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Have you ever had this scenario – multiple team members from different groups come to you frustrated because the working relationship between their groups is “broken?” Legal is saying they aren’t getting what they need, IT says they are providing what’s asked, and finance doesn’t understand why we are paying our outside vendor for something that the internal IT and legal teams are “supposed to do.” You are responsible for process improvement among these groups so the questions and frustration lands on your desk! This is a common issue. So common, in fact, that this was a big part of a recent Legal Operators webinar I attended. The good news is that the solution may be simple.Often times, the issue revolves around language and how different departments are using the words differently. Let’s explore the above scenario a bit further. The legal team member says they asked IT to gather all data from a certain “custodian.” The IT team took that to mean all “user-created data” on the network from one certain employee, so that is what they provided. They didn’t, however, gather the items on the person’s desktop nor did they gather records that the person created in third-party systems such as the HR and sales systems that the company uses. The legal team, therefore, asked the outside vendor to collect the “missing” data and that vendor sent a bill for their services. Finance is now wondering why we are paying for collecting data when we have an IT team that does that. The issue is that different teams have slightly different interpretations of the request. Although this scenario is eDiscovery specific, this can happen in any interaction between departments. As legal operations is often responsible for process improvement as well as the way legal functions with other departments, the professionals in that group find themselves trying to navigate the terminology. To prevent such misunderstandings in the future, you can proactively solve this problem through a dictionary.Creating a dictionary can be really simple. It is something I have seen one person start on their own just by jotting down words they hear from different groups. From there, you can share that document and ask people to add to it. If you already have a dictionary of your company acronyms, you can either add to it or you can create a specific “data dictionary” for the purposes of legal and IT working together. Another option is to create a simple word document for a single use at the outset of a project. Which solution you select will vary based on the need you are trying to solve. Here are some considerations when you are building out your dictionary.What is the goal of the data dictionary? Most commonly I have seen the goal to be to improve the working relationship of specific teams long term. However, you may have a specific project (e.g., creation of a data map or implementation of Microsoft 365) that would benefit from a project-specific dictionary.Where should it live? This will depend on the goal, but make sure you choose a system that is easy to access for everyone and that doesn’t have a high administrative burden. Choosing a system that the teams are using for other purposes in their daily work will increase the chances of people leveraging this dictionary.Who will keep it updated? This is ideally a group effort with one accountable person who will make any final decisions on the definitions and own updating in the future. There will be an initial effort to populate many terms and you may want a committee of 2 or 3 people to edit definitions. After this initial effort, you can allow access to everyone to edit the document or you can have representatives from each team. The former allows the document to be a living, breathing document and encourages updating, however, may require more frequent oversight by the master administrator. The latter allows each group to have its own oversight but increases the burden of updating. Whichever method you choose, the ultimate owner of the dictionary should review it quarterly to ensure it is staying up to date.Who will have access? I recommend broader access over more limited access, especially for the main groups involved. The more people understand each other’s vocabulary, the easier it is for teams to work together. However, you should consider your company’s access policies when making this decision.What should it include? All department-specific business terms. It is often hard to remember what vernacular in your department is specific to your department as you are so steeped in that language. One easy way to identify these terms is to assign a “listener” from another department in each cross-functional meeting you have for a period. For example, for the next 3 weeks, in each meeting that involves another department, ask one person from that other department to write down any words they hear that are not commonly used in their department. This will give you a good starting point for the dictionary.Note that. although I am talking about a cross-functional effort in the above, this dictionary can also be leveraged within a department. I have found it very effective to create a legal ops dictionary that includes terms from all other departments that you pick up in your work with those other departments. This can still help your goal of resolving confusion and will allow you to get to a common understanding quickly as you are then better equipped with the language that will make your ask clear to the other team.legal-operationsediscovery-process, legal-ops, blog, legal-operations,ediscovery-process; legal-ops; bloglighthouse

Executive SummaryThe GDPR and Data Subject Access Requests (DSARs) are a key reason why companies are starting to focus their attention on information governance strategically, as opposed to simply reacting each time they get a request. With GDPR, companies have seen a significant increase in DSARs and the resulting requirement to look inwardly at their data landscape is timed perfectly with advances in cloud computing.Inconsistent NeedOver the last 20 years, I have assisted clients in responding to triggering events such as litigation and investigations by helping to identify where their data is and how to retrieve, preserve, and filter it for legal review. Rarely have those same clients been interested in proactively implementing information governance frameworks and policies without a consistent need to do so. A General Counsel once told me they face an investigation about as often as every Olympic cycle, so they don’t prioritise resources to prepare for such an infrequent event.The GDPR and associated DSAR obligations have provided exactly this motivation. However, this stick has combined with the carrot of cloud computing to provide the right mix of requirement and capability, not just to make compliance a token project stream within a company, but an enterprise-wide strategic initiative to focus on how data is generated, accessed, managed, and deleted. Common and Civil Law EnvironmentsThroughout my career, I have worked closely with companies in mainland Europe and the Middle East on cross-border litigation and investigations. In my experience, companies operating in civil law jurisdictions are not as familiar with the eDiscovery process as their common law counterparts unless they have faced regulatory scrutiny (such as companies in the financial services or technology industry). This is because they and their counsel do not face the same discovery obligations and thus have not traditionally focused on gathering evidence to produce to a court or third party. The result is inadequate retention procedures and disconnected strategies regarding data management.However, one thing all companies have in common is that using technology to make data management more efficient has become essential as data volumes grow. For example, DSAR responses may not be as ‘normal’ in mainland Europe as they are in the US or UK, but they have universally added motivation to those tasked with managing data within the company.Information Governance Buy-InNow that awareness has increased on the significant consequences of holding certain data longer than you need, senior leadership is prioritising (even at board level) how to effectively manage data within the company. This comes at a time when most companies have moved or are moving to the Cloud. According to Microsoft, “97% of Fortune 500 and 95% of Fortune 1000 companies have Office 365.” Notably, these companies are not moving to the Cloud for compliance or eDiscovery reasons, they are doing so for overall enterprise reasons including streamlining IT operations by moving off premise, giving employees access to modern workplace tools, and for security purposes. But as a bonus, when it comes to comprehensive cloud platforms such as Office 365, information governance, compliance, and eDiscovery tools are already included.Cloud Relevance for Legal TeamsNow that companies are shifting their focus to information governance, what can legal teams do to utilise the investment they’ve made in cloud computing? Since business efficiencies are important but not what legal is primarily concerned about, risk management is the key and to that end, data management is the order of the day. With increased GDPR penalties looming and cloud capabilities at their disposal, lawyers are now turning to the central pillars of information governance – document retention, categorisation, preservation, defensible deletion, identification, collection, and, depending on cloud maturity, data migration.For example, utilising functionality within Office 365, a company has a fighting chance to develop very effective and granular document retention policies that actually work and are dynamic (rather than a dusty document no one ever refers to). Categorising a document (or having it automatically categorised) when it is created, as well as determining, based on its content, when it will be deleted, is a very powerful capability. Setting email and chat message retention based on a defined policy is a significant achievement that goes a long way to limiting what data is kept and for how long.Not Just TechnologyAs GDPR and the Cloud have revolutionised information governance and provided the motivation and capability to address new and existing risks and inefficiencies, for these technology solutions to work in the long term, there needs to be a strong focus on people and processes. Change management has always been the Achilles heel of technology implementation and it is no different for Office 365 when it comes to effective information governance. First and foremost, understanding who in the company has responsibility for various processes needs to be determined. For example, who will respond to a DSAR? Who will create the data searches, preserve the data, and retrieve it for review? When it comes to labelling a document, what is the criteria for determining what qualifies as personal data? How does the technology assist in the decision making? How can a remediation exercise tie into an ongoing retention policy?Overall ComplianceIt is very hard for a multinational company to become 100% GDPR compliant. However, the Cloud offers significant capability for a company to take very reasonable and appropriate measures that go a long way. It’s better to be in the middle of the sheep pack than on the outside when the wolf is close and modern cloud technology allows companies to develop enterprise-wide frameworks to better manage their data. Let the regulators worry about companies with no demonstrable plans, not those who have made comprehensive changes to their data landscape. Even for companies that are not used to the fraught discovery world of US or even UK discovery, information governance has become a key priority due to GDPR and increasingly complex data environments that can now be managed in an effective and coordinated manner.More on this topic can be found in this article, Three Steps to Tackling Data Privacy Compliance Post GDPR. To discuss this article further, please feel free to reach out to me at MBrown@lighthouseglobal.com. data-privacycloud, gdpr, dsars, blog, data-privacy,cloud; gdpr; dsars; blogmichael brown

In a recent post, we discussed that requesting parties often demand more transparency with a Technology Assisted Review (TAR) process than they do with a process involving keyword search and manual review. So, how do you get started using (and understanding) TAR without having to defend it? A fairly simple approach: start with some use cases that don’t require you to defend your use of TAR to outside parties.Getting Comfortable with the TAR WorkflowIt’s difficult to use TAR for the first time in a case for which you have production deadlines and demands from requesting parties. One way to become comfortable with the TAR workflow is to conduct it on a case you’ve already completed, using the same document set with which you worked in that prior case. Doing so can accomplish two goals: You develop a better understanding of how the TAR algorithm learns to identify potentially responsive documents: Based on documents that you classify as responsive (or non-responsive), you will see the algorithm begin to rank other documents in the collection as likely to be responsive as well. Assuming your review team was accurate in classifying responsive documents manually, you will see how those same documents are identified as likely to be responsive by the algorithm, which engenders confidence in the algorithm’s ability to accurately classify documents. You learn how the TAR algorithm may identify potentially responsive documents that were missed by the review team: Human reviewers are only human, and they sometimes misclassify documents. In fact, many studies would say they misclassify them regularly. Assuming that the TAR algorithm is properly trained, it will often more accurately classify documents (that are responsive and non-responsive) than the human reviewers, enabling you to learn how the TAR algorithm can catch mistakes that your human reviewers have made.Other Use Cases for TAREven if you don’t have the time to use TAR on a case you’ve already completed, you can use TAR for other use cases that don’t require a level of transparency with opposing counsel, such as: Internal Investigations: When an internal investigation dictates review of a document set that is conducive to using TAR, this is a terrific opportunity to conduct and refine your TAR process without outside review or transparency requirements to uphold. Review Data Produced to You: Turnabout is fair play, right? There is no reason you can’t use TAR to save costs reviewing the documents produced to you to while determining whether the producing party engaged in a document dump. Prioritizing Your Document Set for Review: Even if you plan to review the entire set of potentially responsive documents, using TAR can help you prioritize the set for review, pushing documents less likely to be responsive to the end of the queue. This can be useful in rolling production scenarios, or if you think that eventual settlement could obviate the need to reduce the entire collection.Combining TAR technology with efficient workflows that maximize the effectiveness of the technology takes time and expertise. Working with experts who understand how to get the most out of the TAR algorithm is important. But it can still be daunting to use TAR for the first time in a case where you must meet a stringent level of defensibility and transparency with opposing counsel. Applying TAR to use cases first where that level of transparency is not required enables your company to get to that efficient and effective workflow—before you have to prove its efficacy to an outside party.ediscovery-review; ai-and-analyticstar-predictive-coding, ediscovery-review, ai-and-analyticstar-predictive-codingmitch montoya

When you’re a kid, you love easy games to learn and play, whether they’re interactive games, board games or card games. One of the first card games many kids learn how to play is “Go Fish.” It’s easy to learn because you simply ask the other player if they have any cards of a certain kind (e.g., “got any Kings?”) – if they do, you collect those cards from them; if they don’t, they say “Go Fish” and you have to draw a card from the deck and your turn ends. Easy, right?Conducting keyword searching without a planned, controlled process that includes testing and verifying the results is somewhat like playing “Go Fish” – you might get lucky and retrieve the documents you need to support your case (without retrieving too many others) and you might not. Yet many lawyers and legal professionals think they “get” keyword searching. Why? Because they learned keyword searching in law school using Westlaw and Lexis? Or they understand how to use “Google” to locate web pages related to their topics? But these examples are designed to identify a single item (or handful of items) related to one topic that you seek.Keyword searching for electronic discovery is about balancing recall and precision to produce a proportional volume of electronically-stored information (ESI) that is responsive to the case, which could be thousands or even millions of responsive documents, depending on the issues of the case.Five Common Keyword Searching MistakesWith that in mind, here are five common mistakes that lawyers and legal professionals make when conducting keyword searches:1. Poor Use of Wildcards: Wildcard characters can be helpful in expanding the scope of the search, but only if you use them well — and understand how they are applied by the search engine you’re using (warning: don’t use Google’s search engine as an exemplar). Poorly placed or ill-advised wildcard character(s) can completely blow up a search. A few years ago, there was a case where one of the goals was to identify documents that related to apps on devices (mobile and PC), so the legal team decided to use a search term “app*” to retrieve words like “app”, “application”, “apps”, etc. Great, right? Not when that same term also retrieves terms like “appear”, “apparent”, “applied”, “appraise”, etc. A better search in this case would have been (app or apps or application*). Make sure to think through word variability and consider word formulations that could be hit by the search. Also consider whether wildcard operators are attached at the appropriate place in the stem of a word so that all of the variants are hit. If not, the search might target too many unrelated words or omit words you want to capture.2. Use of Noise or Stop Words: To keep retrieval responsive even in large databases, most platforms don’t index certain common words that appear regularly (defined as “noise” or “stop” words), yet many legal professionals fail to exclude these noise words in the searches they conduct – yielding unexpected results. Search terms such as “management did” or “counseled out” won’t work if “did” and “out” are noise words that can’t be retrieved. There are typically 100 or more words that are not indexed by a typical platform, so it’s important to understand what they are and plan around them in creating searches that can get you as close as possible to your desired result.3. Starting with Searches That Are Too Broad: Another common mistake is to start with searches that are too broad, assuming that you’ll get a result that will be easy to narrow down through additional search. In fact, you may get a result that makes it nearly impossible to determine what might be causing your search to retrieve unexpected results. Keyword search works best when the hard work has been done up front, either by working with subject matter experts who have provided insight into likely vocabulary used (e.g., shorthand, code words, slang) or via a targeted exploration of the document population. That knowledge, coupled with the effective use of Boolean operators like AND, OR, and NOT, should enable you to craft initial searches that put targeted words in the appropriate context, increasing the likelihood that relevant material will be found at the outset. That result will provide the necessary fodder for developing additional searches that are more precise.4. Failing to Test What’s Retrieved: Many legal professionals create a search, perform that search and then proceed to review without testing the results. Performing a random sample on the results could quickly identify a search that is considerably overbroad and would result in a low prevalence rate of responsive documents, driving up costs for review and production. Testing the result set to ensure the search is properly scoped is well worth the time and effort to take that extra step in terms of potential cost savings. Better to review an extra few hundred documents than an extra hundred thousand documents.5. Failing to Test What’s Not Retrieved: It’s just as important to test the documents that were not retrieved in a search to identify areas that were potentially missed. Not only does a random sample of the “null set” help identify searches that were too narrow in scope, they also are important in addressing defensibility concerns related to your search process if it is challenged by opposing counsel.The ”Go Fish” analogy isn’t an original one – then New York Magistrate Judge Andrew J. Peck used it in his article Search, Forward over nine years ago (October 2011) when he observed that “many counsel still use the “Go Fish” model of keyword search.” If you’re making some of the mistakes listed above, you might be doing so as well. Proper keyword searching is an expert planned and managed process that avoids these mistakes to maximize the proportionality and defensibility of your discovery process. It’s not a kid’s game, so make sure you don’t treat it like one.ediscovery-reviewblog, -keyword-search, ediscovery-review,blog; keyword-searchlighthouse

