Objective: Identify, label, and protect high‑value IP across M365 Business Challenge Conventional pattern matching missed nuanced research content; labels were inconsistent. Emerging IP taxonomy lacked consistent, enforceable labels across repositories. Conventional pattern matching couldn’t reliably detect unstructured, nuanced IP. Teams needed clarity on when to use Sensitive Info Types (SITs), Exact Data Match (EDM), and Trainable Classifiers, and how to govern them. Wanted to compare outcomes with prior third‑party classifiers. What Lighthouse Did IP Taxonomy + Purview Labels Mapped proprietary IP categories to a label set Blended Classifier Strategy Combined SIT, EDM, and Trainable Classifiers Operationalize Piloted and tuned models aligned with retention/legal hold/eDiscovery, with auto‑labeling and user prompts. Controls Developed change‑management materials Outcomes Common IP Language: Agreed taxonomy mapped to enforceable labels. High‑Confidence Detection: Trainable classifiers surfaced custom IP Consistent Protection: High‑value content auto‑labeled with policy‑driven controls in M365. Governed Workflows: Clear guidance on SIT vs EDM vs Trainable; fewer false positives/negatives; faster to eDiscovery. Timeline Weeks 0–1 — Kickoff + Plan Weeks 2–4 — Design + Setup Weeks 5–9 — Run Pilots Weeks 10–11 — High Level Design + Training Why Microsoft Purview for Data Protection Enterprise-wide strategy - Unified data security, governance, compliance Integrated governance - DLP, retention, legal hold, eDiscovery Flexible detection models - Sensitive Info Types, Exact Data Match, Trainable Classifiers Persistent, label-based protection - Embedded permissions travel with data
Protecting Proprietary Clinical IP in Microsoft 365
Case Study
Key ResultsDocument set reduced from 750,000 to 158,000 documents Review speed increased from 10 to up to 60 docs/hour from bulk issue coding AI privilege model trained for reuse, improving speed and consistency 310 key documents identified across six core topics Production delivered with confidence, accuracy, and defensibility The Challenge: A Sweeping Request and a Tight Timeline At the outset, the FTC issued an expansive request that pulled in more than 750,000 records including emails and Slack messages. Agreement on keywords proved difficult, as regulators pushed for maximum disclosure.Lighthouse supported outside counsel through nine rounds of negotiation, including line-by-line responses to regulator objections, landing on a refined population of 158,000 documents—an 80% reduction in review scope. Review at Scale: Fast, Focused, and Credible One immediate challenge with prioritized document review for this matter was the large number of issue codes. Previously, similarly complex issue codes had slowed review to just 10 documents per hour. Moreover, outside counsel expected the FTC to heavily scrutinize the issue code distribution, making accuracy and nuance critical. To guide reviewers away from default or overly broad issue codes, a classifier was used to apply issue codes to responsive documents. Three refinement cycles ensured the issue codes were applied accurately, and as counsel directed. This method not only passed regulator scrutiny, review was accelerated by 4.5-6x. Key Document Identification and Proactive QC In parallel to review, Lighthouse began 4 rolling deliveries of key documents supporting six topics. Over four weeks, the team surfaced a highly-curated set of 310 documents to support case strategy. The work to identify key documents was also used to identify documents that were likely under-coded by contract reviewers—enabling the team to course-correct in real time. Building an AI Privilege Model for This Matter—and the Next The team next trained an AI privilege model to support privilege review, not just for this matter, but for future matters as well. The process began with a linguistically curated sample set, which counsel coded with future applicability in mind. The trained AI privilege classifier analyzed documents, delivering outputs in Relativity, allowing reviewers to reference privilege scores as part of their decision-making. Technical Execution: Overcoming Real-World Complexity Behind the scenes, Lighthouse had to address several technical hurdles. The review was hosted in RelativityOne, and initial data connectors required custom adjustments to work with the client’s Slack and metadata structure. In particular, Lighthouse developed a workaround to solve for Slack transcripts, which didn’t have file extensions, thus breaking standard ingestion processes.
Using AI, a Tech Company Reduced Review by 80% and Produced to Regulators with Confidence
Case Study
The ChallengeIn a high-stakes regulatory investigation for a heavily regulated client, outside counsel faced a massive task: produce a 200,000-entry privilege log with specificity, consistency, and speed—without drawing regulatory fire. The Lighthouse SolutionLighthouse’s GenAI-powered privilege log solution gave outside counsel something neither traditional privilege log methods or other GenAI privilege log solutions could: customized, defensible entries at scale—with almost no manual drafting by review teams or outside counsel. What set it apart? The human-in-the-loop model. Lighthouse AI experts partnered with the legal team to fine-tune outputs for that matter’s unique needs, iterating on key components of each log line until the results were exactly right. Why It WorkedRather than force-fit the log into one-size-fits-all templates or get stuck with GenAI outputs that weren’t a good fit for this very unique matter, Lighthouse tailored and continuously iterated our GenAI prompting across three key dimensions: Document Type (e.g., Email, Memo) Legal Hook (Why the document is privileged e.g., “requesting legal advice”)Subject Matter (What the privileged information is generally regarding)How We Did ItOutside counsel needed subject matter descriptions to be as specific as possible without giving away privilege content, while creating uniformity across the document type and legal hooks based on the unique documents at issue in the investigation. Through prompt engineering and targeted feedback with outside counsel, the AI’s first draft evolved from raw potential to precision output that exactly met their needs:100+ document types condensed to a consistent set of 9 that outside counsel needed 80+ legal hooks refined down to 8, specific to the way attorneys worked at the underlying company 120,000+ unique Re: line descriptions that explained specific legal projects and work, none reused more than 1% of the time The Results200K+ log entries generated on a tight timeline No vague or red-flag phrasing—achieved by iterating with GenAI prompts to ensure that negative language caught in QC was removed across the entire privilege log Near-zero manual drafting by the legal team Custom configurations (e.g., suppressing references to specific entities) tailored to client preferencesFocused QC efforts where it mattered—resulting in massive time and cost savingsThe ROIOutside counsel’s job? Review, not write. By shifting their time to targeted QC and feedback instead of manual drafting, the legal team met their deadline under pressure—and under budget.
Custom, Not Cookie-Cutter: How Lighthouse AI Delivered a Tailored 200K Privilege Log
Case Study
Company Overview A global Fortune 500 manufacturing company with facilities and offices across North America, Latin America, Europe, Asia, and Australia.ChallengesThe company was evaluating Microsoft Purview E5 licenses to support its information protection, insider risk management, data loss prevention, and sensitivity labeling goals. The data protection team needed to validate the efficacy of the Purview tools when applied to company data within their M365 environment. The data project leader shared a list of use cases to test against the platform’s risk identification and alert capabilities. SolutionLighthouse’s consultants designed and ran a four-month pilot to test Microsoft Purview’s sensitivity labeling, Data Loss Prevention (DLP), Insider Risk Management (IRM), and Defender for Cloud Apps capabilities across the client’s live Microsoft 365 environment. The team configured and validated more than 10 distinct data protection policies, including global personal information labels for Exchange, Teams, OneDrive, and endpoint devices. The project included six sensitive information types (such as PII, PCI data, and passport numbers), and piloted risk-based alerts for questionable user and departing employee behavior. Lighthouse developed a detailed Report Card and Recommendations Report, delineating a clear path for full implementation of validated controls company-wide. Key OutcomesDuring the initial four-month engagement, Lighthouse’s experts successfully validated each use case, demonstrating that Microsoft Purview E5 was indeed the correct tool for the client’s data protection needs. The client purchased Purview E5 licenses and engaged Lighthouse to guide the full implementation of all the capabilities we had piloted. By following the guidance of Lighthouse data experts, the company’s data protection team developed an ongoing, flexible data protection strategy and program which mitigated multiple risks by automating data classification, labeling, and user notifications. Lighthouse helped this client accelerate its data protection maturity model and establish best practices, workflows, and classifiers to strengthen data privacy and security. We can do the same for you. Contact an expert to get started.
Global Manufacturing Company Onramps to the Purview Data Protection Highway
Case Study
During the first trial of a high-stakes, serialized product liability case, a legal team was stunned when opposing counsel introduced damaging documents that had originated from the client’s own production. Despite months of review by both in-house and outside counsel, these documents had slipped through the cracks—threatening to derail the case and set a dangerous precedent for future litigation.With millions at stake, they needed a solution—and fast. They turned to Lighthouse. In just three days, a Lighthouse expert dug into the 25,000 documents in the production, uncovering 14 crucial rebuttal documents that counsel used at trial to challenge the plaintiffs’ claims.This swift, targeted response set the client up for success and in a position to save the company millions of dollars in judgments and protect them from similar challenges in upcoming cases.In the world of serialized product liability litigation, where one case can impact many others, the power of rapid, focused eDiscovery can be the difference between a costly loss and a decisive win.
Turning the Tables: How Lightning-Fast eDiscovery Defense Saved Millions
Case Study
SolutionThe Director of Information Security partnered with Lighthouse to conduct a comprehensive scan using Lighthouse’s proprietary environment scan technology and Microsoft Information Protection (MIP). This scan could locate sensitive data across the enterprise and provide the necessary visibility to roll out full MIP policies.1. Lighthouse’s Comprehensive Environment Scan Lighthouse’s scan helped identify and locate sensitive data, helping the security team to understand its exposure and design its protection strategy. An example of findings included:Teams: /LegacyRightAngleData contained 139,000+ instances of sensitive data. SharePoint: /Financial_DMS stored 52,000+ instances of sensitive data. OneDrive: /[single employee] held 18,900+ instances of sensitive data. Most Common Sensitive Data TypesABA Routing NumbersEU Passports NumbersSWIFT CodesU.K. National Health identifiers2. Created Sensitivity Labels in Pilot Mode Following the scan, Lighthouse supported the security team in developing sensitivity labels in pilot phase, including: Testing Auto-Labeling & Classification: Defining initial label rules based on scan results. Evaluating Impact Before Full Rollout: Assessing how sensitivity labels functioned across departments and workflows.Preparing for Future Policy Implementation: Establishing a structured data protection strategy before MIP policies were fully deployed. Key Outcomes The Lighthouse environment scan gave the organization critical visibility into sensitive data locations, laying the groundwork for stronger data governance, protection, and compliance. Critical Visibility for Future Protection: Identified where sensitive data resided to guide security and governance efforts. Pilot Sensitivity Labeling Program: Launched sensitivity labels to test the efficacy of policies and refine data governance practices. Foundation for MIP Rollout: Positioned the team to automate protection and enforce compliance through Microsoft Purview. The Lighthouse environment scan helped the client uncover hidden risks and build a foundation for stronger data governance. With clear visibility and a pilot labelling program, the organization is prepared to advance its Microsoft Purview rollout and reduce exposure.
Multinational Energy Company Discovers Sensitive Data in All the Wrong Places
Case Study
The ChallengeRecently, the U.S. Department of Justice (DOJ) issued a broad and urgent HSR Second Request in connection with a high-profile merger for a large, highly-regulated corporation. The regulatory inquiry required fast, defensible data collection from a range of custodians, many of whom were senior executives. With just weeks to act, the stakes were clear: respond efficiently and thoroughly or risk delaying the transaction’s approval.The request included nearly 30 custodians spread across the U.S., many with privacy sensitivities around their mobile data.The SolutionLighthouse assembled a cross-functional team of digital forensics experts and client services professionals to lead a high-touch, high-urgency workflow. Coordination between the digital forensics project manager and client services project manager ensured that collections, handoffs, and processing moved forward without bottlenecks—driven by daily alignment and real-time communication.Over six weeks, Lighthouse collected mobile data from all 27 custodians using a mix of remote and on-site methods, all handled in-house to minimize disruption and maintain control. The team leveraged industry-standard tools and proprietary workflows to extract encrypted messaging data from apps like WhatsApp and Signal, even when on-site collection was required. To address privacy concerns, Lighthouse implemented a workflow where custodians approved contact lists before any messages were filtered and prepared for review. This approach ensured rapid turnaround—often within one business day—without compromising data integrity or custodian trust.ResultsBy strategically splitting collections between remote and on-site, the Lighthouse team accelerated the project, completing collection in just 1.5 months and saving an estimated 60 hours of work time. More importantly, the client was able to respond to the DOJ within deadline—and was armed with complete, accurate, and defensible data drawn from even the most sensitive mobile sources.
Fast, Defensible Mobile Collections Support DOJ Second Request
Case Study
Challenges The legacy environments included approximately 2,200 repositories with structured data. IT aimed to decommission these systems to reduce costs, while Legal needed confirmation that legal holds were preserved before signing off on each system. The client also had to navigate international data privacy regulations, particularly when data consolidation meant data was moved across borders. Initially, two service providers split the responsibilities: the General Counsel’s office engaged one, and the eDiscovery department turned to Lighthouse because they had a long-term relationship. This fragmented approach introduced inefficiencies and risk.Solutions Lighthouse consultants:Liaised between Legal and IT, validating preservation plans for each repository. Built a detailed playbook, documentation standards, and a quality control process to provide consistency across the project. Conducted regular review calls with IT. Approved or rejected plans based on standards defined by Legal, ensuring retrieval capabilities, immutability, and long-term access. When the client saw our approach, they consolidated the work under Lighthouse, extended the engagement by 24 months, and rescoped the project.Wins The acquiring company: Gained a defensible, repeatable preservation process aligned with legal and regulatory obligations. Decommissioned costly legacy systems while maintaining legal hold compliance. Improved coordination between Legal and IT, expediting approvals. Mitigated regulatory risk by tracking and documenting preservation decisions. Ensured cross-border data preservation aligned with jurisdictional privacy regulations.Reduced long-term operational costs by retiring expensive platforms.Take Aways This project illustrates how cross-departmental cooperation can reduce risk and costs in post-acquisition decommissions and rationalizations. With a well-designed playbook and a team fluent in legal obligations and technical systems, the client adopted a defensible preservation strategy and unlocked long-term savings.
2,200 Systems Decommissioned Without Compromising Legal Holds
Case Study
How Lighthouse DeliveredLighthouse piloted its tailored end-to-end eDiscovery experience, including our self-service eDiscovery solution (Lighthouse Spectra) and deep capabilities in forensics, full-service support, and advanced AI tools that are driving ROI for law firms now (including custom predictive and GenAI technology). The firm’s eDiscovery team was particularly drawn to Lighthouse’s early investment and leadership in these practical AI solutions.The OutcomeFollowing a successful pilot, the firm selected Lighthouse as a strategic eDiscovery partner. The decision was driven by Lighthouse’s ability to meet the firm’s need for both flexible, self-directed tools and deep bench strength in complex discovery. As a result, the firm:Adopted Lighthouse Spectra as its self-service eDiscovery platformEngaged Lighthouse for digital forensics, full-service eDiscovery, and advanced AI solutions—including custom predictive models and generative AINamed Lighthouse a preferred eDiscovery provider, formalizing a partnership focused on innovation and efficiencyLighthouse Solutions Delivered
AmLaw 100 Firm Taps Lighthouse to Power End-to-End Discovery
Case Study
The Challenge Four executives from a multinational food company were sued by the Department of Justice for alleged price fixing. A joint defense group of law firms represented the executives and sought a fast, flexible way to find key documents for the case. The SolutionLighthouse utilized Key Document Identification (KDI) to serve as a central search desk to lower costs for the group’s firms and ensure consistency across case teams. ResultsLighthouse reduced the 16M documents down to 10k that were useful to counsel and saved the client an estimated $3M by supporting the joint defense group with a single team. In all, we supported the client through three trials: Two resulted in mistrials, and the third resulted in a complete acquittal.
Finding Evidence to Disprove Major Price Fixing Accusations
Case Study
The challenge wasn’t just about volume—it was about orchestrating a symphony of moving parts. Each jurisdiction had its own unique scope of relevancy and was managed by different case and eDiscovery teams. To tackle this challenge, Lighthouse architected a strategic workflow powered by AI. The cornerstone of the approach was creating a unified document repository alongside jurisdiction-specific databases and training a team of specialized reviewers to handle both universal and jurisdiction-specific responsiveness criteria. The results exceeded expectations on multiple fronts. The review scope was reduced to just 90,000 documents requiring human review. Automating coding propagation to families, this resulted in a national database of 150,000 documents. This database meant that counsel could instantaneously produce a tranche of documents, buying them more time to review documents unique to each jurisdiction and for strategic case assessment.
From Chaos to Clarity: How AI-Powered Review Transformed a High-Stakes Case
Case Study
An employee complaint about potential improper expenses on a healthcare company’s financial statements triggered in internal investigation. The company turned to Lighthouse to quickly identify documents needed for counsel to decide next steps. Day 1, 67K relevant docs handed to Lighthouse. Day 10, 150 unique key documents delivered to client. Counsel had the time and documents needed to determine next steps due to the speed and curation of the Lighthouse key document identification process.
Finding the 150 Hot Docs Needed for an Internal Investigation
Case Study
The ChallengeA healthcare technology company faced over 7.4M documents following collection, processing and deduplication in a civil litigation. Lighthouse used AI to remove relevance review, reduce privilege review to a fraction of the responsive set, and perform privilege logging and key document identification with minimal linear coding. The Solution The client and counsel opted to use a document review workflow powered by AI to optimize both efficacy and efficiency. ROI Overall, using Lighthouse AI saved $13M. AI-Powered TAR Counsel reviewed less than 5K documents to stabilize, measure, and validate a model that measured 83% precision at 75% recall. This TAR workflow removed 5M documents from review, delivering an ROI of $11M on 1L contract attorney and outside counsel review and QC. Non-TAR: 93% Review Reduction Junk file analysis identified that 1.2M documents out of the 1.3M non-TAR eligible documents were highly likely to be junk and could undergo a sampling workflow instead of a full linear review. AI-Powered Privilege Review: 40% Review Reduction Lighthouse used an AI classifier for privilege for culling and review acceleration. Based on AI results and sampling, counsel determined that 88K documents could be removed without individual review. Once the privileged documents were identified, Lighthouse used AI to generate first-pass privilege descriptions for the 43K documents in the privilege log. This fully removed 1L human drafting of log lines and instead enabled a quick creation of the log for internal and outside counsel QC.
AI-Powered Document Review Workflow Delivered Speed and $13M Savings
Case Study
Solution Lighthouse has long used AI to support data breach matters. With the emergence of more sophisticated LLMs, we can more finely tune our approaches to each client’s data. For this matter, we built an AI workflow calibrated to analyze scanned documents while maintaining PII linkage.
Mid-way through review, it became necessary to add business-level information about the types of accounts that created some of the PII. The teams deployed AI with prompts already calibrated to the document set, enabling rapid analysis without delaying the timeline. Conventional methods would have required document re-review, resulting in significant schedule setbacks. Conclusion The implementation of a generative AI solution by Lighthouse proved to be a highly effective solution for the financial intuition’s data breach response. Using AI, 30 PII components were efficiently identified and extracted from a dataset of 300K documents and link them to individuals and account details. Lighthouse’s generative AI expertise and custom workflows ensured the accuracy and integrity of the data being extracted. Overall, the project demonstrated the power of Lighthouse AI in expediting the review process in a complex data breach, leading to a total savings of $550K. Novel AI Image Analysis Speeds Data Breach Response
While the organization of data breach responses can be similar, every company’s data contains unique PII, making it an arduous process, even when using technology. Lighthouse partnered with outside counsel to create and deploy a novel approach using GenAI to alleviate the burden of PII extraction and linking while maintaining the rigor that a breach response requires. Challenge When a financial institution suffered a data breach, outside counsel was faced with 300K documents—many scanned—to review and support the response. OCR is a common way to include images into document review, but can lose key information and formatting, including removal of the link between a piece of data and its data owner(s). Further, in addition to standard pieces of PII that needed to be extracted, there were client-specific nuances we needed to capture and address.
Novel AI Image Analysis Speeds Data Breach Response
Case Study
The traditional approach to document review and fact-finding was wasting valuable time and resources for a telecommunications company and their outside counsel during a complex litigation. The usual search and review methods were also failing to surface the critical insights counsel needed to prepare their litigation strategy and minimize risk in a timely manner. Lighthouse experts stepped in and transformed the process by integrating AI and linguistic modeling to streamline review, reduce costs, and get critical insights into the hands of the case team, faster.The Problem: An Inefficient and Ineffective WorkflowThe contract review team had initially been tasked with analyzing and categorizing each document for various factors, including: Responsiveness 17 Issue Codes 4 Levels of Confidentiality Privilege Hot/Key StatusThe Result: Linear Review at a Snail’s Pace A sluggish and expensive review process that drained resources—while burying counsel under a mountain of redundant documents that delayed key decisions and increased the risk of unwanted surprises. The Pivot: A Better Approach to Fact-Finding and Doc ReviewRather than continue with the traditional approach, Lighthouse experts built tailored AI classifiers to tackle specific review tasks—e.g., confidentiality, privilege, and identifying key documents related to specific issues. The goal of this modern, more strategic approach was to help counsel remove large swaths of documents from the review queue, speed up review on the documents that remained, and get critical insights into the hands of the case team faster.The Result: Accelerating Review with AILighthouse AI and linguistics accurately classified confidentiality and privilege for the vast majority of documents (see above) and enabled Lighthouse search experts to quickly identify 1.6K unique key documents across a variety of areas for the case team. For the 120K documents that remained in the review queue, the review team was able to double their review pace because they could focus solely on reviewing for responsiveness.Read on to learn the details about how Lighthouse experts used AI and linguistic modeling to tackle specific classifications and fact-finding tasks.Confidentiality Classifications All responsive documents needed to be classified into one of four distinct confidentiality levels: Outside Counsel Eyes Only (OCEO) Confidential – Restricted Confidential Not-ConfidentialTo ensure precision in the AI model, Lighthouse experts collaborated closely with outside counsel to define the specific criteria for each level. With this input, they built tailored linguistic classifiers to automate the confidentiality classification. Samples were sent to outside counsel to test and refine the classifier before Lighthouse deployed it on the remaining document population. The result: Outside counsel only needed to review a total of 630 documents to validate and refine the Lighthouse AI linguistic classifier. From there, the classifier was able to accurately determine the correct confidentiality level for all responsive documents within the 590K document population. Lighthouse experts then continued to deploy the classifier on all newly collected documents. Identifying Telecom Agreements To protect confidentiality, as well as mitigate risks to the company, it was critical to identify all instances of specific types of agreements at issue in the litigation. Unfortunately, there was no definitive list of the parties involved in those agreements. To tackle this challenge, Lighthouse search experts created advanced linguistic models specifically tailored to recognize the unique language patterns within the types of agreement at issue. The result: Lighthouse linguistic models identified all 15K+ agreements within the document population. Lighthouse experts de-duplicated the agreements before delivering the comprehensive set to the case team well before production deadlines. Key Document Identification and Trial Prep A dedicated Lighthouse search team used a combination of linguistic modeling, advanced search technology, and unique search expertise to find the critical documents the case team needed to see across a variety of areas.The result: Lighthouse’s small team of search experts identified 1.6K unique and critical documents and excerpts of important language buried within the large document tranche.They quickly provided these documents to the case team in small, curated deliveries for a variety of fact-finding and trial preparation needs, including: 8 essential key document topic areas Third-party production gap analysis Documents showing evidence of fraud and malfeasance Deposition preparation kits Ad-hoc case team search requests as the case evolved The speed at which Lighthouse experts were able to find critical information—in combination with the value and uniqueness of the information they found—ensured that the case team could make quicker, more informed decisions throughout the remainder of case and reduce the risk of wanted surprises.Efficiency, Accuracy, and Strategic Value with Lighthouse AI and Linguistic Modeling By deploying AI and linguistic modeling, Lighthouse not only enhanced the efficiency and accuracy of document review but also empowered the legal team to make more strategic decisions faster. This modern, data-driven approach resulted in significant cost savings, time reductions, and an improved case strategy, minimizing risks and accelerating the pace toward trial preparation.
Modernizing Document Review with AI and Linguistic Modeling
Case Study
Initial Efforts Allow Source Code to Slip Through the Cracks A multinational technology company needed to find and protect sensitive source code information before producing documents to opposing counsel. The document corpus totaled 100K documents, and initial search and review efforts were underwhelming.The company used traditional search terms and metadata analyses to find documents with source code and submit them for 1L review.1L reviewers identified and protected 800 documents—but the company feared that wasn’t all of them. The 1L reviewers were inexperienced in identifying source code and could have let sensitive information slip through.To make sure they caught every doc, they brought in Lighthouse to conduct another search.Lighthouse Uses AI Classifier to Find the Remaining DocsLighthouse has pioneered the use of AI in responsive review and the detection of privileged and sensitive information. For this matter, we collaborated with subject matter experts on the client team to tune our source code AI classifier for the specific types of source code data they were most concerned about protecting.We ran the classifier on the entire 100K document set, and the client passed our results on to their team of 2L reviewers. They confirmed that another 300 documents contained source code—25% of the total that were protected prior to production.Thanks to Lighthouse’s AI solutions and experts, the company avoided sharing precious code with a rival corporation and losing its competitive edge in the industry.
Tech Company Avoids Sharing Source Code with Opposing Counsel by Using AI
Case Study
Uncertainty on How to Proceed Effectively, Timely, and Defensibly with 70M Documents to ReviewA Fortune 500 health insurance provider was facing a fast-approaching deadline set by the DOJ Antitrust Division for producing documents related to a planned upcoming high-stakes merger. To comply with the DOJ’s request, over 31.5TB of data from 137 custodians and 170 separate media sources needed to be collected, processed, filtered, and reviewed. Sources included: legacy email databases, SharePoint repositories, shared and personal network drives, laptop/hard drives, and hard copy documents. It was unclear to the health insurance provider how to proceed with this massive review of 70M documents in the most effective, timely, and defensible manner. Significant Reduction Out the Gate Using Lighthouse Structured AnalyticsUsing Lighthouse deduplication and filtering, the processed data set was substantially culled down from 70M documents to 21M, a 70% reduction. In parallel to these data reduction efforts and in preparation for the next phase of work, Lighthouse TAR experts created a TAR protocol and production schedule.Precision and Speed: Reviewing 21M Documents in 3 monthsUsing the TAR protocol, the team achieved a high-precision, high-recall output across the range of diverse data in the review set. The entire review of 21M documents was completed with three months, resulting in 5M responsive documents produced to regulators. Lighthouse’s expert handling of massive data volumes through analytics and technology-enabled review protocols enabled the Fortune 500 health insurance provider to meet stringent DOJ deadlines efficiently, ensuring compliance and readiness for their high-stakes merger.
Streamlining Document Review for DOJ Antitrust Division Compliance
Case Study
The project included replacing expensive third-party archives with native tools in M365, utilizing an automation solution that Lighthouse had recently prototyped for a large global manufacturer, and other breakthroughs the institution was unable to make before engaging with Lighthouse. Our work with the institution helped unblock their Microsoft 365 deployment and ultimately led to disclosure to regulators for institution’s intent to use M365 as system of record.SIFIs have long wished for a better way to meet their mutability requirement. Historically, they have relied on archiving solutions, which were designed years ago and are poorly suited for the data types and volume we have today. For years, people in the industry have been saying, “Someday we’ll be able to move away from our archives.” It wasn’t until the introduction of M365 native tools for legal and compliance that “someday” became possible.Data Management for SIFIs is Exceptionally ComplexThe financial services industry is one of the most highly regulated and litigious sectors in the world. As a result, companies tend to approach transformation gradually, adopting innovations only after technology has settled and the regulatory and legal landscape has evolved.However, the rate of change in the contemporary world has pushed many financial heavyweights into a corner: They can continue struggling with outdated, clunky, inadequate technologies, or they can embrace change and the disruption and opportunities that come with it.From an eDiscovery perspective, there are three unique challenges: (1) as a broker-dealers, they have a need to retain certain documents in accordance with specific regulatory requirements that govern the duration and manner of storage for certain regulated records, including communications (note that the manner of storage must be “immutable”). This has traditionally required the use of third-party archive solutions that has included basic e-discovery functionality. (2) As a highly regulated company with sizable investigation and litigation matters, they have a need to preserve data in connection with large volumes of matters. Traditionally, preservation was satisfied by long-term retention (coupled by immutable storage) and without deletion. Today, however, companies seek to dispose of legacy data—assuming it is expired and not under legal hold—and are eager to adopt processes and tools to help in this endeavor. (3) They have a need to collect and produce large volumes of data—sometimes in a short timeframe and without the ability to cull-in-place. This means they are challenged by native tooling that might not complete the scale and size of their operations. This particular company’s mission was clear: to use M365 as a native archive and source of data for eDiscovery purposes. To meet this mission, Lighthouse needed to establish that the platform could meet immutability and retrievability requirements—at scale and in the timeframe needed for regulatory and litigation matters. Lighthouse Helps a Large Financial Institution Leverage M365 to Replace Its Legacy Archive SolutionLighthouse is perfectly positioned to partner with financial services and insurance organizations ready to embrace change. Many on our team previously held in-house legal and technology roles at these or related organizations, including former in-house counsel, former regulators, and former heads of eDiscovery and Information Governance. Our team’s unique expertise was a major factor in earning the trust and business of a major global bank (“the Bank”). The Bank first engaged with Lighthouse in 2018, when we conducted an M365 workshop demonstrating what was possible within the platform—most notably, at the time, the potential for native tools to replace their third-party archives. Following the workshop, the Bank attempted, together with Microsoft, to find a viable solution. These efforts stalled, however, due to the complexity of the Bank’s myriad requirements. In 2020, the Bank re-engaged Lighthouse to supports its efforts to fully deploy Exchange and Teams and, in doing so, to utilize the native information governance and e-discovery toolset, paving way for the Bank to abandon its use of third-party archiving tools for M365 data. Our account team had the nuanced understanding of industry regulations, litigation and regulatory landscape, and true technical requirements needed to support a defensible deployment.As a result, we were able to drive three critical outcomes that the bank and Microsoft had not been able to on their own: (1) A solution adequate to meeting regulatory requirements (including immutability and retrievability). (2) A solution adequate to meeting the massive scale required at an institution like this. (3) A realistic implementation timeline and set of requirementsLighthouse Ushers the Bank Through Technical and Industry MilestonesWe spent six months designing and testing an M365-based solution to support recording keeping and e-discovery requirements for Teams and Exchange (including those that could support the massive scalability requirements). The results of these initial tests identified several gaps that Microsoft committed to close. The six month marked a huge milestone for the financial services industry, as the Bank disclosed to regulators their intent to use M365 as system of record. This showed extreme confidence in Lighthouse’s roadmap for the Bank, since a disclosure of this nature is an official notice and cannot be walked back easily. Over the next few months, we continued to design and test, partnering with Microsoft to create a sandbox environment where new M365 features were deployed to the Bank prior to general availability, to ensure we were able to validate adequate performance. During this time, Microsoft made a series of significant updates to extend functionality and close performance gaps to meet the Bank’s requirements. Finally, in February 2021, all the Bank’s requirements had been met and they went live with Teams—the first of their M365 workload deployments. That configuration of M365 met only some of the Bank’s need, however, so Lighthouse had to enable additional orchestration and automation on top. As it happens, we had recently done this for another company, creating a proof of concept for a reusable automation framework designed to scale eDiscovery and compliance operations within M365. Building on this work, we were able to quickly launch development of a custom automation solution for the Bank. This project is currently underway and is slated to complete in June, coinciding with their deployment of Exchange Online.Lighthouse Enables Adoption of Teams and Exchange and Scales M365 Compliance FunctionalityCompliant storage of M365 communications using native tools, rather than a third-party archive. Scaled and efficient use of M365 eDiscovery, including automation to handle preservation and collection tasks rather than manual processes or simple PowerShell scripts.Improved update monitoring, replacing an IT- and message-center-driven process with a cross-functional governance framework based on our CloudCompass M365 update monitoring and impact assessment for legal and compliance teams.Framework for compliant onboarding of new M365 communication sources like Yammer. Framework for compliant implementation of M365 in new jurisdictions, including restricted country solutions for Switzerland and Monaco. Framework to begin expanding to related use cases within M365, such as compliance and insider risk management. Lighthouse Paves the Way for Broader M365 Adoption Across the Financial Services IndustryFollowing the success of this project, we have been engaged by a dozen other large financial institutions interested in pursuing a similar roadmap. The roadblocks we removed for the Bank are shared across the sector, so the project was carefully watched. With the Bank’s goals confidently achieved and even surpassed, its peers are ready to begin their own journey to sunset their archives and embrace the opportunities of native legal and compliance tools in M365.
