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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.

At Lighthouse our teams have the benefit of working across numerous clients, cases, and jurisdictions. As a result, we are building deep institutional knowledge across many aspects of eDiscovery that may be more difficult for individuals or teams to amass organically. To benefit our clients, we regularly share these insights in an ongoing series of best practices articles. This article provides updated guidance on cross-border eDiscovery in the wake of a recent adequacy determination by the European Commission for EU-US data transfers.Best Practices to Support Cross-Border Data Transfers in eDiscovery In any matter that potentially involves the processing and transfer of personal data across country borders, case teams should consider the following factors before deciding on a strategy:The underlying company’s own policy governing the processing of personal data (including transfer mechanisms, such as consent and/or binding corporate rules)The specific countries at issue (some countries have additional requirements for data residency, heightened consent requirements, etc.)The nature of the data (including special categories of protected data, i.e., high risk data), as well as the importance of the custodian and uniqueness/criticality of the dataThe options and feasibility of obtaining custodian consent for the transfer of their data (e.g., time to obtain consent, employment status of the custodian, the impact of obtaining consent on an investigation)When evaluating options for where the data should be processed, case teams should also consider:The country where most custodians are located (i.e., where the largest volume of data will be located) Data center options (if no data center, consider other cloud based or remote kit options and the impact on downstream search/review)The pros and cons of processing data in a single data repositoryMinimization at the point of collection as opposed to once data is processed into a review toolNote that most clients follow a “hub-centric” approach and process data in accordance with specific regions, e.g., data stored in the US is processed in the US; data stored in Europe is processed in a European data center; data stored in APAC is process either in APAC, depending on the country-specific laws, or in Europe, and so forth.Whenever non-U.S. data is present in a matter, case teams should consider the following best practices for cross-border data transfers:Establish lawful grounds for processing personal data (e.g., custodian consent, adequacy decision, or a legal exception defined by applicable data privacy regulations, such as the GDPR’s legitimate business interest exception). Note that many case teams choose not to rely solely on custodial consent for larger matters, unless the data originates from a highly restrictive jurisdiction (e.g., Switzerland, France, Germany, Luxembourg, etc.) or the matter involves specially protected data. Ensure there are adequate safeguards in place to support exceptions, such as the legitimate business interest exception. At a minimum, this includes efforts to “minimize” what is being processed (i.e., collecting only data that is necessary for the activity at hand). Case teams can minimize the volume of data being processed by using keywords or other filters to reduce what is collected, culling data at the processing stage, conducting a search for certain categories of personal data, redacting personal data, and permitting a custodian to review data prior to transfer.Case teams should also follow specific best practices when encountering any of the below scenarios during eDiscovery: Matters involving U.S. litigations and eDiscovery: Consider adding supplemental data privacy safeguards, including putting a protective order in place that specifically addresses the handling of personal data subject to applicable law (e.g., GDPR and other applicable country specific regulations). This includes provisions to designate certain data as subject to the protective order and specific provisions that require the deletion of data (and confirmation of deletion) once the litigation concludes. Matters involving cross-border transfers from other (non-U.S.) countries: Ensure an appropriate cross-border transfer mechanism is in place for all data transfers. Common examples of appropriate cross-border transfer mechanisms include model contract clauses, intra-company agreements, and adequacy decisions rendered by the European Commission (including the adequacy decision for the new EU-U.S. Data Privacy Framework).Matters involving data originating in China (PRC): Take into consideration all data security implications and PRC laws before transferring any data out of the country (including the requirement to conduct a state-secrets review in-country before any data can be transferred outside the country).Matters involving data originating in countries with heightened privacy restrictions and/or sector-specific requirements (i.e., bank secrecy): Consider processing (and potentially reviewing) data in-country.Document the protocol adhered to for each matter.ConclusionWhile transferring personal data across borders may feel like an increasingly complicated task for legal and eDiscovery teams, it is also a task that will be increasingly necessary as corporate data volumes grow and spread. The good news is that case teams do not have to navigate those complexities alone. An experienced eDiscovery partner with a global footprint and information governance/legal experts on staff can work closely with both outside and in-house counsel to develop a solution for cross-border data transfers that meets the legal requirements and needs of each matter. resource-article; data-privacy; information-governanceCross-border data transfercross-border-data-transfersjamie brown

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

“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

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

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

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

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

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

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.

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.

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

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.

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

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

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

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

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

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

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

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 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

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

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'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

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

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

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,

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

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

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

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

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 helps global British bank resolve critical risks during a major technology overhaul. Key Actions Microsoft referred Company to Lighthouse to address eDiscovery needs within Microsoft 365 (M365) Lighthouse assembled a team whose members had former expertise gained from stakeholder departments that were affected by the unresolved needs Key Results Compliance risks were successfully remediated using native M365 tools The Company used its new platform to avoid the need for add-on services or vendors What They Needed M365 Implementation Yields Data Risk Management As one of the nation’s largest financial institutions, the Company’s move to M365 required exceptional time and care—further complicating compliance requirements for record-keeping, data protection, and regulated conduct, and ultimately placing demands on M365 that created uncertainty of whether the platform could be resolved. The complex compliance requirements fueled an internal audit, revealing several risks related to the Company’s management of unstructured data, including its practices for retention, deletion, preservation, and protection of sensitive information. The Company asked Microsoft for help—and Microsoft referred the Company to Lighthouse. Tight Deadlines, Exceptional Solutions Lighthouse was tasked to explore whether M365’s native information governance (IG) and eDiscovery tools could address the risks identified in the audit. The team launched a series of workshops, interviews, and research tasks to: Educate stakeholders about M365’s native capabilities for records and information management (RIM) and IG Define stakeholders’ needs and current workflows regarding RIM and IG Analyze gaps in the current state Test and propose new workflows using native M365 tools Executives intensely monitored this project, as every identified risk was critical, so the pressure on the teams’ proposed workflows was tremendous—not to mention a tight 12-week timeline. Lighthouse prevailed, fielding a team of experienced peers with the Company stakeholders. Every business group—from records management to IT that were responsible for remediating risks—was paired with a Lighthouse consultant who had previously filled a similar role at a comparable institution. Our experts gained rapid credibility with each stakeholder group, and they ultimately accomplished a unified solution that was acceptable to all parties. Our solution succeeded in remediating all flagged risks using RIM and IG workflows within M365. It required the Company to upgrade its M365 licensing agreement from E3 to E5, but the company agreed that the added cost was more than worth it. In the end, Lighthouse achieved two key wins: 1) demonstrating to the Company that M365 could meet even the most stringent security and compliance needs, and 2) securing a new trusted partnership with the customer that has continued to develop. ‍ Corporate Case Studycase-study; big-data; cloud-migration; cloud; cloud-services; corporate; corporation; emerging-data-sources; information-governance; ediscovery; microsoft; legacy-data-remediation; risk-management; record-management; financial-services-industrymicrosoft-365; information-governance; client-success; lighting-the-path-to-better-information-governanceCase-Study, client-success, Big-Data, Cloud-Migration, cloud, Cloud-Services, Corporate, Corporation, Emerging-Data-Sources, Information-Governance, eDiscovery, microsoft, Legacy-Data-Remediation, microsoft, risk-management, Record-Management, financial-services-industry, microsoft-365, information-governance

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

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

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 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

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

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

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

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

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

Lighthouse goes beyond linear review to help a global technology company make its case to the IRS. Key Actions Targeting critical case documents with Key Document Identification 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

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