Investigators experienced in interrogating data know that there may be more to a communication than meets the eye. Whether from intentional or unconscious behavior, clues abound.When key facts are conveyed in nuanced or disguised language, it is important to explore the available collection of documents and communications with a linguistic and forensic sensibility. Although a difficult endeavor, the payoff is high when previously hidden meaning and intent surfaces in your investigation. In the process, individual finds often lead to a larger set of findings providing you a deeper understanding of who exactly knew or did what, and how they felt about it.Follow the ScentUnlike for a typical discovery request, searching for hidden meaning and intent in large data sets requires an ability to pinpoint nuanced — and often indirect — textual cues. This capability is distinct from relevance-based classification techniques such as TAR, which are optimized to ensure consistent coverage for a topic across a large data set. When looking for possible subterfuge or heightened emotion, for example, the task is more akin to incremental detective work than it is batch or prioritized classification. As such, it is useful to frame your efforts within an iterative search workflow that brings you into contact with potentially interesting content and communications, while also allowing you an ability to pivot off your search to explore particular key people, events, and timelines where interesting content appears to be clustered. Make a ListAn important first step in searching for key content you might otherwise be missing is to develop or tailor pre-existing lists of keywords and phrases targeting the types of behaviors and sentiments you are interested in uncovering.For example, if you are investigating possible fraud, you may want to focus part of your search on isolating communications in which there are textual traces suggesting concealment. Some concealment-related phrases to add to a keyword list for a fraud investigation could include “do not share this,” “take off line,” or “delete email,” to name just a few.Additionally, if you are interested in isolating internal chatter conveying strong concern or worry, you could include items like “atrocious,” “huge mistake,” “ill advised,” or “ordeal.” Ziti? Or Fraud?Apart from language expressing worry or concealment, other language worth targeting to get at hidden meaning and intent could include profanity and slang. Also, keep in mind the cultural context in which the communications and documents you are searching through were produced. For example, in a recent bribery and corruption case in NY state involving NY state government officials and private business executives, “ziti” (or “zitti”) was used as a code word to refer to bribes and extortion money. This particular code word in this context was borrowed from the language used by organized crime in New York and surrounding states.Stay on TopicGiven the richness of language and culture, keyword lists targeting hidden figurative meaning can grow to hundreds, even thousands, of words and phrases. To avoid a deluge of hits, it is useful to pair these special keywords with broad issue indicators to make sure you are targeting not only figurative language, but also potentially relevant content. For example, if you are interested in isolating potential fraud around billing practices, one possible tactic would be to leverage proximity search by pairing fraud-related terms like “unusual” with a broad topical keyword term “billing” (e.g., unusual /50 bill[s,ed,ing]). Using this tactic in a systematic way across targeted sentiments and topics will get you a richer result set to focus your in-depth review on.Prepare Ahead of TimeAs with any search effort, setting up your data by threading email conversations and identifying near-duplicate sets of documents are two of the many approaches available to winnow down and prioritize the set of documents you perform targeted searches on. Techniques such as name normalization can also be especially helpful when your aim is to understand who is communicating with whom on a consistent basis.Keep Smiling It is also useful to explore how best to tailor the indexing of your data for searching — for instance, emojis are often used in key relevant conversations, yet they are rarely indexed automatically for search in review platforms. From both a discovery and investigative perspective, this can be a big blind spot. Preliminary research on the topic shows an increase in the number of US cases referring to emoji as evidence increased from 33 in 2017 to 53 in 2018.Searching for key content conveyed through nuanced language is a complex task that is substantively distinct from relevance and topic classification. With the right mindset, workflow, and tools, you will be able to structure and manage this effort in order to isolate key facts otherwise left hidden that are relevant to your case.ai-and-analyticsblog, key-document-identification, fraud-detection, ai-and-analytics,blog; key-document-identification; fraud-detectionlighthouse

Facing a second request can be painful, kind of like searching for a needle in a haystack exacerbated by a strict deadline looming above it all. And, as volumes of data continue to grow and types of data become increasingly complex, these matters are often inefficient and costly, while getting to the key documents (needles) quickly can feel like an insurmountable challenge.In the 2019 Antitrust Leadership Panel, I gathered together a group of top antitrust experts to discuss the grueling challenges, the role of technology and emerging trends, and a few concrete recommendations for progress to make second requests more efficient and less costly. The video series of the panel was very well received and I have since been asked by several viewers, “So, Bill, how do I apply these ideas to my current antitrust practice or process? How do I find the needles in the haystack?”In this blog, I will answer just that and distill the key takeaways from the panel to share with your team so that you can be better equipped to tackle a second request and find the critical needle in that giant, ever-evolving haystack of data.Lesson 1: Technology is a must, but so is trust.Our expert panelists all agreed that although the usage of technology can be challenging to negotiate with the DOJ and the FTC, its application is paramount in getting to key documents quickly. With that in mind, the first phase in preparing for your next second request and conquering the haystack of data is to leverage technology. Here are some simple steps to get you started:It’s critical to understand what technology is out there and what it can do (i.e. AI, predictive coding, email threading, deduplication, etc.). Ensure you and your team stay on top of what each of these tools does and how you can leverage them in second requests. Understanding and educating yourself on all aspects of the technology is key to increasing the government’s trust and acceptance of new tools they may not be familiar with…more on that in the next step.Once you understand what technology options are available and have the best probability for success in your specific case, select the tool or tools that make the most sense for your team and secure them (i.e. by leveraging your vendor’s tools or procuring them in house). Work with your vendor or in-house team to develop sound evidence that will persuade the DOJ and FTC to accept technology so that it can be more broadly used and leveraged within your matters. This will allow you to save significant time and money and, who knows, if we all did it the DOJ and FTC may be more likely to accept itLesson 2: Proportionality can save you time and money, leverage it.The panel also discussed that although the DOJ and FTC sometimes don’t seem to make proportionality a priority in second requests and may intentionally request broader swaths of data to buy more time outside of the strict statutory guidelines, it’s clear that proportionality should be a primary focus for both parties to limit the burdensome amount of data that must be collected and reviewed. Consider this next set of steps as another way to potentially save time and money when trying to dig through the haystack of second request data.When faced with a second request, first discuss amongst your team what arguments for proportionality can be made.Ensure your arguments for proportionality are based on compelling evidence and bring them to the DOJ and FTC at the onset of the second request.If your argument is not accepted on one matter, work with your vendor to focus on building more evidence to get the DOJ and FTC on the side of proportionality in your next matter.Lesson 3: Privilege review tools can be a privilege in the long run.According to the panelists, having better and more user-friendly privilege review tools would result in a significantly improved second request process for everyone involved. So, how do you take concrete action on that? Here are a few additional steps to improve the privilege review process and break down one of the most burdensome parts of tackling the haystack.Reach out to your vendor and ask what tools and solutions they have around privilege review.Test out their privilege tools on your next matter and provide feedback for continuous process improvement.Work with your vendor to develop customized privilege tools using advanced analytics to find privileged documents more quickly and easily.When leveraging privilege tools, be sure to track solid metrics and develop new evidence to showcase to the DOJ and FTC why they can trust the advanced technology.Share these takeaways within your team and apply the steps that make sense for your practice so that the next time you’re faced with a daunting second request and a seemingly insurmountable amount of data, you’ll be well positioned to tackle the challenge and find the right needles in the haystack from the onset.Want to discuss this topic more? Feel free to reach out to me at BMariano@lighthouseglobal.com.To explore related content, click the links below:Antitrust Leadership Panel: Time and CostAntitrust Leadership Panel: The Role of TechnologyAntitrust Leadership Panel: Evolving for the Futureai-and-analytics; antitrustanalytics, hsr-second-requests, blog, ai-and-analytics, antitrustanalytics; hsr-second-requests; blogbill mariano

In honor of International Women’s Day 2019, Lighthouse highlighted a few female thought leaders who are changing the game in the eDiscovery, compliance, and information governance space. Check out our featured ladies below and discover what they are doing to lead change as well as some of their key tips for success: Take a look at our 2020 International Women's Day Campaign!diversity-equity-and-inclusionediscovery-process, blog, diversity-equity-and-inclusion,ediscovery-process; bloglighthouse

Your team is facing a wall of mounting compliance requirements and internal investigations, as well as a few larger litigations you fear you may not be able to handle given internal resource constraints. Each case involves unwieldy amounts of data to wade through, and that data must be collected from constantly-evolving data sources—from iPhones to Microsoft Teams to Skype chats. You’re working with your IT team to ensure your company’s most sensitive data is protected throughout the course of all those matters.All of this considered, your team is faced with vetting eDiscovery vendors to handle the large litigation matters and ensuring those vendors can effectively protect your company’s data. Simultaneously, you are shouldering the burden of hosting a separate eDiscovery platform for internal investigations with a legal budget that is already stretched thin. Does this sound familiar? Welcome to the life of a modern in-house attorney. Now more than ever, in-house counsel need to identify cost-effective ways to improve the effectiveness and efficiency of their eDiscovery matters and investigations with attention to the security of their company’s data. This is where adopting a cloud-based self-service, spectra eDiscovery platform can help. Below, I’ve outlined how moving to this type of model can ease many of the burdens faced by corporate legal departments.1. The Added Benefit of On-Demand Scalability‍A cloud-based, self-service, spectra platform provides your team the ability to quickly transfer case data into a cutting-edge review platform and access it from any web browser. You’re no longer waiting days for a vendor to take on the task with no insight into when the data will be ready. With a self-service, spectra solution, your team holds the reigns and can make strategic decisions based on what works best for your budget and organization. If your team has the bandwidth to handle smaller internal investigations but needs help handling large litigations, a scalable self-service, spectra model can provide that solution. If you want your team to handle all matters, large and small, but you worry about collecting from unique sources like Microsoft Teams or need help defensibly culling a large amount of data in a particular case, a quality self-service, spectra provider can handle those issues and leave the rest to you. In short, a self-service, spectra solution gives you the ability to control your own fate and leverage the eDiscovery tools and expertise you need, when you need them. 2. Access to the Best eDiscovery Tools – Without the Overhead Costs A robust self-service, spectra eDiscovery solution gives your team access to the industry’s best eDiscovery tools, enabling you to achieve the best outcome on every matter for the most efficient cost. Whether you want to analyze your organization’s entire legal portfolio to see where you can improve review efficiency across matters, or you simply want to leverage the best tools from collection to production, the right solution will deliver. And with a self-service, spectra model, your team will have access to these tools without the burden of infrastructure maintenance or software licensing. A quality self-service, spectra provider will shoulder these costs, as well as the load of continuously evaluating and updating technology. Your team is free to do what it is does best: legal work.3. The Peace of Mind of Reliable Data Security In a self-service, spectra eDiscovery model, your service provider shoulders the data security risk with state-of-the-art infrastructure and dedicated IT and security teams capable of remaining attentive to cybersecurity threats and evolving regulatory standards. This not only allows you to lower your own costs and free up valuable internal IT resources, but also provides something even more valuable than cost savings—the peace of mind that comes with knowing your company’s data is being managed and protected by IT experts.4. Flexible, Predictable Pricing and Lower Overall Costsself-service, spectra pricing models can be designed around your team’s expectations for utilization—meaning you can select a pricing structure that fits your organization’s unique needs. From pay-as-you-go models to a subscription-based approach, self-service, spectra pricing often differs from traditional eDiscovery pricing in that it is clear and predictable. This means you won’t be blindsided at the close of the month with hidden charges or unexpected hourly fees from a law firm or vendor. Add this type of transparent pricing to the fact that you will no longer be shouldering technology costs or paying for vendor services you don’t need, and the result is a significantly lower eDiscovery overhead that can fit within any legal budget. These four benefits can help corporations and in-house counsel teams significantly improve eDiscovery efficiency and reduce costs. For more information on how to move your organization to a self-service, spectra eDiscovery model, be sure to check out our other articles related to the self-service, spectra eDiscovery revolution – including tips for overcoming self-service, spectra objections and building a self-service, spectra business case.ediscovery-review; ai-and-analyticsself-service, spectra, blog, ediscovery-review, ai-and-analyticsself-service, spectra; bloglighthouse