Modernizing Compliance and eDiscovery
Case Study
Two Months to Tackle Three Million DocumentsA financial institution with an urgent matter had two months to review 3.6M documents (2.4TB of data).With that deadline, any time that reviewers spent on irrelevant documents or unnecessary tasks risked missing their deadline. So outside counsel called on Lighthouse to help efficiently review documents.AI and Experience Prove Up to the ChallengeUsing our AI-powered review solution, we devised an approach that coordinated key data reduction tactics, modern AI, and search expertise at different stages of review.Junk Removal and Deduplication Set the Stage We started by organizing the dataset with email and chat threading and removing 137K junk documents. Then we shrank the dataset further with our proprietary deduplication tool, which ensures all coding and redactions applied to one document automatically propagate to its duplicates. AI Model Removes 1.5 Million Nonresponsive Documents To build the responsive set, we used our AI algorithm, built with large language models for sophisticated text analysis. We trained the model on a subset of documents then applied it to all 2.2M TAR-eligible documents, including transcripts from chat platforms. The model identified 80% of the documents containing responsive information (recall) with 73% accuracy (precision). The final responsive set consisted of 650K family-inclusive documents—18% of the 3.6M starting corpus. AI Supports Privilege Detection, QC, and Descriptions Our AI Privilege Review solution supported reviewers in multiple ways.First, we used a predictive AI algorithm in conjunction with privilege search terms to identify and prioritize potentially privileged documents for review. During QC, we compared attorney coding decisions with the algorithm’s assessment and forwarded any discrepancies to outside counsel for final privilege calls. For documents coded as privileged, we used a proprietary generative AI model to draft 2.2K unique descriptions and a privilege log legend. After reviewing these, attorneys left nearly 1K descriptions unchanged and performed only light edits on the rest.Search Experts Surface the 300 Documents Most Important for Case Prep Alongside the production requirements for the Second Request, Lighthouse also supported the institution’s case strategy efforts. Each tranche of work was completed in 4 days and within an efficient budget requested by counsel, who was blown away by the team’s speed and accuracy. Using advanced search techniques and knowledge of legal linguistics, our experts delivered: 130 documents containing key facts and issues from the broader dataset, for early case analysis. 170 documents to prepare an executive for an upcoming deposition. Beating the Clock Without Sacrificing Cost or QualityWith Lighthouse Review—including the strategic use of state-of-the-art AI analytics—outside counsel completed production and privilege logging ahead of schedule. The financial institution met a tough deadline while controlling costs and achieving extraordinary accuracy at every stage.
AI Powers Successful Review in Daunting Second Request
Case Study
Searching for Evidence in 8TB of Chat and Technical Data Senior executives at an information technology company suspected that former employees had utilized company resources and intellectual property when starting a rival company. To determine whether litigation was called for, executives needed to find the most relevant documents within 8TB of processed data. The data was extremely complex, dating back 6+ years and consisting mostly of Slack data and attachments including highly technical documents, applications, logs, and related system files—tallying over ten million files. The company engaged a senior partner at an AM50 law firm, who recommended using keyword search terms, filters, and targeted linear review to find the “smoking gun” documents—which was estimated to take several months. The company came to Lighthouse looking for a faster, more strategic search alternative for their investigation. Pinpointing Key Docs with Linguistic Analysis Two Lighthouse search and linguistics experts met with company executives to learn exactly what information they suspected the former employees had misappropriated. From there, our experts created linguistic-based search criteria that go well beyond keywords, taking into consideration the unique vocabulary and syntax of software engineers and developers, the conversational quirks of Slack and other chat-based communications, and the coded language used by people who are trying to get away with something. The team delivered documents in 2 batches, refining their search based on input from the executives—and resulting in only 39 files for the company to review. Getting Results—and a Start on Case Strategy—in Days In less than 10 days, 2 Lighthouse experts pierced the subterfuge in the employees’ chat messages to reveal patterns in their behavior and attempts to cover their tracks. In all, we found 39 documents representing possibly questionable conduct, which required only 141 hours of eyes-on review. In comparison, using conventional analytics would have identified 5-20% of the search population as key documents—up to 50K documents to review in this matter. So in the end, Lighthouse saved the company over 3 months and nearly $200K.Armed with knowledge of the key events, timelines, and context of conversations buried within the data, the company was primed to begin litigation efforts and had a team ramped up to perform additional searches when needed.Lighthouse KDI vs Linear Review
Lighthouse Uncovers Key Facts In Misappropriation Investigation
Case Study
Firms Needed Fast Analysis of 25M Documents More than a dozen international law firms—including a Joint Defense Group (JDG) of 11 firms and several firms representing defendants outside the JDG—were engaged in a complex cluster of cases spanning over 30 US jurisdictions. The total document tranche included over 25M documents. The firms needed to find and understand the key players, timelines, and nuances involved in each litigation, while also preparing for hundreds of depositions, witness interviews, hearings, and trials scheduled across the litigation universe. However, traditional approaches to fact-finding and litigation (i.e., document review, keyword searches, etc.) were drowning case teams in extraneous and duplicative information. They came to Lighthouse looking for a strategic, unified approach to fact-finding, led by experts who could deliver the key documents, information, and details the case teams needed—and nothing more. Custom Workflows Power Consistency, Speed, and Efficiency Our experts started by creating a topic map across matters, which helped them quickly provide case teams with the core themes in each jurisdiction while reducing redundant search work. From there, as case strategy for each matter developed, the Lighthouse team drilled down into more nuanced fact-finding to help surface the documents case teams needed to learn the key details of each matter, through strategies like: State/Jurisdictional Overview Workflow – We used advanced search technology to target key documents in incoming productions and categorize them by jurisdiction, providing case teams with an immediate thematic overview of key facts and timelines. Re-Deployable Linguistic Model Workflow – Lighthouse linguists developed models based on intimate knowledge of the language used within the datasets, then deployed them within proprietary search technology to sort documents into tiers based on the likelihood that they contained key information. Deposition Kit Bundle Workflow – By bundling deposition kit requests from the same jurisdictions and departments together, we could search across smaller collections of documents and take a deponent-agnostic approach. Previously Delivered Name Hit Workflow – We provided case teams with documents from previously delivered results, giving them an advanced start on deposition preparation while further reducing duplicative searching. These repeatable workflows significantly reduced the volume of searching and coordination required across matters and enabled Lighthouse experts to quickly zero-in on the exact documents needed—without wasting counsels’ time with redundant and unimportant documents. Critical Docs Found and Delivered Across Dozens of Matters and Hundreds of Kits Over the course of two years, Lighthouse experts prepared dozens of case teams for complex litigation and handled a deluge of competing deadlines, priorities, and ad hoc requests (totaling as many as 70 requests at a time). For the Joint Defense Group, this meant: Over 1,150 deposition kits across 24 matters, encompassing 245K unique documents Over 100 state overviews across 21 different jurisdictions, encompassing 80K documents For law firms representing individual defendants, Lighthouse provided an additional:150 deposition kits, encompassing 13K documents 30 defensive overviews across 20 jurisdictions, encompassing 6K documents 1.3K documents in response to ad hoc requests and trial support Each delivery was limited to essential information—including key themes and players in every jurisdiction, potential gaps in productions, lists of hot/sensitive documents and potential deponents, and key strategy documents—and avoided redundant and unimportant documents. The combination of innovative workflows and cutting-edge technology enabled Lighthouse to keep our team small and consistent throughout the engagement, so the entire effort was achieved by a handful of Lighthouse experts with institutional knowledge of every matter. Since this engagement, we have used the same workflows for other clients facing complex Multidistrict Litigation (MDL)—making Lighthouse key document identification one of the most valuable and scalable litigation technology solutions on the market today.
Lighthouse Litigation Prep Proves Invaluable in Complex Litigation
Case Study
Privilege Terms Yield a Mountain of DocumentsA global law firm was engaged to help a company respond to an HSR Second Request. Standard privilege term filters left the firm with nearly 90K documents to review. They turned to Lighthouse to reduce that document set and meet the government’s production deadline.Lighthouse AI Enhances the Review Team’s Strategy and EfficiencyLighthouse used our proprietary AI to prioritize and whittle down the documents requiring eyes-on review, resulting in a privilege review process that was far more nuanced, detailed, and faster than if the firm had used a traditional privilege term approach.First, we partnered with counsel to identify a small number of privilege documents (less than 2K) to train our AI technology on the privilege parameters involved in the matter. After training on that small sample set, Lighthouse AI provided component-level privilege scoring and categorization to the entire dataset. The results were so accurate that counsel confidently excluded tens of thousands of Lighthouse AI-identified non-privilege documents from eyes-on review, sending them straight to production instead. The remaining documents were prioritized for review based on their higher likelihood of being privileged, per Lighthouse AI scoring. Time and Money Saved by Removing Non-Privileged DocsLighthouse AI enabled the law firm to make strategic and efficient use of privilege review time and resources by: Removing 20K+ non-privileged documents from eyes-on privilege reviewFocusing attorney review time on documents that were highly likely to require more nuanced, complex privilege analysesOverall, we saved the law firm 5 to 10 days in review time and helped them meet their deadline with a defensible process.
Using AI to Reduce Privilege Review During an HSR Second Request
Case Study
The Lighthouse team of SMEs applied their dedication to exemplary customer experience and unique strategy of marrying compliance, security, IT, and legal needs to help a global chemistry solutions and specialty material producer meet the ever-evolving security and compliance demands and challenges facing international manufacturing and regulations to effectively deploy Microsoft Purview across workstreams while preparing for needs and reducing costs. Global Leader in Chemistry Solutions Transforms Enterprise Data Protection with Microsoft Purview An international producer of commercial chemicals and specialty materials upholds a commitment to people safety and well-being as part of their core tenets. As cyber risks increased along with data volumes, the organization extended their commitment to safety to include the security of data accessed, produced, and stored within their enterprise. Now, the company has implemented a comprehensive data protection program using the entire Microsoft 365 Information Protection suite. After careful design, the team is piloting the solution before a global rollout. A Commitment to Physical and Digital Safety As one of the world’s largest acetyl products manufacturers and a top-tier producer of high-performance engineered polymers, the company supplies chemicals across major industries and for a variety of industrial and consumer applications. Over 10,000 employees in offices, technical centers, and 50+ manufacturing facilities work to realize a vision of improving the world and everyday life through people, chemistry, and innovation—with products that impact the lives of millions. For the organization, an operational approach rooted in well-being has always meant physically safe working environments for employees, and safe solutions for their customers and their communities. However, in this digital age, they have expanded their notion of safety to include data protection for employees, customers, shareholders, and the communities in which they operate. The company’s Chief Information Security Officer (CISO) notes that committing to data protection means a “higher level of assurance—making sure that our security controls keep pace with the threats that surround us every day and seek to exploit vulnerabilities in companies like us every day. You can’t stand still. You always have to evolve—you always have to get better, otherwise you’re devolving, and you’re getting worse, and becoming more vulnerable.” Advancing Data Protection with a Trusted Partner A few years ago, when the company decided to make the move to the cloud, they chose Microsoft 365 E5 and Microsoft Azure, building on their longstanding use of Microsoft technologies. Prior efforts to overhaul their data protection program had been unsatisfactory. However, with access to new Microsoft Purview capabilities, the Information Security team saw an opportunity to try again. They hoped to utilize the full breadth of the Microsoft 365 Information Protection suite including Information Protection Classification and Labeling, Data Loss Prevention (DLP), and Insider Risk Management solutions. Microsoft tapped Security Solutions and Advanced Specialization Designation-Information Protection and Governance Partner Lighthouse Global to lead the engagement for their ability to effectively understand complex compliance needs across IT, security, and legal departments. They hoped that together they could develop a solution to realize the investment they’d made in Microsoft 365, and to support their corporate commitment to safety for both employees and customers. “If you were to interview a bunch of companies, those who have actual, very successful DLP and data labeling programs typically have a hodgepodge of solutions that get melded together,” reflected the CISO, “and that’s where Lighthouse was successful…we’ve been able to leverage the investment…and get it to work, [and not] have to go spend more money to hodgepodge together a solution.” Developing a Comprehensive, Scalable Solution The Lighthouse team started by holding a series of working sessions to align the company’s vision and requirements and design the implementation approach. Using Microsoft Compliance Check, Lighthouse scanned the company’s environment to get an understanding of current state activity and sensitivity intelligence. The team also reviewed existing policies and approaches for the handling of sensitive data and data loss prevention to identify any areas of opportunity or gaps that could exist. From there, the combined teams were able to successfully design and configure a holistic data protection solution leveraging multiple Microsoft Purview products including Data Loss Prevention, Information Protection, and Insider Risk Management. Starting with data classification, the team defined the sensitive information types that needed to be identified. From there, they developed a set of sensitivity labels corresponding to the data protection policy. This set of classification techniques and labels were generated in the course of both Data Loss Protection and Insider Risk Management implementation, ensuring a comprehensive data life cycle protection program from content identification through insider threat analysis. Finally, the Lighthouse team supported the integration of the Microsoft products with the company’s third-party HR software to feed HR data into the Data Theft by Departing Employee Policy, enabling the creation of a truly end-to-end solution. Fulfilling a Mission of Security The company’s dedication to safety, security, and well-being across applications and contexts drove this project’s success. “Because we see security as part of our commitment to people and innovation, we take a uniquely holistic approach and have strong support all the way up to our board of directors,” says the company’s CISO. The CISO also credits Lighthouse’s unwavering commitment to partnership. “They helped us not only implement the technology and guide us through some of the critical points to consider as we implemented the technology, but also the process and decision points with data—which ultimately, in the end, actually worked,” they conclude. Now, with the design and implementation of the Microsoft Purview-based Data Protection program behind them, the organization’s information security team is focused on operationalizing the program through a series of pilots scheduled over the next year. Their ultimate goal is total, global implementation of the solution—and total, global protection for all employee and customer data. Corporate Case Studymicrosoft; big-datamicrosoft-365; data-privacy
Lighthouse Transforms Complex Enterprise Data Protection with Microsoft Purview
Case Study
A global biotech achieves consistent and efficient document review with Lighthouse review. Key Actions Coordinating efforts across disparate review teams and counsel Integrating advanced AI and other innovations on an incremental basis ‍ Key Results Streamlined and efficient approach to document review Saving more than $340,000 through a tailored workflow in one recent matter A Lack of Coordination Drove High Costs and Complexity Document review for a global biotech was expensive and inconsistent, due to a high frequency of litigations with often overlapping timelines and different outside counsel. Lighthouse had been managing the company’s electronically stored information (ESI) for years, saving the company hundreds of thousands of dollars through plans and policies introduced over time. After learning of our expertise in managed review, the company hired Lighthouse to bring order and efficiency to that domain as well. Laying a Foundation with Standard Protocols Our first order of business was to establish universal standards across matters, outside firms, and review vendors. These included: Upstream changes , such as data management protocols that made documents easier to search and sort. Overarching review protocols , such as QC process guidelines and specifications for production. Changes to specific tasks , such as refining privilege filters and standardizing coding layouts so review performance could be compared across different matters and teams. A Lighthouse review manager trained all current firms and vendors and was on hand to monitor progress and answer questions, as well as onboard new firms and vendors as needed. Increasing Efficiency Through Technology Over time, Lighthouse gradually introduced accelerators to help increase efficiency and cost savings. Initially, this consisted of: Deduplication improvements , through strategies like single-instance review and normalized deduplication. Review accelerators such as privilege log automation and redaction automation. To drive even more savings, Lighthouse led the company through a test-and-learn process for building workflows around advanced AI and other, more in-depth technology. The process involved trying out a new technology on a live matter, then conducting a post-mortem to clarify what worked and what could be improved. In this way, Lighthouse and the company developed a rubric for determining which workflows were the right fit for different matters. Streamlined, Aligned, and Eager to Keep Innovating In 5 years, Lighthouse transformed the company’s disconnected, manual, expensive approach to document review into a coordinated and robust program that boosts efficiency at every level. For one recent matter—a patent litigation with a tight timeline overlapping the winter holidays—this review program drove extraordinary efficiency and savings. Tailoring the client playbook for the specific matter, the review manager designed a complex workflow that reduced eyes-on review: The initial dataset of almost 8M documents was reduced to a corpus of 388K through deduplication, culling, and removal of embedded and redundant documents. The population was further reduced through search hit only protocols and by employing a continuous active learning (CAL) model, stopping review when responsive documents became scarce. Finally, Lighthouse reunited document family members, automatically giving members tied to responsive documents the coding of their source docs. In the end, Lighthouse: Reduced eyes-on review to just 92K documents (25% of the documents promoted to review) Saved the company an estimated $341,000 in review costs Going forward, the company is ready to increase its use of technology, including classifiers built with advanced AI and an automated workflow for redactions of personally identifiable information (PII). Corporate Case Studyai-and-analytics; ediscovery-reviewediscovery-review, ai-and-analytics, biotech
Alignment and Savings Across a Dynamic Portfolio
Case Study
Lighthouse leveraged linguistic expertise and cutting-edge analytics to efficiently locate only the documents that mattered in a complicated, year-long antitrust criminal investigation and trial. What They Needed Senior executives from a global food manufacturing company faced federal criminal antitrust charges related to allegations of 15 instances of price fixing over a five-year period. A joint defense team comprised of outside counsel representing each of the executives was assembled by the company. The prosecution expected to make rolling productions of evidence up to and through the trial. As those productions rolled in, the joint defense team could tell that many of the evidentiary documents, timelines, and conversations that were key to the prosecution’s case were taken out of context or failed to include all the exculpatory evidence. However, the joint defense team was having trouble finding key evidence because much of the nuance was located within piecemeal chat conversations and complex bid spreadsheets that were buried among millions of similar documents. The joint defense team needed a document search team that was nimble and could quickly identify the most important documents to the defense and share them across the team. They came to Lighthouse because we could quickly identify key documents with accuracy and nuance. How We Did It Lighthouse first organized a central search desk, where all members of the joint defense team could go for document search requests, with results shared across three defense teams. Next, the Lighthouse team located the most important documents related to each of the 15 episodes of price-fixing allegations, on a priority basis. They used linguistic expertise to create narrow searches, taking into consideration the nuance of acronyms, slang, and terminology used within the company and the food manufacturing industry. They also leveraged Lighthouse’s proprietary, cutting-edge search analytic tools to look for key information buried in hundreds of thousands of Excel spreadsheets and chat messages. As the government produced more documents, the Lighthouse team refreshed their searches, looking for key documents in each new production and quickly sharing results across the defense team. As defense preparations continued throughout the year, we we supported all aspects of trial preparation, including two mock trials, all witness preparation binders, and the James hearing. Lighthouse support will continue through the criminal trial for the senior executives, due to our proven success in supporting ad hoc search requests and providing results in real time. The Results The Lighthouse team efficiently delivered incredibly accurate results, saving the underlying client more than $3M thus far. Out of an always-in-flux review population that eventually grew to over 16M documents, Lighthouse was able to cull through the irrelevant data to find and deliver only the most important documents for the defense team’s utilization. In the end, that amounted to less than 1% of the initial review population, including: 4.7K documents for the joint defense group to defend the episodes of alleged price fixing 5.3K documents for defense team’s specific ad hoc and witness kit requests (an average of 400 documents per witness kit) In comparison, a traditional linear review using search terms and conventional analytics performed by multiple case teams typically results in 5-20% of the data population being tagged as “key documents.” This volume would then be funneled to the case teams for review as well, where they would waste valuable time and resources looking at hundreds of thousands of irrelevant or run-of-the-business documents. In addition to cost-efficiency, the team has gained expertise in the key events, timelines, and context of conversations buried within the data. As such, the team is now a critical resource to the defense, supporting all stages of the investigation and assisting in pivot ad hoc requests. Examples include finding a unique pricing document buried among volumes of near duplicates, as well as the relevant context surrounding a single line of a chat message. In the end, Lighthouse saved the underlying company significant time and money that could not have been achieved otherwise. Additionally, our expertise in the data was a critical resource to the joint defense team, which relied on Lighthouse at each step of trial preparation. Lighthouse expert support will continue throughout the criminal trial. ‍ Corporate Case Studyantitrust; ai-and-analytics; ediscovery-reviewantitrust, ai-and-analytics-ediscovery-review, kdi, key document identification
Lighthouse Key Document Identification Proves Pivotal to Antitrust Defense
Case Study
In-house legal and compliance teams use Lighthouse Spectra, a cloud-based, self-service legal technology platform, to achieve a more efficient and scalable approach to compliance monitoring. Our self-service technology keeps clients well ahead of audits and compliance risks, while lowering the costs and inefficiencies inherent to compliance monitoring, particularly for companies working in heavily regulated industries. Clients avoid the processing fees and wait times that burden compliance reviews by quickly and easily loading their own data. Then, they leverage industry leading technology to create repeatable, scalable compliance workflows that quickly cull out irrelevant data and uncover key information. The results are lower risk, faster results, and unprecedented savings. Repeatable and Effective Self-Service Compliance Investigation Workflow Below, we’ve detailed a sample self-service compliance workflow—including real results that our clients have achieved at each step during internal investigations. Similar workflows have been used by our clients to deliver up to 96% reduction in document review and over $800K in savings across a single investigation. Step 1: Automated Data Upload, Processing, and Deduplication What it does : Reduces administration time, speeds up investigation setup, reduces hosting costs, reduces review population by removing duplicates Lighthouse self-service automation features reduce the manual set up tasks that often delay the start of an investigation (data import, processing, etc.). Clients can leverage Lighthouse’s native file managing technology at this point to significantly reduce hosting costs—by only loading native files if or when they’re necessary to the investigation. Once data is uploaded and processed, clients can deploy Lighthouse deduplication technology to immediately remove redundant data. Results : Enabled an investigation team to start analysis one week earlier than standard processing; reduced data population by 25%. Step 2: ECA Culling and Search Term Iteration What it does : Reduces review populations by removing irrelevant documents Once processed and deduplicated, clients use our customized culling and search term iteration processes to swiftly narrow the scope of documents for review. Results : Reduced review population of an internal investigation by over 78%. Step 3: Thread Suppression and Proprietary Review Technology What it does : Reduces review populations by identifying the most unique documents Clients can then implement customized workflows that combine email thread suppression with Lighthouse review technology to identify the most unique documents. Results : Reduced review population of an internal investigation by over 50%. Step 4: Lighthouse TAR and Advanced Analytics What it does : Finds the key documents that matter to investigations. After the culling process, clients often deploy Lighthouse’s Continuous Active Learning TAR workflows to find relevant documents. Once reaching a point of diminishing returns, advanced analytics such as clustering, categorization, and concept searches can be deployed to ensure that no relevant documents were left behind. Results : Reduced review population of an internal investigation by over 60%. Corporate Case Studyspectra; self-service, spectra; compliance-and-investigationsediscovery-review; client-success; ai-and-analyticsCase-Study; client-success; ai-and-analytics; analytics; Compliance-and-Investigations; Corporate; Corporation; data-analytics; eDiscovery; fact-finding; healthcare-investigations; investigations; machine-learning; predictive-coding; Processing; risk-management; self-service, spectra; Spectra; TAR; TAR-Predictive-Coding; technology-assisted-review; edicovery-review; ai-and-analytics
Lighthouse Self-Service Solution Uplevels Compliance Investigations
Case Study
A global transportation company was under investigation for possible infractions of the Foreign Corrupt Practices Act (FCPA) in India. The company’s legal counsel needed to quickly produce responsive documents and find key documents to prepare their defense. Key Results 4M total documents reduced to 250K through 2 rounds of responsive review, with precision rate and recall of 85% or higher. 810 key documents quickly delivered to outside counsel, saving them hours of review and gaining more time for case strategy. A Complex Dataset Requiring Nuanced Approaches The company collected 2M documents from executives in India and the U.S. Information in the documents was extremely sensitive, making it critical to produce only those documents related to the India market. This would be impossible for most TAR tools, which use machine learning and therefore can’t reliably differentiate between conversations about the company’s business in India from discussions solely pertaining to U.S. business. Finding key documents to prepare a defense was challenging as well. The company wanted to learn whether vendors and other third parties had bribed officials in violation of the FCPA, but references to any such violations were sure to be obscure rather than overt. Zeroing In On the Right Conversations Lighthouse used a hybrid approach, supplementing machine learning models with powerful linguistic modeling. First, our linguistic experts created a model to remove documents that merely referred to India but didn’t pertain to business in that market, so that the machine learning TAR wouldn’t pull them into the responsive set. Then our responsive review team developed geographic filters based on documents confirmed as India-specific and used those filters to train the machine learning model. The TAR model created an initial responsive set, which our linguists refined even further with an additional model, based on nuances of English used in communications across different regions of India. By the end, our hybrid approach had reduced the corpus by 97%, with an 87% precision rate and 85% recall. Once this first phase of review was successfully completed, Lighthouse dove into an additional 2M documents collected from custodians located in India. Finding Key Documents Among Obfuscated Communications To help inform a defense, our search specialists focused on language that bad actors outside the company might have used to obfuscate bribery. The team used advanced search techniques to examine how often, and in what context, certain verb-noun pairs indicating an “exchange” were used (for instance, commonly used innocent pairings like give a hand vs. rarer pairs like give reward). The team could then focus on the documents containing language indicating an attempt to conceal or infer. $1.7M Saved, 810 Key Documents Found to Support Defense Lighthouse performed responsive review on two datasets of 2M documents each, reducing them to less than 250K and saving the client more than $1.7M. Out of the 237K responsive documents, Lighthouse uncovered 810 hot docs spanning 7 themes of interest. The work was complete in just 3 weeks and enabled outside counsel to provide the best defense to the underlying company. Corporate Case Studykdi; key-document-identification; case-study; investigations; reviewediscovery-review; client-success; ai-and-analyticsCase-Study; client-success; ai-and-analytics; analytics; document-review; eDiscovery; fact-finding; investigations; KDI; key-document-identification; keyword-search; TAR; TAR-Predictive-Coding; technology-assisted-review; machine-learning; transportation-industry; automotive-industry; edicovery-review; ai-and-analytics
Unprecedented Review Accuracy and Efficiency in Federal Criminal Investigation
Case Study
A healthcare provider needed help simplifying ESI hosting for a complex series of 14 related matters across 9 states (and growing). Lighthouse went above and beyond—providing a unified workflow from hosting to review. Key Actions Quickly migrated 11M documents from existing Relativity and non-Relativity databases into a single repository, supported by AI Created one sophisticated workflow—from ESI storage to managed review—for over 14 matters across 9 states (and any other matters that arise in the future) Leveraged advanced technology to facilitate data re-use, data reduction, and review efficiency ‍ Key Results Avoided duplicate collections, hosting, and review of 1.2M documents Instantaneously provided production sets to all 14 matters, giving local counsel time to focus on unique matter documents before production Set case teams up for success in future matters with a readymade data repository, workflow, and trained review team—exponentially increasing the client’s ROI Data Everywhere and No One to Turn To A large healthcare provider was facing a growing number of separate but related litigations. With 14 ongoing matters in 9 different jurisdictions, the company’s data was spread out across multiple ESI vendors and a variety of review databases. The hosting costs of this data sprawl was threatening to explode the company’s overall budget. And with each case team and vendor taking their own approach to case strategy and review, in-house counsel was busy herding cats rather than managing overall litigation strategy. They came to Lighthouse desperately seeking a way to consolidate their overall eDiscovery approach to these matters. A Streamlined Solution for Multiple Matters, from Hosting Through Review Lighthouse seamlessly integrating all related matters into an advanced document repository. Backed by AI, this repository connected insights across matters and maximized work product reuse. Using this repository as a base, our experts built a sophisticated eDiscovery workflow for all 14 individual matters. Each process in every individual matter—from hosting to document review—was purposefully designed around insights and data from all other related matters. The result of this holistic approach was more efficient, consistent, and accurate eDiscovery across every matter—at a much lower cost than could ever have been achieved with a traditional siloed approach. Here’s how we did it: Faster, More Versatile Migration Capabilities With our advanced technology and unique migration expertise, Lighthouse quickly migrated 11M documents from existing databases—including Relativity and non-Relativity—into an advanced AI-backed document repository. At the outset, the team worked closely with the client to understand the scope, types of data, and future needs, so that the migration flowed quickly and efficiently. This approach meant that the client only had to process data once, rather than paying for processing and re-processing data with every matter. Individual case teams also immediately reaped the benefit of data and insights from every related matter, including matters that had already been successfully litigated. This helped counsel anticipate issues in their own matters, while re-using review work product for greater efficiency and consistency—ultimately saving costs and improving matter outcomes. One Hash for Unprecedented Cross-Matter Deduplication and Efficiency Unlike other data storage repositories, the Lighthouse AI-backed repository adds a hash system unique to Lighthouse. This technology normalizes documents before adding a hash value, extending our deduplication power and allowing us to identify all duplicate documents beyond what is possible using traditional deduplication technology. Our unique AI hash system also enabled faster insights into opposing party productions. The Lighthouse team used the system to compare newly received productions in one matter against documents previously received in other matters. Where matches were found, any issue coding one case team applied to a document was carried over and applied to new matching documents. This helped facilitate case team collaboration and a consistent legal strategy across matters. Broad Bench of Data Experts Rather than paying separate vendors for expertise in individual matters, in-house counsel and local case teams leaned on Lighthouse’s unified bench of subject matter experts—including ESI processing and hosting, advanced analytics, and review specialists. These experts worked together as a dedicated client service team, providing a uniquely holistic view of the entire array of related matters. However, individual specialists tagged in to perform work only when their expertise was needed, ensuring that the company didn’t rack up expensive invoices for consulting services they didn’t need or use. When our experts were called in to help, they were able to identify areas for greater efficiency and cross-matter consistency that would have been impossible if the client had remained with a siloed approach to each matter. For example, before review began, Lighthouse review experts counseled individual case to teams to implement a coding layout for each jurisdiction that facilitated work product reuse and consistency across matters. As new related matters come up, our experts will bring their deep institutional knowledge to continue to drive these types of unique efficiency and consistency gains. A Strategic Approach Leads to Faster Reviews and Productions Once data was migrated into the document repository, Lighthouse review experts designed one strategic review plan for all 14 matters that lowered costs and maximized data reuse and cross-matter insights. As part of this plan, Lighthouse created one national review database and separate jurisdiction-specific review databases. Then, Lighthouse experts used advanced AI and review technology to isolate a core set of 150K documents within the 11M documents housed in the repository that were most likely to be responsive across all jurisdictions. This core set was published to the national review database and fully reviewed by an experienced Lighthouse review team trained by our review managers to categorize each document for both national and jurisdictional responsiveness. After review, Lighthouse copied this strategic production set to each jurisdictional database. This approach kept hosting costs drastically lower for each individual matter, while providing all local case teams with an immediate first production, well ahead of production deadlines. Corporate Case Studyai; ai-and-analytics; analytics; artificial-intelligence; big-data; case-study; corporation; corporate; data-analytics; data-re-use; data-reuse; document-review; ediscovery; ediscovery-migration; healthcare-litigation; litigation; managed-review; prism; tar; tar-predictive-coding; technology-assisted-reviewediscovery-review; ai-and-analytics; client-successAI, ai-and-analytics, analytics, artificial-intelligence, Big-Data, Case-Study, Corporation, Corporate, data-analytics, Data-Re-use, Data-Reuse, data-re-use, document-review, eDiscovery, eDiscovery-Migration, healthcare-litigation, litigation, managed-review, Prism, TAR, TAR-Predictive-Coding, technology-assisted-review, ediscovery-review, ai-and-analytics
Connecting Matters for Better, Faster eDiscovery
Case Study