In honor of International Women’s Day 2020, Lighthouse is featuring female leaders within the industry who actively choose to challenge stereotypes, fight bias, broaden perceptions, improve situations, and celebrate women's achievements. Below are spotlights on each of our 2020 featured females helping to make a gender equal world. Check them out!1. What does a gender-equal world mean to you? It means a meritocracy where everyone with skill, hard work, and imagination may aspire to, and actually can achieve, the highest level regardless of gender. It means the elimination of explicit and implicit biases that can skew professional relationships and result in disparate opportunities. It means having a voice and a seat at the table earned through performance and not being sidelined because of gender.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I was raised in a counter-stereotypical environment. My mother was the primary breadwinner and a full-time working professional, while my father took on most of the childcare responsibilities after a full work day of physical labor that began at 5 a.m. I grew up playing backyard tackle football with my brother and male family friends in mud, ice, and rain, and they did not go easy on me. I then joined the Marine Corps. Until a few years ago, I never had the perception that there were limits on what I could achieve because I am female.Unfortunately, I am now intimately aware of the ugly reality of gender discrimination. My experiences allow me to better understand the elements that contribute to disparate treatment and what can be done to address them. Raising awareness of these issues in a more vocal way is in the works. I have never been afraid to challenge the status quo (like using predictive coding in 2012) and I will continue to do so to effectuate positive change.When faced with bias in the past, I researched and gathered information regarding best practices to address such issues. I presented recommendations to leadership and organized events to build community and provide training. I continue to provide mentorship and support to other women. And, I challenge stereotypes by persevering as a working mom in big law.3. How do you celebrate other women's achievements? I like to spread awareness of other women’s achievements and provide other women opportunities to shine. I go out of my way to ensure key decision makers know about the accomplishments of other women.4. What recommendations do you have for others looking to ensure a gender equal workplace? For those trying to establish best practices internally, there are a myriad of resources available. For example, the Center for Worklife Law, spearheaded by the Professor Joan Williams, provides an array of practical tools, model policies, training, and best practice guides. Vote with your feet and dollars. If efforts to effectuate change internally fall on deaf ears, go somewhere else where there is a demonstrated commitment to providing a level playing field. Dentons is truly invested in supporting women, as apparent through their review processes, bias training and safeguards, development and authentic leadership diversity. Support vendors and consultants who demonstrate gender equality. Be cognizant of who you work with and keep busy. Build community.1. What does a gender-equal world mean to you? To me a gender-equal world means not having to over analyze each piece of my daily life to assure my value is recognized by all participants. It means not having to change my approach, tone, or demeanor to be heard by my male colleagues. It means I can be ME.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I personally challenge stereotypes at my firm by being a strong leader, volunteering for important projects, speaking up in meetings, offering feedback to my colleagues equally, male and female. Importantly, I recognize my value to the firm. I am BRAVE. I am CONFIDENT.3. How do you celebrate other women's achievements? Through my leadership in the GOIC Lean In Circle and membership in the Diversity and Inclusion Committee at Orrick, I help host events and provide a forum for women’s accomplishments to be recognized. When working with my colleagues and teams I assure that credit earned is given.4. What recommendations do you have for others looking to ensure a gender equal workplace? Be persistent! Be ambitious! Don’t settle. Recognize your value. People live up to expectations. Make your value known, expect credit. If you don’t get it, seek it out. If you don’t expect to get the next big project, you may never get it. Volunteer and make your voice heard.1. What does a gender-equal world mean to you? A human is recognized for "their" personality and knowledge in all capacities. Mental and physical health are supported and provided for without bias. "We" are respected for virtues both positive and negative.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? Initially and always, listening. What's the reason for the bias? Challenging the responses with actions, calmness, and, ultimately, calling out the unbalanced views. Empathy to all is the sincerest way to "fight" and remove bias.3. How do you celebrate other women's achievements? I like to send notes or cards to congratulate as a small but personal article of celebration. Telling women how fantastic the achievements are and discussing them in other communities. Sharing the knowledge equates to opening new conversations or relighting old topics.4. What recommendations do you have for others looking to ensure a gender equal workplace? Develop an altruistic culture focusing on team dynamics, envelop clients into team and workspace initiatives, and, importantly, talk about it! Publicise the how, the who, and the why.1. What does a gender-equal world mean to you? It means fair treatment across the gender identity spectrum. It does not mean we have to look, talk, or act the same. We all bring something unique to the conversation and should be celebrated equally for our contributions. Rights, opportunities, obligations, and pay should not take gender into consideration. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? My workplace makes diversity a priority. That being said bias still exists, often when you least expect it. When you experience bias, gather your thoughts, speak up, and don’t tolerate bad behavior. Set an example by never apologizing for being at the table. Your opinion matters so speak with authority. 3. How do you celebrate other women's achievements? We’re often bad at celebrating our own achievements, making it more important that we celebrate each other. Words of encouragement when things don’t go as expected and notes of recognition when they do. Use your organization's award, bonus, and feedback structure, especially if achievements were missed by the broader group. 4. What recommendations do you have for others looking to ensure a gender equal workplace? Begin with the end in mind. My organization works hard to expand our candidate pool, rethink our interview process so that a diverse panel interviews candidates, and set up mentor and onboarding programs that match diverse candidates. For my team, work life balance, flexibility, and open communication have been key.1. What does a gender-equal world mean to you? I aspire to a world where we equally value the attributes of all genders and celebrate the power of teams of people with different experiences, perspectives, and strengths. It may seem funny, but when traveling for business, I am often struck by the fact that I am the only woman in the hotel restaurant at breakfast. It would be inspiring to see that change. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? My career path and non-partner role defy stereotypes. In my role, I strive to create an environment where it is safe to disagree and challenge the status quo. The success of my team shows that when you refuse to do things as they have always been done by the same people who have always done them, great things can happen. But, most of all, I love what I do contrary to stereotypes!3. How do you celebrate other women's achievements? As a team we foster meaningful relationships and connections among women so that we can lift each other up and challenge one another. We are active in Women in eDiscovery and She Breaks the Law, and recently nominated 16 women to the ABA Women in Tech list. When selecting vendors, technology solutions, and making investments via our legal tech fund, we look at whether the company has women in senior leadership roles. 4. What recommendations do you have for others looking to ensure a gender equal workplace? Re-imagine the skill set and talent profiles for new hires. Women are under-represented in senior leadership positions in the legal and technology industries. To expand your talent pool, look for candidates in other industries and value innate ability over previous titles and years of experience. Give early opportunities and invest in creating the next generation of women leaders. 1. What does a gender-equal world mean to you? At a basic level, gender equality means having gender never enter into the equation. However, for my everyday reality, it means a workplace where being a working mother that values and prioritizes time with her family does not count against me and is actually celebrated. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? As a manager, I promote an environment that has open and honest communication and treats everyone equally. As a mother, I am raising my two young boys to think of women as not just equals, but as powerful forces. 3. How do you celebrate other women's achievements? As the world comes closer to gender equality, it is important that we reward all individuals in a way that does not create a greater divide. At a basic level, this means rewarding people for the quality of work they do and not just the number of hours they put in. 4. What recommendations do you have for others looking to ensure a gender equal workplace? There are a number of actions companies and individuals can take to help ensure gender equality in the workplace. These can be as simple as removing names from resumes to make them gender neutral, create pay bands based on position and not previous salary, and using gender neutral leave policies. 1. What does a gender-equal world mean to you? A world where gender is no longer a barrier to equal opportunity. A world free of the biases and prejudice currently associated with gender, both overtly and unconsciously, where everyone has a chance to develop their potential. 2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I support diversity in groups and teams, both during the hiring phase and after hiring. When hiring, I work with recruiters to ensure a diverse applicant pool. When managing, I encourage inclusion and collaboration, thereby allowing for a wide range of perspectives and opinions from which everyone will benefit.3. How do you celebrate other women’s achievements? Whenever a female colleague accomplishes something important, I take the time to recognize, support and encourage her. Where possible, I do so in person. In addition, and where necessary, I also use one of the other myriad avenues for such recognition, including email, phone, text, social media, company intranet.4. What recommendations do you have for others looking to ensure a gender equal workplace? Use best efforts to support and encourage diversity, and celebrate important accomplishments. Start during hiring, working with recruiters to ensure it includes both women and men. When managing, encourage inclusion and collaboration, encourage everyone to develop their potential, and take the time to celebrate the successes.1. What does a gender-equal world mean to you? Girls are often encouraged to believe they can do anything they set out to do, as long as they aren’t too loud about it, because, after all, they must behave like proper young ladies. In a gender-equal world, girls should be as brash as they wish and women should tout their accomplishments.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I lead by example, making sure my voice is heard. When I run meetings, I ensure that every participant has the opportunity to contribute if they wish. I acknowledge great ideas put forth by women when their male counterparts try to co-opt them.3. How do you celebrate other women’s achievements? I choose words carefully when describing women’s achievements to ensure they are gender-neutral and give credit that is deserved. I use active voice to indicate a female team member has worked for her accomplishments, rather than phrases that seem to imply she was lucky to have something happen for her.4. What recommendations do you have for others looking to ensure a gender equal workplace? If you feel overlooked in the workplace, develop allies and mentors. Allies are female and male counterparts who will amplify your voice. Mentors can help navigate workplace politics and educate male-dominated leadership on the importance of gender equality.1. What does a gender-equal world mean to you? A gender-equal world is on in which all people, regardless of their sex, have the same opportunities and receive equal compensation.2. How do you personally challenge stereotypes and/or fight biases around females in the workplace? I definitely lead by example. As a leader in my organization, I also have a responsibility to identify and correct when stereotypes or biases surface. I find one-on-one conversations with a person who has articulated the stereotype or bias is effective. Some people don't even realize that they have biases. It is important to me that I am known for cultivating a fair work environment for everyone.3. How do you celebrate other women’s achievements? Women need more professional mentors. I seek mentors out myself and I have served as a mentor for many other women in my career. I celebrate the achievements of the women I have mentored with a personal note or even a quick text. I have close professional female counterparts at other organizations. We are intentional about staying connected. Congregations with these ladies at industry events often turn into think tanks of sorts and we are always celebrating someone's latest accomplishment. Women have to hold up and support other women.4. What recommendations do you have for others looking to ensure a gender equal workplace? If you are in the job market, look at the leadership of the organization. That will speak volumes about their efforts to ensure a gender equal workplace. Ask about their commitments to gender quality and any corporate programs they have in place to support those efforts. If you are in a company that lacks in this area, take the initiative to raise it and spearhead a proposal to help them elevate their efforts.A big shout out to the women who participated in our International Women's Day Campaign focused on #EachforEqual! Take a look at our 2019 International Women's Day Campaign. diversity-equity-and-inclusionediscovery-process, blog, diversity-equity-and-inclusion,ediscovery-process; bloglighthouse

Planning the best ways to find key documents will pay off in the long run. Getting to the bottom of alleged claims is often a high-stakes race to find critical information amidst an avalanche of data. Regardless of whether you are conducting an internal investigation, early case assessment, or preparing for depositions, there is no time to waste. Although it’s surely tempting to dive right into document reviews to find the key documents that will shed light on the matter at hand, litigators and investigators know that good preparation leads to a better result.Conducting fact-finding in a reactive manner by skipping upfront preparation diminishes the ability to systematically investigate the full set of allegations and compromises the development of a comprehensive factual narrative. Here are a few things to keep in mind as you prepare.Consider the source(s).To conduct efficient fact-finding through key document identification, you need to first take stock of the various sources of data available for review and then map them to the type of evidence they may contain.Is the evidence you are looking for likely to reside in reports, communications, or memos? Are there particular sets of custodial data that are likely more important to understanding the case than others? Are inbound consumer marketing solicitations to employees, or bulk email news alerts likely to contain important information for the case? Taking the time to consider these questions and articulate hypotheses about where important evidence may reside allows you to effectively prioritize which data sets to search through first.What are the targets?In addition to prioritizing the data, it’s critically important to articulate the array of evidence you are looking for based on the set of allegations at issue. Your understanding of the case will certainly evolve as fact-finding progresses, but defining evidentiary targets in advance better enables you to assess later on whether you have diligently investigated all possible angles. Moreover, defining discrete targets for fact-finding allows you to articulate searches at a more granular level. Rather than leveraging one fully encompassing crude keyword search to hunt for key documents, creating a net of many targeted searches will lead to more comprehensive results in a more efficient manner.What tools should you use?Another key to efficient and successful fact-finding is selecting the right data analytics tools that will help reduce the noise and boost the signal. For example, threading email conversations and identifying near-duplicate sets of documents are two of the many approaches available to winnow down and prioritize the set of documents you perform targeted searches on. Techniques such as name normalization can also be especially helpful when your aim is to understand who is communicating with whom about which underlying facts. It might even be worth investigating how to best tailor the way the data is indexed for searching — for instance, emojis are often used in key conversations useful in investigations yet they are rarely indexed for search in review platforms unless you explicitly specify them to be.Understanding the data, articulating an evidentiary approach, and equipping yourself with the right data analytics helps ensure that critical facts do go undiscovered. Although it’s natural to want to get right into the thick of it, skilled counsel know that high-stakes fact-finding is a complex affair requiring forethought and preparation. And once in place, a well-informed search strategy can be quickly executed allowing your team to spend more time understanding the significance of key documents, and less time re-evaluating and tinkering with approaches for finding them.Want to know more? Watch “Winning the Race for the Facts: Case Studies on How to Leverage Technology and Search Expertise for Investigations and Case Preparation,” a joint webinar with H5 and Covington & Burling, for further tips on finding key documents for investigations.ediscovery-reviewblog, -key-document-identification, kdi, ediscovery-review,blog; key-document-identification; kdilighthouse