A large healthcare provider faced a series of related matters requiring document review. Lighthouse designed and executed a single review workflow that provided accurate, consistent, and efficient productions. Lighthouse Managed Review Results Efficient, compliant productions across 14 matters in 9 states (and counting) Nuanced document review performed by one experienced review team, eliminating the need to train multiple review teams Case teams avoided re-reviewing 150K core documents by reusing 100K high-quality review decisions and redactions A Perfect Storm of Review Complexities A large healthcare provider was facing 14 related matters across 9 states. The initial corpus of documents numbered 11M, with each jurisdiction adding more. While each matter shared a core set of relevant issues, they all had their own unique relevancy scope and were being handled by different outside counsel and eDiscovery teams. The corpus was also littered with personally identifiable information (PII) that required identification and redaction by review teams before production. Combining Expertise and Tech to Drive Efficiency The company turned to Lighthouse because of our extensive experience working on complex document review. Our review managers developed a sophisticated workflow to reduce the number of documents requiring review and re-review across jurisdictions by leveraging advanced technology. Custom Workflow Enables Work Product Reuse To lower costs and maximize consistency across matters, Lighthouse created an overall document repository and review database, as well as separate jurisdictional databases. The team migrated all 11M documents into the document repository and used advanced AI and review technology to isolate a core set of documents that were most likely to be responsive across all jurisdictions. Our review managers efficiently worked with all outside counsel teams to validate this core set. They also suggested and implemented a coding layout for each jurisdiction to facilitate work product reuse and consistency across matters. One Skilled Review Team and Review Process for All Matters Our combination of managed review, advanced technology, and custom data re-use workflow resulted in a single document set that met all jurisdiction-specific production requirements. These documents were duplicated across all databases for immediate production in multiple matters. To get to this caliber of review, our review managers used technology to reduce the number of documents needing eyes-on review to 90K and trained an experienced review team on both universal and jurisdictional responsiveness. Technology was also used to expedite PII redaction and propagate coding to the core set of 150K documents. Unprecedented Review Time and Cost Savings With Lighthouse’s review approach, each case team had more freedom in how they structured their post-production workflows. Our approach also provided stricter control of data and enabled more accurate and predictable billing for the client. Further, all 14 matters now had an initial production ready at the push of a button. In addition to lowering costs, this gave local counsel additional time to assess case strategy, with the first production available in advance of agreed-upon deadlines. Instantaneous Initial Production for Multiple Matters Beyond the stellar review outcomes achieved across each matter, Lighthouse’s strategic workflow and use of technology also saved the client an impressive $650K—a delightful surprise to the client, who was prepared to pay more for such a complex litigation series. As new related matters arise, the client can engage a trained and experienced review team ready to hit the ground running. Corporate Case Studycase-study; ai; ai-and-analytics; analytics; artificial-intelligence; big-data; corporation; corporate; data-analytics; data-re-use; data-reuse; document-review; ediscovery; litigation; prism; pii; phi; healthcare; healthcare-litigation; hipaa-phi; managed-review; review; tar-predictive-coding; technology-assisted-review; tar; productionediscovery-review; ai-and-analytics; client-successCase-Study, client-success, AI, ai-and-analytics, analytics, artificial-intelligence, Big-Data, Corporation, Corporate, data-analytics, Data-Re-use, Data-Reuse, data-re-use, document-review, eDiscovery, litigation, Prism, PII, PHI, Healthcare, healthcare-litigation, PII, PHI, HIPAA-PHI, managed-review, document-review, review, TAR-Predictive-Coding, technology-assisted-review, TAR, Production, ediscovery-review, ai-and-analytics
Simplifying Complex Multi-District Document Review
Case Study
Over the course of five months, Lighthouse delivered approximately 4,500 documents for review—out of the 2.3 million document review set—for a Fortune 100 health insurance provider. The Challenge Complex internal False Claims Act investigation 2.3M total documents for review Five-month timeline and tight budget Lighthouse Key Actions Provided curated weekly deliveries of the most important, inclusive documents for review—with no redundant or duplicative versions Compiled summary reports of each delivery (including highlights of high-priority information) to expedite counsel review Out of 2.3M documents, identified and delivered just the 4,500 documents counsel needed to review in order to conduct a comprehensive legal analysis Key Results for Counsel Immediately gained a grasp on the relevant facts and timelines hidden within a massive review set—without wasting time reviewing irrelevant information Quickly developed a deeper understanding of the underlying risks and nuances of the investigation, through consistent and iterative communication with Lighthouse search experts Confidently completed the investigation on time and within budget—even after large volumes of new data were added mid-investigation A Challenging Internal Investigation into False Claims Act Violations A Fortune 100 health insurance provider was pursuing an internal investigation involving potentially improper diagnosis practices undertaken by a wholly-owned provider group. The scope of the investigation included analysis of reimbursements processed across 20+ disease categories, potentially triggering False Claims Act violations. With 2.3M documents to review, it was unclear how the internal investigation would be completed within a constrained budget and timeline. Counsel reached out to Lighthouse for help. Lighthouse Hands Counsel the Keys to a Focused, Efficient Investigation A small team of Lighthouse information retrieval, legal, data science, and linguistic experts immediately began working with counsel to understand the specific allegations at issue, as well as catalogue the various sources of data that needed to be investigated. The team then designed and executed a battery of complex searches tailored to find instances of fraud or wrongdoing related to the allegations at hand. By staying in close communication with counsel, the Lighthouse team ensured that new search requirements and data sources were quickly integrated into the workstream to support fact development. On a weekly basis, Lighthouse delivered a streamlined set of documents responding to counsel’s evolving theory of the case. These deliveries also included a detailed breakdown of the categories of documents identified each week, descriptions of relevant internal processes and policies, and flagging of high-priority documents of particular interest to counsel. Each delivery was distilled down to only the most inclusive, non-redundant versions of relevant documents. In addition to keeping pace with ongoing requests and deliverables, the Lighthouse team also re-executed previous searches to address waves of new data rolling in midway through the engagement. A Faster and More Comprehensive Investigation Resolution Over the course of five months, Lighthouse delivered approximately 4,500 documents for review—out of the 2.3 million document review set. The Lighthouse deliveries encompassed everything counsel needed to know in order to resolve their investigation—and nothing more. The team accomplished this precision through deep subject matter expertise surrounding the allegations and underlying issues at play, consistent and effective communication with counsel, expert topic-based searching, and additional proprietary data analytics to remove unnecessary duplicative content. By the end of their short engagement with Lighthouse, counsel had developed a comprehensive understanding of the pertinent risk areas and confidently completed their investigation—on time and within budget. Corporate Case Studycase-study; corporate; corporation; ediscovery; fact-finding; document-review; investigations; kdi; key-document-identification; keyword-search; insurance-industry; analytics; ai-and-analyticsediscovery-review; ai-and-analytics; client-successCase-Study, client-success, Corporate, Corporation, eDiscovery, fact-finding, document-review, investigations, KDI, key-document-identification, keyword-search, insurance-industry, analytics, ai-and-analytics, ediscovery-review, ai-and-analytics
Lighthouse Streamlines a Complicated False Claims Investigation
Case Study
Lighthouse experts uncover key evidence in just two weeks eliminating 97% of document set. The Challenge Complex internal investigation into potential employee fraud 627K total documents Two-week timeline Key Results for Counsel Confidently completed a complex fraud investigation in just two weeks—without fear of missing critical information Significantly mitigated risk to the company through the identification of previously unknown internal control gaps Lighthouse Key Actions Executed 22 strategic searches, based on expert analysis, to identify all relevant evidence of employee fraud and misconduct Uncovered hidden information, previously unknown to counsel, that revealed additional acts of fraud, embezzlement, and misconduct by targeted employees—as well as potentially problematic internal control gaps Out of 627K documents, identified and delivered, just the 16K documents counsel needed to review in order to conduct a comprehensive fact investigation A Complex Employee Fraud Investigation The audit division of a health insurance provider was pursuing an internal investigation involving potentially concealed employee conflicts of interest with external vendors. The allegations involved possible defrauding of the parent organization through noncompliant contract and billing practices, as well as embezzlement of membership incentives for personal use and gain. With approximately 627K documents to review on an exceptionally tight timeline of two weeks, it was unclear how a comprehensive internal investigation would be completed to ensure proper due diligence. Counsel reached out to Lighthouse for help. Lighthouse Experts Quickly Uncover Key Evidence A small team of Lighthouse information retrieval, legal, data science, and linguistic experts immediately began working with counsel to understand the specific allegations at issue. As part of this work, the Lighthouse team catalogued the various sources of data that needed to be investigated. Based on counsel’s theory of the case, the team devised eight main search themes that would enable them to find instances of fraud or wrongdoing related to the allegations at hand. Over the course of the short two-week engagement, the Lighthouse team completed 22 discrete searches with corresponding deliveries based on expert analysis of the eight priority search themes. Each delivery was distilled down to include only the most inclusive, non-redundant versions of relevant documents so counsel wasn’t bogged down by reviewing a slew of duplicative and/or irrelevant documents. Over the course of searching, Lighthouse experts quickly uncovered new key information that was previously unknown to counsel. This information revealed a picture of internal control gaps used to circumvent company policies, leading to problematic vendor contract arrangements and suspect billing practices. Separately, the Lighthouse team also uncovered details of relevant personal circumstances of targeted employees. This new information shed light on the potential motivation for bad acts, including substantial personal debt, resentment of parent company controls, and personal relationships with superiors in the management reporting structure. Significant Risk Mitigation and Faster Investigation Resolution with Lighthouse In just two weeks, Lighthouse delivered a targeted set of approximately 16K documents, out of a total 627K in the review set. The Lighthouse deliveries represented everything counsel needed to know about the possible fraudulent employee activity—including concealed information that posed significant risk to the company if it had been left undiscovered. The team was able to accomplish this precision through deep subject matter expertise regarding the fraud allegations, comprehensive metadata analysis and emotional content detection, consistent and effective communication with counsel, expert topic-based searching, and exhaustive content deduplication. With Lighthouse’s partnership, counsel quickly gained a thorough understanding of the internal controls, potential fraud, and the embezzlement issues at play—ultimately enabling them to significantly mitigate risk and complete their investigation in just two weeks. Corporate Case Studycase-study; corporate; corporation; ediscovery; fact-finding; document-review; investigations; kdi; key-document-identification; keyword-search; insurance-industry; analytics; ai-and-analytics; fraud-detectionediscovery-review; ai-and-analytics; client-success; lighting-the-path-to-better-ediscoveryCase-Study, client-success, Corporate, Corporation, eDiscovery, fact-finding, document-review, investigations, KDI, key-document-identification, keyword-search, insurance-industry, analytics, ai-and-analytics, fraud-detection, ediscovery-review, ai-and-analytics
Lighthouse Uncovers Key Evidence in Fast-Paced Employee Fraud Investigation
Case Study
By partnering with Lighthouse, clients reduce their data and save millions of dollars while ensuring quality and security. What They Needed Recently, Lighthouse was brought in by the Department of Justice (DOJ) of a large western US state who had to produce data for a high-stakes, multi-million dollar breach of contract matter. The client was dissatisfied with their current eDiscovery panel and was looking for a new provider who could help centralize eDiscovery with document review, use advanced technologies to reduce data, and ensure quality and security. How We Did It To kick things off, Lighthouse and the client team met to discuss the key goals and expected outcomes of this particular case. It became very clear that the client wanted to reduce data in a defensible way and so our team of legal and technology experts got to work. At the start of the matter, our team collected and processed more than 3.5TBs of client source data (i.e. 9M documents) as well as 98K documents that had been produced by opposing counsel and 135K documents that had been produced by 22 various third parties. In addition, we collected approximately two dozen mobile devices as well as advised and assisted outside counsel on a declaration defending the process for collection and production of mobile devices. Next, we brought in the use of best-in-class technology. We leveraged our search consulting team to apply our early case assessment (ECA) tool to the data after processing, and less than 14% of the original corpus (i.e. 1.2M documents) was promoted from the ECA database. Within the ECA environment, we assisted the client with culling, search term iteration, and helped the client to develop and sample search terms for use during negotiations with opposing counsel. After agreeing upon and validating search terms with opposing counsel, the result set was promoted from ECA for review. Within the review environment, we instituted a technology assisted review (TAR) workflow to reduce the overall review population to 420K documents (a 65% reduction after applying ECA) and prepared defensibility reports for opposing counsel. Finally, we used our thread suppression technology to suppress duplicative emails. ‍ We then developed a custom automated workflow to incorporate confidential de-designation decisions from 16 co-defendants on individual documents and reproduced them. An additional 155K documents were loaded directly to review without culling. For review of the remaining ~500K records, we then implemented our managed review solution—managing a review team (provided by our trusted review partner) through a very successful first pass review, privilege review, and privilege log creation process. ‍ The Results Ultimately, the client produced 260K documents in this matter and saved significant time and money. Lighthouse was able to reduce the original corpus by more than 95% through the use of best-in-class technology and our legal, review, and technology experts. Because of the service quality, support, breadth of capabilities, and expertise exhibited during the matter, the client has since migrated several active matters from different providers to Lighthouse. ‍ Corporate Case Studycase-study; ediscovery; tar; tar-predictive-coding; investigations; analytics; predictive-coding; privilege; privilege-reviewediscovery-review; ai-and-analytics; client-successCase-Study, client-success, eDiscovery, TAR, TAR-Predictive-Coding, investigations, analytics, predictive-coding, privilege, privilege-review, ediscovery-review, ai-and-analytics
The Benefits of Best-in-Class Technology on a High-Stakes Matter
Case Study
Lighthouse partners with a healthcare company, saving $145K in document review costs after reducing review time by 90% through a custom review process. How We Did It Initial Processing Lighthouse used our proprietary processing automation to ingest, load, and deduplicate a total of 690K documents. Our deduplication process was able to immediately achieve a 25% data reduction by removing 175K documents. ECA Culling and Search Term Iteration Results Next, Lighthouse applied our customized culling and search term iteration processes to the 143K eligible documents and families. This process removed 81K documents, reducing the review population by over 55%. Thread Suppression and Proprietary Review Technology Results Lighthouse then implemented a customized workflow that combined email thread suppression with our proprietary review technology to identify the most unique documents. This process removed a total of 31K documents from the review population, thereby reducing the review population by another 50%. Lighthouse TAR and Advanced Analytic Results After the culling process, Lighthouse’s Review & Advanced Analytics team guided counsel through a Continuous Active Learning TAR workflow to find relevant documents. Once we reached a point of diminishing returns, we leveraged advanced analytics such as clustering, categorization, and concept search to ensure that no relevant documents were left behind. Our TAR and advanced analytics removed 17K documents, representing another 50% in data reduction. Corporate Case Studycase-study; corporate; corporation; ediscovery; tar; tar-predictive-coding; ai-and-analytics; analytics; predictive-coding; healthcare-litigation; healthcare; processing; machine-learningediscovery-review; client-successCase-Study, client-success, Corporate, Corporation, eDiscovery, TAR, TAR-Predictive-Coding, ai-and-analytics, -analytics, predictive-coding, healthcare-litigation, Healthcare, Processing, machine-learning, ediscovery-review
Lighthouse Achieves Review Efficiency and Cost Control for a Global Healthcare Company
Case Study
Lighthouse's proprietary AI technology solves a unique data deduplication challenge while migrating over 25 terabytes for an extensive healthcare system. Key Results In 5 months, Lighthouse migrated four databases—with 25 TBs of data—all while keeping the databases active for review and production for current matters. Leveraging our AI technology, Lighthouse created an innovative solution for a large volume of Lotus Notes files originally processed as HTML files by a legacy processing tool. This solution ensured that any new Lotus Notes files would deduplicate against the migrated data, regardless of the file type or the tool used for processing. A Challenging Data Deduplication Problem A large healthcare system had been hosting its data (over 25 TBs of data across four databases) on another vendor’s platform for nearly a decade. The company knew it was time to modernize its eDiscovery program with Lighthouse. In order to do so, all 25 TBs would need to be migrated over to Lighthouse for hosting and future processing. However, in addition to data migration, the company also had a unique deduplication challenge due to the previous vendor’s original processing tool. The company’s data had originally been processed with the vendor’s legacy processing tool—which processed Lotus Notes data as HTML files, rather than the more modern EML version. The prior processing of these files into an HTML format meant that whenever duplicate Lotus Notes files were added to the database and processed using a more modern processing tool, those EML files would not deduplicate against the older HTML files in the databases. With over half their data consisting of Lotus Note files processed by the older tool in HTML format, the company was concerned that this issue would significantly increase review cost and slow down review time. Thus, in addition to the overall migration process, the company came to Lighthouse with an unfortunate Catch-22: in order to modernize its processing and eDiscovery capabilities, it was losing the ability to deduplicate a majority of its data with each new ingestion. Lighthouse Migration Expertise Because of the volume of new clients moving to Lighthouse for eDiscovery support, Lighthouse has developed an entire practice group dedicated to data migration. This group is adept at creating customized solutions to the unique challenges that often arise when migrating data out of legacy systems. The team works closely with each client to understand the scope, types of data, challenges, and future needs so that the data migration process is seamless and efficient. The Lighthouse migration team quickly got to work gathering information from the healthcare company to start this process, paying particular attention to the Lotus Notes deduplication issue. Once all relevant information was gathered, Lighthouse worked with stakeholders from the organization to form a comprehensive migration plan that minimized workflow disruption and included a detailed schedule and workflow for future data. In the process, Lighthouse also developed a custom solution for the Lotus Notes issue using our proprietary AI technology. An Innovative Solution: Lighthouse AI Lighthouse’s advanced AI technology can create a unique hash value for all data, no matter how it was originally processed. The Lighthouse migration team leveraged this innovative technology to create a unique hash value for the Lotus Notes files that were originally processed as HTML files. That hash value could then be matched against any new Lotus Notes files that were added to the database by the company, even when those files were processed as EML files. With this proprietary workflow, the healthcare company was able to seamlessly move to Lighthouse’s eDiscovery platform, which was better equipped to serve its eDiscovery needs—without losing the ability to deduplicate its data. Set Up for Success In just five months, Lighthouse completed a seamless migration of the healthcare company’s data by creating a custom migration plan that minimized blackouts and kept all databases up and running. Importantly, Lighthouse also leveraged its proprietary AI to create an innovative solution to a complex problem, ensuring continued deduplication capability and reduced discovery costs. ‍ Corporate Case Studycase-study; ai; ai-and-analytics; ai-big-data; corporate; corporation; ediscovery; ediscovery-migration; prism; processing; project-management; healthcareediscovery-review; ai-and-analytics; client-successCase-Study, client-success, AI, ai-and-analytics, AI-Big-Data, Corporate, Corporation, eDiscovery, eDiscovery-Migration, Prism, Processing, Project-Management, Healthcare, ediscovery-review, ai-and-analytics
Lighthouse Uses AI to Complete a Seamless, Customized Data Migration
Case Study
Top ten global law firm revitalizes their eDiscovery program with Lighthouse Managed Services for one predictable, recurring price. What They Needed After years of carrying hefty infrastructure costs and operating with limited access to emerging eDiscovery solutions, one of the ten largest law firms globally decided to look for a new eDiscovery partner that could advance their existing eDiscovery program without the burden of unpredictable, piecemeal pricing and sub-par technology. In particular, the firm was interested in a predictable cost model that would provide them with access to forensics, information governance, and eDiscovery experts as well as innovative new analytic and chat technology. To further complicate things, they had less than two months to migrate all of their existing data to the newly selected vendor before they would have to renew payments with their existing vendor. How We Did It Lighthouse Managed Services was a natural fit for this cutting-edge client. We were selected as the firm’s eDiscovery provider because it was clear we could provide a wide-range of subject-matter experts, access to best-in class technology (particularly our proprietary Spectra ® and SmartSeries ™ , as well as third-party tools like Nuix, Relativity, and Brainspace) and deliver within their tight timeline requirements – all for one predictable, recurring price. After the selection process, Lighthouse immediately tackled the migration of over 130 cases and ~13 TB of the firm’s data from their existing vendor’s environment to the Lighthouse environment within the 45-day requirement. Once the cases were restored, we worked with the firm to develop custom workflows that would allow the new data to flow through active migrated matters seamlessly without loss of deduplication, matter-level settings, or work product. We then developed a comprehensive eDiscovery playbook for our client detailing customized, repeatable, and defensible eDiscovery processes for every stage of the EDRM. We also began technology training sessions to allow our client to effectively utilize their access to tools like Relativity and Brainspace, as well as our proprietary Spectra and SmartSeries technology. Further, Lighthouse developed a custom Relativity template to ensure the user experience in Relativity mirrored the law firm’s workflows for continuity. We scheduled bi-weekly meetings with the Lighthouse Product Development team to keep the firm’s team abreast of new features on the horizon as well as allow the firm an opportunity to influence the overall product roadmap. All of this work was completed under a predictable, recurring pricing model, with custom reports around the firm’s matters and metrics. Results Overall, Lighthouse Managed Services surpassed of all the firm’s expectations – completely revitalizing their eDiscovery program for one predictable pricing model. We successfully completed the entire data migration within 45 days, without any disruption to case teams. Once migrated, our client was elated with the access Lighthouse provided to the best technology on the market, as well as the comprehensive training we offered their teams which enabled them to leverage these tools more effectively. In particular, Spectra enabled the firm to administer matters autonomously while getting data into a review platform at a much greater speed than ever before. Since the time of the launch, this client has started over 90 new matters in Spectra, leveraging the analytics, predictive coding, automated redaction, privilege log creation, and chat messaging tools that make our self-service solution the best in its class. Providing all these comprehensive services under a recurring, predictable processing model allowed this client to successfully manage cost recovery and integrate with their client billing seamlessly. Law Firm Case Studycase-study; ediscovery; self-service, spectra; spectra; analytics; processing; managed-review; document-review; review; law-firmediscovery-review; client-success; lighting-the-path-to-better-ediscoveryCase-Study, client-success, eDiscovery, self-service, spectra, Spectra, analytics, Processing, managed-review, document-review, review, Law-Firm, ediscovery-review
Top-Ten Global Law Firm Overcomes Budgetary Challenges
Case Study
Lighthouse collected, processed, and imaged 550 GB of data in less than 96 hours, saving a client from an eight-figure sanction. What They Needed Lighthouse’s client, an Am Law 100 firm, had to respond to a request for production in a highly sensitive matter. The client originally contracted another eDiscovery service provider for collection, processing, and production. Much of the collected data was corrupt and the other service provider was unable to handle a large majority of the data. Facing an eight–figure sanction if the production deadline was missed, the client abandoned their provider and contacted Lighthouse. Lighthouse had 14 days to resolve corrupt data, process the data, identify and segregate the already reviewed data, provide the unreviewed data for review, and produce the responsive data. Complicating matters even further, the data set was sizeable—550GBs—and the client needed at least a week to review the data before production. How We Did It Collect, Analyze, Repair A close inspection of the data revealed that another on-site collection would be necessary in order to deal with the corrupt data. On February 9, two forensic experts from Lighthouse collected three email exchange servers totaling 550 gigabytes. Lighthouse was able to repair some of the corrupt data; however, some data was corrupt at the source. This corrupt data could not interfere with the production to the government so Lighthouse processed the non-corrupt data overnight. The client then requested additional searching and culling for a specific list of custodians. Reduce, Process, Deliver As a result of the way the data was stored, Lighthouse had to navigate through a large number of files to identify the data belonging to the list of custodians. Ultimately, Lighthouse was left with 245 gigabytes which it further culled and filtered. Lighthouse’s experts then segregated 8,000 documents that the client previously reviewed so that the client did not have to waste time re-reviewing these documents. With the deadline looming, Lighthouse immediately imaged the documents for review. Lighthouse provided client with just over 25,000 images for review on February 13. Results As a result of Lighthouse’s speed and ability to handle the corrupt data, the client avoided an eight-figure sanction. In a matter of 96 hours, Lighthouse forensically collected 550 gigabytes from three email exchange servers, extracted 245 gigabytes from those servers, identified 8,000 documents in a corrupted media environment, and imaged over 25,000 documents. Law Firm Case Studybig-data; case-study; collections; ediscovery; forensics; law-firm; processing; production; project-managementediscovery-review; digital forensics; client-successBig-Data, Case-Study, collections, eDiscovery, digital forensics, Law-Firm, Processing, Production, Project-Management, ediscovery-review, digital forensics
Big Data, Impossible Timeline, Successful Results
Case Study
A prominent law firm leveraged a cloud-based software solution to increase efficiency and scale, resulting in significant costs savings. What They Needed A mid-sized East Coast law firm­—known for its expertise and experience in complex and high-stakes matters—was looking for new software to replace its in-house legacy technology. Their in-house tool did not provide the level of sophistication or throughput the team needed to continue to scale their work for their clients. In assessing their potential new partner, the firm required access to best-in-class technology, in particular Relativity and Nuix, as the firm’s employees were already familiar with these platforms. In addition, they wanted to leverage automation to have repeatable processes that would save both themselves and their clients time and money. ‍ How We Did It Lighthouse Spectra was selected for its simple and intuitive interface that allows users to internally manage client matters across best-in-class technology – including Relativity, Nuix, and even Brainspace. With Spectra, the firm can now start matters immediately, without having to go through the vendor solicitation and/or statement of work processes, creating real time savings. And the monthly subscription price for Spectra gave them more transparency around billing and greater cost control to help them stay within their budget. The onboarding and training processes were quick, due to the experience of the internal team coupled with the ease of use of Spectra’s. After the initial deployment of Spectra, the firm started processing client data through the tool immediately. They were able to get these matters through processing (Nuix) to review (Relativity) within a few hours, rather than an entire day or more, as was typical with their previous in-house solution. We can go from soup to nuts without having to reinvent the wheel each time. It is truly self-service. — Law Firm The Results Soon after onboarding, the firm took on a couple quick-turn and complex matters that they were able to handle more quickly due to the speed and scale of Spectra, as well as the support of Spectra team. In one instance, they received a request late in the work day that needed to be turned around within a short period of time. Prior to deploying Spectra, that would have taken some hands-on experience and a day’s worth of time. With Spectra, they were able to process it as soon as they received it and it was available for review within a few short hours. In another instance, the firm received a request with a pressing deadline where the document set consisted of approximately 95% foreign-language text. Quickly translating the text to English was imperative to firm’s success. To solve this problem, the Spectra team pointed the firm to a machine language translation tool that easily integrates with Spectra. By deploying the integrated translation service on the workspace, documents submitted for translation were loaded back into the workspace as easily as if it was performing a mass edit. This provided an easy solution for the firm for this particular matter, and now that it’s integrated, the feature is available to the firm on demand. By moving to Spectra, the law firm was able to leverage best-in-class technology, gain more transparency and control around the entire eDiscovery process, and create efficiencies and therefore, reduce costs for themselves and their clients. Leveraging Spectra, the law firm can now do more with less and scale their business to support their clients’ growing needs. ‍ Law Firm Case Studycase-study; ediscovery; self-service, spectra; spectra; ai-and-analytics; analytics; processing; tar-predictive-coding; technology-assisted-review; tar; law-firmediscovery-review; client-successCase-Study, client-success, eDiscovery, self-service, spectra, Spectra, ai-and-analytics, analytics, Processing, TAR-Predictive-Coding, technology-assisted-review, TAR, Law-Firm, ediscovery-review,
Law Firm Gets Ahead with In-House eDiscovery Software
Case Study
With Spectra, Penningtons Manches Cooper accelerated their ediscovery workflow and created a more efficient and cost-effective process. What They Needed Penningtons Manches Cooper LLP, a leading UK and international law firm, was looking for an innovative solution to enable more efficient and cost-effective management of their increasing eDiscovery needs. At the same time, they also wanted a solution that would not require a large investment in hardware, additional personnel, or training. When the team at Penningtons Manches Cooper reached out to Lighthouse about their needs, we suggested Spectra, our cloud-based, self-service eDiscovery solution that would enable the team at Penningtons Manches Cooper to easily run their matters in a more efficient and predictable manner. Additionally, the team at Penningtons Manches Cooper also wanted the option of leveraging experienced, knowledgeable, and on-demand assistance as required. Because Spectra offers the ability to seamlessly transition a matter from self-service to Lighthouse’s full-service team of eDiscovery experts, it provided the Penningtons Manches Cooper team a level of reassurance that there would always be help on hand should it be needed. The team at Penningtons Manches Cooper agreed that Spectra was the right eDiscovery solution for them. How They Did It Penningtons Manches Cooper partnered with Lighthouse to deploy Spectra, which was implemented within three months from initial proof of concept to rollout with live matters. Primary areas of focus during the implementation were training, process design, and internal change management. The project began with roundtable sessions to fully understand the scope and ensure that deployment was customized to fit Penningtons Manches Cooper’s requirements, deliverables, and goals. And because Spectra is a cloud-based solution, there was no capital expenditure or additional IT resourcing required for implementation. This allowed for a flexible approach, fast implementation, and low ongoing maintenance for Penningtons Manches Cooper. Once the tool was initially implemented, the team at Penningtons Manches Cooper identified a suitable matter to be used in a proof of concept. Lighthouse trained key Penningtons Manches Cooper personnel on how to use Spectra, and together the two teams worked to create a scalable and repeatable workflow for particular work types. All items were recorded in a bespoke playbook, which fully documents Spectra’s capabilities and process as well as specific Penningtons Manches Cooper requirements. Next, Lighthouse provided training to the wider Penningtons Manches Cooper team on Spectra, Brainspace, and Lighthouse’s proprietary SmartSeries® tools to enable the firm to leverage automated redaction, chat, and other emerging solutions. Due to the simplicity and on-demand nature of Spectra, the team at Penningtons Manches Cooper was able to realize a 1 to 4-hour reduction in the time it takes to create a matter and upload data into Relativity. Further, Lighthouse developed a custom Relativity template. to ensure the user experience in Relativity is mirrored across matters and complements the firm’s workflows. Following the successful trial period, Penningtons Manches Cooper has identified and managed many other matters in Spectra with very little external support. Setup of each new matter has been reduced significantly, in some circumstances by up to 2-3 days, as there has been a significant reduction in the number of steps required to instruct external eDiscovery vendors, including no need to gather price proposals, no delay while vendors run conflict checks, and no need for any additional contract negotiation. As a consequence, each legal team was typically able to begin reviewing documents on the same day the data was received by the firm. In conjunction with the above, predictable and recurring billing practices were implemented and custom reports were developed around the firm’s matters and metrics. This, in turn, will allow Penningtons Manches Cooper to manage cost recovery and integrate billing for a more seamless and efficient process. The Results Penningtons Manches Cooper partnered with Lighthouse to roll out Spectra, which enabled their team to control the process from the very start and create efficiency and predictability of cost and process. By using Spectra, the team at Penningtons Manches Cooper was able to create matters in Relativity and Brainspace as well as upload and process data quickly, all within a simplified and intuitive interface. The use of best-in-class technology, combined with repeatable process and in-house expertise, created a tangible benefit, ensuring eDiscovery and document review are completed with minimal cost, a savings which can be passed on directly to the client. Law Firm Case Studycase-study; financial-services-industry; corporate; corporation; ediscovery; self-service, spectra; spectra; analyticsediscovery-review; client-successCase-Study, client-success, financial-services-industry, Corporate, Corporation, eDiscovery, self-service, spectra, Spectra, analytics, ediscovery-review
Penningtons Manches Cooper Takes Control of their eDiscovery Process with Lighthouse Spectra
Case Study
Lighthouse Spectra helps a considerable healthcare organization gain control, pricing transparency, and efficiency gains in the eDiscovery process. What They Needed A large healthcare organization was looking to solve their eDiscovery challenges around speed and cost. Specifically, they needed to increase their overall efficiency, and have more control over their matters with truly transparent and lower ediscovery-related costs. How We Did It Lighthouse Spectra was chosen to help achieve these key goals. Spectra is a self-service, on-demand eDiscovery tool with a transparent subscription-based pricing model. Spectra users can also access a full-time project management team at Lighthouse, whenever needed – all for one predictable price. Spectra onboarding was tailored to the users’ needs and focused on teaching users how to use Spectra itself, as well as when and how to use Brainspace, an analytics engine available inside the platform. Since Spectra is built with an intuitive interface, it only took a few short trainings over the course of a few weeks for the users to become comfortable using it. The Lighthouse team also ensured that Relativity and Spectra were customized to the organization’s specific needs. Our teams ensured that all customized permissions and views were set up within Relativity and worked with the organization to create custom Relativity templates to apply their standard coding pallets, rule-based coding propagations, pre-baked saved searches, standard views/layouts, imaging profiles, and more. Additionally, the Lighthouse team also assisted in building a continuous multi-model learning (CMML) workflow for their team to leverage within Spectra. Once set up was complete, the organization immediately started leveraging Spectra to process their data and run search terms as needed on a variety of diverse case types, including labor and employment cases, internal investigations, and OIG requests. The Results By moving to Spectra, the healthcare organization gained more control over their eDiscovery processes, created more efficient workflows, and achieved significant cost savings with transparent and predictable pricing. Since deploying the tool, the organization found that using the search and analytics capabilities of Spectra reduced the volume of natives to just 4.5% of the total hosted volume, minimizing the count of documents being reviewed by 95%. The custom Relativity template prevents the need to reinvent the wheel with each new matter and drive consistency across their portfolio. Further, the CMML workflow allows the organization to prioritize review of documents that are most likely to be responsive, as well as minimize the number of documents that go to review. Both of these enhancements allowed the organization to increase their overall speed from collection to production while lowering their overall eDiscovery-related costs. Through these new workflows and processes, the healthcare organization has achieved both defensibility and affordability and reduced review time from days to hours. This has resulted in an overall savings of $500K in their first year with Spectra.\ Corporate Case Studycase-study; corporate; corporation; ediscovery; self-service, spectra; spectra; ai-and-analytics; analytics; processing; tar-predictive-coding; technology-assisted-review; tar; healthcareediscovery-review; client-successCase-Study, Corporate, Corporation, eDiscovery, self-service, spectra, Spectra, ai-and-analytics, analytics, Processing, TAR-Predictive-Coding, technology-assisted-review, TAR, Healthcare, ediscovery-review
Fortune 500 Company Saves $500K+ with New In-House eDiscovery Software
Case Study