Ever since ABA Model Rule of Professional Conduct 1.1 [1] was modified in 2012 to include an ethical obligation for attorneys to “keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology [2]” (emphasis added), attorneys in almost every state have had a duty to stay abreast of how technology can both help and harm clients. In other words, most attorneys practicing law in the United States have an ethical obligation to not only understand the risks created by the technology we use in our practice (think data breaches, data security, etc.), but also to keep abreast of technology that may benefit our practice.Nowhere is this obligation more implicated than within the eDiscovery realm. We live in a digital world and our communications and workplaces reflect that. Almost any discovery request today will involve preserving, collecting, reviewing, and producing electronically stored information (ESI) – emails, text messages, video footage, Word documents, Excels, PowerPoints, social media posts, collaboration tool data – the list is endless. To respond to ESI discovery requests, attorneys need to use (or in many cases, hire someone who can use) technology for every step of the eDiscovery process – from preservation to production. Under Model Rule 1.1, that means that we must stay abreast of that technology, as well as any other technology that may be beneficial to completing those tasks more effectively for our clients (whether we are providing legal advice to an organization as in-house counsel or externally through a law firm).In this post, I posit that in the very near future, this ethical obligation should include a duty to understand and evaluate the benefits of leveraging Artificial Intelligence (AI) during almost any eDiscovery matter, for a variety of different use cases.AI in eDiscoveryFirst, let’s level set by defining the type of technology I’m referring to when I use the term “AI,” as well as take a brief look at how AI technology is currently being used within the eDiscovery space. Broadly speaking, AI refers to the capability of a machine to imitate intelligent human behavior. Within eDiscovery, the term is often also used broadly to refer to any technology that can perform document review tasks that would normally require human analysis and/or review.There is a wide range of AI technology that can help perform document review tasks. These include everything from older forms of machine learning technology that can analyze the text of a document and compare it to the decisions made about that document by a human to predict what the human decision would be on other documents to newer generations of analytics technology that can analyze metadata and language used within documents to identify complicated concepts, like the sentiment and tone of the author. This broad spectrum of technology can be incredibly beneficial in a number of important document review use cases – the most common of which I have outlined below: Culling Data - One of the most common use cases for AI technology within eDiscovery is leveraging it to identify documents that are relevant to the discovery request and need to be produced. Or, conversely, identify documents that are irrelevant to the matter at hand and do not need to be produced. AI technology is especially proficient at identifying documents that are highly unlikely to be responsive to the discovery request. In turn, this helps attorneys and legal technologists “cull” datasets, essentially eliminating the need to have a human review every document in the dataset. Newer AI technology is also better at identifying documents that would never be responsive to any document request (i.e., “junk” documents) so that these documents can be quickly removed from the review queue. More advanced AI technology can do this by aggregating previously collected data from within an organization as well as the attorney decisions made about that data, and then use advanced algorithms to analyze the language, text, metadata, and previous attorney decisions to identify objectively non-responsive junk documents that are pulled into discovery request collections time and time again. Prioritizing and Categorizing Data - Apart from culling data, AI can also be used to simply make human review more efficient. Advanced AI technology can be used to identify specific concepts and issues that attorneys are looking for within a dataset and group them to expedite and prioritize attorney review. For example, if a litigation involves an employee accused of stealing company information, advanced AI technology can analyze all the employee’s communications and digital activities and identify any anomalies, such as an activity that occurred during abnormal work hours or communications with other employees with whom they normally would not have reason to interact. The machine can then group those documents so that attorneys can review them first. This identification and prioritization can be critical in evaluating the matter as a whole, as well as helping attorneys make better strategic decisions about the matter. Review prioritization can also simply help meet court-imposed production deadlines on time by enabling human reviewers to focus on data that can go out the door quickly (i.e., documents that the machine identified as highly likely to be responsive but also highly unlikely to involve issues that would require more in-depth human review like privilege, confidentiality, etc.). Identifying Sensitive Information - On the same note, AI technology is now more adept at identifying issues that usually require more in-depth human review. Newer AI technology that uses advanced Natural Language Processing (NLP) and analyzes both the metadata and text of a document is much better at identifying documents that contain sensitive information, like attorney-client privileged communications, company trade secrets, or personally identifiable information (PII). This is because more advanced NLP can take context into account and, therefore, more accurately identify when an internal attorney is chatting with other employees over email about the company fantasy football rankings vs. when they are providing actual legal advice about a work-related matter. It can do this by analyzing not only the language being used within the data, but also how attorneys are using that language and with whom. In turn, this helps attorneys conducting eDiscovery reviews prioritize documents for review, expedite productions, and protect privileged information.Attorneys’ Ethical Obligation to Consider the Benefits of AI in eDiscovery The benefits of AI in eDiscovery should now be clear. It is already infeasible to conduct a solely human linear review of terabytes of data without the help of AI technology to cull and/or prioritize data. A review of that amount of data (performed by humans reviewing one document at a time) can require months and even years, a virtual army of human reviewers (all being paid at an hourly rate), as well as the training, resources, and technology necessary for those reviewers to perform the work proficiently. Because of this, AI technology (via technology assisted review (TAR)) has been widely accepted by courts and used by counsel to cull and prioritize large sets for almost a decade.However, while big datasets involving terabytes of data were once the outliers in the eDiscovery world, they are now quickly becoming the norm for organizations and litigations of all sizes due to exploding data volumes. To put the growing size of organizational data in context, the total volume of data being generated and consumed has increased from 33 zettabytes worldwide in 2018 to a predicted 175 zettabytes in 2025[3]. This means that soon, even the smallest litigation or investigation may involve terabytes of data to review. In turn, that means that AI technology will be critical for almost any litigation involving a discovery component.And that means that we as attorneys will have an ethical duty to keep abreast of AI technology to competently represent our clients in matters involving eDiscovery. As we have seen above, there is just no way to conduct massive document reviews without the help of AI technology. Moreover, the imperative task of protecting sensitive client data like attorney-client privilege, trade secret information, and PII (which all can be hidden and hard to find amongst massive amounts of data) also benefits from leveraging AI technology. If there is technology readily available that can lower attorney costs and client risk, while ensuring a more consistent and accurate work product, we have a duty to our clients to stay aware of that technology and understand how and when to leverage it.But this ethical obligation should not scare us as attorneys and it doesn’t mean that every attorney will need to become a data scientist in order to ethically practice law in the future. Rather, it just means that we, as attorneys, will just need to develop a baseline knowledge of AI technology when conducting eDiscovery so that we can effectively evaluate when and how to leverage it for our clients, as well as when and how to partner with appropriate eDiscovery providers that can provide the requisite training and assist with leveraging the best technology for each eDiscovery task.ConclusionAs attorneys, we have all adapted to new technology as our world and our clients have evolved. In the last decade or so, we have moved from Xerox and fax machines to e-filings and Zoom court hearings. The same ethic that drives us to evolve with our clients and competently represent them to the best of our ability will continue to drive us to stay abreast of the exciting changes happening around AI technology within the eDiscovery space.To discuss this topic more, feel free to connect with me at smoran@lighthouseglobal.com.‍[1] “Client-Lawyer Relationship: A lawyer shall provide competent representation to a client. Competent representation requires the legal knowledge, skill, thoroughness and preparation reasonably necessary for the representation.” ABA Model Rules of Professional Conduct, Rule 1.1.[2] See Comment 8, Model Rules of Professional Conduct Rule 1.1 (Competence)[3] Reinsel, David; Gantz, John; Rydning, John. “The Digitization of the World From Edge to Core.” November 2018. Retrieved from https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf. An IDC White Paper, Sponsored by SEAGATE.ai-and-analyticsanalytics, ai-big-data, ediscovery-process, red-flag-reporting, departing-onboarding-employee, prism, blog, focus-discovery, ai-and-analytics,analytics; ai-big-data; ediscovery-process; red-flag-reporting; departing-onboarding-employee; prism; blog; focus-discoverysarah moran

Below is a copy of a featured blog written by Debora Motyka Jones for CLOC's Legal Operations Blog.One of the most common complaints I hear from General Counsels and Chief Legal Officers is that they are not able to sit at a table full of their executive peers and provide metrics on how legal is impacting the core business. Sure, they are able to show their own department’s spending, tasks, and resource allocation. But wouldn’t it be nice to tell the business when revenue will hit? Or insights about what organizational behaviors are leading to inefficiency and, if changed, will impact spending. More specifically, as the legal operations team member responsible for metrics, wouldn’t it be great to share these key insights with your GC as well as your finance, sales, IT, and other department counterparts? Good news! Legal has this type of information, it is just a matter of identifying and mining it!Keeping metrics has become table stakes in today’s legal department and it often falls on the shoulders of legal operations to track and share those metrics. In fact, CLOC highlights business intelligence as a core competency for the legal operations function. Identifying metrics, cleansing those metrics, and putting them forth can be quite a lift, but once you have the right metrics in place, you are able to make data-driven decisions about how to staff your team, what external resources you need, and drive efficiencies. If you are still at the early stages of figuring out which metrics you should track for your department, there are many good resources out there including a checklist of potential metrics by Thompson Reuters, and a blog by CLOC on where to start. HBR also conducts a survey so you can see what other departments are seeing – this can be helpful for setting targets and/or seeing how you compare. When you analyze these and other resources, you will notice that many of the metrics are legal department centric. Though they are helpful for the department, they are not very meaningful when they are sitting around the table with executives doing strategic business planning for the business as a whole. So what types of metrics can legal provide in those settings and how do you capture them? There are many ways to go about this, but I have highlighted a few that can provide a robust discussion at the executive table.Leading Indicators of RevenueMost companies are reviewing the top line with some frequency and in many industries it is a challenge to predict the timing of that revenue. Given its position at the end of the sales cycle, in the contracting phase, legal has excellent access to information about revenue and the timing thereof. Here are the most common statistics your legal department can provide in that area:New Customer Acquisition: Number of Customer Contracts Signed this Month – Signing up paying customers is a direct tie to revenue and the legal department holds the keys to one of the last steps pre-revenue: contract signing. By identifying the type of contract that leads to revenue, the legal department is able to share with the business how many new customers are coming online. The metric is typically a raw number and can be compared against the number of contracts in a prior period. If not all customers who sign this contract lead to revenue, you will want to report (or at least know) the ratio of contracts to paying customers in order to give an accurate picture. Once you have been tracking this metric, you may want to take it a step further and identify and contracts that come earlier in the process. For example, in some companies, prospective clients sign NDAs earlier in the sales cycle. By reporting on the number of NDAs signed, you will start to see a ratio of the number of NDA to the number of MSAs and can give even earlier visibility into the customer acquisition pipeline.Expected New Customers: Contracts in Negotiation and Contract Negotiation Length – If your company has negotiated contracts then reporting on the number of contracts in negotiation can also help with revenue planning. Knowing the typical length of that negotiation will give an indication as to the timing of that revenue.Expected Revenue: Timing – The final piece of the revenue puzzle is when the above revenue will hit. You can work with the finance team to get the typical time between contract signing and revenue. This will often vary by contract size so layering in the contract size is helpful. If contract size if not available in the contract itself, that is likely information that sales keep so they can report that metrics if legal cannot.The two departments most interested in all three the above metrics are likely to be sales and finance but depending on the detail reported at the executive level, these may be executive-level metrics. If the above seems like a lot, know that many contract management tools and/or contract artificial intelligence tools can mine your contracts for the above information.Efficiency in Business OperationsLegal operations also has a unique ability to look back and reflect on the efficiency in some areas of business operations. More specifically, in the course of litigation and investigations, cross sections of the business are examined with hindsight and as we all know, hindsight is 20/20. Providing that look back information to the business can help in overall business efficiency. In addition, legal has access to payment clauses, in contracts, that can ensure efficiency in cash management. Here are some helpful statistics your legal department can provide on the state of legal operations.Early Payment Discount Usage: Number of Contracts with Early Payment and Percentage of Early Payment Discounts Used – When signing vendor contracts, there are often provisions allowing for discounts if certain terms – e.g. payment within a short timeframe, are met. Although this may be fresh on everyone’s mind at the time of negotiation, this often gets lost over time. Using current technologies, the legal operations team can identify these contracts and provide the number of contracts in which such provisions exist. You can then work with finance to determine how many of these provisions are being leveraged – e.g. is the business actually paying early and taking the percentage reduction. The savings for the business can be material by just providing visibility into this area.Data Storage: How Much Data to Keep – A common IT pain point is storage management and having to add servers in order to keep up with the business needs. With cloud technologies, IT often knows how much space they have allocated to each user’s mail or individual drives but what is unknown is how much data users are keeping on their machines or in collaborations tools and shared drives. With data collections for litigation or regulatory matters, the legal team has access to this information. This information can help IT understand its storage needs and put in place technologies to minimize storage per person thereby saving on storage costs.Business Intelligence from Active Matters – This one isn’t a specific metric. Instead, this is more focused on the business intelligence that comes out of the legal department’s unique position as a reviewer of sets of documents. In litigation or investigations, the legal department has access to a cross section of data that the business doesn’t pull together in the regular course of business. Technology is now advanced enough to be able to provide business insights from this data that can be shared with the business as a whole.Example #1: Artificial intelligence can be used to create compliance models that show correlations between expense reports, trade journals, and sales behavior to identify bad behaviors. Sharing these types of learnings from matters can open up discussions among executives as to which learnings deserve a deeper dive. As an aside, you could also imagine a scenario where this same logic can also be used inversely – when combined with revenue it could identify effective sales behaviors – although this is something that would be a bigger lift and I would expect the sales department to drive this type of work.Example #2: The amount of duplicative data is a common metric reported in litigations or investigations. Sharing this with your IT team can highlight an easy storage win and legal can help craft a plan of how to attack duplicative data thereby leading to lower storage costsI would be remiss if I didn’t mention that there are opportunities for the legal department in these metrics as well. By using these metrics, as well as the artificial intelligence mentioned above, legal operations can resource plan and drive savings within the legal department. For example, the number of NDAs and sales contracts can inform staffing. Technology can identify contracts or other documents that are repetitive and automate the handling of those documents. Within litigation and investigations, technology can identify objectively non-responsive data so that it does not need to be collected as well as identify sources that are lower risk which don’t require outside counsel review and previously collected data that can be re-used.I hope that with the above metrics, you’re able to participate in some great business discussions and show how your legal department is not only effective in its own right but how integral a unit it is to driving the core business.ai-and-analytics; legal-operationsreporting, legal-ops, blog, ai-and-analytics, legal-operationsreporting; legal-ops; bloglighthouse

Evolving analytics tools and methods can help expedite review.Analyze this! No, we’re not talking about the 1999 movie starring Robert DeNiro and Billy Crystal, but rather analytics mechanisms that many organizations are using today to streamline discovery. As these mechanisms become more sophisticated, it pays to keep abreast of the ways in which they can impact a review, including how data can be organized, visualized, identified and reduced.For example, conceptual clustering can identify groups of topics that might be clearly responsive or non-responsive. Communication visualization maps can identify communication patterns of key parties within a data collection And, of course, predictive coding can train a supervised machine learning algorithm to identify potentially responsive and non-responsive documents based on classifications of other documents.But there are other use cases for eDiscovery analytics many organizations aren’t taking advantage of that make eDiscovery workflows even more efficient and more cost effective. To improve the efficiency of eDiscovery workflows, organizations can now implement technology with the following analytics features.Email Threading and Near Duplicate IdentificationYou may have heard the famous phrase “Insanity is doing the same thing over and over again expecting a different result.” But, in document review, insanity is simply doing the same thing over and over again. De-duplication using hash values identifies documents that are exact duplicates in content and format, but there is considerable additional content within document collections that is also duplicated within documents that aren’t exact matches. Email conversation threads contain considerable duplicative information, but conversations between multiple people can branch off, so you can’t just assume that the last message for the thread contains the entire thread discussion.Documents converted to PDF may be identical in content but not format, so they have different hash values and are not “de-duped.” ESI collections often include multiple drafts of documents that have both duplicative and unique content. To avoid over-capture of duplicates and gain visibility into email branches, organizations can now employ advanced analytics that can help in the following ways:Utilize advanced algorithms to identify email thread relationships and individual emails in a thread with unique contentGroup similar documents with flexible near-duplicate identification to easily review and compare to determine whether the differences are significantIdentify exact content duplicates with only formatting differences that hash de-duplication would not catch.Name Normalization and Entity AnalysisWhat’s in a name? Potentially, a whole lot of options! If the sixth US president were alive today and sending emails, here are some ways that you might see him represented within the collection:John AdamsJohnny AdamsJohn Q. AdamsQ. AdamsQuincy AdamsAdams, JohnAdams, John Q.Adams, J.Q.Adams, J. Quincyjadams@xyzcorp.com/O=XYZCORP/OU=EXCHANGE ADMINISTRATIVE GROUP (FYDIBOHF23SPDLT)/CN=RECIPIENTS/CN=jadamsAdams@gmail.comAnd potentially more…That’s a lot of variation – just for one person! Case teams often waste significant time and energy sorting through the numerous variations of names and email addresses for individuals in a matter. Advanced analytics solutions can be used to automated name normalization algorithms to link different name variations and email addresses to a single individual, format those names uniformly and aggregate the normalized participants that appear across an entire email thread group. The result? Refined results that streamline processes such as privilege logging without the intensive manual cleanup typically associated with the process.Metadata AnalyticsAI-driven analytics applied to the metadata can streamline eDiscovery by:a) identifying mass email communications so that reviewers can focus on more likely responsive emails;b) filtering email signature images and other extraneous embedded objects; andc) remediating data populations with missing or incomplete metadata by auto-detecting and populating email metadata fields on inbound productions.Privilege AnalyticsAutomated categorization and classification powered by advanced analytics can also be applied to privilege review to weed out non-responsive and non-privileged material early and rapidly identify, elevate and prioritize potentially privileged information. Customizable rules to exclude disclaimers and boilerplate language can also improve the accuracy of that identification process by eliminating many false positives.As most privilege determinations involve considerations of nuance and context, human judgments are a necessary part of the process. Pre-built and customized linguistic models, name normalization and email thread identification can extend those automated privilege determinations more quickly through the collection, with automated identification of legal concepts, privilege actors and law firms and a reusable asset with consistent propagation of privilege designations across matters.And clean name normalization outputs, along with automated and customizable privilege reasons assigned to each document expedite privilege log creation, significantly decreasing the manual cleanup often associated with this time-consuming task.Personal Identifiable Information (PII) DetectionFinally, with all of the data privacy requirements associated with recent regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), identifying and protecting PII has become a requirement within every phase of the eDiscovery lifecycle. Using analytics and pattern matching through regular expressions (RegEx) to identify common format numbers such as passport IDs, social security numbers, drivers license numbers and credit card numbers, as well as identification of common form types that often contain PII (such as loan applications or IRS forms) will help flag those documents so that they can be adequately protected throughout the process.Newer, more advanced AI-driven analytics solutions go a step further by utilizing highly precise classifiers to model the way in which different forms of supported personal data appear in data populations. These automated solutions provide rapid identification of likely and potential PII, resulting in rapid insights and immediate access to the most relevant documents first.ConclusionYou may be using analytics to streamline parts of your eDiscovery process, but there are always new use cases being identified to leverage analytics to make your eDiscovery workflows more efficient. Even Analyze This had a sequel!For more information on ways H5 Matter Analytics® can assist your organization in creating efficiencies and expediting eDiscovery workflows, click here.ediscovery-reviewblog, -ediscovery, data-analytics, document-review, ediscovery-review, aiandanalyticsblog; ediscovery; data-analytics; document-reviewlighthouse

Artificial intelligence (AI) has proliferated across industries, in popular culture, and in the legal space. But what does AI really mean? One way to look at it is in reference to technology that lets lawyers and organizations efficiently manage massive quantities of data that no one’s been able to analyze and understand before.While AI tools are no longer brand new, they’re still evolving, and so is the industry’s comfort and trust in them. To look deeper into the technology available and how lawyers can use it Lighthouse hosted a panel featuring experts Mark Noel, Director of Advanced Client Data Solutions at Hogan Lovells, Sam Sessler, Assistant Director of Global eDiscovery Services at Norton Rose Fulbright, Bradley Johnston, Senior Counsel eDiscovery at Cardinal Health, and Paige Hunt, Lighthouse’s VP of Global Discovery Solutions.Some of the key themes and ideas that emerged from the discussion include:Defining AIMeeting client expectationsUnderstanding attorneys’ duty of competenceIdentifying critical factors in choosing an AI toolAssessing AI’s impact on process and strategyThe future of AI in the legal industryDefining AIThe term “AI” can be misleading. It’s important to recognize that, right now, it’s an umbrella term encompassing many different techniques. The most common form of AI in the legal space is machine learning, and the earliest tools were document review technologies in the eDiscovery space. Other forms of AI include deep learning, continuous active learning (CAL), neural networks, and natural language processing (NLP).While eDiscovery was a proving ground for these solutions, the legal industry now sees more prebuilt and portable algorithms used in a wide range of use cases, including data privacy, cyber security, and internal investigations.Clients’ Expectations and Lawyers’ DutiesThe broad adoption of AI technologies has been slow, which comes as no surprise to the legal industry. Lawyers tend to be wary of change, particularly when it comes at the hands of techniques that can be difficult to understand. But our panel of experts agreed that barriers to entry were less of an issue at this point, and now many lawyers and clients expect to use AI.Lawyers and clients have widely adopted AI techniques in eDiscovery and other privacy and security matters. However, the emphasis from clients is less about the technology and more about efficiency. They want their law firms and vendors to provide as much value as possible for their budgets.Another client expectation is reducing risk to the greatest extent possible. For example, many AI technologies offer the consistency and accuracy needed to reduce the risk of inadvertent disclosures.Mingled with client expectations is a lawyer’s duty to be familiar with technology from a competency standpoint. We aren’t to the point in the legal industry where lawyers violate their duty of competence if they don’t use AI tools. However, the technology may mature to the point where it becomes an ethical issue for lawyers not to use AI.Choosing the Right AI ToolDecide Based on the Search TaskThere’s always the question of which AI technology to deploy and when. While less experienced lawyers might assume the right tool depends on the practice area, the panelists all focused on the search task. Many of the same search tasks occur across practice areas and enterprises.Lawyers should choose an AI technology that will give them the information they need. For example, Technology-assisted review (TAR) is well-suited to classifying documents, whereas clustering is helpful for exploration.Focus More on FeaturesTeams should consider the various options’ features and insights when purchasing AI for eDiscovery. They also must consider the training protocol, process, and workflow. At the end of the day, the results must be repeatable and defensible. Several solutions may be suitable as long as the team can apply a scientific approach to the process and perform early data assessment. Additional factors include connectivity with the organization’s other technology and cost.The process and results matter most. Lawyers are better off looking at the system as a whole and its features in deciding which AI tech to deploy instead of focusing on the algorithm itself.Although not strictly necessary, it can be helpful to choose a solution the team can apply to multiple problems and tasks. Some tools are more flexible than others, so reuse is something to consider.Some Use Cases Allow for ExperimentationThere’s also the choice between a well-established solution versus a lesser-known technology. Again, defensibility may push a team toward a well-known and respected tool. However, teams can take calculated risks with newer technologies when dealing with exploratory and internal tasks.A Custom Solution Isn’t NecessaryThe participants noted the rise in premade, portable AI solutions more than once. Rarely will it benefit a team to create a custom AI solution from scratch. There’s no need to reinvent the wheel. Instead, lawyers should always try an off-the-shelve system first, even if it requires fine-tuning or adjustments.AI’s Impact on ProcessThe process and workflow are critical no matter which solution a team chooses. Whether for eDiscovery, an internal investigation, or a cyber security incident, lawyers need accurate and defensible results.Some AI tools allow teams to track and document the process better than others. However, whatever the tool’s features, the lawyers must prioritize documentation. It’s up to them to thoughtfully train the chosen system, create a defensible workflow, and log their progress.As the adage goes: garbage in, garbage out. The effort and information the team inputs into the AI tool will influence the validity of the results. The tool itself may slightly influence the team’s approach. However, any approach should flow from a scientific process and evidence-based decisions.AI’s Influence on StrategyThere’s a lot of potential for AI to help organizations more strategically manage their documents, data, and approach to cases. Consider privileged communications and redactions. AI tools enable organizations to review and classify documents as their employees create them—long before litigation or another matter. Classification coding can travel with the document, from one legal matter to another and even across vendors, saving organizations time and money.Consistency is relevant, too. Organizations can use AI tools to improve the accuracy and uniformity of identifying, classifying, and redacting information. A well-trained AI tool can offer better results than people who may be inconsistently trained, biased, or distracted.Another factor is reusing AI technology for multiple search tasks. Depending on the tool, an organization can use it repeatedly. Or it can use the results from one project to the next. That may look like knowing which documents are privileged ahead of time or an ongoing redaction log. It can also look like using a set of documents to better train the algorithm for the next task.The Future of AIThe panelists wrapped the webinar by discussing what they expect for the future of AI in the legal space. They agreed that being able to reuse work products and the concept of data lakes will become even greater focuses. Reuse can significantly impact tasks that have traditionally had a huge cost burden, such as privilege reviews and logs, sensitive data identification, and data breach and cyber incidents.Another likelihood is AI technology expanding to more use cases. While lawyers tend to use these tools for similar search tasks, the technology itself has potential for many other legal matters, both adversarial and transactional. To hear more of what the experts had to say, watch the webinar, “Deploying Modern Analytics for Today’s Critical Data Challenges.” ai-and-analytics; ediscovery-review; lighting-the-path-to-better-ediscoveryai-big-data, blog, data-reuse, project-management, ai-and-analytics, ediscovery-reviewai-big-data; blog; data-reuse; project-managementai-analyticslighthouse

Much of the workforce has been forced into remote work due to social distancing requirements because of the pandemic, and that includes the workforce conducting services related to electronic discovery. Many providers have been forced into remote work for services including collection and review. Other providers have been already conducting those services remotely for years, so they were well prepared to continue to provide those services remotely during the pandemic.Make no mistake, it’s important to select a review provider that has considerable experience conducting remote reviews which extends well before the pandemic. Not all providers have that level of experience. But the success of your reviews isn’t about location, location, location; it’s about process, process, process — and the ability to manage the review effectively regardless of where it’s conducted. Here are four best practices to make your document reviews more efficient and cost effective, regardless of where they’re conducted:Maximize culling and filtering techniques up front: Successful reviews begin with identifying the documents that shouldn’t be reviewed in the first place and removing them from the document collection before starting review. Techniques for culling the document collection include de-duplication and de-nisting and identification of irrelevant domains. But it’s also important to craft a search that maximizes the balance between recall and precision to exclude thousands of additional documents that might otherwise be needlessly reviewed, saving time and money during document review.Combine subject matter and best practice expertise: Counsel understands the issues associated with the case, but they often don’t understand how to implement sophisticated discovery workflows that incorporate the latest technological approaches (such as linguistic search) to maximize efficiency. It’s important to select the provider that knows the right questions to ask to combine subject matter expertise with eDiscovery best practices to ensure an efficient and cost-effective review process. It’s also important to continue to communicate and adjust workflows during the case as you learn more about the document collection and how it relates to the issues of the case.Conduct search and review iteratively: Many people think of eDiscovery document review as a linear process, but the most effective reviews today are those that implement an iterative process that that interweave search and review to continue to refine the review corpus. The use of AI algorithms and expert-designed linguistic models to test, measure and refine searches is important to achieve a high accuracy rate during review, so remember the mantra of “test, measure, refine, repeat” for search and review to maximize the quality of your search and review process.Consider producing iteratively, as well: Discovery is a deadline driven process, but that doesn’t mean you have to wait for the deadline to provide your entire production to opposing counsel. Rolling productions are common today to enable producing parties to meet their discovery obligations over time, establishing goodwill with opposing counsel and demonstrating to the court that you have been meeting your obligations in good faith along the way if disputes occur. Include discussion of rolling productions in your Rule 26(f) meet and confer with opposing counsel to enable you to manage the production more effectively over the life of the project.You’re probably familiar with the famous quote from The Art of War by Sun Tzu that “every battle is won or lost before it is ever fought,” which emphasizes the importance of preparation before proceeding with the task or process you plan to perform. Regardless where your review is being conducted, it’s not the location, location, location that will determine the success of your review, but the process, process, process. After all, it’s called “managed review” for a reason!ediscovery-reviewblog, -document-review, ediscovery-review,blog; document-reviewlighthouse