Lighthouse partners with a global law firm to meet a 60-day production deadline for an 11.5 million-document population, saving the firm millions. What They Needed A global law firm was representing a large analytics company being investigated by the Federal Trade Commission (FTC) for antitrust activity. The company faced an extremely aggressive production deadline—approximately 60 days to collect, review, and produce responsive documents from an initial data population of roughly 11.5M. How We Did It The firm partnered with Lighthouse to create a workflow to execute multiple work streams simultaneously (collections, processing, TAR, privilege review, and logging) to ensure the company could meet the production deadline. Lighthouse expert teams managed the entire process, implementing daily standup calls and facilitating communication between all stakeholders to ensure that each workflow was executed correctly and on time. Lighthouse clients that leverage our AI technology to its full potential can realize even more cost savings and efficiency. For example, in this case, this global law firm would have seen the removal of close to 420K documents from privilege review that our AI accurately (as verified in the qc process) deemed to be highly unlikely or unlikely to be privilege. The Lighthouse team also provided strategic and defensible review methods to attack data volume and increase overall efficiency throughout the project. This included Technology Assisted Review (TAR) and email thread suppression in combination with our proprietary AI-technology and privilege log application. The different work streams that Lighthouse designed and executed to reduce the time, burden, and expense of review included: Lighthouse Forensic Collection : Lighthouse’s dedicated expert forensic team implemented a workflow to perform all initial collections, as well as all refresh collections across M365 mailboxes, Teams data, OneDrive, and SharePoint. TAR 1.0 : Lighthouse implemented predictive coding via a TAR 1.0 workflow to systematically find and remove non-relevant documents in a defensible manner. Not relevant documents that fell below the cutoff score were removed from the review population to reduce privilege review. Non-TAR Review : A detailed file analysis was conducted on documents that could not be scored via the TAR model by Lighthouse experts to remove non-responsive documents from eyes-on responsiveness review. Email Threading : Once TAR 1.0 reached stability and a cutoff score was achieved, Lighthouse applied email thread suppression on the documents above the cutoff score to further decrease privilege review and the production set overall. Managing Teams data : The Lighthouse team leveraged our proprietary chat tool to deduplicate Microsoft Teams data. Using the tool, the team stitched Teams messages back together in a format that allowed outside counsel to easily see the conversation in totality (e.g., who was part of the thread, who entered/left the chat room, who said what, at what time, etc.). The tool then integrated and threaded chat messages with search and filtering capabilities for review directly in Relativity. Privilege Review : Even as collections, TAR 1.0, email threading, and document review workflows were ongoing, the Lighthouse advanced analytics team leveraged technology in combination with their expertise to drastically reduce the privilege review set and guard against inadvertent production of privileged documents: Lighthouse Strategic Privilege Reduction : Lighthouse data reduction experts worked with outside counsel to analyze the data to identify large categories of documents that could be safely removed from privilege review, such as two large tranches of calendar items that were pulled into the privilege review. Lighthouse also ran a separate header-only privilege screen across and located a pattern in the privilege hits, which outside counsel confirmed were not privileged and removed from privilege review. AI-enabled Privilege QC : To minimize risk and increase efficiency of privilege review, Lighthouse deployed our advanced AI-technology, which uses multiple algorithms to analyze the text and metadata of documents, enabling highly accurate privilege predictions. First, it analyzed the entire review workspace and identified additional privileged documents that were not picked up by the conventional privileged screen approach. Then, the tool was utilized in privilege review QC workflows where it helped reviewers overturn first and second level privilege calls. Privilege logging application : Lighthouse also leveraged our privilege logging application to automate privilege log generation, saving outside counsel significant time and driving consistent work product in creating their privilege log. The Results Lighthouse forensic collection collected roughly 11.5M documents from more than 600 unique datasets and over 90 custodians, spanning M365 mailboxes, Teams data, OneDrive, and SharePoint sources. Lighthouse’s TAR 1.0 workflow then dramatically reduced the document population for privilege review, ultimately removing over 6M documents in full families from review, thereby delivering a savings of nearly $6.2M. The Lighthouse team’s detailed file analysis of non-TAR universe resulted in an additional 640K files removed from responsiveness review—encompassing close to a 90% reduction in the non-TAR review volume and delivering a savings of roughly $640K. Our email thread suppression process then removed another 1.1M documents from review (for a savings of $1.1M), while the Lighthouse proprietary chat tool removed over 63K Teams items and generated over 200K coherent transcript families from 1.3M individual messages. Law Firm Case Studycase-study; antitrust; ediscovery; tar; tar-predictive-coding; law-firm; hsr-second-requests; investigations; mergers; ai-and-analytics; ai-big-data; artificial-intelligence; ai; acquisitions; analytics; predictive-coding; prism; privilege; privilege-review; name-normalization; microsoft; emerging-data-sources; forensics; collectionsediscovery-review; ai-and-analytics; antitrust; chat-and-collaboration-data; client-successCase-Study, client-success, Antitrust, eDiscovery, TAR, TAR-Predictive-Coding, Law-Firm, HSR-Second-Requests, investigations, Mergers, ai-and-analytics, AI-Big-Data, artificial-intelligence, AI, Acquisitions, analytics, predictive-coding, Prism, privilege, privilege-review, name-normalization, microsoft, Emerging-Data-Sources, digital forensics, collections, ediscovery-review, ai-and-analytics, antitrust, chat-and-collaboration-data
Law Firm Saves Millions in Gov't Investigation with AI
Case Study
Cleary Gottlieb and Lighthouse save millions of dollars and thousands of hours in HSRs Second Request for Fortune 500 company. What They Needed A global Fortune 500 electronics company received an HSR Second Request from the Department of Justice (DOJ), with an extremely aggressive timeline to reach substantial compliance. They engaged Cleary Gottlieb (“Cleary”), a global technology-savvy and innovative law firm with extensive experience handling challenging Second Requests. After Cleary led negotiations with the DOJ to reduce the scope of the investigation, the client was faced with 3.3M documents to review—a significant subset of which included CJK language documents that would require expensive and time-consuming translation. To further complicate matters, the DOJ and Cleary remained engaged in ongoing scope negotiations, resulting in additional data being added throughout the project. Cleary knew that conventional TAR technology was not capable of evaluating a dataset with ever-changing review parameters. How Cleary and Lighthouse Did It CJ Mahoney, counsel and head of the eDiscovery and litigation technology group at Cleary, has extensive experience working on complex HSR Second Requests and has pioneered a number of different analytics-driven methods to reach substantial compliance in the past. Based on prior joint success in innovating new ways to use this technology to improve privilege analytics, CJ immediately saw the potential of Lighthouse’s proprietary AI technology for this challenge. Together, CJ and the Lighthouse data scientists developed a unique training workflow to achieve highly precise responsive prediction results on this challenging dataset. CJ secured the DOJ’s first-ever approval of this workflow with Lighthouse’s proprietary AI technology. Immediately after approval, responsive and privilege analysis and review began simultaneously, enabled by AI technology. For responsiveness, the teams utilized an active learning TAR workflow wherein subject matter experts reviewed a control set of randomly selected documents. After only a few training rounds, the system reached stability and began scoring the remaining dataset for responsiveness. A privilege classifier was built based on 20K previously confirmed privilege calls and applied to score all documents in the privilege workspace. The teams used a combination of the analytic results and privilege terms to identify potential privileged documents. All documents within this set that were scored as “highly likely to be privileged” were immediately routed to reviewers for review and privilege logging. Conversely, documents scored as “unlikely to be privileged” were removed from privilege review after Cleary’s attorneys verified the accuracy of the results using a random sample. Further, the teams used the privilege classifier to identify additional privilege documents that had not hit on privilege terms. As the timeline for substantial compliance approached, negotiations with DOJ regarding relevant timeframes and custodians continued, resulting in the near-constant addition and removal of documents from the dataset. The Lighthouse and Cleary teams managed the ever-changing dataset with ease using the Lighthouse technology and workflow developed by the teams. The Results Using a specialized TAR workflow leveraging advanced AI, the teams delivered highly accurate responsive classification, resulting in more than 500K (or more than 40%) fewer documents requiring further review and production to the DOJ, when compared to legacy TAR tools. By creating a smaller volume of documents requiring production, the amount of privilege and foreign language review was also lessened. For example, 120K fewer foreign language documents were included in the final responsive set compared to legacy TAR tool results. This reduction of review and translation saved approximately $1M alone. For the client, the smaller responsive set meant faster production turnaround times, lower overall costs, and risk mitigation through the decreased chance for inadvertent production of non-responsive documents. The Lighthouse and Cleary partnership resulted in the removal of 200K documents from privilege review beyond what could have been possible through conventional methods, leading to cost savings of $1.2M and time savings of 8K review hours. The team further mitigated risk to the client by identifying privilege documents that did not hit on standard privilege terms. The Cleary and Lighthouse partnership resulted in substantial compliance with the HSR Second Request, increased risk mitigation, faster document review, and remarkable savings for the client. Law Firm Case Studycase-study; antitrust; ediscovery; tar; tar-predictive-coding; law-firm; hsr-second-requests; investigations; mergers; ai-and-analytics; ai-big-data; artificial-intelligence; ai; acquisitions; analytics; predictive-coding; prism; privilege; privilege-review; tech-industryediscovery-review; antitrust; ai-and-analytics; client-success; lighting-the-path-to-better-ediscoveryCase-Study, client-success, Antitrust, eDiscovery, TAR, TAR-Predictive-Coding, Law-Firm, HSR-Second-Requests, investigations, Mergers, ai-and-analytics, AI-Big-Data, artificial-intelligence, AI, Acquisitions, analytics, predictive-coding, Prism, privilege, privilege-review, tech-industry, ediscovery-review, antitrust, ai-and-analytics
Saving Millions in a Demanding HSR Second Request
Case Study
A global pharmaceutical company leverages Lighthouse's AI-powered analytics to reduce legal spending, increase efficiency, and decrease risk in their matters. Driving Value on Individual Matters The pharmaceutical company first came to Lighthouse for better, faster review for a single matter. Leveraging our unparalleled range of advanced analytics accelerators, our experienced review managers and expert consultants created a custom review workflow that significantly reduced data volume, expedited review, and increased the accuracy of data classification. Individual Matter Review Workflow and Metrics Driving Value Across All Matters Based on the results from the first matter and Lighthouse’s ability to attain even more review efficiency by connecting matters, the company sent additional matters to Lighthouse. Applying advanced AI across the company’s matters resulted in deeper matter insights and upleveled the accuracy of classification models in ways that that would be impossible on one single matter. As each new matter is added, Lighthouse AI identifies data that overlaps with past and concurrent matters. This has two impacts at the outset: 1) significant processing cost savings and unprecedented 2) early insights into new matters. These insights empower counsel to make more strategic, data-backed decisions from the start, leading to extraordinary downstream efficiencies and significantly reduced risk. For example, across five currently connected matters for the company, Lighthouse AI showed that: “Outside Counsel A” email domains were coded privileged over 95% of the time. Emails with a government email domain on the communication were coded privilege 15% of the time. 20K documents of Custodian B were collected and processed across multiple matters, but only 10 documents were ever actually reviewed. Custodian C’s documents were reviewed and produced across multiple matters, with a 0% privilege rate. Lighthouse AI-powered insights and connections supercharge the efficiency, accuracy, and consistency for each subsequent matter. Past attorney work product and metadata are used to reduce the need for eyes-on review and improve the consistency and accuracy of review for responsiveness, privilege, PII, confidentiality, redactions, and more. Driving Value into The Future The efficiency and risk mitigation benefits continue to grow for the pharmaceutical company with each new matter. A true big data technology, the more data Lighthouse advanced analytics ingests, the deeper and more nuanced its decision-making and insights become. Opportunities for data and attorney work product re-use will also grow with each new matter ingested, amplifying the company’s ROI into the future. Corporate Case Studycase-study; ai; ai-and-analytics; analytics; artificial-intelligence; big-data; corporation; corporate; data-analytics; data-re-use; data-reuse; document-review; ediscovery; litigation; prism; privilege; privilege-review; pii; phi; pharmaediscovery-review; ai-and-analytics; client-success; lighting-the-path-to-better-ediscoveryCase-Study, client-success, AI, ai-and-analytics, analytics, artificial-intelligence, Big-Data, Corporation, Corporate, data-analytics, Data-Re-use, Data-Reuse, data-re-use, document-review, eDiscovery, litigation, Prism, privilege, privilege-review, PII, PHI, Pharma, ediscovery-review, ai-and-analytics
Lighthouse AI and Analytics Drive Unprecedented Savings Across Multiple Matters
Case Study
Lighthouse saves insurance giant millions of dollars during major technology upgrade. Key Actions Microsoft referred the Company to Lighthouse to resolve existing concerns from the Company’s IT and legal departments that were stifling their automation and transition process to Microsoft 365 (M365). Lighthouse held educational workshops on eDiscovery tools within M365, and devised a comprehensive plan for the compliance. Key Results Unblocked the M365 transition effort and enhanced the partnership between legal and IT. Compliance concerns were answered within M365, saving the company millions of dollars in retaining or updating legacy data management systems. What They Needed Legal Concerns Churn 11th Hour Nightmare for IT Department In 2017, a nationwide insurance giant initiated a transition from an on-premises Microsoft solution to a cloud-based M365 solution fueled by gain from cost, performance, and security improvements. Years later, and well past the intended launch date, the Company’s legal team suddenly halted the transition entirely due to concerns of M365’s eDiscovery capabilities, specifically, how M365 would handle the identification, preservation, and collection of email, instant messages, and files for the Company. The legal department insisted the company retain its custom-built archival solution until all compliance concerns were allayed. These demands put the IT department in an extremely tough spot after having already invested several years into the transition to M365. If forced to extend their aging, on-premises solution, the team would face substantial costs. To help unstick the implementation project, Microsoft suggested the Company engage Lighthouse to assist. Lighthouse immediately understood the legal team’s concerns and acted swiftly to address the Company’s insistence on exercising the transition to M365 with great caution, all while remaining vigilant of the Company’s receipt of hundreds of new legal matters monthly. The sensitive nature of data in this industry and the complex regulatory environment made the potential risk related to mismanagement very high. The process was intricate and complex, and required high-level integration to mitigate the significant risks that were specific to individual privacy regulations, such as the California Consumer Privacy Act (CCPA) and the European Union’s General Data Protection Regulation (GDPR). Hands-on Experience and High-touch Service Bridge the Gaps Lighthouse fielded a team of experts with direct experience in the same or similar roles as the various client stakeholders, ranging from IT to records management, corporate legal, and public affairs. This hand-selected team led a three-part process with their counterparts from the Company: Providing education on the eDiscovery aspects of M365 Analyzing current workflows and performance, and expressing their desired future state Devising a high-level design document for how relevant parties could conduct eDiscovery tasks in compliance with the requirements while using M365 The first two processes helped restore unity among stakeholders, while the design document delivered on the legal team’s concerns, including specified settings for a range of M365 applications and components, such as Exchange Online, SharePoint Online, OneDrive for Business, and Teams. The design document made room for process automation and/or custom workflows, as well as for third-party system integration (for compliance archive, legal hold, matter management, etc.). The initial project success led to a continuing relationship between the Company and Lighthouse, and over time Lighthouse has become a critical element in the Company’s ongoing M365 implementation and adoption journey helping them in charting a path forward. Corporate Case Studycase-study; big-data; cloud-migration; cloud; cloud-services; ccpa; corporate; corporation; data-privacy; data-protection; emerging-data-sources; information-governance; ediscovery; microsoft; gdpr; legacy-data-remediation; legal-holds; risk-management; insurance-industry; record-managementmicrosoft-365; data-privacy; information-governance; client-success; lighting-the-path-to-better-information-governanceCase-Study, Big-Data, Cloud-Migration, cloud, Cloud-Services, ccpa, Corporate, Corporation, Data-Privacy, data-protection, Emerging-Data-Sources, Information-Governance, eDiscovery, microsoft, gdpr, Legacy-Data-Remediation, Legal-Holds, microsoft, risk-management, insurance-industry, Record-Management, microsoft-365, data-privacy, information-governance
Gap Analysis Solution for IT and Legal Teams Transitioning to M365
Case Study
Lighthouse bridges internal gaps during technology overhaul and solves longstanding compliance issues for a German multinational healthcare manufacturer. Key Actions Lighthouse engaged company stakeholders in operational planning and received funding from Microsoft to devise and integrate a premium Microsoft 365 (M365) add-on to existing Purview Premium eDiscovery, which resolved an outstanding compliance need. Key Results The proof-of-concept achieved a zero-trust security model integrated with third-party software, and satisfied the barring of critical needs for the Company that centralized IT and legal departments after years of dysfunction. What They Needed Automating a transition to M365 commonly yields a clash between IT, legal, and compliance stakeholders if the decision to convert was spearheaded by IT and made without consulting legal and compliance teams. Typically, during planning or implementation of converting to M365, legal teams ask IT how the new platform will manage compliant and defensible processes, and if IT doesn’t have the answers, the project stalls. This was the situation facing a multinational manufacturing Company that engaged Lighthouse for help during the spring of 2020. At that time, the Company was several years into its M365 transition, and the legal teams’ requirements for adoption of native M365 compliance tools barred a complete transition. Pressure to adopt the tools escalated as M365 workloads for content creation, collaboration, and communication were already rolled out, creating an increasingly large and complex volume of data with significant degrees of risk. Lighthouse Responds to Need and Launches New Technology In partnership with Microsoft Consulting Services, Lighthouse organized a companywide M365 “reset,” hosting a three-day workshop to revamp the transition process and generate an official statement of work. The strategic goal was to streamline the stakeholders from litigation, technical infrastructure, cybersecurity, and forensics teams that previously failed to align. The workshop fielded critical topics geared to encourage constructive discussions between stakeholders and to strengthen departmental trust. The outcome of these discussions eventually enabled the company to move forward with critical compliance updates, including the collection and parsing of Microsoft Teams data, and the management of myriad files and email attachments. Lighthouse took stock of the current state, testing potential solutions, and arrived at a proof-of-concept for an eDiscovery Automation Solution (EAS) that augmented existing M365 capabilities to meet the legal team’s security requirements and remediate any performance gaps. Microsoft recognized the potential value of the EAS for the wider market, ultimately leading to Microsoft funding for the proof-of-concept. Inside the eDiscovery Automation Solution (EAS) Technology Azure-native web application designed to orchestrate the eDiscovery operations of an M365 subscriber through Purview Premium eDiscovery automation Maximized Microsoft Graph API “/Compliance/eDiscovery/” functions and other Microsoft API Simplified to Azure AD trust boundary, targeting the M365 tenant hosted within, and enabling full governance of identity and entitlement throughout Azure and M365 security features Benefits Achieved a zero-trust security model Authorized high-velocity, high-volume eDiscovery tasks without outside technology through automation and orchestration of existing M365 eDiscovery premium capabilities native to M365 Mobilized integration with third-party software included in the Company’s eDiscovery workflows Amplified workload visibility by automatically surfacing relevant Mailboxes, OneDrives, and other M365 group-based technologies dependent upon selected Custodians’ access Corporate Case Studybig-data; case-study; cloud-migration; cloud; cloud-services; cloud-security; corporate; corporation; data-privacy; emerging-data-sources; information-governance; ediscovery; microsoft; manufacturing-industry; risk-managementchat-and-collaboration-data; ediscovery-review; microsoft-365; data-privacy; information-governance; client-success; lighting-the-path-to-better-information-governanceBig-Data, Case-Study, Cloud-Migration, cloud, Cloud-Services, Cloud-Security, Corporate, Corporation, Data-Privacy, Emerging-Data-Sources, Information-Governance, eDiscovery, microsoft, manufacturing-industry, risk-management, chat-and-collaboration-data, ediscovery-review, microsoft-365, data-privacy, information-governance
Engineering a Customized M365 eDiscovery Premium Add-on
Case Study
Lighthouse's forensics experts found hidden clues missed during an internal investigation, proving a departing employee was stealing company data. Lighthouse Key Results By quickly engaging Lighthouse forensics experts: The company stopped proprietary and sensitive information from being disseminated and used by competitors. The company’s law firm was able to quickly take action against the employee, preventing any further malfeasance or damage. Investigation Overview Week 1 Day 1 – 4 — Employee uploads company data onto a personal Google Drive account over the span of four days. ‍ Day 4 – 5 — An internal investigation concludes that all company data has been deleted from the employee’s personal data sources and no further action is needed. However, the company’s outside counsel calls in Lighthouse forensics experts to perform a separate investigation for affirmation. ‍ Day 6 — Lighthouse forensics experts find evidence missed during the company’s internal investigation, indicating that the laptop provided to internal investigators was a “decoy,” and that the employee had actually transferred the proprietary company data onto an as-of-yet undisclosed laptop. Week 2–4 Outside counsel uses Lighthouse’s findings to file a restraining order against the employee and elicit a confession wherein the employee admitted they had downloaded the proprietary data onto a secret laptop—owned by another business. Week 6 Lighthouse forensics team is provided access to the additional laptop and the employee’s private Google Drive account. Although there is no company data stored on the drive, the Lighthouse team dives deeper and immediately finds that the employee had restored the previously deleted company data back to their Google Drive account, transferred it the secret laptop, and then deleted it again from the Google Drive account. These findings enable outside counsel to take additional remediating actions. Suspicious Activity by a Departing Employee Raises Alarm Bells During routine internal departing employee analysis, a global company was alerted to the fact that an employee had uploaded more than 10K files containing sensitive proprietary data to a personal Google Drive account. The company immediately launched an internal investigation and engaged their outside counsel. Over the course of the internal investigation, the employee admitted they had uploaded company data to their Google Drive, and then used an external hard drive to transfer that data onto a personal laptop. However, the employee avowed that all company data had since been deleted—which the company’s IT team confirmed by examining all three data sources. However, due to the sensitivity of the data, outside counsel wanted additional reassurance that the employee was no longer concealing proprietary company data. The law firm had previously relied on Lighthouse forensics experts for similar investigations and knew that they could count on Lighthouse expertise to find any hidden clues that would point to additional hidden data. Finding the Forensic Breadcrumbs Week 1 The Lighthouse forensics team received access to forensic images of the employee’s personal laptop and external hard drive within one week of the first suspicious upload. The team immediately noticed that the employee’s data tracks conflicted with the timelines and statements provided by the employee during the company’s internal investigation. Key Evidence Found by Lighthouse Forensics Experts The external hard drive used to transfer company data had not been plugged in to the personal laptop during the relevant time frame. File paths identified on the external hard drive (which show the file locations where data was downloaded upon connection) did not match those on the personal laptop provided to internal investigators. This evidence led the Lighthouse team to conclude that the laptop provided by the employee was not the laptop used to download company data—and that a different laptop with the stored proprietary company data existed but had not been disclosed by the employee. Week 2–4 A Lighthouse forensics expert provided a sworn declaration explaining the evidence found during the examination of the employee’s personal devices. The company’s law firm used this declaration to file a restraining order to stop the employee from continuing to steal or disseminate proprietary data. The law firm also used Lighthouse’s findings to elicit a confession from the employee, admitting that they had been secretly working part-time for another business, and had transferred the company’s proprietary data onto a laptop provided to the employee by that business. Week 6 Within two weeks of the Lighthouse forensics expert’s sworn declaration, the Lighthouse team was provided access to the laptop owned by the other business, as well as the employee’s personal Google Drive account. Lighthouse’s inspection of the Google Drive did show that all company data had been deleted, as had been confirmed by internal investigators. However, Lighthouse immediately went deeper into the Google Drive and found conclusive evidence that the employee had subsequently “restored” the deleted proprietary data just a few days after the internal investigation ended, in an attempt to continue with the data theft. Key Evidence Found by Lighthouse Forensics Experts Despite the fact that no company data was stored on the employee’s personal Google Drive account at the time Lighthouse received access to it, Lighthouse forensics experts went above and beyond to do a deeper forensic dive into the user activity log, email account, and internet searches stored on the Google Drive. That deeper analysis showed that: Two days after the internal investigation ended, the employee began conducting numerous internet searches for ways to “restore” deleted files on Google Drive. Two weeks later, the employee emailed a private IT company asking for help restoring deleted Google Drive files. One day after sending that email, thousands of files were restored to the employee’s Google Drive. Those restored files were once again deleted a few days later. Before the restored files were re-deleted, the employee downloaded some of the files containing company data to the “secret” laptop owned by another business. Keeping a Lid on Pandora’s Box The evidence found by Lighthouse forensics experts after their initial examination of the employee’s personal devices enabled the company’s law firm to take legal action against the employee less than one month after the first suspicious data upload. Within one day of being provided access to the employee’s personal Google Drive account, Lighthouse forensics experts were able to find exactly how and where the stolen proprietary and sensitive data was hidden. This enabled the company to permanently prevent any dissemination of that proprietary and sensitive data to competitors. ‍ ‍ Corporate Case Studycase-study; corporate; corporation; g-suite; forensics; investigations; collections; fraud-detection; red-flag-reporting; departing-onboarding-employeedigital forensics; client-successCase-Study, client-success, Corporate, Corporation, -G-Suite, digital forensics, investigations, collections, fraud-detection, Red-Flag-Reporting, Departing-Onboarding-Employee, digital forensics
Lighthouse Finds the Hidden Forensic Evidence Other Teams Miss
Case Study
Lighthouse experts distilled crucial information from millions of produced documents for a client's legal strategy during a Department of Justice investigation. Key Actions Lighthouse created 35 deposition kits by conducting two large-scale data investigations—and addressing multiple ad-hoc emergency investigations in the process—on an initial production set of six million documents, identifying the 4,100 most relevant items. Lighthouse adhered to a complex delivery schedule so the case team had time to prepare for each deposition. ‍ Key Results Counsel was well-prepared for 35 depositions using the deposition kits delivered by Lighthouse. Instead of spending time and review cycles finding they evidence, they used the bandwidth they saved to hone their legal strategy. ‍ Responding to a Fast-Moving Government Investigation, with a Merger on the Line When two of the largest publishing companies in the country entered a merger deal, the Department of Justice (DOJ) reacted with a large anti-trust investigation. Pursuant to an HSR Second Request, the companies produced a combined six million documents to the DOJ. In response, the DOJ sought to depose 35 individuals within a few months’ time. This left outside counsel with just two months to prepare for the defense of a massive potential merger, including intensive preparation for all 35 depositions. To do so, they knew they would need to find every shred of relevant information hidden within those six million documents—as quickly as possible. Executing a Plan for Better Legal Strategy When the law firm reached out to Lighthouse for help, our agile search team of analytic, legal, and linguistic experts immediately got to work, consulting with counsel to understand the specifics of the investigation, as well as the case team’s initial strategy for response. Using this background, the Lighthouse team mapped out a information search plan leveraging advanced volume reduction technologies and linguistic search models, delivering: Comprehensive deposition kits for all 35 deponents. Each kit was scheduled to be delivered well ahead of the corresponding deposition date, and included summaries of Lighthouse experts’ findings and highlights of notable documents and facts, in order to give counsel adequate time to prepare for each deposition. Key and relevant documents related to the DOJ’s anti-trust concerns and outside counsel’s defense strategies. These documents, provided on a rolling timeline, were uncovered by conducting two large scale data investigations: one to find all documents related to determining which publishers participated in or won the auctions, and another to find all documents necessary to facilitate the creation of an all-encompassing book auction timeline. Given the legal and analytic expertise of our specialists, Lighthouse search results often uncovered new areas of importance for the case team. When the case team responded to this new information with urgent follow-up search requests (with results sometimes needed in 24 – 48 hours), our team also boosted efforts to provide the requested information. Powering Counsel with Knowledge—and Time By partnering with Lighthouse, the case team stayed focused on preparing for depositions and crafting a response to the DOJ’s concerns to the merger, instead of conducting database searches and reviewing irrelevant or redundant documents. In just two months, Lighthouse found and delivered the 4,100 documents the case team needed, out of an initial population of six million documents. This included creation and delivery of 35 deposition preparation kits, all documents related to the case team’s strategy for responding to the DOJ’s antitrust concerns (delivered on a rolling basis), and results of six ad hoc case team investigation requests. All deposition kit and derivative search deliveries met or exceeded counsel’s delivery deadline expectations. Law Firm Case Studycase-study; document-review; ediscovery; fact-finding; kdi; key-document-identification; law-firm; hsr-second-requests; investigations; mergers; acquisitionsediscovery-review; ai-and-analytics; antitrust; client-successCase-Study, client-success, document-review, eDiscovery, fact-finding, KDI, key-document-identification, Law-Firm, HSR-Second-Requests, investigations, Mergers, Acquisitions, ediscovery-review, ai-and-analytics, antitrust
Law Firm Equipped with 35 Deposition Kits, At or Before DOJ Deadlines, for Massive Antitrust Investigation
Case Study
Lighthouse applies language models and human expertise to uncover critical evidence. What We Did Outside counsel for a large construction firm partnered with Lighthouse to identify key documents Lighthouse used its proven iterative process to reduce the review set Collaborative approach continuously incorporated counsel’s insights into model results Key Results 92,000 documents reduced to 871 Key handwritten reports identified using metadata Counsel freed to focus on most important documents Review completed within the 3-week deadline Piecing Together Contract History Without a Guide A large construction company facing a breach-of-contract suit retained outside counsel. Because personnel involved in the contract were no longer employed by the contractor, the law firm needed to reconstruct the agreement’s history based on related documents and communications. However, with just three weeks for review, a keyword search returned more than 90,000 items. The firm needed a way to identify the most critical documents rapidly and accurately. Iterating and Adapting to Unearth Critical Information The Lighthouse team applied advanced technology and review expertise to get the job done. Counsel provided Lighthouse with 15 topics relevant to contractual changes, such as cost, delays, and weather conditions. The team identified an initial set of documents using linguistic modeling. The law firm provided feedback to update the search models. The insights of the experienced attorneys directed the investigation, while Lighthouse people and technology accelerated the discovery of relevant information. As new topic areas emerged, Lighthouse adapted. They identified additional contractors involved in the dispute and concerns such as employee discontent and time-keeping accuracy. As the search proceeded, they captured important documents even though they were outside the original search parameters. Most importantly, Lighthouse used metadata to highlight relevant site incident reports, the contents of which were not searchable. The law firm could review salient reports in depth, discovering key information concerning the disputed contract. Ensuring Response Readiness Over four iterations, Lighthouse escalated 871 key documents related to 16 case themes, in addition to the handwritten incident reports. Lighthouse data retrieval experts highlighted key language in Relativity and coded and prioritized critical documents to expedite review. Using a powerful combination of linguistic models and case experience, Lighthouse shrank the unwieldy dataset to a manageable size and brought the most critical information to the forefront. Counsel could focus their resources on the most relevant data and maximize value for their client. By the end of the third week and final delivery, the attorneys were well-prepared for negotiations and litigation. Law Firm Case Studycase-study; document-review; ediscovery; fact-finding; kdi; key-document-identification; law-firm; ai-and-analytics; analyticsediscovery-review; ai-and-analytics; client-success; lighting-the-path-to-better-ediscoveryCase-Study, client-success, document-review, eDiscovery, fact-finding, KDI, key-document-identification, Law-Firm, ai-and-analytics, analytics, ediscovery-review, ai-and-analytics
Law Firm Leverages LighthouseIQ to Reconstruct Contract History
Case Study
Lighthouse proprietary, technology-enabled strategy for finding key documents gives counsel a strategic advantage in a challenging HSR Second Request. Key Results In just three weeks, the Lighthouse team found the 1K most important documents out of an initial data population of 19M documents. Lighthouse experts began flowing key documents to the case team just three days after the initial kickoff meeting. Lighthouse saved counsel at least a month’s worth of preparation time for witness interviews and defense planning by efficiently finding the most important documents. A Mountain of Data and a Short Timeline A global technology company and their two outside counsel teams needed to quickly prepare a winning defense in a high-stakes, time-sensitive, Department of Justice (DOJ) Hart-Scott-Rodino (HSR) Second Request. To do so, they would have to identify and review all potentially damaging (or alternatively, helpful) documents within an initial data population of 19M documents. Finding the most important documents within that massive data volume—in less than one month—presented a Herculean task. A Proprietary Solution for Finding the Most Important Documents Lighthouse’s technology-enabled search strategy is led by information retrieval experts with decades of industry experience, who utilize robust search technologies that support large data volumes beyond industry-standard tools. Together, this combination of cutting-edge technology and data expertise quickly surfaces critical documents, streamlining legal analysis and case preparation for case teams. Handing Over the Keys to a Strategic Defense With no time to lose, Lighthouse TAR and review experts were able to whittle down the 19M documents to just over 990K responsive documents for production to meet substantial compliance. Simultaneously, Lighthouse experts quickly got to work finding the most important documents for the case team. Rather than relying on keyword culling, the Lighthouse team analyzed the data population and leveraged proprietary algorithms to safely reduce the universe to documents that contained the unique content the case team needed. From there, a team of six data retrieval experts leveraged proprietary search technology and institutional knowledge of the client’s data, gleaned from working with the company in a managed services capacity, to find key documents that were critical to the case team. Our experts used an iterative process and had weekly meetings with the case team so that they could instantly integrate counsel and witness feedback throughout the project, which helped yield more accurate search results. With this process, the Lighthouse team began flowing key documents to the case team just three days after the initial kickoff meeting. Over the course of the next three weeks, the Lighthouse team provided a total 1K key documents (out of a 990K responsive documents) in eight rolling deliveries. By gaining immediate access to these documents and eliminating the need for time-consuming and costly manual review, Lighthouse saved the team at least a month’s worth of preparation time for witness interviews and defense preparation. Law Firm Case Studyantitrust; case-study; document-review; ediscovery; fact-finding; kdi; key-document-identification; tar; tar-predictive-coding; law-firm; hsr-second-requests; investigations; mergers; acquisitionsediscovery-review; ai-and-analytics; antitrust; client-successAntitrust, Case-Study, document-review, eDiscovery, fact-finding, KDI, key-document-identification, TAR, TAR-Predictive-Coding, Law-Firm, HSR-Second-Requests, investigations, Mergers, Acquisitions, ediscovery-review, ai-and-analytics, antitrust
Finding the Keys to a Strategic Defense in a Second Request
Case Study
Lighthouse partners with a rapidly expanding pharmaceutical company to streamline its eDiscovery workflow and meet obligations more efficiently. What They Needed A large pharmaceutical client received subpoenas from several regulators. The subpoenas covered multiple product lines, implicated 60 custodians, and virtually all the company’s email. The client’s IT group identified over 35TBs of data requiring collection, processing, and review. Complicating matters further, the company had only 60 days to respond, well outside its estimated time of nine months to complete the project. Faced with this near impossible timeline, the client looked to Lighthouse for support. How We Did It Relying on procedures outlined in a jointly developed eDiscovery Playbook, Lighthouse’s data collection and forensics experts worked closely with the client’s legal and IT groups to implement a defensible strategy that greatly reduced the amount of data requiring collection. Experts from Lighthouse’s Advisory Services group worked with the client to implement a legal hold and data retention policy, customized to the various subpoenas. Lighthouse provided a unified review database, allowing outside counsel (who was responding to separate subpoenas) to leverage each other’s work product, greatly reducing review costs and preventing the inadvertent production of privileged and other sensitive materials. The Results Our combined efforts reduced the originally estimated 35TBs of data requiring review to less than 3TBs. By greatly reducing the amount of data requiring processing and review, the client saved significant review costs and reduced the estimated project completion time from nine months to only four weeks. Review cost reductions were achieved by leveraging Lighthouse’s project management team as well as the company’s proprietary suite of technology-assisted review offerings. These, and other efficiencies discovered during the project, have been implemented in future matters, continuing to drive down costs and increase value. Corporate Case Studyadvisory-services; big-data; case-study; collections; corporate; corporation; ediscovery; forensics; information-governance; investigations; pharma; privilege; privilege-review; processing; project-management; tar; tar-predictive-coding; technology-assisted-reviewediscovery-review; digital forensics; ai-and-analytics; information-governance; client-successAdvisory-Services, Big-Data, Case-Study, collections, Corporate, Corporation, eDiscovery, digital forensics, Information-Governance, investigations, Pharma, privilege, privilege-review, Processing, Project-Management, TAR, TAR-Predictive-Coding, technology-assisted-review, ediscovery-review, digital forensics, ai-and-analytics, information-governance