What is data reuse? There are many different flavors and not everyone thinks about it the same way. In the context of eDiscovery, subject-matter specific work product in the form of responsiveness or issue coding often comes to mind and is then immediately dismissed as untenable given that the definitions for these can change from matter to matter. This is just one tiny piece of what’s possible, however. We need to consider the entire EDRM from end to end. What else has already been done, and what can be gained from it?First, there’s the source data itself. The underlying electronically stored information (ESI) is foundational to the reuse of data as a whole. Many corporations deal with frequent litigation and investigations, and those matters often include the same or at least overlapping players, i.e. the “frequent flier” custodians. This means the same data is relevant to multiple matters, which means it can be reused. There’s the potential for a one-to-many relationship here. In other words, instead of starting from scratch with each new project by going back to the same sources to collect the same data, why not take stock of what has been collected already? Compare the previously collected inventory to what is required for each specific matter, and then return to the well for the difference as needed. It may be as simple as a “refresh” to capture a more recent date range, or, even better, there’s no new collection to be done at all.Next up is the processed data. Once it’s collected, a lot of time, effort, and money are spent transforming ESI into a more consumable format. Extracting and indexing the metadata such that it can easily be searched and reviewed in your platform of choice takes real effort. Considering the lift, utilizing data that has already undergone processing makes a lot of sense. Depending on volume, significant savings in terms of timeline and fees are often realized, and this is not a one-time thing. The same data often comes up over and over across multiple matters, compounding savings over time.Finally, after processing comes review, which is where reusing existing work product comes in. This isn’t limited to relevance calls, which may or may not consistently apply across matters. There’s limited application for the reuse of subject-matter specific work product as mentioned earlier. The real treasure trove is all the different types of static work product – the ones that remain the same across matters regardless of the relevance criteria – and there are so many! One valuable step that is often overlooked is the ability to dismiss portions of the data population upfront. Often there is some chunk of data that will simply never be of interest. These are the “junk” or “objectively non-relevant” files that can clog a review. For example, automatic notifications, spam advertisements, and other mass mailings can contribute a lot of volume and rarely have any chance of including relevant content. Also, think about redactions and what often drives them: PII, PHI, trade secret, IP, etc. These are a pain to deal with, so why force the need to do so repeatedly? And, what about privilege? Identifying it is one thing, and then there are the incredibly time intensive privilege log entries that follow. These don’t change, and the cost to handle them can be steep. On top of that, they are incredibly sensitive, so ensuring accuracy and consistency is key. That’s pretty difficult to accomplish from matter to matter if you rely on different reviewers starting over each time.At the end of the day, no one wants to waste time and effort on unnecessary tasks, especially considering how often intense deadlines loom right out of the gate. The key is understanding what has already been done that overlaps with the matter at hand and leveraging it accordingly. In other words, know what you have and use it to avoid performing the same task twice wherever possible.ai-and-analytics; ediscovery-reviewediscovery-process, data-re-use, blog, ai-and-analytics, ediscovery-reviewediscovery-process; data-re-use; bloglighthouse

As summarized in the first installment of our two-part blog series, President Biden recently issued a sweeping Executive Order aimed at improving the nation’s cybersecurity defense. The Order is a reaction to increased cybersecurity attacks that have severely impacted both the public and private sectors. These recent attacks have evolved to a point that industry solutions have a much more difficult time detecting encryption and file state changes in a reasonable timeframe to prevent an actual compromise. The consequence is that new and evolving ransomware and malware attacks are now getting past even the biggest solution providers and leading scanners in the industry.Thus, while on its face, many of the new requirements within the Order are aimed at federal agencies and government subcontractors, the ultimate goal appears to be to create a more unified national cybersecurity defense across all sectors. In this installment of our blog series, I will outline recommended steps for private sector organizations to prepare for compliance with the Order, as well as general best-practice tips for adopting a more preemptive approach to cybersecurity. 1. Conduct a Third-Party AssessmentFirst and foremost, organizations must understand their current cybersecurity posture. Given the severity and volume of recent cyberattacks, third-party in-depth or red-team assessments should be done that would include not only the organization’s IT assets, but also include solutions providers, vendors, and suppliers. Red teaming is the process of providing a fact-driven adversary perspective as an input to solving or addressing a problem. In the cybersecurity space, it has become a best practice wherein the cyber resilience of an organization is challenged by an adversary or a threat actor’s perspective.[1] Red-team testing is very useful to test organizational policies, procedures, and reactions against defined, intended standards.A third-party assessment must include a comprehensive remote network scan and a comprehensive internal scan with internal access provided or gained with the intent to detect and expose potential vulnerabilities, exploits, and attack vectors for red-team testing. Internal comprehensive discovery includes scanning and running tools with the intent to detect deeper levels of vulnerabilities and areas of compromise. Physical intrusion tests during red-team testing should be conducted on the facility, networks, and systems to test readiness, defined policies, and procedures.The assessment will evaluate the ability to preserve the confidentiality, integrity, and availability of the information maintained and used by the organization and will test the use of security controls and procedures used to secure sensitive data.2. Integrate Solution Providers and IT Service Companies into Plans to Address Above Executive Order StepsTo accurately assess your organization’s risk, you first have to know who your vendors, partners, and suppliers are with whom you share critical data. Many organizations rely on a complex and interconnected supply chain to provide solutions or share data. As noted above, this is exactly why the Order will eventually broadly impact the private sector. While on its face, the Order only seems to impact federal government and subcontractor entities, those entities’ data infrastructures (like most today) are interconnected environments composed of many different organizations with complex layers of outsourcing partners, diverse distribution routes, and various technologies to provide products and services – all of whom will have to live up to the Order’s cybersecurity standards. In short, the federal government is recognizing that its vendors, partners, and suppliers’ cybersecurity vulnerabilities are also its own. The sooner all organizations realize this the better. According to recent NIST guidance, “Managing cyber supply chain risk requires ensuring the integrity, security, quality, and resilience of the supply chain and its products and services.” NIST recommends focusing on foundational practices, enterprise-wide practices, risk management processes, and critical systems. “Cost-effective supply chain risk mitigation requires organizations to identify systems and components that are most vulnerable and will cause the largest organizational impact if compromised.[2]In the recent attacks, hackers inserted malicious code into Orion software, and around 18,000 SolarWinds customers, including government and corporate entities, installed the tainted update onto their systems. The compromised update has had a sweeping impact, the scale of which keeps growing as new information emerges. Locking down your networks, systems, and data is just the beginning! Inquiring how your supply chain implements a Zero Trust strategy and secures their environment as well as your shared data is vitally important. A cyber-weak or compromised company can lead to exfiltration of data, which a bad actor can exploit or use to compromise your organization.3. Develop Plan to Address Most Critical Vulnerabilities and Threats Right AwayThird-party assessors should deliver a comprehensive report of their findings that includes the descriptions of the vulnerabilities, risks found in the environment, and recommendations to properly secure the data center assets, which will help companies stay ahead of the Order’s mandates. The reports typically include specific data obtained from the network, any information regarding exploitation of exposures, and the attempts to gain access to sensitive data.A superior assessment report will contain documented and detailed findings as a result of performing the service and will convey the assessor’s opinion of how best to remedy vulnerabilities. These will be prioritized for immediate action, depending upon the level of risk. Risks are often prioritized as critical, high, medium, and low risk to the environment, and a plan can be developed based upon these prioritizations for remediation.4. Develop A Zero Trust StrategyAs outlined in Section 3 of the Order, a Zero Trust strategy is critical to addressing the above steps, and must include establishing policy, training the organization, and assigning accountability for updating the policy. Defined by the National Security Agency (NSA)’s “Guidance on the Zero Trust Security Model”: “The Zero Trust model eliminates trust in any one element, node, or service by assuming that a breach is inevitable or has already occurred. The data-centric security model constantly limits access while also looking for anomalous or malicious activity.”[3]Properly implemented Zero Trust is not a set of access controls to be “checked,” but rather an assessment and implementation of security solutions that provide proper network and hardware segmentation as well as platform micro-segmentation and are implemented at all layers of the OSI (Open Systems Interconnection) model. A good position to take is that Zero Trust should be implemented using a design where all of the solutions assume they exist in a hostile environment. The solutions operate as if other layers in a company’s protections have been compromised. This allows isolation of the different layers to improve protection by combining the Zero Trust principles throughout the environment from perimeters to VPNs, remote access to Web Servers, and applications. For a true Zero Trust enabled environment, focus on cybersecurity solution providers that qualify as “Advanced” in the NSA’s Zero Trust Maturity Model; as defined in NSA’s Cybersecurity Paper, “Embracing a Zero Trust Security Model.”[4] This means that these solution providers will be able to deploy advanced protections and controls with robust analytics and orchestration.5. Evaluate Solutions that Pre-emptively Protect Through Defense-In-DepthIn order to further modernize your organization’s cybersecurity protection, consider full integration and/or replacement of some existing cybersecurity systems with ones that understand the complete end-to-end threats across the network. How can an organization implement confidentiality and integrity for breach prevention? Leverage automated, preemptive cybersecurity solutions, as they possess the greatest potential in thwarting attacks and rapidly identifying any security breaches to reduce time and cost. Use a Defense-in-Depth blueprint for cybersecurity to establish outer and inner perimeters, enable a Zero Trust environment, establish proper security boundaries, provide confidentiality for proper access into the data center, and support capabilities that prevent data exfiltration inside sensitive networks. Implement a solution to continuously scan and detect ransomware, malware, and unauthorized encryption that does NOT rely on API calls, file extensions, or signatures for data integrity.Solutions must have built-in protections leveraging multiple automated defense techniques, deep zero-day intelligence, revolutionary honeypot sensors, and revolutionary state technologies working together to preemptively protect the environment. ConclusionAs noted above, Cyemptive recommends the above steps in order to take a preemptive, holistic approach to cybersecurity defense. Cyemptive recommends initiating the above process as soon as possible – not only to comply with potential government mandates brought about due to President Biden’s Executive Order, but also to ensure that organizations are better prepared for the increased cybersecurity threat activity we are seeing throughout the private sector. ‍[1]“Red Teaming for Cybersecurity”. ISACA Journal. October 18, 2018. https://www.isaca.org/resources/isaca-journal/issues/2018/volume-5/red-teaming-for-cybersecurity#1 [2] “NIST Cybersecurity & Privacy Program” May 2021. Cyber Supply Chain Risk Management C-SCRM” https://csrc.nist.gov/CSRC/media/Projects/cyber-supply-chain-risk-management/documents/C-SCRM_Fact_Sheet_Draft_May_10.pdf [3] “NSA Issues Guidance on Zero Trust Security Model”. NSA. February 25, 2021. https://www.nsa.gov/Press-Room/News-Highlights/Article/Article/2515176/nsa-issues-guidance-on-zero-trust-security-model/[4] “Embracing a Zero Trust Security Model.” NSA Cybersecurity Information. February 2021. https://media.defense.gov/2021/Feb/25/2002588479/-1/-1/0/CSI_EMBRACING_ZT_SECURITY_MODEL_UOO115131-21.PDFdata-privacy; information-governancecloud, cybersecurity, blog, corporate, data-privacy, information-governancecloud; cybersecurity; blog; corporatelighthouse

Now more than ever, data security has become priority number one, especially in the context of litigation and eDiscovery. And as the worlds of eDiscovery, information governance, and cybersecurity continue to rapidly converge, cybersecurity incidents are alarmingly on the rise, showcasing all of the weaknesses in an organization’s information governance system. Addressing cybersecurity continues to be a top challenge in eDiscovery. Many are unsure if their own internal processes are safe, not to mention those of the vendors who manage their outsourced eDiscovery.So, how can you protect your ESI all the way from preservation and collection to review and production? In a Law and Candor podcast episode, special guest David Kessler, Head of Data and Information Risk at Norton Rose Fulbright US LLP, discussed with our hosts the diverse set of challenges that arise with data security at each stage of the EDRM. Most understand the right methods start with implementing the fundamentals of cybersecurity, but some have learned the hard way that you can’t fix a house built on a shaky foundation after a cybersecurity disaster strikes. With the protection of client ESI first and foremost top of mind, here are the some of the most pressing cybersecurity challenges in eDiscovery as well as actionable solutions.Cybersecurity Challenges in eDiscoveryThe intersection of information governance, eDiscovery, and data security: The nature of data has evolved such that eDiscovery and information governance naturally intersect with data privacy and security. We’ve learned that issues around data access are very similar to eDiscovery issues and the next challenge is learning how to operate the areas together cohesively. In addition, with the shift to scrutiny on privacy and what can be done with personal data, now we know almost all cases that involve ESI have tremendous privacy concerns.The important role eDiscovery plays in cybersecurity: No longer are the days where confidential data relevant to litigation is primarily found in email and simply on computers. Now, data is created and stored across a wide variety of mediums and the amount of data continues to grow at an exponential rate. For cybersecurity criminals, this is a gold mine of confidential data available to steal and access.The outstanding security gaps throughout the EDRM: Historically, we’ve been focused on the responding parties’ obligations to securely undertake discovery. The business process of eDiscovery is primarily about collecting, copying, and transferring data outside of an organization, which creates concerns about securing that information at every stage of the process. Both the responding and requesting parties need to find a way to collaboratively and cooperatively work together at the beginning of a case to ensure data is protected through the entire EDRM lifecycle.The weakest part of the cybersecurity chain is when you hand over sensitive data: How do we help clients make sure their data isn’t accidentally or intentionally taken from them during the eDiscovery process? Everyone from eDiscovery vendors to law firms has an obligation to shore up their security and organizations have a responsibility to thoroughly vet those partners as they hand over their most sensitive data. In the EDRM, attention has shifted to making sure cybersecurity protections span the entire EDRM and the last step that hasn’t received much attention is making sure the requesting party is taking the appropriate steps to secure the data once they receive it.Cybersecurity Solutions in eDiscoveryShore up cybersecurity contracts and repurpose existing security riders: When an organization engages law firms and eDiscovery vendors to handle discovery, it’s important they work closely with their data security IT team. These teams can help to repurpose some of the standard security riders from other contracts and use it to create new contracts with the appropriate protections in place.Establish comprehensive protective orders at the beginning of cases: With respect to the requesting party, who you will ultimately be producing the data to, ensure that early in the case you’ve negotiated a comprehensive protective order that includes reasonable and proportionate requirements for the protection of data. In that protection order (and a step that’s often forgotten), follow up and confirm the data you produced has been deleted after a case is over.Keep open lines of communication with law firms and eDiscovery vendors: Your discovery partners understand and have a significant stake in their security reputations. They have a strong motivation to work with you to execute risk assessments and other agreements that contain the necessary security provisions to ensure your data is safe at every step of the process. Also, include a breach notification order if data is accidentally lost or there’s an attack.Focus on things you can do to strengthen your productions: Think about the most efficient ways to reduce the number of copies involved in productions where appropriate. For example, use redaction as much as possible and consequently less copies of data. Don’t produce sensitive and irrelevant portions of data – redact it instead.Ultimately, most people have become acutely aware of the vulnerabilities that exist in data security as it travels through the EDRM, and as law firms and eDiscovery vendors become accustomed to deeper vetting, it’s at the production stage where the biggest security vulnerabilities seem to remain. To get ahead of all aspects of potential cybersecurity failures, the use of well-written protective orders will get you a long way. Requirements in protective orders can ensure all parties take reasonable steps to protect data from third-party hackers and unauthorized access, as well as include protections based on encryption, access controls, passwords, etc.data-privacy; information-governance; ediscovery-reviewcybersecurity, cloud-security, ediscovery-process, preservation-and-collection, blog, data-privacy, information-governance, ediscovery-review,cybersecurity; cloud-security; ediscovery-process; preservation-and-collection; bloglighthouse

When it comes to storing organizational data in the Cloud, a few phrases come to mind: the train has left the station; the ship has sailed; the horse is out of the barn, etc. No matter how you phrase it, the meaning is the same – the world is moving to the Cloud, with or without you. It is no longer an oncoming revolution. The revolution is here and your organization needs to prepare for dealing with data in the Cloud, if it hasn’t already. With that in mind, let’s talk cloud logistics – namely, security and cost.First up to the Plate – Cloud Security You might have heard the analogy circulating in technology forums recently that storing your data within the Cloud is akin to storing data on someone else’s hard drive. Unfortunately, from a security perspective, that’s not quite an accurate analogy (although life would be much easier if it were true).Don’t get me wrong - a significant benefit of moving to the Cloud is that it allows an organization to transfer much of the day-to-day security management to a technology company with the resources and expertise to handle that risk. Thus, if you are moving to a private cloud (i.e., renting data center space for your equipment), you can ease security concerns by ensuring that the hosting company maintains widely recognized security attestations/certifications and has a demonstrated commitment to data center security in accordance with strict vendor management risk processes. And of course, there’s always the reassurance when moving to a public cloud (Microsoft’s Azure or Amazon’s AWS) that you’re entrusting your data to companies with seemingly infinite security resources and expertise. That all certainly helps me sleep better at night.However, working within the Cloud still poses unique internal security challenges that will only amplify any of your existing security weaknesses if you’re not prepared for them. To put it another way: ISO certifications from cloud service providers cannot protect you from yourself. Risk, governance, and compliance teams will need to identify, plan for and adapt to internal security challenges. To do so, be sure to have a change management and review approval process in place (ideally before moving to the Cloud, but if not, as soon as possible once you’ve migrated). Also, ensure that your company has someone on hand (either through a vendor or within your IT staff) with the expertise needed to manage your internal cloud security who can stay abreast of all updates and changes.Next up – CostTo plan for a cloud migration, all stakeholders (including Legal Operations, Finance, DevOps, Security, and IT) should have a seat at the table and a plan in place for scaling up in the Cloud. Each team should understand the plan and process, as well as the role their team plays in controlling cost and risk for the company.Cloud Security and Costs Best PracticesTo plan for security risk in the Cloud, companies should ensure that:All cloud service providers are fully vetted, security certified, and have the requisite posture in place to fully protect your data.Company internal processes are evaluated for security risks and gaps. Have a change management and review approval process in place and ensure that you have the experts on hand to manage your cloud security practices and stay abreast of all updates and changes.To plan for costs, companies should ensure that:All stakeholders (including Legal Operations, Finance, DevOps, Security, and IT) collaborate and have a plan in place for scaling up within the Cloud when needed.Each team understands the plan and process, as well as the role their team plays in controlling cost and risk for the company.data-privacy; information-governancecloud-security, cloud-migration, blog, data-privacy, information-governancecloud-security; cloud-migration; blogmarcelino hoyla

On May 12, President Biden issued a landmark Executive Order (“the Order”) aimed at improving the country’s cybersecurity threat defense. This Order is an attempt to create a “whole of government” response to increasingly frequent cybersecurity incidents that have wreaked havoc in the United States in recent months, affecting everything from energy supplies to healthcare systems to IT infrastructure systems. In addition to becoming more frequent, recent cyberattacks have also become increasingly more sophisticated – and even somewhat professional. In response to these attacks, the Biden administration seeks to build a national security framework that aligns the Federal government with private sector businesses in order to “modernize our cyber defenses and enhance the nation’s ability to quickly and effectively respond to significant cybersecurity incidents.” Prior to this Order, there has been no unified system to report or respond to cybersecurity threats and breach incidents. Instead, there is currently a patchwork of state legislation and separate federal government agency protocols, all with differing reporting, notification, and response requirements.In the first of this two-part blog series, I will broadly outline the details of this Order and what it will mean for private sector companies in the coming years. In the second installment, Rob Pike (CEO and Founder of Cyemptive Technologies) will provide guidance on how to set up your organization for compliance with the Order, as well as general best-practice tips for adopting a preemptive cybersecurity approach. What is in President Biden’s Executive Order on Improving the Nation’s CybersecurityThere are nine main sections to the Order, which are summarized below.Section 1: PolicyThis section outlines the overall goal of the Order – namely that, with this Order, the Federal government is intent on making “bold changes and significant investments in order to defend the vital institutions that underpin the American way of life.” To do so, the Order states that the government must improve its efforts to “identify, deter, protect against, detect, and respond to” cybersecurity attacks. While this may sound like a purely governmental task, the Order specifically states that this defense will require partnership with the private sector. Section 2: Removing Barriers to Sharing Threat Information As noted above, prior to this Order, there was no unified system for sharing information regarding threats and data breaches. In fact, separate agency procurement contract terms may actually prevent private companies from sharing that type of information with federal agencies, including the FBI. This section of the Order responds to those challenges by requiring the government to update federal contract language with IT service providers (including cloud service providers) to require the collection and sharing of threat information with the appropriate government agencies. While the Order currently only speaks to federal subcontractors, it is expected that this information-sharing requirement will have a trickle-down effect across the private sector, with purely private companies falling in line to share threat information once federal subcontractors are required to do so. Section 3: Modernizing Federal Government CybersecurityThis section calls for the federal government to adopt security best practices – and is specifically aimed at adopting Zero Trust Architecture and pushing a move to secure cloud services, including “Software as a Service (SaaS), Infrastructure as a Service (IaaS), and Platform as a Service (PaaS).” It requires that each government agency update plans to prioritize the adoption and use of cloud technology and develop a plan to implement Zero Trust Architecture, in part by incorporating the migrations steps outlined by the National Institute of Standards and Technology (NIST).Section 4: Enhancing Software Supply Chain SecurityThis section deals with increasing the cybersecurity standards of software sold to the government. It specifically calls out the fact that the development of commercial software “often lacks transparency, sufficient focus on the ability of the software to resist attack, and adequate controls to prevent tampering by malicious actors.” It, therefore, calls for “more rigorous and predictable mechanisms for ensuring that products function securely.” Thus, this section calls for NIST to issue new security guidelines for software used by the government. These new guidelines will include encryption requirements, multi-factor and risk-based authentication requirements, vulnerability detection and disclosure programs, and trust relationship audits, among others.Section 5: Establishing a Cyber Safety Review BoardThis section establishes a federal Cyber Safety Review Board, which will convene following significant cyber incidents, providing recommendations to the Secretary of Homeland Security for improving cybersecurity and incident response practices. It will be made up of federal officials, as well as representatives from private sector entities.Section 6: Standardizing the Federal Government’s Playbook for Responding to Cybersecurity Vulnerabilities and IncidentsThis section again speaks to the patchwork of differing vulnerability and incident response procedures that currently exists across multiple federal agencies. The goal here is to create a standard set of operational procedures (or a playbook) for cybersecurity vulnerability and incident response activity. The playbook will have to incorporate all appropriate NIST standards, be used by all Federal Civilian Executive Branch (FCEB) Agencies, and spell out all phases of incident response.Sections 7 and 8: Improving Detection, Investigation, and Remediations of Cybersecurity Vulnerabilities and Incidents on Federal Government NetworksThese two sections focus on creating a unified approach to the detection, investigation, and remediation of cybersecurity vulnerabilities and incidents. Section 7 focuses on improving detection – mandating that all FCEB agencies deploy an “Endpoint Detection and Response (EDR)” initiative to support proactive detection of cybersecurity incidents and establishes a procedure for the implementation of threat hunting and detection, as well as inter-agency information sharing around threat detection. Section 8 is focused on improving the government’s investigative and remediation capabilities – namely, by establishing requirements for agencies and their IT service providers to collect, maintain, and share specified information from Federal Information System network logs.Section 9: National Security SystemsThis section requires the Secretary of Defense to adopt National Security System requirements that are at least equivalent to the requirements spelled out by the above sections in the Order.Who Will This Impact?As noted above, while the Executive Order is aimed at shoring up the federal government’s cybersecurity detection and response systems – its impacts will be felt throughout much of the private sector. That isn’t a bad thing! A patchwork cybersecurity system is clearly not the best way to respond to the increasingly sophisticated cybersecurity incidents currently threatening both the United States government and the private sector. Responding to these threats requires a robust, unified national cybersecurity system, which in turn requires updated and unified cybersecurity standards across both government agencies and private sector companies. This Executive Order is a great stepping stone towards that goal.As far as timing for private sector impacts: the first impacts will be felt by software companies and other organizations that directly contract with the federal government, as there are direct requirements and implications for those entities spelled out within the Order. Many of those requirements come into play within 60 days to a year after the date of the Order, so there may be a quick turnaround to comply with any new standards for those organizations. Impacts are then expected to trickle down to other private sector organizations: as government subcontractors update policies and systems to comply with the Order, they will in turn require the companies that they do business with to comply with the new cybersecurity standards. In this way, the Order actually creates an opportunity for the federal government to create a cybersecurity floor above which most companies in the US will eventually have to comply.ConclusionDetecting and defending against cybersecurity threats is an increasingly difficult worldwide challenge – a challenge to which, currently, no perfect defense exists. However, with this Order, the United States is taking a step in the right direction by creating a more unified cybersecurity standard and network that will encourage better detection, investigation, and mitigation.Check out the second installment of this blog series, where Rob Pike, CEO and Founder of Cyemptive Technologies, provides guidance on how to set up your organization for compliance with the Executive Order, as well as general best-practice tips for adopting a preemptive cybersecurity approach. If you would like to discuss this topic further, please reach out to me at erubenstein@lighthouseglobal.com.data-privacy; information-governancecloud, cybersecurity, blog, corporate, data-privacy, information-governancecloud; cybersecurity; blog; corporateerin rubenstein