Big Pharma Relies on Lighthouse to Manage Complex eDiscovery
Case Study
Lighthouse red flag report prevents proprietary data from being taken by departing employee. Key Actions A global company partnered with Lighthouse to create a proactive departing employee program to prevent data loss and theft. Lighthouse forensics experts prepared Red Flag Reports for every departing employee that fell within a specific category of employees. Each report outlined the risks associated with the departing employee based on a skilled forensic examination of their activity and data. Soon after implementing the program, a Lighthouse Red Flag Report alerted the company to suspicious activity by a departing employee indicating a high risk for data loss. Key Results Because of Lighthouse’s analysis and quick response, the company was able to: Prevent sensitive data from being disseminated outside the company. Avoid costly litigation associated with proprietary data loss. Reevaluate the departing employee’s severance package due to breach of contract, resulting in additional cost savings. ‍ What They Needed A global company was dealing with an increased risk of data loss and theft from departing employees. The company retains large volumes of proprietary data spread across their entire data landscape. Much of that data is also highly sensitive and would create a competitive disadvantage for the company if it were to end up in competitors’ hands. The company was also facing a higher volume of employee turnover—especially within roles that had access to the company’s most sensitive data (e.g., company executive and management roles). The company was concerned that these factors were creating a perfect storm for data theft and loss. They realized they needed a better system to catch instances of proprietary data loss before any data left the company. Company stakeholders reached out to Lighthouse because they knew our forensics team could help them build a proactive, repeatable solution for analyzing and reporting on departing employee activity. How We Did It Lighthouse forensics experts worked with the company to create a custom departing employee program for data loss prevention. With this program, Lighthouse experts prepared a Red Flag Report for every departing employee that fell within specified high-risk categories (e.g., employees above a specific seniority level, or employees that had access to highly sensitive company data, etc.). Each Red Flag Report was prepared by a Lighthouse forensics expert and summarized the data theft risk associated with the underlying employee. Every report contained: A high-level summary of the risk of data theft presented by the employee. A collection of attachments with highlights and comments by the Lighthouse forensics examiner (for example, a list of files stored in an employee’s personal cloud storage account, with an explanation of why that activity may indicate a higher risk of data theft). A forensic artifact categorization with associated risk ratings (e.g., if there were no suspicious search terms found during a scan of the employee’s Google search history, the examiner assigned that category a lower risk rating of “1”). Recommended next steps, with options for substantiating high-risk employee behavior. Reports were delivered to a cross-functional group of company stakeholders, including IT, human resources, and legal groups. The Results The Lighthouse program very quickly paid off for the company. Soon after initiation, Lighthouse escalated a Red Flag Report for a departing employee that showed a high risk of data loss. Specifically, the Lighthouse forensics examiner flagged that the employee had connected two different external thumb drives containing sensitive company data to their laptop. This activity was flagged by the Lighthouse forensics examiner as high risk because: The employee had already been directed by the company to return any device that had corporate data saved on it; and The employee had previously indicated that they didn’t have any devices to return. As soon as Lighthouse escalated the Red Flag Report, company stakeholders scheduled an interview with the employee. This interview resulted in the employee admitting that they had taken corporate data with them, via the two thumb drives. Because Lighthouse was able to quickly flag the employee’s suspicious activity, the company was able to retrieve the thumb drives before the proprietary data was disseminated to a competitor. The company was also able to reevaluate the employee’s severance package due to the breach of company policy, resulting in a significant cost saving. Even more importantly, the company now has a proven, proactive, and customized solution for preventing data loss and theft by departing employees—implemented by Lighthouse’s highly skilled forensics team. ‍ Corporate Case Studycase-study; corporate; corporation; forensics; investigations; collections; fraud-detection; red-flag-reporting; departing-onboarding-employeedigital forensics; client-successCase-Study, client-success, Corporate, Corporation, digital forensics, investigations, collections, fraud-detection, Red-Flag-Reporting, Departing-Onboarding-Employee, digital forensics
Lighthouse Secure IP On-Demand Services Prevent Proprietary Data Theft by Exiting Employee
Case Study
A leading energy company gained the flexibility to use self-service technology and full-service expertise as needed, reducing costs and optimizing outcomes. Key Actions A multinational energy company sought eDiscovery efficiency and scalability A seamless combination of self-service Lighthouse Spectra eDiscovery and full-service Lighthouse consulting enabled them to meet a wide range of needs Minor matters can be addressed with low-cost self-service tools A full-service Lighthouse team applies in-depth review expertise to complex matters Key Results $50,000 year-over-year cost reduction 100+ hours freed for matter-critical work Flexibility to meet varying matter requirements Training improved speed and accuracy of self-service eDiscovery What They Needed A multinational energy company wanted to stop relying on an expensive patchwork of third-party eDiscovery providers and adopt a unified, cost-effective strategy. It sought transparent pricing and self-service access to the latest technology, including Relativity and Brainspace. At the same time, it needed a consistent team of experienced eDiscovery and review experts for more in-depth needs. How We Did It Lighthouse listened closely as the company described its desire for greater scalability and efficiency. We proposed a seamless combination of self-service capabilities on the Lighthouse Spectra platform and a dedicated full-service team for complex matters. This proven, flexible approach minimizes cost for minor matters while ensuring available capacity and expertise for complex projects. The Lighthouse Spectra support team accelerated onboarding through technical assistance and training. After completing a proof of concept, the client immediately began ingesting matters into Spectra. At the same time, we assembled a dedicated full-service team to be ready when needed. The Results Using the intuitive, familiar Lighthouse Spectra experience—incorporating Relativity and Brainspace functionality—the client rapidly discovered and reviewed data for internal investigations, subpoenas, and other minor matters. They no longer needed to license and manage Relativity and Brainspace separately, benefitting from a predictable, fixed-fee pricing model that fits their budget and scales to meet their needs. The Lighthouse team simplified data processing and exception handling, freeing resources to focus on strategic aspects of a given matter. As soon as a case warranted, they could triage it to the full-service team directly from the Spectra workspace. The result is a more responsive, cost-effective eDiscovery strategy, saving the company hundreds of hours and almost $50,000. Corporate Case Studycase-study; corporate; corporation; ediscovery; self-service, spectra; spectra; energy-industry; analyticsediscovery-review; client-success; lighting-the-path-to-better-ediscoveryCase-Study, Corporate, Corporation, eDiscovery, self-service, spectra, Spectra, energy-industry, analytics, ediscovery-review
Energy Company Saves Time & Costs with Tech and Expertise
Case Study
Lighthouse goes beyond linear review to help a global technology company make its case to the IRS. Key Actions Targeting critical case documents with LighthouseIQ for rather than performing linear review on the whole document set. Identifying key events that took place within specific hours, by applying advanced linguistic modelling to overcome challenges presented by multiple time zones and different time stamp formats within email traffic. Key Results 1.5 million total documents reduced to roughly 37,500. Results in 100-500% less time and at 90-240% lower cost than linear review. Building a Case for Tax-Exempt Lunches A global technology company was facing IRS scrutiny over the complementary lunches the company provided to staff. Full-time workers were comped the meals because, the company claimed, staff were required to respond to emergencies during lunch hours. The IRS was dubious of that claim and inclined to consider the lunches a taxable benefit. To prevent the meals from being taxed, the company needed to demonstrate to the IRS that, over a two-year period, at least 50% of employees at its San Francisco office had in fact responded to an emergency between the hours of 11 a.m. and 2 p.m. local time. For evidence, the company had 1.5 million documents—mostly emails—pertaining to about 1,000 employees. The company reached out to Lighthouse for help finding the best case-building documents within those 1.5 million. Lighthouse offered its Key Document Identification service. Rather than prioritize documents for linear review, the Lighthouse team promised to identify the most valuable and evidential documents—and do so in less time and at a lower cost. Hacking Through the Haystack The Lighthouse team eliminated less-valuable documents in stages. First, they used an advanced algorithm to remove junk and duplicative documents, reducing the document set to 943,000 (a 38% reduction). Among those, the team targeted San Francisco employee names and emails, which brought the total down to 484,000 (an additional 49% reduction). From here, the team employed nuanced, multi-layered linguistic search techniques to zero in on the most necessary and informative documents. Along the way, Lighthouse encountered a number of challenges that would have thwarted other search tools and teams. One of these was the knot of different time stamps attached to emails: the last in time email in every thread was converted to Coordinated Universal Time (UTC), while every previous email in the thread was stamped according to the local time zone of the sender. The Lighthouse team circumvented this by searching the emails’ metadata, which converted all times to UTC. Using this metadata, the team was able to search using a single timeframe (6 to 9 p.m. UTC, corresponding with 11 a.m. to 2 p.m. Pacific). Another challenge was looping together all emails stemming from the same incident, so that Lighthouse could provide the company with a complete account of each emergency response (and avoid counting a given emergency more than once). The team did this by flagging one email tied to a specific emergency and using proprietary threading technology to propagate that flagging to all other emails associated with that emergency. Finally, the Lighthouse team had to classify documents by level of emergency, to help the company build the strongest case. The emergency level of some documents was already classified, thanks to a system installed by the company toward the end of the two years under investigation. But for the majority of documents, it was unknown. Lighthouse was able to classify them using advanced search features of proprietary technology, which identified key terms like “time-sensitive” and other ways emergencies were referenced in the document population. Major Savings and Critical Insights In only two weeks, a two-person team delivered on Lighthouse’s promise to help the company gather evidence, shrink the document population, and save time and money. Had the company tried to build a case with linear review instead, it would have taken up to 5 times longer and cost up to twice as much. Of the 1.5 million total documents, Lighthouse escalated approximately 37,500 (2.5% of the original dataset). To help with case building, the team sorted documents into three tiers of descending priority: employees responding to high-level emergencies during the lunch hour, employees responding to any level of emergency during the lunch hour, and employees responding to high-level emergencies at any time in the day. The Lighthouse team also normalized the metadata for all documents to make it easy for company counsel to see which employees were involved in each document and thread. Across the three tiers: 78% of San Francisco employees were tied to at least one document 74% were tied to at least one non-propagated document (i.e., an email associated with a unique emergency) 68% were the sender of at least one non-propagated document This strongly suggested that more than 50% of employees actively responded to emergencies in the target timeframe and helped counsel hit the ground running in collecting the facts to prove it. Corporate Case Studycase-study; corporate; corporation; ediscovery; fact-finding; document-review; investigations; kdi; key-document-identification; keyword-search; tech-industry; analyticsediscovery-review; ai-and-analytics; client-successCase-Study, Corporate, Corporation, eDiscovery, fact-finding, document-review, investigations, KDI, key-document-identification, keyword-search, tech-industry, analytics, ediscovery-review, ai-and-analytics
Beyond Relevance: Finding Evidence in a Fraction of the Time
Case Study
Spectra, Lighthouse's cloud-based eDiscovery software, saved a pharmaceutical company cost by managing eDiscovery for a third-party subpoena in-house. What They Needed Faced with yet another third-party subpoena, a large pharmaceutical company started to question how they could address these types of matters in a more cost-effective manner. Although sometimes larger in terms of data volume, these types of matters aren’t generally complex and commonly don’t require the expertise and oversight of an outside vendor to manage the eDiscovery process. This case, in particular, had a large data volume with a low dollar value, so the company wanted to explore options outside of the traditional vendor and outside counsel review and production process. How They Did It Lighthouse had been exploring the idea of Spectra, our cloud-based, user-driven eDiscovery solution, with this client for some time and this third-party subpoena seemed to be the perfect fit for their first run. Although the matter was a bit larger in nature, with over 150 GBs of email, it could easily be self-driven by the client’s in-house team of experts within the Spectra environment. To begin, the Spectra team onboarded the client’s team into the tool and provided training, documentation, and access. From there, the client kicked off the matter and uploaded all the documents into Nuix to be processed with the click of a button. Nuix then quickly processed this data and loaded the resulting documents into Relativity for review. Upon investigation of the resulting ~750K document set, the client decided that instead of taking the time to craft and test search terms to identify the potentially relevant files, they preferred to engage Lighthouse’s Focus Discovery team to further reduce and refine the files needing to be reviewed. As a first step, all documents were run through Brainspace to flag lesser included emails that could be removed from the review. Out of the 771,825 documents loaded to Relativity, 168,628 (or 22% of the population), were able to be removed from the review entirely. Next, the client sent Lighthouse’s Focus Discovery team a request for production as well as the subpoena to aid in the search term creation and optimization process. The Focus group worked with the client to create and then optimize the search terms until only ~5,000 hits (0.6% of promoted docs) were flagged for review. At this point, the client team was able to organize the review and review the documents to ensure privilege was considered. Finally, the ~250 relevant documents were produced inside of Spectra and delivered for service to the other side. ‍ The Results Overall, the client was not only able to save significant money on linear review due to a reduced data volume, but also on the traditional review process, as they did not have to outsource it and instead could run their matter in one easy-to-use solution, while accessing on-demand expertise of the Focus Discovery team. The experience thus far has been overwhelmingly positive and the client now has an easy-to-use, self-service solution for handling third-party subpoenas (and other similar matters) in a more cost-effective manner. ‍ ‍ Corporate Case Studycase-study; corporate; corporation; ediscovery; self-service, spectra; spectra; analytics; pharma; ai-and-analytics; processingediscovery-review; ai-and-analytics; client-successCase-Study, client-success, Corporate, Corporation, eDiscovery, self-service, spectra, Spectra, analytics, Pharma, ai-and-analytics, analytics, Processing, ediscovery-review, ai-and-analytics
Significant Cost Savings Achieved Through Lighthouse Spectra
Case Study
Lighthouse analytics reduce responsive review by 80% and privilege review by 45%. What They Needed On behalf of a healthcare technology company, a law firm needed to review more than 3 million documents in 11 weeks under a Hart-Scott-Rodino (HSR) Second Request. Broad search terms meant more than 50 percent of the data population was potentially privileged. How Lighthouse Did It Reducing the Responsive Set and Identifying Privilege Lighthouse used a proven, court-approved technology-assisted review (TAR) approach to minimize costly and error-prone human review. Lighthouse technology quickly integrated Skype and Microsoft Teams chat data into the TAR workflow. Subject matter experts from outside counsel coded document sets to train the AI-powered models. Separate models were used to reduce the responsive set and to perform privilege detection. Once the models were trained, they rapidly and accurately analyzed the entire population of documents, achieving a recall rate of 76 percent and a precision rate of 79 percent. During privilege review, documents on which humans and models disagreed were routed to second-level privilege review. After this quality control step, Lighthouse applied its privilege log and name normalization software, helping outside counsel produce the final privilege log faster. Identifying Sensitive Data Lighthouse created regular expressions, which were used in conjunction with AI to find documents containing protected health information (PHI) or personally identifiable information (PII), which were then marked for redaction without manual review. Lighthouse AI technology also identified potentially toxic communications and flagged them for additional review before production. Results 80 percent reduction in the responsive set, eliminating 1.3 million documents 51 percent reduction in eyes-on review for PII/PHI Eliminated manual review of chat data Identified toxic communications for review before production, typically impossible in Second Request reviews 45 percent reduction in privilege review Identified 55 percent of privilege QC documents incorrectly coded by human reviewers 19,000 documents added to the privilege log efficiently and accurately using Lighthouse technology Law Firm Case Studycase-study; antitrust; ediscovery; tar; tar-predictive-coding; law-firm; hsr-second-requests; investigations; mergers; ai-and-analytics; ai-big-data; artificial-intelligence; ai; acquisitions; analytics; pii; phi; predictive-coding; prism; privilege; privilege-review; name-normalization; hipaa-phi; healthcareediscovery-review; ai-and-analytics; antitrust; client-successCase-Study, client-success, Antitrust, eDiscovery, TAR, TAR-Predictive-Coding, Law-Firm, HSR-Second-Requests, investigations, Mergers, ai-and-analytics, AI-Big-Data, artificial-intelligence, AI, Acquisitions, analytics, PII, PHI, predictive-coding, Prism, privilege, privilege-review, name-normalization, HIPAA-PHI, Healthcare, ediscovery-review, ai-and-analytics, antitrust
How a Law Firm Cut 3M Docs to 440K for Fast HSR Compliance
Report
Beyond the 70%: Market Signals About Microsoft 365 Copilot Adoption
Introduction Go online, and you find blogs, articles, webinars, and podcasts about generative AI (GenAI) everywhere. The subject feels ubiquitous, but how ubiquitous is the official adoption of this innovative technology? We wanted to provide benchmarks to reassure you that you aren’t behind the curve. Since most large organizations use the Microsoft M365 suite, and Copilot is the GenAI tool built into that platform, we investigated Copilot adoption. Our investigations found that a large percentage of organizations are testing Copilot with a group of cross-functional employees, while few have reached enterprise-wide adoption. Many groups have found that a lack of sufficient internal data governance controls places their sensitive information at risk. The need to close this gap is elevating information governance to a business-critical function. Let’s look at what the market has to say about Copilot adoption. Methodology and Sources This piece synthesizes publicly available information from 2024 and 2025. We reviewed Microsoft investor call transcripts, first-party blogs, analyst research and press coverage, and named-party case studies. Where we reference proprietary research that we did not access directly (e.g., Gartner), we rely on reputable secondary summaries.
Adoption
In its FY25 Q1 investor call, Microsoft stated that 70% of the Fortune 500 companies have adopted Copilot. But they did not specify the level of adoption. In fact, in the FY25 Q4 call, they stated that they are in a “seat-add and expansion” phase and optimistically told investors that “customers [are] returning to buy more seats.” These statements are a clear indication that companies are still staging their deployments. A recent Gartner report, “How to Secure and Govern Microsoft 365 Copilot at Scale” (Gartner, Max Goss, Avivah Litan, Dan Wilson, January 2025), highlights a growing challenge in enterprise AI adoption: Security and governance concerns are slowing Microsoft 365 Copilot adoption. In fact, 47% of IT leaders report they are either not very confident or have no confidence at all in their ability to manage Copilot’s security and access risks. Lighthouse’s information governance experts are seeing the same phenomenon in their client interactions. Department Specific Adoption In its Microsoft 365 Copilot Adoption Playbook, Microsoft recommends launching with a limited pilot group first, gathering feedback, assessing value, and optimizing configurations before a wider rollout. While many organizations identify and turn to cross-departmental teams as testers, others have selected departments. Legal In a CLOC 2025 survey, 30% of corporate legal team respondents stated that they have adopted GenAI tools for some tasks, which is nearly double the adoption rate from 2023. While the survey didn’t ask about Copilot use specifically, we can safely extrapolate these numbers for the legal departments within Microsoft-centric enterprises to come up with Copilot adoption. Even when they are not the first group to adopt Copilot, legal departments are integrally involved with initiatives, balancing productivity improvements with ethical, privacy, and compliance considerations. Finance Microsoft has identified the finance department as a good target for Copilot programs, as demonstrated by the fact that they have delivered the most prescriptive content and product depth for them. These tools tend to shorten time-to-value for first deployments. Technology Companies As you might expect, adoption of GenAI tools by technology companies is high. An SAS press release1 referenced earlier supports this assumption; it found that 70% of tech companies (telecom specifically) have already adopted GenAI tools. Since a 2024 report identified Microsoft 365 as the number one app in Fortune 500 companies, we can assume that Copilot is the GenAI tool of choice. Financial Services A recent global banking study2 found that banking leads GenAI integrations. This is supported by Microsoft’s reporting: Sharing wins with investors, it noted that financial institutions lead the way with the largest deployments. Barclays rolled out M365 Copilot to 100,000 employees, and UBS completed a 50,000-license deployment in 2025. Most FinServ organizations are following the typical staged adoption process, and rather than beginning with Finance or HR, they are piloting GenAI in Marketing (47%), IT (39%), and Sales (36%) Departments. Life Sciences Copilot adoption by life sciences (biotech and pharma) companies outpaces the market as a whole with a 58% adoption rate. Of those companies, 34% are using it to help their research efforts. Data Governance, Privacy, and Security Concerns Data security preparedness has been identified as the most significant roadblock to enterprise Copilot adoption. This is a valid concern. One author referred to Copilot as the “world’s greatest bloodhound.”3 M365 Copilot can draw on any content the user can access across SharePoint, Teams, OneDrive, and email, and can base its answers on that information. This all-access capability spotlights lax data governance practices. A 2023 data risk report4 found that 15% of enterprises’ business-critical data is at risk. This issue must be addressed prior to roll-out. In its Copilot implementation documentation, Microsoft emphasizes the importance of ensuring “just enough access” for Copilot users. Highly regulated regions, like the EU/UK have raised concerns about Copilot as it relates to data protection laws. One prominent example is the Data Protection Impact Assessment commissioned by the Dutch government. The report identified four areas of concern: the retention time for user behavior and system usage data, whether DSAR results contain all data required under GDPR, the lack of transparency regarding personal data included in required service data and diagnostic data, and the potential for Copilot to create inaccurate personal data via hallucinations. To its credit, Microsoft has begun to address these concerns. Data security professionals are also concerned about external risks. A M365 Copilot vulnerability called EchoLeak was identified in early 2025. The zero-click attack could secretly and automatically capture and exfiltrate valuable company information or other sensitive information from a user’s email. Microsoft developed a server-side patch, but these types of threats add credence to security concerns. eDiscovery Concerns U.S. Courts are beginning to treat Copilot content, prompts, responses, and, in the case of Andersen v Stability AI / Midjourney (N.D. Cal., 2025), training data, as a new class of ESI subject to preservation and production when relevant and proportional. This potential inclusion in discovery data sets can slow adoption as legal departments create data retention frameworks for this new data type. Lighthouse’s Jason Covey addresses this issue regularly:
Copilot conversations with eDiscovery teams have been limited almost exclusively to how to address compliance considerations with Copilot data artifacts.
— Jason Covey, Senior Consultant, Information Governance, Lighthouse
Accelerators Microsoft has taken steps to mitigate these risks with built-in governance functions. To curb oversharing, SharePoint Advanced Management is now included with M365 Copilot, and Restricted SharePoint Search can be used to scope which sites are accessible by Copilot. It has answered the eDiscovery retention issue with dedicated Copilot prompts and responses. These governance tools are likely to drive quicker adoption. But the true accelerator is likely to be Microsoft’s enormous install base. With over 430 million M365 commercial seats as of FY25 Q3, Copilot is the clear choice as enterprises adopt GenAI. ROI Microsoft’s claims about Copilot’s ability to boost productivity and work quality have been the adoption incentive for many organizations. Forrester noted in its blog that leaders are “seeking a clear payout” and want the true ROI in the form of a “hard-nosed business case.” However, some enterprise leaders are finding that a measurable return on investment is elusive. Effective implementation can be a heavy lift for users and IT staff. User enablement, including prompt design training and implementing new workflows, cuts into already busy work schedules. And prior to releasing the tool, the IT team can spend weeks preparing the data, configuring permissions and security controls, and building governance frameworks. There are documented instances of measurable ROI in the public and private sectors. In a 12-week UK government trial including approximately 20,000 users, participants self-reported that they saved an average of 26 minutes per day by using Copilot.
On average, how much time does using Copilot save you on a daily basis? Microsoft’s legal department measured 32% faster task completion with >20% accuracy. These types of results can create a fear of missing out. This fear of falling behind the AI train has driven some organizations to jettison the business case and proceed with only a promise of future benefits. Conclusion The market signals are clear: Copilot adoption is broad across the market but limited within individual enterprises. This makes sense, given that Microsoft recommends a pilot-first adoption framework. Security, privacy, and eDiscovery risks can slow timelines without preexisting data privacy and regulatory frameworks. But Microsoft is making strides in its efforts to mitigate these risks by adding problem-specific functionality within the M365 platform. Beginning October 2025, Microsoft will bundle the Sales, Service, and Finance Copilots into the core Microsoft 365 Copilot at no additional cost, removing a price barrier to adoption. Beyond Microsoft’s claim of a 70% adoption rate with the Fortune 500, the real story is cautious expansion that follows a proven path: operationalize governance, measure outcomes, and grow from pilots to programs.
eBook
From Buzzword to Bottom Line: AI's Proven ROI in eDiscovery
[h2] Not All AI is Created Equally The eDiscovery market is suddenly crowded with AI tools and platforms. It makes sense—AI is perfectly suited for the large datasets, rule-based analysis, and need for speed and efficiency that define modern document review. But not all AI tools are created equally—so how do you sort through the noise to find the solutions best fit for you? What’s most important? The latest, greatest tech or what’s tried and true? At the end of the day, those aren’t the most important questions to consider. Instead, here are three questions you need to answer right away: What is my goal? How Is AI uniquely suited to help me? What are the measures of success? These questions will help you look beyond the “made with AI” labels and find solutions that make a real difference on your work and bottom line. To get you started, here are 4 ways that our clients have seen AI add value in eDiscovery. [h2] AI in eDiscovery: 4 ways to measure ROI Document review accuracy Risk mitigation Speed to strategy and completion Cost of eDiscovery [h2] AI Improves Document Review Deliverables and Timelines Studies have shown that machine learning tools from a decade ago are at least as reliable as human reviewers—and today’s AI tools are even better. Lighthouse has proven this in real-world, head-to-head comparisons between our modern AI and other review tools (see examples below). Analytic tools built with AI, such as large language models (LLMs), do a better job of detecting privilege, personally identifiable information, confidential information, and junk data. This saves a wealth of time and trouble down the line, through fewer downstream tasks like privilege review, redactions, and foreign language translation. It also significantly lowers the odds of disclosing non-relevant but sensitive information that could fuel more litigation. [h3] Document review accuracy [tab 1: open] Comparison [tab 2: closed] Examples No/Old AI Modern AI Words evaluated individually, at face value Words evaluated in context, accounting for different usages/meanings Analysis limited to text Analysis includes text, metadata, and other data types Broad analysis pulls in irrelevant docs for review Variable efficacy, highly dependent on document richness and training docs Nuanced analysis pulls in fewer irrelevant docs for review Specific base models for each classification type leads to more accurate analytic results [tab 1: closed] Comparison [tab 2: open] Examples Lighthouse AI Results in Smaller, More Precise Responsive Sets* During review for a Hart-Scott-Rodino Second Request, counsel ran the same documents through 3 different TAR models (Lighthouse AI, Relativity, and Brainspace) with the same training documents and parameters. *Data shown is for 70% recall. 308K fewer documents than Relativity; ~94K fewer than Brainspace 89% precision, compared to 73% for Relativity and 83% for Brainspace Lighthouse AI Outperforms Priv Terms In a matter with 1.5 million documents, a client compared the efficacy of Lighthouse AI and privilege terms. The percentage of potential privilege identified by each method was measured against families withheld or redacted for privilege. 8% privilege search terms 53% Lighthouse AI [h2] AI Mitigates Risk Through Data Reuse and Trend Analysis The accuracy of AI is one way it lowers risk. Another way is by applying knowledge across matters: Once a document is classified for one matter, reviewers can see how it was coded previously and make the same classification in current and future matters. This makes it much less likely that you’ll produce sensitive and privileged information to investigators and opposing counsel. Additionally, AI analytics are accessible in a dashboard view of an organization’s entire legal portfolio, helping teams identify risk trends they wouldn’t see otherwise. For example, analytics might show a higher incidence of litigation across certain custodians or a trend of outdated material stored in certain data sources. [h3] Risk mitigation [tab 1: open] Comparison [tab 2: closed] Examples No/Old AI Modern AI Search terms miss too many priv and sensitive docs Search terms cannot show historical coding Nuanced search finds more priv and sensitive docs Historical coding insights help reviewers with consistency Docs may be coded differently across matters, increasing risk of producing sensitive or priv docs Coding can be reused, increasing consistency and lowering risk QC relies on the same type of analysis as initial review (i.e., more humans) QC bolstered by statistical analysis; discrepancies between AI and attorney judgments indicate a need for more scrutiny [tab 1: closed] Comparison [tab 2: open] Examples Lighthouse AI Powers Consistency in Privilege Review A global pharmaceutical company asked Lighthouse to use advanced AI analytics on a group of related matters. This enabled the company to reuse a total of 26K previous privilege coding decisions, avoiding inadvertent disclosures and heading off potential challenges from opposing counsel. Reused priv coding Case A 4,300 Case B 6,080 Case C 970 Case D 4,100 Case E 11,000 [h2] AI Empowers with Early Insights and Faster Workflows Enhancements in AI technology in recent years have led to tools that work faster even when dealing with large datasets. They provide a clearer view of matters at an earlier stage in the game, so you can make more informed legal and strategy decisions right from the outset. They also get you to the end of document review more quickly, so you can avoid last-minute sprints and spend more time building your case. [h3] Speed to strategy and completion [tab 1: open] Comparison [tab 2: closed] Examples No/Old AI Modern AI Earliest insights emerge weeks to months into doc review Initial insights available within days for faster case assessment and data-backed case strategy Responsive review and priv review must happen in sequence Responsive review and priv review can happen simultaneously Responsive model goes back to start if the dataset changes Responsive models adapt to dataset changes False negatives lead to surprises in later stages No surprises QC spends more time managing review and checking work QC has more time to assess the substance of docs Review drags on for months Review completed in less time [tab 1: closed] Comparison [tab 2: open] Examples Lighthouse AI Crushes CAL for Early Insights Case planning and strategy hinge on how soon you can assess responsiveness and privilege. Standard workflows for advanced AI from Lighthouse are orders of magnitude faster than traditional CAL models. Dataset: 2M docs Building the responsive set Detecting sensitive info CAL & Regex 8 weeks 8+ weeks Lighthouse AI 15 days including 2 wks to train and 24 hrs to produce probability assessments (highly likely, highly unlikely, etc.) 24 hrs for arrival of first probability assessments [h2] AI Lowers eDiscovery Spend The accuracy, risk mitigation, and speed of advanced AI tools and analytics add up to less eyes-on review, faster timelines, and lower overall costs. [h3] Cost of eDiscovery [tab 1: open] Comparison [tab 2: closed] Examples No/Old AI Modern AI Excessive eyes-on review requires more attorneys and higher costs Eyes-on review can be strategically limited and assigned based on data that requires human decision making Doc review starts fresh with each matter Doc review informed and reduced by past decisions and insights Lower accuracy of analytics means more downstream review and associated costs Higher accuracy decreases downstream review and associated costs ROI limited by document thresholds and capacity for structured data only ROI enhanced by capacity for an astronomical number of datapoints across structured and unstructured data [tab 1: closed] Comparison [tab 2: open] Examples Lighthouse AI Trims $1M Off Privilege Review Costs In a recent matter, Lighthouse’s AI analytics rated 208K documents from the responsive set “highly unlikely” to be privileged. Rather than verify via eyes-on review, counsel opted to forward these docs directly to QC and production. In QC, reviewers agreed with Lighthouse AI’s assessment 99.1% of the time. 208K docs removed from priv review = $1.24M savings* *Based on human review at a rate of 25 docs/hr and $150/hr per reviewer. Lighthouse AI Significantly Reduces Eyes-On Review The superior accuracy of Lighthouse AI helped outside counsel reduce eyes-on review by identifying a smaller responsive set, removing thousands of irrelevant foreign-language documents, and targeting privilege docs more precisely. In terms of privilege, using AI instead of privilege terms avoided 18K additional hours of review. “My team saved the client $4 million in document review and translation costs vs. what we would have spent had we used Brainspace or Relativity Analytics.” —Head of eDiscovery innovation, Am Law 100 firm [h2] Finding the Right AI for the Job We hope this clarifies how AI can make a material difference in areas that matter most to you—as long as it’s the right AI. How can you tell whether an AI solution can help you accomplish your goals? Look for key attributes like: Large language models (LLMs) – LLMs are what enable the nuanced, context-conscious searches that make modern AI so accurate. Predictive AI – This is a type of LLM that makes predictions about responsiveness, privilege, and other classifications. Deep learning – This is the latest iteration of how AI gets smarter with use; it’s far more sophisticated than machine learning, which is an earlier iteration still used by many tools on the market. If you find AI terminology confusing, you’re not alone. Check out this infographic that provides simple, practical explanations. And for more information about AI designed with ROI in mind, visit our AI and analytics page below.
eBook
AI for eDiscovery: Terminology to Know
Everybody’s talking about AI. To help you follow the conversation, here’s a down-to-earth guide to the AI terms and concepts with the most immediate impact on document review and eDiscovery. Predictive AI. AI that predicts what is true now or in the future. Give predictive AI lots of data—about the weather, human illness, the shows people choose to stream—and it will make predictions about what else might be true or might happen next. These predictions are weighted by probability, which means predictive AI is concerned with the precision of its output. In eDiscovery: available now Tools with predictive AI use data from training sets and past matters to predict whether new documents fit the criteria for responsiveness, privilege, PII, and other classifications. Generative AI AI that generates new content based on examples of existing content ChatGPT is a famous example. It was trained on massive amounts of written content on the internet. When you ask it a question, you’re asking it to generate more written content. When it answers, it isn’t considering facts. It’s lining up words that it calculates will fulfill the request, without concern for precision. In eDiscovery: still emerging So far, we have seen chatbots enter the market. Eventually it may take many forms, such as creating a first draft of eDiscovery deliverables based on commands or prior inputs. Predictive AI and Generative AI are types of Large Language Models (LLMs) AI that analyzes language in the ways people actually use it LLMs treat words as interconnected pieces of data whose meaning changes depending on the context. For example, an LLM recognizes that “train” means something different in the phrases “I have a train to catch” and “I need to train for the marathon.” In eDiscovery: available but not universal Many document review tools and platforms use older forms of AI that aren’t built with LLMs. As a result, they miss the nuances of language and view every instance of a word like “train” equally. Ask an expert: Karl Sobylak, Director of Product Management, AI, Lighthouse What about “hallucinations”? This is a term for when generative AI produces written content that is false or nonsensical. The content may be grammatically correct, and the AI appears confident in what it’s saying. But the facts are all wrong. This can be humorous—but also quite damaging in legal scenarios. Luckily, we can control and safeguard against this. Where defensibility is concerned, we can ensure that AI models provide the same solution every time. At Lighthouse, we always pair technology with skilled experts, who deploy QC workflows to ensure precision and high-quality work product. What does this have to do with machine learning? Machine learning is the older form of AI used by traditional TAR models and many review tools that claim to use AI. These aren’t built with LLMs, so they miss the nuance of language and view words at face value. How does that compare to deep learning? Deep learning is the stage of AI that evolved out of machine learning. It’s much more sophisticated, drawing many more connections between data. Deep learning is what enables the multilayered analysis we see in LLMs.
Podcast
A Less is More Strategy for Data Risk Mitigation
Podcast
Innovation in Second Requests: Data is Your Greatest Asset
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All in the Family: What’s Next for Cloud Attachments in eDiscovery?
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eDiscovery Needs Digital Forensics for a Mobile World
Podcast
Generative AI and Healthcare: A New Legal Landscape
Lighthouse welcomes Ty Dedmon, Partner and lead of Bradley’s healthcare litigation team, to assess how generative AI is impacting litigation and what we can do to minimize the risk., Although the novel and often comical uses of generative AI have captured more recent headlines—think philosophical conversations with a chatbot or essays written in seconds using AI—there are big changes happening across sectors of the economy thanks to adoption of new tools and programs, including the legal and healthcare spaces. Recent case law and legislation highlights the new landscape emerging in healthcare litigation with potential long-term implications. Lighthouse welcomes Ty Dedmon , Partner at Bradley who leads their healthcare litigation team, to assess how generative AI is impacting litigation and what we can do to prepare, and to share advice on leverage AI innovation while minimizing the risk. This episode’s sighing of radical brilliance: “ Top AI companies agree to work together toward transparency and safety ,” Kevin Collier, NBCNews , July 21, 2023. Learn more about the show and our speakers on lawandcandor.com , rate us wherever you get your podcasts, and join in the conversation on LinkedIn and Twitter . , ai-and-analytics; ediscovery-review; information-governance, AI, analytics, eDiscovery, Review, information governance, generative AI, PHI, PII, healthcare, HIPAA, podcast, ai-and-analytics; analytics; artificial-intelligence; compliance; data-privacy; healthcare; healthcare-litigation; hipaa-phi; phi; pii; podcast; regulation
Podcast
Why Your eDiscovery Program and Technology Need Scalability
Lighthouse’s Brooks Thompson, Executive Director of Spectra, provides use cases for scaling and diversifying your eDiscovery platform and technology., As the demands of modern data, litigation, investigations, and data privacy continue to grow in scale and complexity, solutions for them need to adapt accordingly. Although there is a lot of noise around the latest generative AI promises or capabilities for eDiscovery, often legal teams and counsel merely need solutions that can effectively scale to their matters at hand. Deploying platforms or technology intended only for larger or more specific matters can be cumbersome and drain resources, leaving teams ill equipped for the variety of projects they encounter. Lighthouse’s Brooks Thompson , Executive Director of Spectra Operations and Support, joins the podcast to provide some practical advice and use cases for scaling and diversifying your eDiscovery platform and technology to make them more comprehensive. This episode’s sighing of radical brilliance: “ Why Companies Can — and Should — Recommit to DEI in the Wake of the SCOTUS Decision , ”Tina Opie and Ella F. Washington, Harvard Business Review , July 27, 2023. Learn more about the show and our speakers on lawandcandor.com , rate us wherever you get your podcasts, and join in the conversation on LinkedIn and Twitter . , ediscovery-review, eDiscovery, Review, , ediscovery; ediscovery-process; analytics; big-data; ai-and-analytics
Podcast
What You Need to Know About the New FTC and DOJ HSR Changes
Brian Rafkin, counsel in Akin’s antitrust and competition practice, joins to examine the HSR rules and share advice for utilizing AI and workflows to manage increased scrutiny., <iframe height="200px" width="100%" frameborder="no" scrolling="no" seamless src="https://player.simplecast.com/f0b5195e-f4b6-4f49-a2ca-4d7aa3638bc2?dark=true"></iframe> ‍ Continuing a more aggressive posture toward corporate mergers, the Department of Justice and Federal Trade Commission recently announced new HSR rules that dramatically change and expand the amount and type of information that needs to be submitted with HSR filings. How will this impact future M&A activity and Second Requests? Brian Rafkin , counsel in Akin’s antitrust and competition practice, joins the podcast to examine the new HSR rules and their potential implications. He also shares best practices for utilizing technology and workflows to manage increased scrutiny and pressure on deals. This episode’s sighing of radical brilliance: “ United States takes on Google in biggest tech monopoly trial of 21st century ,” Dara Kerr, NPR, September 12, 2023. Learn more about the show and our speakers on lawandcandor.com , rate us wherever you get your podcasts, and join in the conversation on LinkedIn and Twitter . , antitrust; ai-and-analytics, antitrust, AI, analytics, HSR, antitrust, FTC, DOJ, M&A, ai-and-analytics; antitrust; artificial-intelligence; biden-administration; document-review; hsr-second-requests; mergers; regulation
Podcast
The Power of Three: Maximizing Success with Law Firms, Corporate Counsel, and Legal Technology
Law & Candor welcomes Michael Bohner, Managing Discovery Attorney at Cleary, and Justin Van Alstyne, Head of Discovery and Information Governance at T-Mobile, to explore the practical aspects of this partnership, including balancing responsibilities, employing technology, and building relationships., In demanding and highly contentious litigation or investigations it can often feel like it’s every person for themselves without much room for partnership. However, this is a lost opportunity. The relationship between the strong trio of corporate counsel, law firms, and legal technology providers is often an unacknowledged key to overcoming critical challenges. By sharing key information, balancing workloads, and building on each other’s expertise, these partners can work together to solve modern data challenges and the toughest matters. Law & Candor welcomes Michael Bohner , Managing Discovery Attorney at Cleary, and Justin Van Alstyne , Head of Discovery and Information Governance at T-Mobile, to explore the practical aspects of this partnership, including balancing responsibilities, employing technology, and building relationships. This episode’s sighing of radical brilliance: “ Meet Aleph Alpha, Europe’s Answer to Open AI ,” Morgan Meaker, Wired, August 30, 2023. Learn more about the show and our speakers on lawandcandor.com , rate us wherever you get your podcasts, and join in the conversation on LinkedIn and Twitter . , legal-operations; ediscovery-review, legal operations, eDiscovery, Review, corporate-legal-ops; ediscovery; law-firm; legal-ops; legal; corporate; ediscovery-process
Podcast
Juneteenth and Legal: A Legacy, Celebration, and Future
In a special series, we unpack the history of Juneteenth, explore what it means for today’s society, and celebrate the successes of African Americans in the legal and legal technology industries., In 2021, Juneteenth became the first new federal holiday since Martin Luther King Jr. Day was recognized in 1983. It was a significant acknowledgement at the national level, but Juneteenth has had a long and rich history in the African American community as a day of celebration and remembrance—of both the history of emancipation, and the past, present, and future fight for freedom. In a special release of Law & Candor, we commemorate Juneteenth with guest hosts Duval Miller and Reem Saffouri as they speak to African Americans in the legal space. In episode one, Ronique Richburg , Review Manager at Lighthouse, joins to explore the history of Juneteenth, discuss its significance today, and celebrate the success of African Americans in the legal and legal technology industries. This episode's sighting of radical brilliance: Black Girls CODE , diversity-equity-and-inclusion, diversity-equity-and-inclusion, dei
Podcast
Juneteenth and Legal: The Work for Advancing Equity
Our guests discuss how grassroots campaigns, allyship, equitable pay policies, and executive visibility and sponsorship can contribute to greater equity in the workplace., June 19th is a day for celebration and a recognition of the continued fight for freedom and equity for African Americans. While progress has been made in recent years, there is still more that organizations in the legal and legal technology industries can invest in to meaningfully contribute to greater equity. Law & Candor welcomes Oral Pottinger , partner at Mayer Brown, and Stacy Ybarra , Chief Marketing Officer at Lighthouse, to discuss how grassroots campaigns, allyship, equitable pay policies, and executive visibility and sponsorship can contribute to greater equity in the workplace. This episode's sighting of radical brilliance: Robert Smith Pledges To Pay Off Student Loans For Morehouse College's Class Of 2019 , NPR Theme music by Vitamin D For more Juneteenth stories and resources, please visit our Juneteenth page or check us out on LinkedIn . , diversity-equity-and-inclusion, diversity-equity-and-inclusion, dei
Podcast
Prioritizing Information Governance and Risk Strategy for a Dynamic Economic Climate
Lica Patterson, Senior Director of Global Advisory Services at Lighthouse, discusses how assessing short and long-term risk can inform a more strategic information governance program., As we continue to grapple with a strange and unpredictable economic environment, establishing your legal and information governance priorities can be daunting. While directing investment and energy into the most urgent matters is a reflex during a down economy, neglecting more long-term data issues and risk can be detrimental. How do you balance these interests with already strapped resources? Lica Patterson , Senior Director of Global Advisory Services at Lighthouse, joins the podcast to discuss how assessing short and long-term risk can inform a more strategic information governance program. She also shares how the right technology and teams contribute to accomplishing goals and evolving your program. This episode's sighting of radical brilliance: 3 trends will shape the future of work, according to Microsoft’s CEO , World Economic Forum, February 10, 2023. If you enjoyed the show, learn more about our speakers and subscribe on lawandcandor.com , rate us wherever you get your podcasts, and join in the conversation on LinkedIn and Twitter . , information-governance; data-privacy; microsoft-365, information-governance, data-privacy, microsoft-365, emerging-data-sources; legal-holds; podcast; record-management; risk-management
Podcast
Legal’s Mental Health Imperative
Amy Sellars, Senior Legal Counsel at CBRE, joins Law & Candor to discuss some of the contributors to mental health challenges in the legal industry and some practical approaches to remedy them., To kick off the episode, Bill and Paige discuss a piece from Law.com that looks at a recent surge in diverse, female general counsels . Next, they welcome Amy Sellars , Senior Legal Counsel, eDiscovery Operations, at CBRE, for an important conversation about the mental health crisis in the legal industry. They discuss some of the drivers of mental health challenges and what can be done at an individual and industry level to help. They explore a variety of questions, including: How has the pandemic or other factors contributed to greater challenges with mental health we’ve read about? Improving mental health is a challenge we’ve seen many industries grapple with recently. Are there unique challenges in legal and eDiscovery that have contributed to the epidemic we’re seeing today? While we’ve heard about ways to personally manage stress, there are also some structural issues at play. What are some strategies or approaches you’ve seen to help improve work/life balance or how work is allocated? As an industry, how can we continue this conversation and keep advancing initiatives to improve mental health and well being for everyone? If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us wherever you get your podcasts, and join in the conversation on Twitter . , diversity-equity-and-inclusion, podcast, mental health, diversity-equity-and-inclusion,, podcast; mental-health
Podcast
The Chat Effect: Improving eDiscovery Workflows for Modern Collaboration Data
Law & Candor welcomes Vanessa Quaciari, Senior eDiscovery Counsel at Baker Botts, to discuss improvements in collection, review, and production that can help you manage collaboration data., We are all participating in the unprecedented evolution of workplace communication. From virtually editing a shared document, to “liking” a chat message, to responding to a colleague with an emoji during a video call—most employees in a modern work environment are actively (and often unknowingly) creating large volumes of collaboration data. For the legal and eDiscovery professions, the speed of this innovation has necessitated parallel rapid advancements in technology and new approaches to workflows to stay ahead of the complexity and scale of chat and collaboration data. Law & Candor welcomes Vanessa Quaciari , Senior eDiscovery Counsel at Baker Botts, to discuss improvements in collection, review, and production that can help you manage collaboration data and scale your approach as the evolution continues. This episode's sighting of radical brilliance: ChatGPT If you enjoyed the show, learn more about our speakers and subscribe on lawandcandor.com , rate us wherever you get your podcasts, and join in the conversation on LinkedIn and Twitter . , chat-and-collaboration-data; ediscovery-review, collections, review, emerging data sources, podcast, production, chat-and-collaboration-data, ediscovery-review, collections; review; emerging-data-sources; podcast; production
Podcast
Optimizing Review with Your Legal Team, AI, and a Tech-Forward Mindset
Lighthouse’s Mary Newman, Executive Director of Managed Review, joins the podcast to explore how adopting a technology-forward mindset can provide better results for document review teams., To keep up with the big data challenges in modern review, adopting a technology-enabled approach is critical. Modern technology like AI can help case teams defensibly cull datasets and gain unprecedented early insight into their data. But if downstream document review teams are unable to optimize technology within their workflows and review tasks, many of the early benefits gained by technology can quickly be lost. Lighthouse’s Mary Newman , Executive Director of Managed Review, joins the podcast to explore how document review teams that adopt a technology-forward mindset can provide better review results now and in the future. This episode's sighting of radical brilliance: An A.I. Pioneer on What We Should Really Fear , New York Times, December 21, 2022. If you enjoyed the show, learn more about our speakers and subscribe on lawandcandor.com , rate us wherever you get your podcasts, and join in the conversation on LinkedIn and Twitter . , ai-and-analytics; legal-operations; lighting-the-way-for-review; lighting-the-path-to-better-review; lighting-the-path-to-better-ediscovery, review, ai/big data, podcast, managed review, ai-and-analytics, legal-operations, review; ai-big-data; podcast; managed-review
Podcast
Why Your Data is Key to Reducing Risk and Increasing Efficiency During Investigations and Litigation
Cassie Blum, Senior Director of Review Consulting at Lighthouse, discusses how to implement a data reuse strategy, including what technology and workflows can optimize its success., Handling large volumes of data during an investigation or litigation can be anxiety-inducing for legal teams. Corporate datasets can become a minefield of sensitive, privileged, and proprietary information that legal teams must identify as quickly as possible in order to mitigate risk. Ironically, corporate data also provides a key to speeding up and improving this process. By reusing metadata and work product from past matters in combination with advanced analytics, organizations can significantly reduce risk and increase efficiency during the review process. Law & Candor welcomes Cassie Blum , Senior Director of Review Consulting at Lighthouse, to discuss how to implement this data strategy, including what technology and workflows can optimize its success. This episode's sighting of radical brilliance: 7 Ways to be a more inclusive colleague , Fast Company , February 24, 2023. If you enjoyed the show, learn more about our speakers and subscribe on lawandcandor.com , rate us wherever you get your podcasts, and join in the conversation on LinkedIn and Twitter . , chat-and-collaboration-data; ediscovery-review; lighting-the-path-to-better-ediscovery, podcast, data reuse, document review, chat-and-collaboration-data, ediscovery-review, podcast; data-reuse; document-review
Podcast
Review Analytics for a New Era
Law & Candor welcomes Kara Ricupero, Associate General Counsel at eBay, for a conversation about how analytics and reimagining review can help solve data challenges and advance business imperatives., In episode two, we introduce our new co-host Paige Hunt , Vice President of Global Discovery Solutions at Lighthouse, who will be joining Bill Mariano as our guide through the legal technology revolution. In their first Sighting of Radical Brilliance together they chat about an article in Wired that explores the rise of the AI meme machine, DALL-E Mini . Then, Paige and Bill interview Kara Ricupero , Associate General Counsel and Head of Global Information Governance, eDiscovery, and Legal Analytics at eBay. They explore how a dynamic combination of new technology and human expertise is helping to usher in new approaches to review and analytics that can help tackle modern data challenges. Other questions they dive into, include: How did you identify the kind of advanced technology needed for modern data challenges? Partnering with the right people and experts across the business to utilize technology and insights seems to be a big part of the equation. How did you work with other stakeholders to leverage analytics? With new analytics and intelligence, has it changed how you approach review on matters or other processes? How do you think utilizing analytics will evolve as data and review continue to change? What kinds of problems do you think it can help solve? If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , listen and rate the show wherever you get your podcasts, and join in the conversation on Twitter . , ai-and-analytics; ediscovery-review; lighting-the-way-for-review; lighting-the-path-to-better-review; lighting-the-path-to-better-ediscovery, review, data-re-use, ai/big data, podcast, ai-and-analytics, ediscovery-review, review; data-re-use; ai-big-data; podcast
Podcast
Everything Dynamic Everywhere: Managing a More Collaborative Microsoft 365
Emily Dimond, Managing Senior Counsel, eDiscovery, at PNC Bank, shares practical strategies for managing updates in Microsoft 365 and how to develop an agile governance program., Collaborative technology—great for employee productivity but often challenging for legal and IT departments. Balancing the risk and reward requires a deep understanding of ever evolving updates while proactively managing those changes. As organizations adopt cloud-based enterprise software like Microsoft 365, previous change management and governance approaches are often no longer sufficient. Emily Dimond , Managing Senior Counsel, eDiscovery, at PNC Bank, shares practical strategies for managing updates in M365, including recent changes to transcripts and loop components, and how to develop a strong governance program equipped for today’s dynamic landscape. This episode's sighting of radical brilliance: Where is Tech Going in 2023? Harvard Business Review, January 26, 2023. If you enjoyed the show, learn more about our speakers and subscribe on lawandcandor.com , rate us wherever you get your podcasts, and join in the conversation on LinkedIn and Twitter . , microsoft-365; chat-and-collaboration-data; lighting-the-path-to-better-information-governance, microsoft, emerging data sources, podcast, record management, microsoft-365, chat-and-collaboration-data, microsoft; emerging-data-sources; podcast; record-management
Podcast
An Expert View on the Critical Data Privacy Issues for 2023 and Beyond
Jennifer Garone—Senior Director of Privacy and Information Governance at Carnival Corporation—joins Law & Candor to discuss what we should know about data privacy in 2023, including GDPR and CCPA., If there has been any constant in the wave of privacy changes since the enactment of GDPR, it’s been the need to stay vigilant about the impacts of evolving regulations and enforcement globally. From changes to the California Consumer Privacy Act to challenges with cross-border data transfers, there is more to keep up with than ever. Data privacy veteran Jennifer Garone —who is currently the Senior Director of Privacy and Information Governance at Carnival Corporation—joins Law & Candor to discuss what we should know about data privacy in 2023 and what’s key for the future. This episode's sighting of radical brilliance: Takeaways from the Supreme Court's hearing in blockbuster internet speech case , CNN, February 21, 2023. If you enjoyed the show, learn more about our speakers and subscribe on lawandcandor.com , rate us wherever you get your podcasts, and join in the conversation on LinkedIn and Twitter . , data-privacy; information-governance, ccpa, gdpr, data-privacy, podcast, data-privacy, information-governance, ccpa; gdpr; data-privacy; podcast
Podcast
Spring Cleaning for Legal Teams: The Cloud and Defensible Deletion of Data
Law & Candor welcomes Erika Namnath of Lighthouse to discuss new challenges with data retention and deletion in the Cloud, developing a defensible disposal program, and getting stakeholder buy-in., To kick off the show, Bill Mariano and Rob Hellewell discuss another Sighting of Radical Brilliance: How scientists are using AI to identify new drug combinations for children with incurable brain cancer. Next, they interview Erika Namnath from Lighthouse about how to develop a sound and efficient defensible deletion program and the benefits of getting buy-in for it throughout an organization. Some of the key questions they discuss include: Defensible disposal of data continues to be a key challenge for eDiscovery and information governance programs. Why has this issue persisted and how has it evolved? Historically, because of the risk of deleting important information or not being able to defend deletion, teams have defaulted to saving as much as possible. Why is this approach becoming increasingly impossible and even poses a greater risk? How should leaders approach developing a data retention and disposal program or updating their existing one? When developing these retention policies and updates, we often hear challenges with legacy data and legal holds. How can teams wrap their heads around existing data while also considering what they’re retaining today? It seems a significant challenge for these programs is gaining stakeholder buy-in and assigning ownership for retention and deletion. What can leaders do to tackle this? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us wherever you get your podcasts, and join in the conversation on Twitter . Related Links : Blog post: Cloud Adaptation: How Legal Teams Can Implement Better Information Governance Structures for Evolving Software Blog post: Making the Case for Information Governance and Why You Should Address It Now Podcast: Achieving Information Governance through a Transformative Cloud Migration Article: Scientists use AI to identify new drug combination for children with incurable brain cancer About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for eDiscovery, compliance, and information governance. To learn more about the show and our speakers, visit the podcast homepage . , data-privacy; chat-and-collaboration-data; microsoft-365, cloud migration, legacy data remediation, legal holds, podcast, record management, preservation, risk management, data-privacy, chat-and-collaboration-data, microsoft-365,, cloud-migration; legacy-data-remediation; legal-holds; podcast; record-management; preservation; risk-management
Podcast
Data Governance for the BYOD Age
Our hosts chat with Lighthouse's John Bair about implementing proactive data management programs and emerging challenges with remote working, including mobile devices and collaboration data., Law & Candor returns for Season 10 with co-hosts Bill Mariano and Rob Hellewell. They kick off the episode with a discussion of a Harvard Business Review article about the ways AI can make strategy more human. Next they are joined by John Bair , Senior Consultant in Digital Forensics at Lighthouse, to discuss bring your own device (BYOD) policies, implementing proactive data management programs, and emerging data challenges with remote working. Some questions that they tackle include: From a data governance and management perspective, what are the greatest challenges that have emerged from working from home and BYOD policies? Many organizations may have governance programs in place but still struggle with new data sources or devices. What can make some programs inadequate to face these changes? For those needing to refresh their governance approach, or build something new, what advice do you have for creating a more proactive program to get ahead of these data challenges? How should legal teams work with IT to ensure these types of programs are a success? How should we think about their roles? As mobile devices and virtual work continue to advance, how can teams ensure their data governance programs keep pace? If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , listen and rate the show wherever you get your podcasts, and join in the conversation on Twitter . , chat-and-collaboration-data; data-privacy; forensics; lighting-the-path-to-better-information-governance, collections, emerging data sources, departing/onboarding employee, podcast, preservation, risk management, chat-and-collaboration-data, data-privacy, digital-forensics,, collections; emerging-data-sources; departing-onboarding-employee; podcast; preservation; risk-management
Podcast
Mapping Updates to Data Privacy Regulations Worldwide
Our hosts chat with Lighthouse's Sarah Morgan about updates to privacy regulations in the U.S., Europe, and China, how they're impacting businesses, and what's next on the horizon., Bill Mariano and Rob Hellewell kick off this episode with another segment of Sightings of Radical Brilliance, where they discuss major privacy changes by Google and Apple in their mobile software. Next, our hosts chat with Sarah Moran , eDiscovery Evangelist and Proposal Content Strategist at Lighthouse, about updates to privacy regulations in the U.S., Europe, and China. They also dive into the following key questions: How is the enforcement of GDPR impacting businesses? How has the UK’s departure from the EU impacted privacy compliance? With so many states pursuing their own privacy regulations, do we anticipate any movement on a federal level? Beyond the U.S. and Europe, what does the privacy landscape look like internationally? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us wherever you get your podcasts, and join in the conversation on Twitter . Related Links : Blog post: 2021 Data Privacy Overview: New Regulations and Guidance Blog post: Navigating the Intersections of Data, Artificial Intelligence, and Privacy Blog post: The Impact of Schrems II & Key Considerations for Companies Using M365: The Cloud Environment Article: Google Plans Privacy Changes, but Promises to Not Be Disruptive , data-privacy, ccpa, gdpr, dsars, cross border data transfers, pii, podcast, privacy shield, data-privacy,, ccpa; gdpr; dsars; cross-border-data-transfers; pii; podcast; privacy-shield
Podcast
Anonymization and AI: Critical Technologies for Moving eDiscovery Data Across Borders
Our hosts are joined by Lighthouse's Damian Murphy for a lively chat about what AI solutions can be deployed to optimize eDiscovery workflows and maximize data insights while adhering to privacy laws., In this episode's Sighting of Radical Brilliance, our hosts discuss strategies for putting your data to work outlined in a recent Harvard Business Review article. To elucidate the complexities of moving data across borders, Lighthouse's Damian Murphy , Executive Director of Advisory Services in EMEA, joins the podcast. With Paige and Bill, Damian explains recent updates to data transfer policies, and what AI solutions can be deployed to optimize eDiscovery workflows and maximize data insights while adhering to privacy laws. Some key questions they answer, include: With fines continuing to be issued for GDPR violations and organizations grappling with how to transfer data across regions, data privacy is still not a resolved issue. What are some recent policy changes our audience should be aware of? How have these created challenges for the ways that data is managed and how organizations can ultimately utilize it? Many of our listeners are likely aware of how anonymization and pseudonymization are being utilized, but can you remind us how they work? Is there a typical approach for a client faced with the need to supply data held within the EU in order to comply with an eDiscovery order in the US? If the past is any indication, we should expect privacy policies to continue to change and impact data governance. How are anonymization and pseudonymization, and other approaches, helping prepare for what’s on the horizon? If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us wherever you get your podcasts, and join in the conversation on Twitter . , data-privacy; chat-and-collaboration-data; microsoft-365; practical-applications-of-ai-in-ediscovery, gdpr, cross border data transfers, podcast, privacy shield, data-privacy, chat-and-collaboration-data, ai and analyics, microsoft-365, gdpr; cross-border-data-transfers; podcast; privacy-shield
Podcast
A Journey from One to All in Legal with Diversity, Equity, and Inclusion
Lighthouse's Reem Saffouri joins Law & Candor to share her personal journey and discuss how individuals can create greater equity and inclusion at work, in their industry, and beyond., Our hosts begin the show with another Sighting of Radical Brilliance, an article in Forbes about one of the most powerful sources of big data your company already owns . Then, Reem Saffouri , Vice President of Clients Solutions and Success at Lighthouse, joins the podcast to share her personal journey and discuss how individuals can create greater equity and inclusion at work, in their industry, and beyond. Here are some of the key questions they dive into: Although it’s a seemingly simple act, why don’t more people share their personal experiences and why is it so important for DEI efforts? Hearing about structural challenges to DEI can be intimidating and somewhat demoralizing. But along with sharing personal experiences what can individuals do to champion DEI at their organizations? There are nuances and specific solutions that work in each industry for improving equity and inclusion. What are you seeing in legal and legal tech that’s moving the needle? As you look to the future, what aspects of DEI are you hoping to impact? If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us wherever you get your podcasts, and join in the conversation on Twitter . , diversity-equity-and-inclusion, podcast, dei, diversity-equity-and-inclusion, podcast; dei
Podcast
Investigative Power: Utilizing Self Service Solutions for Internal Investigations
Our hosts chat with Justin Van Alstyne, Senior Corporate Counsel at T-Mobile, about best practices for handling internal investigations including the self service tools that have been most effective., Paige and Bill start the show with new and exciting research from MIT Sloan on artificial intelligence and machine learning. Next, their interview with Justin Van Alstyne , Senior Corporate Counsel, Discovery and Information Governance at T-Mobile. They dive into internal investigations, including how a simple, on-demand software solution can offer the scalability and flexibility teams need to manage investigations with varying amounts of data. Some other questions they explore are: How we collaborate and work has changed immensely over the past few years and that evolution doesn’t appear to be slowing down. How have new tools and data sources complicated conducting internal investigations? With organizations encountering investigations of different sizes and degree, what workflows or approaches have you found are most flexible to respond to this variability? Along with process, technology is another key part of the equation. When choosing the right technology for internal investigations, what are some of your high-priority considerations? Are there any features that are must-haves? For people contemplating deploying a self service solution, what advice do you give to ensure your team has the right level of expertise and technology to handle their internal investigations at scale? If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us wherever you get your podcasts, and join in the conversation on Twitter . , ediscovery-review; ai-and-analytics; lighting-the-path-to-better-ediscovery, self-service, spectra, podcast, ediscovery-and-review, ai-and-analytics, self-service, spectra; podcast
Podcast
Microsoft 365 and the Age of Automation
Microsoft’s Stefanie Bier joins Law & Candor to delve into the key types of automation required to support Microsoft 365 at scale for large organizations using Core or Advanced eDiscovery., Bill Mariano and Rob Hellewell bring listeners another Sighting of Radical Brilliance. They discuss an episode of Fast Company’s podcast Innovation Unrestricted that explores how companies can incorporate diversity and inclusion into product design. They are then joined by Stefanie Bier , Senior Program Manager at Microsoft, to chat about how to deploy critical automation in Microsoft 365 and key updates on the horizon. Some questions they explore, include: Automation is increasingly becoming a critical component of managing data and scaling programs. What are some of the new ways collaboration platforms, specifically M365, have introduced automation? What are the benefits of adopting these automated processes? What are some of the key types of automation that are necessary to optimize M365? With the cloud and automated updates, platforms are undergoing faster changes than ever before. How do you stay on top of them and ensure there’s cross-functional alignment at your organization? Whether it’s fear of error or worry about loss of control, some are reticent to automate certain aspects of their programs. What are the risks in not adopting automation? Our co-hosts wrap up the episode with advice for amplifying other women’s voices in the legal and technology industries and some key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , listen and rate the show wherever you get your podcasts, and join in the conversation on Twitter . Related Links Podcast: Understanding Microsoft 365 Unindexed Items Blog post: An Introduction to Managing Microsoft 365 Updates that Present Legal and Compliance Considerations Blog post: Breaking the Bias: Strategies from Top Women Leaders in Legal Technology Podcast: Innovation Unrestricted – How companies can incorporate diversity and inclusion into product design , microsoft-365; information-governance, microsoft, cloud services, podcast, microsoft-365, information-governance, microsoft; cloud-services; podcast
Podcast
Leading in Legal with Inclusive Mentorship
Kelly McGill, Chief People Officer at Lighthouse, discusses the value of mentorship, what a good mentorship program looks like in a virtual work environment, and how to create inclusive cultures., Kicking off season 9 of Law & Candor, co-hosts Bill Mariano and Rob Hellewell , welcome listeners back for a celebration of Women’s History Month. Each guest this season is a woman breaking bias, advancing technology, and championing inclusion in the legal and technology industries. First, they dive into Sightings of Radical Brilliance, discussing a Harvard Business Review article about being a better ally in a remote workplace . Bill and Rob are then joined by Kelly McGill , Chief People Officer at Lighthouse, to chat about the value of mentorship, what a good mentorship program looks like in a virtual or hybrid work environment, and how to create a more inclusive culture. Some key questions they explore, include: Why is mentorship so powerful? What should people seek in a mentor and what makes a good mentee? What are best practices for mentoring in a virtual environment? How does mentorship contribute to more inclusive cultures? Our co-hosts wrap up the episode with advice for amplifying other women’s voices and key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , listen and rate the show wherever you get your podcasts, and join in the conversation on Twitter . Related Links Blog post: Breaking the Bias: Strategies from Top Women Leaders in Legal Technology Blog post: Charting the Path to Progress: A Conversation with Economic Forecaster Marci Rossell and Lighthouse CEO Brian McManus Podcast: Diversity and eDiscovery: How Diverse Hiring Practices Lead to a More Innovative Workforce Article: Managers, Here’s How to Be a Better Ally in the Remote Workplace , diversity-equity-and-inclusion, podcast, diversity-equity-and-inclusion,, podcast
Podcast
Legal’s Balancing Act: Risk, Innovation, and Advancing Strategic Priorities
Megan Ferraro, Associate General Counsel, eDiscovery & Information Governance at Meta, joins Law & Candor to discuss the pivotal role legal is playing in helping innovation thrive while managing risk., Co-hosts Bill Mariano and Rob Hellewell start the show with Sightings of Radical Brilliance. In this episode, they review an article in Reuters exploring lawyer attrition and the “great resignation.” Next, their interview with Megan Ferraro , Associate General Counsel, eDiscovery & Information Governance, Meta. They discuss the delicate balance that must be struck between risk and innovation and explore some of the following questions: How did the legal function evolve to play a bigger role in corporate strategy and innovation? What are the broader trends in the ways legal teams are supporting innovation? With businesses growing, adding new technology, and pivoting strategy quickly, what are the most critical risk challenges legal teams face today? How can legal best work with other functions in an organization to ensure strategic priorities are advanced—through new deals or technology, for example—while also balancing the risk factors? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us wherever you get your podcasts, and join in the conversation on Twitter . Related Links Blog post: Analytics and Predictive Coding Technology for Corporate Attorneys: Six Use Cases Podcast: Innovating the Legal Operations Model Blog post: What Skills Do Lawyers Need to Excel in a New Era of Business? Blog post: Purchasing AI for eDiscovery: Tips and Best Practices Article: To stem lawyer attrition, law firms must look beyond cash - report , ai-and-analytics; legal-operations; ediscovery-review, podcast, project management, risk management, ai-and-analytics, legal-operations, ediscovery-review,, podcast; project-management; risk-management
Podcast
Staying Ahead of the AI Curve
Our hosts and Harsha Kurpad of Latham Watkins discuss how to stay apprised of changes in AI technology in the ediscovery space and practical applications for more advanced analytics tools., Co-hosts Bill Mariano and Rob Hellewell start the show with Sightings of Radical Brilliance. In this episode, they review a recent New York Times article by Cade Metz that explores how new organizations are using AI to find bias in AI . Next, they bring on Harsha Kurpad of Latham Watkins who answers the following questions around staying ahead of AI innovation in legal technology: What are some current barriers to adopting AI? How do you stay apprised of new AI technology, tools, and solutions? What are new data challenges that are leading to a greater adoption of AI or requiring the use of more sophisticated tools? How are government entities like the FTC and DOJ changing how AI is being used and what is required during investigations? What are some best practices for training algorithms and staying on top of new approaches to training? What are some of the risks in not adopting AI or not staying apprised of changes to the tools, platforms, and how it’s being used. Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . Related Links White Paper: The Challenge with Big Data Blog Post: What Attorneys Should Know About Advanced AI in eDiscovery: A Brief Discussion Podcast: AI and Analytics for Corporations: Common Use Cases Blog Post: What is the Future of TAR in eDiscovery? (Spoiler Alert – It Involves Advanced AI and Expert Services) , ai-and-analytics; ediscovery-review, privilege, review, ai/big data, tar/predictive coding, podcast, production, ai-and-analytics, ediscovery-review, privilege; review; ai-big-data; tar-predictive-coding; podcast; production
Podcast
Understanding Microsoft 365 Unindexed Items
James Hart of Lighthouse and our hosts discuss this complex aspect of Microsoft 365 eDiscovery, identify best practices and mitigation strategies, and proactive tips for the future., Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss a framework for building accountability into AI from an article in Harvard Business Review by Stephen Sanford . In this episode, Bill and Rob are joined by James Hart of Lighthouse. They discuss this critical component of Microsoft 365 and its important role in maximizing the effectiveness of ediscovery workflows and mitigation strategies. Key questions from their conversation include: What are unindexed items and how critical are they to efficiency in ediscovery workflows? After identifying unindexed items, what is the next step and how do you approach it? What are some key strategies for handling unindexed items? How are different organizations approaching unindexed items from a policy perspective? What are best practices for approaching this unique issue in Microsoft 365? In conclusion, our co-hosts end the episode with key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . Related Links Blog Post: An Introduction to Managing Microsoft 365 Updates that Present Legal and Compliance Considerations Blog Post: Making the Case for Information Governance and Why You Should Address It Now White Paper: The Impact of Schrems II and Key Considerations for Companies Using M365 Podcast: Keeping Up with M365 Software Updates , microsoft-365; chat-and-collaboration-data; information-governance; lighting-the-path-to-better-information-governance, microsoft, emerging data sources, podcast, record management, preservation, microsoft-365, chat-and-collaboration-data, information-governance,, microsoft; emerging-data-sources; podcast; record-management; preservation
Podcast
Closing the Deal: Deploying the Right AI Tool for HSR Second Requests
Gina Willis of Lighthouse joins the podcast to explore some of the modern challenges of HSR Second Requests and how a combination of expertise and AI technology can lead to faster and better results., Bill Mariano and Rob Hellewell kick off this episode with another segment of Sightings of Radical Brilliance, where they discuss JPMorgan becoming the first bank to have a presence in the metaverse. Next, our hosts chat with Gina Willis , Analytics Consultant at Lighthouse, about how the right AI tool and expertise can help with HSR Second Requests. They also dive into the following key questions: What are some of the contemporary challenges with Second Requests? What AI tools are helping with some of these modern challenges? For Second Requests, what interaction and feedback between attorneys and AI algorithms is optimal to ensure substantial compliance is reached efficiently? Are there some best practices for improving this relationship—deploying the AI better or optimizing algorithms? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us wherever you get your podcasts, and join in the conversation on Twitter . Related Links : Blog post: Deploying Modern Analytics for Today’s Critical Data Challenges in eDiscovery Blog post: Biden Administration Executive Order on Promoting Competition: What Does it Mean and How to Prepare Article: JPMorgan bets metaverse is a $1 trillion yearly opportunity as it becomes first bank to open in virtual world , ai-and-analytics; antitrust; practical-applications-of-ai-in-ediscovery, ai/big data, tar/predictive coding, hsr second requests, podcast, acquisitions, mergers, ai-and-analytics, antitrust, ai-big-data; tar-predictive-coding; hsr-second-requests; podcast; acquisitions; mergers
Podcast
Getting Personal—Wearable Devices, Data, and Compliance
Thora Johnson of Orrick joins Bill and Rob to discuss the new data landscape with wearable devices and health apps, and how it has impacted data compliance, cybersecurity, and privacy concerns., In the final episode of the season, co-hosts Bill Mariano and Rob Hellewell review a New Yorker piece by Kyle Chayka about the beauty and uncanniness of AI-created images delivered by the Twitter handle @images_ai. The co-hosts then bring on Thora Johnson of Orrick for a riveting discussion about the rise in wearable devices and the personal data they’re collecting. They discuss the fascinating innovation in health-related technology and apps and the significant data compliance, privacy, and cybersecurity issues that are accompanying it. Some key questions from their conversation include: Beyond the more well-known wearable devices and health-related apps, what others are out there and what types of data are they collecting? The proliferation of data these devices and apps are generating have created a unique set of intersecting compliance, security, and privacy challenges—what are some of the most critical to understand? How can teams mitigate the risk of a cyber breach? And in the event it does happen, what are best practices in terms of responding to a breach? What should attorneys and legal teams know about the FTC’s recent announcement that it plans to “vigorously” enforce its 2009 Health Breach Notification rule? What regulatory issues related to apps collecting genetic information that people should be aware of? The season ends with key takeaways from the guest speaker section. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . , data-privacy; information-governance, ccpa, gdpr, cybersecurity, emerging data sources, pii, podcast, hipaa/phi, data-privacy, information-governance, ccpa; gdpr; cybersecurity; emerging-data-sources; pii; podcast; hipaa-phi
Podcast
Finding Lingua Franca: The Power of AI and Linguistics for Legal Technology
In this episode, Amanda Jones of Lighthouse will illuminate some common challenges and pitfalls that can arise with modern language in ediscovery., In the very first episode of season eight, co-hosts Bill Mariano and Rob Hellewell introduce themselves and welcome listeners back for another riveting season of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution. They start off with some exciting news about Lighthouse and the recent acquisition of H5 . They then dive into Sightings of Radical Brilliance, the part of the show highlighting the latest news of noteworthy innovation and acts of sheer genius. In this episode, they discuss an article in the AP that investigates how AI-powered tech landed a man in jail with scant evidence . Bill and Rob discuss the case and the AI technology involved, and what questions this raises regarding scientifically validating AI and its use as evidence in criminal cases. Bill and Rob are then joined by Amanda Jones of Lighthouse to discuss common challenges and pitfalls that can arise with modern language in ediscovery, and the interplay between AI and linguistics. Some key questions they explore, include: What is linguistic modeling? What are the critical challenges with modern language and ediscovery today? How is linguistics informing and impacting AI in ediscovery? What are best practices for implementing AI solutions and tools? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . , ai-and-analytics; ediscovery-review, review, emerging data sources, ai/big data, podcast, ai-and-analytics, ediscovery-review, review; emerging-data-sources; ai-big-data; podcast
Podcast
eDiscovery Review: Family Vs. Four Corner
Pooja Lalwani of Lighthouse and our hosts discuss these two ediscovery review methodologies, and walk through the advantages and disadvantages of both and which better supports AI technology., Bill Mariano and Rob Hellewell kick off this episode with another segment of Sightings of Radical Brilliance, where they discuss Dalvin Brown’s piece in the Washington Post about how AI was used to recreate actor Val Kilmer’s voice . Bill and Rob consider this great scientific achievement along with the potentially nefarious ways it can used. Next, our hosts chat with Pooja Lalwani of Lighthouse about two key approaches to ediscovery review: family and four corner. Pooja helps break down the benefits and drawbacks of each through questions such as: What are some of the key differences between both approaches? With modern communication platforms and data creating a more dynamic and complex review process, what are some of the considerations for when and how to deploy family and four corner review? What review methodology is better suited to supporting TAR and AI tools? How do these review methodologies either help classify privilege more efficiently or potentially create limitations? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . , ediscovery-review; ai-and-analytics; lighting-the-way-for-review; lighting-the-path-to-better-review, privilege, review, ai/big data, tar/predictive coding, podcast, ediscovery-review, ai-and-analytics, privilege; review; ai-big-data; tar-predictive-coding; podcast
Podcast
Achieving Cross-Matter Review Discipline, Cost Control, and Efficiency
Bill and Rob bring on Jason Rylander of Axinn to discuss techniques for unifying matter data across an organization's portfolio and how it can save significant time and money on document review., Join co-hosts Bill Mariano and Rob Hellewell as they discuss a law firm that only works on artificial intelligence and whether this is an emerging trend for the industry. Next, they’re joined by Jason Rylander of Axinn to discuss the antitrust landscape, benefits of cross-matter review, and techniques for unifying matter data across an organization’s portfolio. Jason and our hosts walk through key questions, including: With a new administration and the continued disruption from COVID, has there been an increase in the volume of antitrust matters, investigations, and litigation? What are some of the challenges or disadvantages of doing the traditional single-matter document review? What are some strategies for identifying work product or data that can be reused or repurposed? What are some best practices when connecting matters? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . , ediscovery-review; ai-and-analytics, collections, tar/predictive coding, hsr second requests, processing, podcast, data reuse, project management, ediscovery-review, ai-and-analytics, collections; tar-predictive-coding; hsr-second-requests; processing; podcast; data-reuse; project-management
Podcast
Innovating the Legal Operations Model
In the second episode of season seven, co-hosts Bill Mariano and Rob Hellewell kick off the show with Sightings of Radical Brilliance. In this episode, they review a recent NY Times article..., In the second episode of season seven, co-hosts Bill Mariano and Rob Hellewell kick off the show with Sightings of Radical Brilliance. In this episode, they review a recent NY Times article written by Brian Chen that focuses on the tech that will invade our lives in 2021 . Next, they bring on Julie Johnson of Align who answers the following questions around innovation in legal operations: How has Covid impacted legal departments and budgets in general? Why did this bring about the need to focus on innovation and automation? What are some of the newer innovations/solutions you are seeing your fellow legal operations peers adopt? What recommendations would you share with those looking to adopt technology and drive efficiency? What advice would you give to other women in the ediscovery industry looking to move their careers forward? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . , legal-operations, legal ops, podcast, legal-operations, legal-ops; podcast
Podcast
Keeping Up with M365 Software Updates
In the fourth episode of the seventh season, co-hosts Bill Mariano and Rob Hellewell discuss why diversity in AI is important and how this could impact legal outcomes and decisions. Next, they..., In the fourth episode of the seventh season, co-hosts Bill Mariano and Rob Hellewell discuss why diversity in AI is important and how this could impact legal outcomes and decisions. Next, they introduce their guest speaker, Jamie Brown of Lighthouse, who uncovers key strategies to keep up with the constant flow of Microsoft 365 software updates. Jamie answers the following questions (and more) in this episode: What are some of the common challenges associated with M365’s rapid software updates? How do these constant updates lead to compliance risks? What are some best practices for overcoming these challenges? What recommendations would you pass along to those who are experiencing these challenges? What advice would you give to other women in the ediscovery industry looking to move their careers forward? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . , microsoft-365; information-governance; chat-and-collaboration-data, microsoft, podcast, microsoft-365, information-governance, chat-and-collaboration-data,, microsoft; podcast
Podcast
Efficiently and Defensibly Addressing Microsoft Teams Data
Bill Mariano and Rob Hellewell kick off episode 3 with another segment of Sightings of Radical Brilliance, where they discuss Anis Uzzaman’s Inc.com article that dives into 2021 business and..., Bill Mariano and Rob Hellewell kick off episode 3 with another segment of Sightings of Radical Brilliance, where they discuss Anis Uzzaman’s Inc.com article that dives into 2021 business and technology trends . Bill and Rob review these trends and discuss how they will have an impact on the space. Next, Bill and Rob chat with Royce Cohen of Lighthouse about key ways to efficiently and defensibly address Microsoft Teams data. In this interview, Royce uncovers the answers to the following questions: How do you achieve a balance between encouraging collaboration amongst colleagues and the ediscovery impact of that collaboration? What are some of the challenges associated with the rise in Teams data? How do you overcome those challenges? How do organizations ensure they are overcoming those challenges efficiently and defensibly? What advice would you give to other women in the ediscovery industry looking to move their careers forward? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . Related Links Blog Post: Key Compliance & Information Governance Considerations As You Adopt Microsoft Teams Podcast: Tackling Modern Attachment and Link Challenges in G-Suite, Slack, and Teams , chat-and-collaboration-data; microsoft-365, microsoft, podcast, chat-and-collaboration-data, microsoft-365, microsoft; podcast
Podcast
Antitrust Changes in a New Administration
In the final episode of season seven, co-hosts Bill Mariano and Rob Hellewell review an article that covers how big tech mergers and acquisitions will drive a busier 2021 for deal lawyers and how..., In the final episode of season seven, co-hosts Bill Mariano and Rob Hellewell review an article that covers how big tech mergers and acquisitions will drive a busier 2021 for deal lawyers and how these impacts may be seen. The co-hosts then bring on Kristin Sanford of Weil to discuss a related topic – the impacts and changes to the antitrust scene with the new administration via the following questions: What are some of the changes brought about by the new administration? How are those making an impact and/or creating change? How do these changes impact how folks manage antitrust matters? What recommendations do you have for folks dealing with these challenges? What advice would you give to other women in the antitrust industry looking to move their careers forward? The season ends with key takeaways from the guest speaker section. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . , antitrust, podcast, antitrust, podcast; antitrust
Podcast
Diversity and eDiscovery: How Diverse Hiring Practices Lead to a More Innovative Workforce
In the very first episode of season seven, co-hosts Bill Mariano and Rob Hellewell, introduce themselves and welcome listeners back for another riveting season of Law & Candor, the podcast wholly..., In the very first episode of season seven, co-hosts Bill Mariano and Rob Hellewell , introduce themselves and welcome listeners back for another riveting season of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution. They note that in celebration of Women’s History Month (March), season seven will feature an all-female guest speaker lineup exploring industry hot topics, as well as key tactics for championing the career growth of females within the space. To kick things off, Bill and Rob begin with Sightings of Radical Brilliance, the part of the show highlighting the latest news of noteworthy innovation and acts of sheer genius. In this episode, they dive into a recent article written by Ayang Macdonald for BiometricUpdate.com that discusses Aratek’s new biometric finger scanner with enhanced security . Bill and Rob discuss this new fingerprint scanning technology and what it (and other tech like it) could mean for the future of the legal space. For the guest speaker segment of the show, Bill and Rob bring on Stacy Ybarra of Lighthouse to discuss diversity in ediscovery and how diverse hiring practices can lead to a more innovative workforce via the following questions: How does diversity feed innovation in ediscovery? What are some of the key ways diversity impacts organizations directly? How does leading with empathy and inclusion make an impact? What are some best practices for those looking to champion diversity within their organization and the industry through employee resource groups? What advice would you give to other women in the ediscovery industry looking to move their careers forward? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . , diversity-equity-and-inclusion, podcast, diversity-equity-and-inclusion,, podcast
Podcast
The Convergence of AI and Data Privacy in eDiscovery: Using AI and Analytics to Identify Personal Information
Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss the challenges and implications of misinformation around voting in..., Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss the challenges and implications of misinformation around voting in the U.S. In this episode, Bill and Rob are joined by John Del Piero of Lighthouse. The three of them discuss how PII and PHI can be identified more efficiently by leveraging tools like AI and analytics via the following questions: Why is it important to identify PII and PHI within larger volumes of data quickly? How can AI and analytics help to identify PII and PHI more efficiently? What are the key benefits of using these tools? Are there any best practices to put in place for those looking to weave AI and analytics into their workflow? In conclusion, our co-hosts end the episode with key takeaways. If you enjoyed the show, subscribe here , rate us on Apple and Stitcher, join in the conversation on Twitter , and discover more about our speakers and the show here . , ai-and-analytics; data-privacy, data-privacy, ai/big data, phi, pii, podcast, ai-and-analytics, data-privacy, data-privacy; ai-big-data; phi; pii; podcast
Podcast
AI and Analytics for Corporations: Common Use Cases
Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss the growing use of emotion recognition in tech in China and how..., Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss the growing use of emotion recognition in tech in China and how this could lead to some challenges in the legal space down the road. In this episode, Bill and Rob are joined by Moira Errick of Bausch Health. The three of them discuss common AI and analytics use cases for corporations via the following questions: What types of AI and analytics tools are you using and for what use cases? What is ICR and how you have been leveraging this internally? What additional use cases are you hoping to use AI and analytics for in the future? What are some best practices to keep in mind when leveraging AI and analytics tools? What recommendations do you have for those trying to get their team on board? What advice would you give to other women in the ediscovery industry looking to move their careers forward? In conclusion, our co-hosts end the episode with key takeaways. If you enjoyed the show, learn more about our speakers and subscribe on the podcast homepage , rate us on Apple and Stitcher , and join in the conversation on Twitter . , ai-and-analytics, ai/big data, podcast, ai-and-analytics, ai-big-data; podcast
Podcast
Tackling Modern Attachment and Link Challenges in G-Suite, Slack, and Teams
In the fourth episode of the sixth season, co-hosts Bill Mariano and Rob Hellewell discuss how GDPR and AI can ensure data protection during their sightings segment. Next, they introduce their..., In the fourth episode of the sixth season, co-hosts Bill Mariano and Rob Hellewell discuss how GDPR and AI can ensure data protection during their sightings segment. Next, they introduce their guest speaker, Nick Schreiner of Lighthouse, who uncovers key ways to tackle modern attachment and link challenges in G-Suite, Teams, and Slack. Nick answers the following questions (and more) in this episode: What are the common challenges around modern attachments and links in ediscovery? How do attachments in these tools differ from traditional email? What strategies can folks put in place to manage these challenges? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, subscribe here , rate us on Apple and Stitcher, join in the conversation on Twitter , and discover more about our speakers and the show here . , chat-and-collaboration-data; microsoft-365, microsoft, emerging data sources, g suite, podcast, chat-and-collaboration-data, microsoft-365, microsoft; emerging-data-sources; g-suite; podcast
Podcast
Special Edition - Law & Candor Live: Putting 2020 in the Rearview and Looking Ahead to 2021
This episode is a recording of the Law & Candor Live eDiscovery Day webinar. In this episode, co-hosts Bill Mariano and Rob Hellewell kick things off by discussing the first-ever AI Santa Claus in..., This episode is a recording of the Law & Candor Live eDiscovery Day webinar. In this episode, co-hosts Bill Mariano and Rob Hellewell kick things off by discussing the first-ever AI Santa Claus in the midst of COVID-19. The co-hosts then bring on Zach Warren of Legaltech News, Ryan O'Leary of IDC and Chris Dahl of Lighthouse to answer to following questions: What are the top trends of 2020? How do you overcome common challenges of key trends in 2020? With these trends in mind, how do you prepare for 2021? Will the pandemic have lasting effects on the ediscovery space? Will this permanently affect how data collections are done? How to prepare for RIFs? Subscribe to the show here , rate us on Apple and Stitcher, connect with us on Twitter , and discover more about our speakers and the show here . , ediscovery-review, emerging data sources, data-privacy, ai/big data, podcast, ediscovery-review,, emerging-data-sources; data-privacy; ai-big-data; podcast
Podcast
Reducing Cybersecurity Burdens with a Customized Data Breach Workflow
Bill Mariano and Rob Hellewell kick off episode 3 with another segment of Sightings of Radical Brilliance where they discuss the EU striking down the Privacy Shield and what that means for the..., Bill Mariano and Rob Hellewell kick off episode 3 with another segment of Sightings of Radical Brilliance where they discuss the EU striking down the Privacy Shield and what that means for the legal realm. Next, Bill and Rob chat with Jeremiah Weasenforth of Orrick about a recent customized data breach workflow that Jeremiah and his team implemented to significantly reduce the burdens of a data breach. In this interview, Jeremiah uncovers the answers to the following questions: What are the burdens of a major data breach? What impacts do DSARs and the CCPA have on these breaches? How do you get started with a customized workflow? What technology should one use? How do you implement the workflow internally? What key tips are there for those experiencing cybersecurity burdens today? The show concludes with key takeaways from the guest speaker segment. Subscribe to Law & Candor here , rate us on Apple and Stitcher, join in the conversation on Twitter , and discover more about our speakers and the show here . , data-privacy; legal-operations; information-governance, cybersecurity, data-privacy, podcast, data-privacy, legal-operations, information-governance,, cybersecurity; data-privacy; podcast
Podcast
Does Cellular 5G Equal 5x the Fraud and Misconduct Risk?
In the very first episode of season six, co-hosts Bill Mariano and Rob Hellewell, introduce themselves and welcome listeners back for another season of Law & Candor, the podcast wholly devoted to..., In the very first episode of season six, co-hosts Bill Mariano and Rob Hellewell , introduce themselves and welcome listeners back for another season of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution. To kick things off, Bill and Rob begin with Sightings of Radical Brilliance, the part of the show where they discuss the latest news of noteworthy innovation and acts of sheer genius. In this episode, they dive into a recent article from ITPro.com that discusses the increase in insider data breaches with the remote work shift . For the guest speaker segment of the show, Bill and Rob bring on Jerry Bui of Lighthouse to discuss cellular 5G and how it could lead to more fraud and misconduct risk via the following key questions: How does 5G lead to fraud and misconduct? What insider threats are there (i.e. shadow IT, encrypted messages, etc.)? What about outsider threats (i.e. outside of IT’s purview, data breaches, hacking, etc.)? How does this impact compliance programs? How does one overcome 5G challenges? Are there other recommended best practices related to this topic? The episode wraps up with key takeaways. If you enjoyed the show, subscribe here , rate us on Apple and Stitcher, join in the conversation on Twitter , and discover more about our speakers and the show here . , forensics; chat-and-collaboration-data, preservation and collection, podcast, digital-forensics, digital-forensics, chat-and-collaboration-data, preservation-and-collection; podcast; digital-forensics
Podcast
Cross-Border Data Transfers and the EU-US Data Privacy Tug of War
In the second episode of season six, co-hosts Bill Mariano and Rob Hellewell kick off the show with Sightings of Radical Brilliance. In this episode, they review a recent trends analysis article..., In the second episode of season six, co-hosts Bill Mariano and Rob Hellewell kick off the show with Sightings of Radical Brilliance. In this episode, they review a recent trends analysis article written by Lighthouse’s very own John Shaw for The Lawyer that dives into new sources of evidentiary data in employment disputes . Next, they bring on Melina Efstathiou of Eversheds Sutherland who answers questions around cross-border data transfers and the EU-US data privacy challenges outlined below: What does the surprise decision to invalidate the EU-US Privacy Shield mean for ediscovery? How does this impact other data transfer mechanisms? What are some of the implications that Brexit could have? Are there any key tips for preparing for the future of cross-border ediscovery? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, subscribe here , rate us on Apple and Stitcher, join in the conversation on Twitter , and discover more about our speakers and the show here . Related Links Blog Post: Worldwide Data Privacy Update Blog Post: Three Steps to Tackling Data Privacy Compliance Post GDPR Blog Post: The U.S Privacy Shield Is No Longer Valid – What Does that Mean for Companies that Transfer Data from the EU into the US? , data-privacy; ai-and-analytics, data-privacy, cross border data transfers, podcast, data-privacy, ai-and-analytics, data-privacy; cross-border-data-transfers; podcast
Podcast
AI, Analytics, and the Benefits of Transparency
In the final episode of season six, co-hosts Bill Mariano and Rob Hellewell review an article covering key privacy and security features on iOS4 and highlight the top features to be aware of.The..., In the final episode of season six, co-hosts Bill Mariano and Rob Hellewell review an article covering key privacy and security features on iOS4 and highlight the top features to be aware of. The co-hosts then bring on Forbes Senior Contributor, David Teich , to discuss AI, analytics, and the benefits of transparency via the following questions: Why is it important to be transparent in the legal realm? How does this come into play with bias? What about AI and jury selection? How do analytics come into play as a result of providing transparency? The season ends with key takeaways from the guest speaker section. Subscribe to the show here , rate us on Apple and Stitcher, connect with us on Twitter , and discover more about our speakers and the show here . Related Links Blog Post: Big Data and Analytics in eDiscovery: Unlock the Value of Your Data Blog Post: The Sinister Six…Challenges of Working with Large Data Sets Blog Post: Advanced Analytics – The Key to Mitigating Big Data Risks Podcast Episode: Tackling Big Data Challenges Podcast Episode: The Future is Now – AI and Analytics are Here to Stay , ai-and-analytics, ai/big data, podcast, ai-and-analytics,, ai-big-data; podcast
Podcast
Top Microsoft 365 Features to Leverage in Your eDiscovery Program
Microsoft’s agile development and rapid product enhancement allows Microsoft 365 (M365) users to stay up to date with emerging industry challenges. However, keeping pace with these M365 features, In the final episode of season five, co-hosts Bill Mariano and Rob Hellewell review an article on a recent ILTA>ON panel that examined how tech has created certain power dynamics in legal space. Next, Bill and Rob bring on John Collins of Lighthouse to walk them through the top M365 features to leverage in an ediscovery program. Together they cover the latest and greatest as well as uncover answers to the following questions: How many updates and enhancements is Microsoft making? How often/fast are these coming out? What are some of the common challenges around these rapid changes? What are the top M365 features that folks in the industry should be aware of? Are there other ways and/or resources folks can use to stay up-to-date? The season ends with key takeaways from the guest speaker section. Subscribe to the show here , rate us on Apple and Stitcher, connect with us Twitter , and discover more about our speakers and the show here . Related Links Blog Post: Microsoft 365, G-Suite, and the Growing Demand for Consulting and ifying Experts Blog Post: Leveraging Microsoft 365 to Reduce Your eDiscovery Spend Blog Post: Key Compliance & Information Governance Considerations As You Adopt Microsoft Teams Podcast Episode: Microsoft Office 365 Part 1: Microsoft’s Influence on the Next Evolution of eDiscovery Podcast Episode: Microsoft Office 365 Part 2: How to Leverage all the Tools in the Toolbox , microsoft-365; ediscovery-review; chat-and-collaboration-data, microsoft, podcast, microsoft-365, ediscovery-review, chat-and-collaboration-data,, microsoft; podcast
Podcast
Leveraging AI and Analytics to Detect Privilege
AI and analytics are picking up momentum in the ediscovery space. With new tools that can help ediscovery professionals see trends and patterns in their data as well as identify inefficiencies and opp, Co-hosts Bill Mariano and Rob Hellewell kick episode 3 of season 5 off with another riveting Sightings of Radical Brilliance segment where they discuss transforming risks into benefits through artificial intelligence and data privacy. Bill and Rob interview CJ Mahoney of Cleary Gottlieb, who discusses some new AI and analytics practices around privilege review. In this segment, CJ uncovers the answers to the following questions: Why the uptick in the adoption of AI and analytics in the industry? Why did it take so long for folks to adopt? How can one leverage AI to detect privilege? What benefits and learnings can one apply to future work? What are some recommendations for those looking to leverage AI and analytics in similar ways? The show concludes with key takeaways from the guest speaker segment. Subscribe to Law & Candor here , rate us on Apple and Stitcher, join in the conversation on Twitter , and discover more about our speakers and the show here . Related Links Blog Post: Big Data and Analytics in eDiscovery: Unlock the Value of Your Data Podcast Episode: Tackling Big Data Challenges Podcast Episode: The Future is Now – AI and Analytics are Here to Stay , ai-and-analytics, analytics, ai/big data, podcast, ai-and-analytics,, analytics; ai-big-data; podcast
Podcast
Achieving Information Governance through a Transformative Cloud Migration
Data migrations are generally perceived as painful and disruptive experiences. However, they also provide unique opportunities to transform the way unstructured data is used and managed within an, In the first episode of season five, co-hosts Bill Mariano and Rob Hellewell , introduce themselves and welcome listeners back for another season of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution. To kick things off, Bill and Rob begin with Sightings of Radical Brilliance, the part of the show where they discuss the latest news of noteworthy innovation and acts of sheer genius. In this first episode, they dive into a recent article written by the folks at Baker Botts LLP around Federal Expedited Review in Response to COVID-19 and what that means for the industry. For the guest speaker segment of the show, Bill and Rob bring on John Holliday of Lighthouse to discuss transformative cloud migrations and how to ensure a successful outcome via the following questions: How do cloud migrations provide an opportunity to transform processes and workflows within an organization? How does information architecture come into play? What benefits can one achieve during a cloud migration? What are best practices for a successful transformative cloud migration? The episode wraps up with key takeaways. If you enjoyed the show, subscribe here, rate us on Apple and Stitcher, join in the conversation on Twitter , and discover more about our speakers and the show here . Related Links Blog Post: Top Three Things That Could Derail Your Cloud Migration Project Blog Post: Why Moving to the Cloud is a Legal Conversation , information-governance; microsoft-365; chat-and-collaboration-data, information-governance, cloud migration, podcast, information-governance, microsoft-365, chat-and-collaboration-data,, information-governance; cloud-migration; podcast
Podcast
Facilitating a Smooth and Successful Large Review Project with Advanced Analytics
Large dataset projects are being addressed with the broadening use of advanced analytics. However, this is introducing another level of complexity into what is already a complicated and potentially st, Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss how law firms are managing the hurdles of remote work , specifically comprehensive security measures, and driving efficiency. In this episode, Bill and Rob are joined by Adam Strayer of Paul Weiss. The three discuss facilitating successful large review projects with advanced analytics and other tools via the following questions: Why has there been an increase in the use of advanced analytics on larger matters across the industry? What are some of the key tools and strategies that drive the most value? What are the most effective and efficient workflows regarding advanced analytics? How does one combine the expertise and talents from each team involved (client, counsel, and service provider(s)) in an organized manner? In conclusion, our co-hosts end the episode with key takeaways. If you enjoyed the show, subscribe here , rate us on Apple and Stitcher, join in the conversation on Twitter , and discover more about our speakers and the show here . Related Links Podcast Episode: New Efficiency Gains in TAR 2.0 and CMML Revealed Case Study: Drug Store Giant Sees Significant Data Reduction , ai-and-analytics; antitrust, analytics, ai/big data, hsr second requests, podcast, ai-and-analytics, antitrust, analytics; ai-big-data; hsr-second-requests; podcast
Podcast
Scaling Your eDiscovery Program: Self Service to Full Service
Being able to scale an ediscovery program from a self-service to a full-service model for particular matters can save both time and money, thus allowing for a more efficient ediscovery program overall, In the second episode of season five, co-hosts Bill Mariano and Rob Hellewell kick off the show with Sightings of Radical Brilliance. In this episode, they discuss Solos Health Analytics’s new technology (FeverGaurd) that was designed as a fever detection software to stop the spread of COVID-19 and the PPI challenges it could raise. Next, they bring on Claire Caruso of Lighthouse. Together, the three of them talk through how to scale ediscovery programs from self-service to full-service and back through the following questions: When would one need to transition from self service to full service, and back to self service? What are the benefits of making these moves? What are some of the key things to look out for? What are some recommendations for folks looking to optimize their structure? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, subscribe here , rate us on Apple and Stitcher, join in the conversation on Twitter , and discover more about our speakers and the show here . Related Links Blog Post: How to Bring eDiscovery In House from Seasoned Self-Service Adopters Podcast Episode: The Future of On-Demand SaaS Software for Small Matters – A Self-Service Model Story Blog Post: Overcoming Top Objections for Moving to a Self-Service eDiscovery Model Blog Post: Building a Business Case for Upgrading Your eDiscovery Self-Service Practices in Six Simple Steps Podcast Episode: Moving to the Cloud Part 1: A Corporate Journey Podcast Episode: Moving to the Cloud Part 2: A Law Firm Journey About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ediscovery-review; ai-and-analytics, self-service, spectra, podcast, ediscovery-review, ai-and-analytics, self-service, spectra; podcast
Podcast
Effective Strategies for Managing DSARs
Since the introduction of the GDPR, organizations with a European presence have seen a rise in the number of Data Subject Access Requests (DSARs). These matters are time-consuming, costly, and not, In the fourth episode of season five, co-hosts Bill Mariano and Rob Hellewell discuss how Relativity is using its technology to help medical researchers comb through COVID-19 journal articles to help battle the virus. Bill and Rob then introduce their guest speaker, Nicki Woodfall of Travers Smith, who uncovers effective strategies for managing DSARs. Nicki answers the following questions in this episode: Why has there been a recent uptick in DSARs over the past few years? What are the top challenges when it comes to managing DSARs? What are key ways to overcome these common challenges? Our co-hosts wrap up the episode with a few key takeaways. If you enjoyed the show, subscribe here , rate us on Apple and Stitcher, join in the conversation on Twitter , and discover more about our speakers and the show here . Related Links Blog Post: How GDPR and DSARs are Driving a New, Proactive Approach to eDiscovery Case Study: Penningtons Manches Cooper Takes Control of their eDiscovery Process with Lighthouse Spectra About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , data-privacy; information-governance; ai-and-analytics, dsars, podcast, data-privacy, information-governance, ai-and-analytics,, dsars; podcast
Podcast
Take the Mystery out of Machine Learning: Success Stories from Real-Life Examples and How Data Scientists Impact eDiscovery
In the final episode of season three, co-hosts Bill Mariano and Rob Hellewell discuss a coronavirus tracing app and the privacy concerns that may come about from a legal perspective. Bill and Rob..., In the final episode of season three, co-hosts Bill Mariano and Rob Hellewell discuss a coronavirus tracing app and the privacy concerns that may come about from a legal perspective. Bill and Rob bring on Sara Lockman of Walmart to discuss the mysteries behind machine learning. Together they cover what machine learning is, the benefits, success stories, and more by uncovering answers to the following questions: What is machine learning? What are the benefits of machine learning? What are some challenges to be aware of when implementing machine learning? What are some best practices to put in place when using machine learning? Are there any major differences between implementing machine learning on investigations versus litigation? What are some of the practical applications you have seen used in the context of cases? How do you convince the non-believers? The season ends with key takeaways from the guest speaker section. Connect with us Twitter , discover more about our speakers and the show here . Related Links Blog Post: Big Data and Analytics in eDiscovery: Unlock the Value of Your Data Podcast Episode: The Future is Now – AI and Analytics are Here to Stay Podcast Episode: Tackling Big Data Challenges Podcast Episode: New Efficiency Gains in TAR 2.0 and CMML Revealed About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ai-and-analytics, analytics, ai/big data, tar/predictive coding, podcast, ai-and-analytics,, analytics; ai-big-data; tar-predictive-coding; podcast
Podcast
Myth Busters - The Managed Services Edition
In the second episode of season four, co-hosts Bill Mariano and Rob Hellewell kick off the show with Sightings of Radical Brilliance. In this episode, they discuss how the U.S. House plans to..., In the second episode of season four, co-hosts Bill Mariano and Rob Hellewell kick off the show with Sightings of Radical Brilliance. In this episode, they discuss how the U.S. House plans to start voting remotely and the impacts this could have on the legal space. They then introduce the next guest speaker segment, which features Tracy Hallenberger of Baker Botts. They unravel the myths behind managed services and discuss the key benefits of this modern approach to ediscovery through the following questions: What are some of the top myths that are associated with managed services? What about this myth around lesser quality? What about the myth around it being more expensive? What about this lower service level to lawyer myth? What are the key benefits of a managed services model? Our co-hosts wrap up the episode with a few key takeaways. Join in the conversation on Twitter and discover more about our speakers and the show here . Related Links Case Study: Lighthouse’s Managed Service Solution Delivers More Than $13 Million in Savings over Six Years Case Study: Top Ten Global Law Firm Realizes Benefits of Lighthouse Managed Services About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ediscovery-review, managed services, podcast, ediscovery-review,, managed-services; podcast
Podcast
Managing Cybersecurity in eDiscovery
Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss how password dumping can improve your security and what that means..., Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss how password dumping can improve your security and what that means for the future of security. In this episode, Bill and Rob are joined by Dave Kuhl of Lighthouse. The three uncover the complexities around managing cybersecurity as well as practical tips for overcoming challenges via the following questions: What are the recent complexities around managing cybersecurity? What are today’s biggest threats? What are some key lessons learned around these challenges? How do you combat cybersecurity challenges? How do you get ahead of these issues before they hit? In conclusion, our co-hosts end the episode with key takeaways. To join the conversation, connect with us Twitter and discover more about our speakers and the show here . Related Links Blog Post: Cybersecurity in eDiscovery: Protecting Your Data from Preservation through Production Blog Post: Top Three Tips for Structuring an Effective eDiscovery Security Evaluation Podcast Episode: Cybersecurity in eDiscovery: Protecting Your Data from Preservation through Production Webinar Recording: The Risks of Cybersecurity in eDiscovery – Is Your Data Safe? About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , data-privacy; ediscovery-review; information-governance, cybersecurity, podcast, data-privacy, ediscovery-review, information-governance,, cybersecurity; podcast
Podcast
eDiscovery Program Starter Pack: Uncover Key Ways to Build an Effective & Efficient eDiscovery Program
In the fourth episode of season four, co-hosts Bill Mariano and Rob Hellewell discuss the first-ever trial by Zoom, how it all went down, as well as what may expect to see looking forward. Bill..., In the fourth episode of season four, co-hosts Bill Mariano and Rob Hellewell discuss the first-ever trial by Zoom , how it all went down, as well as what may expect to see looking forward. Bill and Rob then introduce their guest speaker, Zander Brandt of Lyft, who shares his experience as a two-time corporate ediscovery “first employee” and what it takes to set up an effective and efficient ediscovery program. Zander answers the following questions in this episode: What is that like being the first corporate ediscovery employee? Where do you start in a role like this? What are the key initial steps to take when coming on board? What are things to avoid? Common pitfalls? What are the recommendations/best practices for those looking to implement an efficient ediscovery program today? Our co-hosts wrap up the episode with a few key takeaways. Follow us on Twitter and discover more about our speakers and the show here . About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ediscovery-review; legal-operations, ediscovery process, legal ops, podcast, ediscovery-review, legal-operations, ediscovery-process; legal-ops; podcast
Podcast
Emerging Data Sources – Get a Handle on eDiscovery for Collaboration Tools
In the first episode of season four, co-hosts Bill Mariano and Rob Hellewell, introduce themselves and welcome listeners back for a fourth season of Law & Candor, the podcast wholly devoted to..., In the first episode of season four, co-hosts Bill Mariano and Rob Hellewell , introduce themselves and welcome listeners back for a fourth season of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution. To kick things off, Bill and Rob begin with Sightings of Radical Brilliance, the part of the show where they discuss the latest news of noteworthy innovation and acts of sheer genius. In this first episode, they dive into a recent story around COVID-19 and the reformation of legal culture . The guest speaker segment for episode one highlights Ellen Blanchard of T-Mobile. Ellen, Bill, and Rob discuss the growth in emerging data sources, especially with the introduction of more remote work due to COVID-19. They cover tips on how to manage, collect, process, and review collaboration data for ediscovery purposes via the following questions: What has changed over the last couple of years and even in the last few months with COVID-19? How do you get a handle on these data sources? How do you weigh that balance between risks and what teams need to use to be productive? What are some key tips to keep in mind when managing ediscovery around collaboration tools? At the end of the episode, Bill recaps key takeaways and thanks Ellen for joining. If you enjoyed the show, join in the conversation on Twitter and discover more about our speakers and the show here . Related Links Case Study: Rapid and Reliable Chat Message Review About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , chat-and-collaboration-data; microsoft-365, emerging data sources, podcast, chat-and-collaboration-data, microsoft-365, emerging-data-sources; podcast
Podcast
Legal Operations 101: Skills for Success
Co-hosts Bill Mariano and Rob Hellewell kick episode 3 of season 4 off with another riveting Sightings of Radical Brilliance segment where they uncover how biometric data will impact ediscovery..., Co-hosts Bill Mariano and Rob Hellewell kick episode 3 of season 4 off with another riveting Sightings of Radical Brilliance segment where they uncover how biometric data will impact ediscovery and why it is important to protect this data . Bill and Rob are accompanied by Debora Motyka Jones of Lighthouse, who shares what today’s legal operations landscape looks like as well as the key competencies for those looking to succeed in the field. In this segment, Debora uncovers the answers to the following questions: What is legal operations? What are today’s legal operations trends? What are some of the core competencies for departments? What are some of the skills that individuals in the field need to focus on? What are the best practices when it comes to legal operations? The show concludes with key takeaways from the guest speaker segment. Join the conversation on Twitter and discover more about our speakers and the show here . Related Links Blog Post: Legal Operations... Is it a Fad or Here to Stay? Blog Post: Managing Your (Legal Ops) Budget with Five Simple Tips Blog Post: Budget Busters and How to Avoid Them: Budgeting Tips for Legal Operations Professionals Blog Post: Putting Together an Effective Legal Strategy Session About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , legal-operations, legal ops, podcast, legal-operations ,, legal-ops; podcast
Podcast
The Future of On-Demand SaaS Software for Small Matters – A Self-Service Model Story
Co-hosts Bill Mariano and Rob Hellewell kick things off with another riveting Sightings of Radical Brilliance segment where they uncover how real-time translation tools are breaking down barriers..., Co-hosts Bill Mariano and Rob Hellewell kick things off with another riveting Sightings of Radical Brilliance segment where they uncover how real-time translation tools are breaking down barriers and what this means for the future of legal space. Next, Bill and Rob set the stage for the final recorded guest speaker segment of the live Law & Candor show during Legaltech. For this session, they were accompanied by TracyAnn Eggen of Dignity Health and Steve Clark of Dentons, who discuss the future of on-demand SaaS software for small matters from both a corporate and a law firm perspective. In this segment, TracyAnn and Steve uncover the answers to the following questions: What triggered the move to a SaaS model? How did you get wide-scale adoption? What are some best practices for implementation? The show concludes with key takeaways from the guest speaker segment. Join the conversation on Twitter and discover more about our speakers and the show here . Related Links Blog Post: Overcoming Top Objections for Moving to a Self-Service eDiscovery Model Blog Post: Building a Business Case for Upgrading Your eDiscovery Self-Service Practices in Six Simple Steps Blog Post: Top Four Considerations for Law Firms When Choosing a SaaS eDiscovery Solution Podcast Episode: Moving to the Cloud Part 1: A Corporate Journey Podcast Episode: Moving to the Cloud Part 2: A Law Firm Journey About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ai-and-analytics, self-service, spectra, podcast, ediscovery-review, ai-and-analytics, self-service, spectra; podcast
Podcast
Tackling Big Data Challenges
Big data challenges and key ways to overcome them with AI, analytics, and data re-use are uncovered in this podcast episode., In the very first episode of season three, co-hosts Bill Mariano and Rob Hellewell , introduce themselves and welcome listeners back for another riveting season of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution. To kick things off, Bill and Rob begin with Sightings of Radical Brilliance, the part of the show where they discuss the latest news of noteworthy innovation and acts of sheer genius. In this first episode, they dive into a recent story around the Astros cheating scandal and their illegal use of technology to observe and relay the signs given by the opposing catcher to the pitcher known as sign-stealing. Before our co-hosts jump directly into the guest speaker segment of today’s episode, they set the stage for the first three episodes of season 3, which are recordings from the first-ever live Law & Candor show during Legaltech this past January. All three live segments are trickled out over the next three episodes. The guest speaker segment for episode one highlights, Josh Kreamer of AstraZeneca. Josh, Bill, and Rob discuss ever-evolving technology and data sources, and how it is now more challenging than ever to combat the cost and complexities associated with legal data. They tackle these key questions and Josh provides answers to the following: What are some of the biggest data challenges in the industry today? What are some key solutions to these challenges? How do you implement these solutions? How do you get buy in from your team/get them excited to move forward with implementation? In conclusion, Rob shares top takeaways from episode one. If you enjoyed the show, join in the conversation on Twitter and discover more about our speakers and the show here . Related Links Podcast Episode: The Future is Now – AI and Analytics are Here to Stay About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ai-and-analytics, ai/big data, podcast, ai-and-analytics,, ai-big-data; podcast
Podcast
eDiscovery Shark Tank - What’s Worth Your Investment in 2020?
In the final episode of season three, co-hosts Bill Mariano and Rob Hellewell discuss the New York SHIELD Act and its impact on data and security requirements within the space in the Sightings of..., In the final episode of season three, co-hosts Bill Mariano and Rob Hellewell discuss the New York SHIELD Act and its impact on data and security requirements within the space in the Sightings of Radical Brilliance segment. Bill and Rob shake things up a bit in the final guest speaker segment of the season by conducting an eDiscovery Shark Tank-style episode, where they bring on Chris Dahl of Lighthouse to share the most forward-thinking and innovative solutions to industry challenges that are worth folks’ 2020 investment. Chris covers the following key questions: What are some of the key innovations in the legal space today? What innovations around SaaS are worth investment? How is the SaaS paradigm impacted on a global perspective? What about big data analytics? When it comes to collaboration, chat, and social, what solutions are there? What about continuous program updates, what can folks be looking for? The season ends with key takeaways from the guest speaker section. Connect with us Twitter , discover more about our speakers and the show here . Related Links Blog Post: Best Practices for Embracing the SaaS eDiscovery Revolution Podcast Episode: Microsoft Office 365 Part 1: Microsoft’s Influence on the Next Evolution of eDiscovery Podcast Episode: Microsoft Office 365 Part 2: How to Leverage all the Tools in the Toolbox About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ai-and-analytics, self-service, spectra, analytics, emerging data sources, ai/big data, podcast, ediscovery-review, ai-and-analytics, self-service, spectra; analytics; emerging-data-sources; ai-big-data; podcast
Podcast
New Efficiency Gains in TAR 2.0 and CMML Revealed
In the fourth episode of season three, co-hosts Bill Mariano and Rob Hellewell converse around the innovation behind family tracking apps and how one app helped capture a criminal in this..., In the fourth episode of season three, co-hosts Bill Mariano and Rob Hellewell converse around the innovation behind family tracking apps and how one app helped capture a criminal in this episode’s Sightings of Radical Brilliance segment. Bill and Rob then introduce their guest speaker, Nordo Nissi of Goulston & Storrs, and together they dive into new and uncovered efficiency gains around TAR 2.0 and CMML. They ask Nordo the following questions: What are TAR 2.0 and CMML? What are some efficiency gains you have seen around these workflows? What are some of the hidden efficiencies you have seen? What are some techniques to get to those? In the end, our co-hosts wrap up the episode with a few key takeaways. Follow us on Twitter and discover more about our speakers and the show here . Related Links Case Study: Drug Store Giant Sees Significant Data Reduction About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ai-and-analytics, tar/predictive coding, podcast, ai-and-analytics,, tar-predictive-coding; podcast
Podcast
Special Edition: The Impact of COVID-19 on the Legal Space Now & Beyond
In this special edition of Law & Candor, co-hosts Bill Mariano and Rob Hellewell, kick things off with Sightings of Radical Brilliance, the part of the show where they discuss the latest news of..., In this special edition of Law & Candor, co-hosts Bill Mariano and Rob Hellewell , kick things off with Sightings of Radical Brilliance, the part of the show where they discuss the latest news of noteworthy innovation and acts of sheer genius. Within this episode, they discuss the recent innovative trend around large car manufactures switching gears around their production plans in the midst of COVID-19 to help develop ventilators and supply masks to help fight the pandemic. Related to COVID-19, the guest speaker segment of the show features Lighthouse’s CEO, Brian McManus, who shares his take on the industry impacts of COVID-19. The trio cover current top company priorities, common themes being heard throughout the industry, as well as the lasting impacts of this pandemic on the legal space by answering the following key questions: What are key company priorities? What are current employee safety priorities and items to be aware of? What is the industry saying? What will be the lasting impact of COVID-19 on the legal space? In conclusion, they share top takeaways from the episode. If you enjoyed the show, join in the conversation on Twitter and discover more about our speakers and the show here . Related Links Webinar Recording: Top Tips for Staying Productive and Connected While Working from Home About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ediscovery-review, ediscovery process, podcast, ediscovery-review,, ediscovery-process; podcast
Podcast
How Microsoft 365 and GDPR Are Driving a Proactive Approach to eDiscovery Across the Globe
Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss changes the legal system may face thanks to innovation brought..., Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss changes the legal system may face thanks to innovation brought about by AI, big data, and online courts . In this episode, Bill and Rob are joined by Mike Brown of Lighthouse. The three uncover how Microsoft 365 (M365) and GDPR are driving change for a more proactive approach to ediscovery across the globe and answer the following questions: How have GDPR and M365 changed company attitudes from a reactive to a more proactive approach to ediscovery? How does Brexit impact this? How does a company actually become GDPR compliant? How do companies prepare? How do DSARs come into play? How does M365 help solve for these concerns? In conclusion, our co-hosts end the episode with key takeaways. To join the conversation, connect with us Twitter and discover more about our speakers and the show here . Related Links Blog Post: Why Moving to the Cloud is a Legal Conversation , data-privacy; microsoft-365; chat-and-collaboration-data, microsoft, gdpr, data-privacy, cross border data transfers, podcast, data-privacy, microsoft-365, chat-and-collaboration data,, microsoft; gdpr; data-privacy; cross-border-data-transfers; podcast
Podcast
Data Privacy in a Post-GDPR World: Facing Regulators and Ensuring Compliance Through Rock-Solid Information Governance Practices
In the second episode of season three, co-hosts Bill Mariano and Rob Hellewell kick off the show with Sightings of Radical Brilliance. In this episode, they discuss how technology competence has..., In the second episode of season three, co-hosts Bill Mariano and Rob Hellewell kick off the show with Sightings of Radical Brilliance. In this episode, they discuss how technology competence has become a priority for today’s lawyers, which has become a recent hot topic within the space as more states make technical competence for lawyers mandatory . They then introduce the next guest speaker segment from the live recording of Law & Candor during Legaltech, which features Kelly Clay from GSK. They explore how GDPR has impacted the ediscovery world, both globally and in the US, since its enactment and focus on ways to mitigate risk by uncovering answers to the following questions: What key challenges have GDPR and the rise of recent privacy laws created globally and in the US? How can information governance and compliance practices mitigate data privacy and security risks? What are best practices or key recommendations for listeners? Our co-hosts wrap up the episode with a few key takeaways. Join in the conversation on Twitter and discover more about our speakers and the show here . About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , data-privacy; information-governance, gdpr, data-privacy, information-governance, compliance and investigations, podcast, data-privacy, information-governance, gdpr; data-privacy; information-governance; compliance-and-investigations; podcast
Podcast
Understanding and Creating Effective and Best eDiscovery Practices for G-Suite
In the final episode of season two, co-hosts Bill Mariano and Rob Hellewell discuss what a US approach to data protection and privacy would look like in the Sightings of Radical Brilliance segment..., In the final episode of season two, co-hosts Bill Mariano and Rob Hellewell discuss what a US approach to data protection and privacy would look like in the Sightings of Radical Brilliance segment of the show. In particular, they discuss how we are seeing these pop up on a state-by-state basis and whether we need a Federal law that applies to privacy. Bill and Rob are joined by Alison Shier , Client Development Manager at Lighthouse, to discuss the challenges and best practices around G-Suite data for their sixth and final episode of the season. The three cover the following questions: Is leveraging G-suite a more common trend/theme in the space? How is Gmail data different than Outlook data? What are some of the challenges around managing this data? What are some of the downstream issues and challenges around review of this data? How do we address these challenges? How do TAR and analytics impact G-suite data? The season ends with key takeaways from the guest speaker section. Connect with us Twitter , discover more about our speakers and the show here , and, if you are interested in attending the live podcast show at Legaltech, email us for details. About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , chat-and-collaboration-data; information-governance, g suite, ediscovery process, podcast, chat-and-collaboration data, information-governance, g-suite; ediscovery-process; podcast
Podcast
Would a No-Deal Brexit Change How We Handle Cross-Border Collections in Europe?
Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss personalized and predictive medicine and how apple watches have..., Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss personalized and predictive medicine and how apple watches have been saving lives . In addition, they dive into what these trends mean for the legal field. In this episode, Bill and Rob are joined Josh Yildirim , Executive Director of Service Delivery of Europe at Lighthouse. The three of them jump into the current status of Brexit and what the future of cross-border data collections could look like. Below are the questions they address: Where we are at currently with Brexit and whether a no-deal is likely? How could this potentially impact data privacy? How could this impact cross-border collections? What are some practical tips when it comes to potential challenges? What are companies going to need to do to prepare? In conclusion, our co-hosts end the episode with key takeaways. To join the conversation, connect with us Twitter and discover more about our speakers and the show here . About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , data-privacy; information-governance, cross border data transfers, podcast, data-privacy, information-governance, cross-border-data-transfers; podcast
Podcast
The Privilege in Leveraging Privilege Review Tools
In the second episode of season two, co-hosts Bill Mariano and Rob Hellewell kick off the show with Sightings of Radical Brilliance. In this episode, they discuss AI and how this comes into play..., In the second episode of season two, co-hosts Bill Mariano and Rob Hellewell kick off the show with Sightings of Radical Brilliance. In this episode, they discuss AI and how this comes into play in the game of poker as well as what that means for the industry. Next, they introduce their guest speaker for episode two, Joanna Harrison ,Solutions Architect at Lighthouse, to discuss the privileges of using privilege review tools in ediscovery. Together, they uncover the answers to the questions below: Why is privilege a priority? Why are the current methods in which privilege gets identified for review inefficient? Why is privilege review so important for folks in the ediscovery space? What kind of tools are out there to assist with privilege review? What about privilege logs? What are some key tips or tricks for setting up privilege workflows? Finally, our co-hosts wrap up the episode with a few key takeaways. Join in the conversation on Twitter and discover more about our speakers and the show here . Related Links Blog Post: Finding the Needle Faster – Speeding up the Second Request Process Case Study: Drug Store Giant Sees Significant Data Reduction Case Study: When the Government Investigates About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ai-and-analytics, privilege, podcast, ai-and-analytics, ediscovery-review, privilege; podcast
Podcast
Data Preservation in the World of Ephemeral Data, Mobile Devices, and Other New Challenges in Forensic Technology
Co-hosts Bill Mariano and Rob Hellewell share details around the five biggest data breaches of the year so far in Sightings of Radical Brilliance and what this means for the future of legal..., Co-hosts Bill Mariano and Rob Hellewell share details around the five biggest data breaches of the year so far in Sightings of Radical Brilliance and what this means for the future of legal space. Next, Bill and Rob bring on Jerry Bui , Executive Director of Digital Forensics at Lighthouse, to help uncover the answers to the following questions around data preservation when it comes to ephemeral and encrypted data: What do ephemeral and encryption mean? What are the different types of enterprise communication platforms? Which platform gives you the most in terms of investments from a legal and compliance perspective? What about data privacy on these platforms? How is the personal data treated? What should IT and Legal departments keep in mind when it comes to platforms that are not encrypted? The show concludes with key takeaways from the guest speaker segment. Join the conversation on Twitter and discover more about our speakers and the show here . Related Links Podcast: Digital Forensics Future About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , chat-and-collaboration-data; forensics; information-governance; microsoft-365, emerging data sources, preservation and collection, podcast, digital-forensics, chat-and-collaboration-data, digital-forensics, information-governance, microsoft-365, emerging-data-sources; preservation-and-collection; podcast; digital-forensics
Podcast
Cybersecurity in eDiscovery: Protecting Your Data from Preservation through Production
In the fourth episode of season two, co-hosts Bill Mariano and Rob Hellewell begin with Sightings of Radical Brilliance and the recent trend of folks moving away from email and towards text and..., In the fourth episode of season two, co-hosts Bill Mariano and Rob Hellewell begin with Sightings of Radical Brilliance and the recent trend of folks moving away from email and towards text and chat tools . They dive into the diverse challenges and risks associated with this shift. Next, Bill and Rob introduce their guest speaker, David Kessler , Head of Data and Information Risk, United States, at Norton Rose Fulbright US LLP, to discuss cybersecurity challenges across the various stages of the EDRM. In this episode they ask the following key questions to David: What does a high-level overview of data security look like today? Who does this affect? Where are vulnerabilities within the EDRM? What are some key solutions for overcoming top challenges? In the end, our co-hosts wrap up with a few key takeaways. Follow us on Twitter and discover more about our speakers and the show here . About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , data-privacy; information-governance, cybersecurity, preservation and collection, processing, podcast, data-privacy, information-governance, ediscovery-review,, cybersecurity; preservation-and-collection; processing; podcast
Podcast
Bridge the Gap: Innovative Ways to Enable eDiscovery Collaboration Between Legal and IT
In the very first episode of season two, co-hosts Bill Mariano and Rob Hellewell, introduce themselves and welcome listeners back for another riveting season of Law & Candor, the podcast wholly..., In the very first episode of season two, co-hosts Bill Mariano and Rob Hellewell , introduce themselves and welcome listeners back for another riveting season of Law & Candor, the podcast wholly devoted to pursuing the legal technology revolution. To kick things off, Bill and Rob begin with, Sightings of Radical Brilliance, the part of the show where they discuss the latest news of noteworthy innovation and acts of sheer genius. In this first episode, they dive into a recent story around how legal technology helped capture the BTK killer and recap the key legal mistakes of this notorious serial killer. In the guest speaker segment of the show, our co-hosts were joined by Craig Shaver , Director, eDiscovery Program, Hilton Worldwide, who helped them uncover the answers to the following questions around cross-departmental collaboration: What are the current challenges in play when IT and Legal are out of sync? Why is it critical for these two groups to be in sync? What are some of the risks of these groups being out of alignment? Who is the best person to lead the effort of aligning Legal and IT? Are there other departments within an organization that need to be at the table as well? What are the greatest challenges you’ve seen in achieving better alignment? What are some new ways these two groups can ensure they are in alignment? What are the benefits to an organization of this alignment? In conclusion, our speakers share top takeaways. If you enjoyed the show, join in the conversation on Twitter and discover more about our speakers and the show here . About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , legal-operations; information-governance, ediscovery process, podcast, legal-operations, information-governance, ediscovery-process; podcast
Podcast
The Truth Behind Data Reuse
Discover how data repositories can be set up to reuse data for future matters in this podcast episode., In the second episode of season one, co-hosts Bill Mariano and Rob Hellewell kick off the show with SIGHTINGS OF RADICAL BRILLIANCE. In this episode, they discuss the company Big Moon Power and some of the exciting things they are doing to harness the power of ocean tides to generate electricity. Next, they introduce their guest Erika Namnath , Executive Director of Advisory Services at Lighthouse, to discuss the truth behind data reuse. Together, they uncover the answers to the questions below: What is data reuse? What are the different types of data reuse? How would you reuse data around trade secrets and IP? What about privilege, PII, and PHI? What are some of the current limitations that companies are facing when trying to leverage data reuse? What about objectively non-responsive documents? How do you handle those types of work product for data reuse? What are the key benefits of data reuse? Finally, our co-hosts wrap up the episode with a few key takeaways. Join in on the conversation on Twitter and discover more about our speakers and the show here . About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ediscovery-review, ediscovery-and-review, data-re-use; podcast
Podcast
The Future is Now – AI and Analytics are Here to Stay
In the début episode, co-hosts Bill Mariano and Rob Hellewell introduce themselves and the premise of Law & Candor – a podcast wholly devoted to pursuing the legal technology revolution.To kick..., In the début episode, co-hosts Bill Mariano and Rob Hellewell introduce themselves and the premise of Law & Candor – a podcast wholly devoted to pursuing the legal technology revolution. To kick things off, Bill and Rob introduce the first segment of the podcast - SIGHTINGS OF RADICAL BRILLIANCE - which, as the name implies, is the part of the show where they discuss the latest news of noteworthy innovation and acts of sheer genius. In this episode, they dive into a recent story around Elon Musk’s brain-to-computer interface and what this means for the legal space. In the next segment - the guest speaker segment - our co-hosts are joined by Karl Sobylak , Senior Product Manager at Lighthouse, to uncover the answers the following questions around AI and analytics: Why do data science and analytics seem to be making great progress in so many industries aside from the law? How will AI and analytics be incorporated in the day to day life of a lawyer? What about the fear that AI and analytics will replace lawyers, is this true? What about the potential for AI and machine learning to be more limited in the law than they are for other industries, is that true? What’s the hardest part about applying data science to the law and how would this work for a corporate legal department? In conclusion, our speakers share three top takeaways and preview the next episode. Enjoy the show? Join in on the conversation on Twitter and discover more about our speakers and the show here . About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , ai-and-analytics, ai-and-analytics, analytics; ai-big-data; podcast
Podcast
Moving to the Cloud: A Law Firm Journey
In the final episode of season one, co-hosts Bill Mariano and Rob Hellewell share their thoughts around AI-enabled deep fakes in SIGHTINGS OF RADICAL BRILLIANCE. In particular, they chat about the..., In the final episode of season one, co-hosts Bill Mariano and Rob Hellewell share their thoughts around AI-enabled deep fakes in SIGHTINGS OF RADICAL BRILLIANCE. In particular, they chat about the implications and dangers around this technology and what that means for the legal space and beyond. Bill and Rob bring on David Arlington , Special Counsel at Baker Botts, to discuss the move to the Cloud from a law firm’s perspective. Bill and Rob cover the following questions with David in the season finale: Why did the firm decide to move to a cloud-based service? Did you get any pushback or fear around moving to the Cloud, and, if so, how did you handle it? How long did it take to get up on the Cloud, from the initial decision to getting up and running on the Cloud? What were some of the unanticipated surprises that popped up during this process? What kind of advantages have you seen so far? The season ends with key takeaways from the guest speaker section and a reminder to watch for the release of season two in December. Connect with us Twitter and discover more about our speakers and the show here . About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , information-governance; microsoft-365, microsoft-365, information-governance, self-service, spectra; cloud-migration; podcast; law-firm
Podcast
Microsoft Office 365 Part 2: How to Leverage all the Tools in the Toolbox
In the fourth episode of season one, co-hosts Bill Mariano and Rob Hellewell begin with SIGHTINGS OF RADICAL BRILLIANCEaround the dawn of realistic face masks as well as retina scans and..., In the fourth episode of season one, co-hosts Bill Mariano and Rob Hellewell begin with SIGHTINGS OF RADICAL BRILLIANCEaround the dawn of realistic face masks as well as retina scans and fingerprints for authentication, and the security and legal concerns that hide beneath. Next, Bill and Rob introduce guest Chris Hurlebaus , eDiscovery Architect at Lighthouse, to discuss the tools that are available in Office 365 and how to leverage them. The speakers cover the following questions in this episode: What do I need to know around Office 365 licensing when having an ediscovery conversation? What Office 365 tools are currently available to users? What are the different options/subscription levels? What are the advanced features of Office 365? What about reporting of ediscovery activities in Office 365? What is Microsoft looking to do next around this technology? In the end, our co-hosts wrap up with a few key takeaways. Follow us on Twitter and discover more about our speakers and the show here . Related Links Case Study: The Benefits of an Office 365 Workshop About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , microsoft-365; information-governance; chat-and-collaboration-data, microsoft-365, information-governance, chat-and-collaboration-data, microsoft; podcast
Podcast
Moving to the Cloud: A Corporate Journey
Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss Rob Robinson's recent article around the eras of ediscovery and..., Law & Candor co-hosts Bill Mariano and Rob Hellewell kick things off with Sightings of Radical Brilliance, in which they discuss Rob Robinson's recent article around the eras of ediscovery and where the industry is going next. In today’s episode, Bill and Rob are joined by Alex Shusterman , eDiscovery Manager at Accenture. The three discuss key components for corporate legal teams to keep in mind when considering the move to the Cloud as well as the benefits. Below are the questions they address: What are the key aspects corporate legal teams should keep in mind when considering the move to the Cloud? Why is it critical for Legal and IT to be in collaboration for these types of moves? What should corporate legal teams avoid when moving to the Cloud? What are lessons learned from moving to the Cloud? What are some of the benefits of moving to the Cloud? In conclusion, our co-hosts end the episode with key takeaways. To join in on the conversation, connect with us Twitter and discover more about our speakers and the show here . About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , information-governance; microsoft-365, information-governance, microsoft-365, self-service, spectra; cloud-migration; corporation; podcast
Podcast
Microsoft Office 365 Part 1: Microsoft’s Influence on the Next Evolution of eDiscovery
Co-hosts Bill Mariano and Rob Hellewell introduce the issues around ephemeral data in SIGHTINGS OF RADICAL BRILLIANCE. In particular, they look at the huge growth rates in Snapchat users and what..., Co-hosts Bill Mariano and Rob Hellewell introduce the issues around ephemeral data in SIGHTINGS OF RADICAL BRILLIANCE. In particular, they look at the huge growth rates in Snapchat users and what the continued growth of ephemeral data means for the legal space. Next, Bill and Rob bring on Mo Ramsey , General Manager of Global Advisory Services at Lighthouse, to help uncover the answers to the following questions around Office 365 in the ediscovery space: What does Microsoft’s evolution of ediscovery capabilities in Office 365 look like? What’s Microsoft doing within ediscovery and how do they want to differentiate? What specific actions are advanced users able to perform in Office 365? What should teams consider when evaluating Office 365? The show concludes with key takeaways from the guest speaker segment. Join the conversation on Twitter and discover more about our speakers and the show here . About Law & Candor Law & Candor is a podcast wholly devoted to pursuing the legal technology revolution. Co-hosts Bill Mariano and Rob Hellewell explore the impacts and possibilities that new technology is creating by streamlining workflows for ediscovery, compliance, and information governance. To learn more about the show and our speakers, click here . , microsoft-365; information-governance, microsoft-365, information-governance, microsoft; podcast
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