There is much out there about cloud solutions and how they improve the lives of users, offer flexibility for expansion and contraction of business, and can lighten the lift for IT. There is even a lot of specific commentary about how cloud can help legal teams and enable change management for the department. But what about the day-to-day tasks? How does the cloud change the legal team’s work and what new governance and skills are necessary to handle that change? This blog will tackle these questions so you can be more prepared and agile as cloud technology advances.Why does a shift to the cloud matter for legal teams?From a practical perspective, it means having to be reactive in areas where legal has traditionally been more proactive. Things like data storage timelines and locations, internal access permissions, and document history are now ever-changing with software updates being automatically pushed to corporate software environments. Many organizations that manage on-premises software have historically had an effective software governance structure in place. They can meet, discuss upcoming upgrades and their impacts, and make decisions about when to execute a software upgrade. Now, in an agile cloud approach, upgrades come frequently, without much notice, and sometimes have highly impactful changes. Traditional governance structures are no longer sustainable given the new timing and volume of updates – sometimes hundreds in a week. Legal and IT teams now need to collaborate more often to quickly analyze any impacts updates will have on the organization and what, if anything, needs to be done to mitigate cloud security risks.Given this, how should corporate legal teams adapt?A typical legal department is organized around areas of expertise – you may have employment, litigation, business advice, and contracts, for example. The department may also have a legal operations function, or a member of the team assigned to certain process improvement and/or corporate programs. One of these programs covers technology changes at an organization. It is this latter set of responsibilities that become much more important, and more voluminous, in an agile software environment. Analyzing the potential risks of cloud updates, advising the business on how to mitigate those risks, and changing any associated legal workflows can become a full-time or close to full-time set of responsibilities. In addition, the culture of the department must change to one that embraces frequent change, understands change management, and is consistently updating and improving processes and procedures.Traditionally, in an on-premises environment, an IT organization would typically manage an upgrade governance structure. They would plan for a software upgrade every six months, outline the changes that are due with each upgrade, and analyze what departments it impacts and the risks of those impacts. Finally, they would present this information to a cross-functional committee who would discuss when the upgrade can be made and what kind of work needs to precede the upgrade. Legal was typically part of that committee. Now, in a cloud environment dozens (or even hundreds) of changes get pushed out weekly and, although there may be some advanced warning, the timing isn’t as flexible, it isn’t uniform across users, and there is usually less time to prepare. In addition, changes may be pushed out, rolled back, and potentially reversed. Updates may also occur without any warning, which can contribute to the cloud challenges for corporate legal departments[1]. To minimize risk in this agile environment some specific steps can be helpful: a similar governance committee needs to meet more frequently, the analysis of impact and risk needs to be done very quickly, and changes need to be made almost immediately to ensure you get ahead of any potential impacts. Due to the frequent nature of these changes, and supervising process updates to mitigate risk associated with the changes, managing cloud updates can be more time-consumingWithout structure, these cloud updates can add stress and increase reactive work. However, with some structure and clearly delineated oversight, they can be managed more efficiently. Although many organizations may not have a structure in place, those that do pull together a committee for each enterprise technology. This committee has IT, legal, compliance, and business-focused representation. It may have multiple representatives from some of these groups, depending on the perspectives needed. The goal is for the business representative to advocate for users of the technology, the legal and compliance representatives to mitigate risk and take into account regulatory, litigation and privacy considerations, and the IT team to represent management of the platform and be a voice for the platform provider. The committee should have access to a sandbox-type environment where they can test changes and should be empowered to lead companywide changes – or at least be able to work with a project management office or other resource to make these changes.Most legal departments run pretty lean so creating a new governance structure can be a significant challenge, but there are ways to make the process easier. First, you can hire outside support to handle all, or some, of this work. For example, outsourcing the creation of the governance structure to manage software updates and staffing that group with your own resources or have your external partner staff and manage it until a time when you are ready to take it over. Second, instead of hiring outside support, you can share your risk concerns with IT and rely on them to raise any potential impact that upgrades may have on risk and legal processes. For example, when IT receives an email from a software provider outlining updates, they would analyze them for potential impact to legal workflows, retention policies, or any other issues you have flagged. They would then test the updates and remediate any negative impacts. Finally, you can rotate governance committee membership so that the work is being shared across your team. Whatever approach you choose, keep in mind that changes in the cloud environment are happening frequently and having someone within your company watching from a legal perspective will pay dividends when it comes to accessing data for legal, compliance, investigative, or other reasons down the line.[1] Victoria Hudgins, “Big Adjustment: Legal Departments Struggle with Lack of Control Over Cloud Technology,” Legaltech news, November 29, 2021, law.com information-governance; microsoft-365; lighting-the-path-to-better-information-governancecloud-security, cloud-migration, blog, risk-management, information-governance, microsoft-365cloud-security; cloud-migration; blog; risk-managementlighthouse

Long gone are days when the majority of discovery records were kept in paper format. Documents, invoices, and other related evidence needed to be scanned and printed in the tens (if not hundreds) of thousands. Today, a huge number of discovery efforts (internal or external) revolve around digital content. Ergo, this article will highlight the collection of digital evidence and how to best prepare your case when it comes to preservation and collections as well as processing and filtering.But, before we get into that, one of the core factors to keep in mind here is time, which will always be there irrespective of what we have at hand. It is especially complicated if multiple parties are involved, such as vendors, multiple data locations, outside counsels, reviewers, and more. For the purposes of this blog, I have divided everything into the following actionable groups - preservation and collection as well as processing and filtering.Preservation and CollectionIn an investigation or litigation there could be a number of custodians involved, for example, people who have or had access to data. Whenever there are more than a handful of custodians the location may vary. It is imperative to consider where and what methods to use for data collection. Sometimes an in-person collection is more feasible than a remote collection. Other times, a remote collection is the preferred method for all those concerned. A concise questionnaire along with answers too frequently asked questions is the best approach to educate the custodian. Any consultative service provider must ensure samples are readily available to distribute that will facilitate the collection efforts.Irrespective of how large the collection is, or how many custodians there are, it is best to have a designated coordinator. This will make the communication throughout the project manageable. They can arrange the local technicians for remote collections and ship and track the equipment.The exponential growth in technology presents new challenges in terms of where the data can reside. An average person, in today’s world, can have a plethora of potential devices. Desktops and laptops are not the only media where data can be stored. Mobile devices like phones and tablets, accessories such as smartwatches, the IoT (everything connected to the internet), cars, doorbells, locks, lights…you name it. Each item presents a new challenge and must be considered when scoping the project.User-generated data is routinely stored and shared on the Cloud using a variety of platforms. From something as ancient as email servers to “new” rudimentary storage locations, such as OneDrive, Google Drive, Dropbox, and Box.com. Others include collaborative applications, such as SharePoint, Confluence, and the like.Corporate environments also heavily rely on some sort of common exchange medium like Slack, Microsoft Teams, and email servers. These applications also present their own set of challenges. We have to consider, not just what and how to collect, but equally important is how to present the data collected from these new venues.The amount of data collected for any litigation can be overwhelming. It is imperative to have a scope defined based on the need. Be warned, there are some caveats to setting limitations beforehand, and it will vary based on what the filters are. The most common and widely acceptable limitation is a date range. In most situations, a period is known and it helps to set these parameters ahead of time. In doing so, only the obvious date metadata will be used to filter the contents. For example, in the case of emails, you are limited to either the sent or received date. The attachment's metadata will be ignored completely. Each cloud storage presents its own challenges when it comes to dates.Data can be pre-filtered with keywords that are relevant to the matter at hand. It can greatly reduce the amount of data collected. However, it is solely dependent on indexing capabilities of the host, which could be non-existent. The graphical contents and other non-indexable items could be excluded unintentionally, even if they are relevant.The least favored type of filter among the digital-forensics community is a targeted collection, where the user is allowed to guide where data is stored and only those targeted locations are preserved. This may not be cost effective, however, it can restrict the amount of data being collected. This scope should always be expected to be challenged by other parties and may require a redo.Processing and FilteringOnce the data collected goes through the processing engine the contents get fully exposed. This allows the most thorough, consistent, and repetitive filtering of data. In this stage, filtering relies on the application vetted by the vendor and accompanied by a process that is tested, proven, and updated (when needed).The most common filtering in eDiscovery matters is de-NIST-ing, which excludes the known “system” files from the population. Alternatively, an inclusion filter can be applied, which only pushes forward contents that typically a user would have created, such as office documents, emails, graphic files, etc. In most cases, both de-NIST-ing and inclusion filters are applied.Once the data is sent through the meat grinder (the core processing engine) further culling can be done. At this stage, the content is fully indexed and extensive searches and filters will help limit the data population even further to a more manageable quantity. The processing engine will mark potentially corrupt items, which are likely irrelevant. It will also identify and remove any duplicate items from all collected media from the entire matter data population. Experts can then apply relevant keyword searches on the final product and select the population that will be reviewed and potentially produced.I hope this article has shed some light on how to best prepare your case when it comes to preservation and collections as well as processing and filtering. To discuss this topic further, please feel free to reach out to me at MMir@lighthouseglobal.com.digital-forensics; information-governance; chat-and-collaboration-datacollections, ediscovery-process, preservation-and-collection, processing, blog, digital-forensics, information-governance, chat-and-collaboration-data,collections; ediscovery-process; preservation-and-collection; processing; blogmahmood mir

Below is a copy of a featured article written by Denisa Luchian for The Lawyer.com, where she interviews Lighthouse's Matt Bicknell. Lighthouse business development director EMEA Matt Bicknell talks to The Lawyer about how in today’s remote environment, cloud based collaboration tools are not just desirable but a necessity – but also the challenges they pose for eDiscovery processes.What is the driving force behind the massive migration to cloud-based environments over the last few years?There are a few factors at play here. Prior to the Covid-19 pandemic, companies were already moving their data to the Cloud (both public and private) in droves, in order to take advantage of unlimited data capacities and drastically lower IT overhead. The move to the Cloud is also being driven by a younger workforce that feels at home working with cloud-based chat and collaboration tools, like M365 or G-Suite. However, the worldwide shift to remote work due to the pandemic really broke the dam when it comes to cloud migration. We’ve seen a seismic shift to cloud-based tools and environments since March of 2020. In a completely remote environment, cloud-based collaboration tools are not just desirable, they are necessary to keep workforces productive. Migrating to the Cloud can greatly reduce the need for workers to be physically present in an office building.What are some of the challenges that cloud migration can pose to the eDiscovery process?Unlimited storage capacity at low cost can be a great thing for an organisation’s bottom line, but can definitely cause issues when it comes time to find and collect data that is needed for a litigation or investigation. Search functions built for cloud-based tools are often built for business use, rather than for the functionality that legal and compliance teams require in order to find relevant information. In addition, collecting and producing from collaboration tools like Teams or Slack can be much more complicated than a traditional email collection. Relevant communications that previously would have happened over email now happen over chat, through emoticon reactions, or through collaboratively editing a document. All of this relevant data may be stored in several different places, in a variety of formats within the Cloud. Even attachments are handled differently in cloud-based applications – instead of sending a static document as an attachment via email, Teams defaults to sending a link to the document in Teams. This means that the document could look significantly different at the time of collection than it did when the link was sent. Collecting from those types of sources, producing them in a format that makes sense to a reviewer/opposing counsel, and accounting for all the dynamic variables can be a difficult hurdle to overcome if the organisation hasn’t planned for it.How can companies prepare for eDiscovery challenges in a cloud environment?First, make sure compliance, legal and IT all have a seat at the table and have input into decisions that may affect their workflows and processes. Understand where your data resides and have effective retention, data governance, and compliance policies in place. Your policies should spell out which cloud-based applications employees may use and also have rules in place regarding how they can be used and where work product should be stored. Understand your legal hold policy and what type of data it encompasses. Make sure you have the right talent (either within your organisation or through a vendor) who understands the underlying architecture behind Teams, G-Suite, or any other cloud-based tool your organisation uses and also knows how to collect relevant information when needed. Ensure that your IT team or vendor has a system in place to monitor application and system updates. Cloud-based updates can roll out on a weekly basis; those changes may significantly impact the efficacy of your data retention and collection policies and workflows.As cloud technology continues to evolve, what does the future hold for eDiscovery? Because of the near endless storage capacity of the Cloud, the amount of data companies generate will just continue to exponentially expand. As a result, the technology behind AI and analytics will continue to improve, and those tools will eventually be less of an option to use in certain matters and more of a necessity to use for most matters. I also think as more companies feel comfortable moving their data to the Cloud, we will start to see more and more of these companies bring their eDiscovery programs in house. Vendors are already beginning to offer subscription-based, self-service, spectra eDiscovery programs which hand over the eDiscovery reigns to the organisation, while the vendor stores and manages the data in the Cloud (both public and private). This type of service allows companies to eliminate the middleman, control their own eDiscovery costs, and easily scale up or down to meet their own needs, while leaving the burden of data storage security and maintenance with the vendor. Finally, look for vendors to start offering subscription-based services to help organisations manage the near-constant stream of application and system updates for cloud-based services.microsoft-365; chat-and-collaboration-data; information-governancemicrosoft, cloud, g-suite, blog, microsoft-365, chat-and-collaboration-data, information-governance,microsoft; cloud; g-suite; blogthe lawyer

In 2021, corporations and law firms alike grappled with yet another year of disruption and unpredictability caused by economic volatility, a lingering global pandemic, increased regulation, and inequality within the workforce. To help our clients prepare for whatever 2022 may have in store, Lighthouse CEO Brian McManus welcomed economic forecaster and former CNBC chief economist and Squawk Box co-host Marci Rossell for a lively discussion centered around these current global macroeconomic trends, with a focus on their effect on the legal industry.Their conversation was wide-ranging and informative, touching on impacts, causes, and forecasts related to inflation, global workforce shortages, inequality in the workplace, technology adoption, and increased regulatory and data privacy restrictions. The key takeaways from this discussion are outlined below.Economic InflationAs of January 2022, the inflation rate was hovering around 7% in the United States (US), and around 5% in the European Union (EU). These are the highest inflation rates both countries have seen in decades. Rossell explained that one of the major contributing factors for this increase is the speed at which the overall economy recovered from the abrupt halt in economic activity in the spring of 2020 due to the COVID-19 pandemic. The sharp economic recovery drove a surge in demand for services and goods, at a time when supply around the world was at an all-time low due to pandemic-related shutdowns. This tension led to the current sustained inflation rates we’re seeing today, and those rates can be expected to remain high for the foreseeable future in markets where production is not expected to meet demand any time soon (such as the energy and oil industries).Within the legal industry, specifically, law firms and organizations have not only been impacted by the typical “cost of goods” inflation described above – they have also been impacted by inflation related to labor shortages and rising wages, as well as costs related to regulation and compliance. “The Great Resignation” and Its Impact on the Legal IndustryOver the last two years, droves of workers have switched employers, changed careers, or left the workforce all together, in what pundits and economists have deemed, “The Great Resignation.” Rossell explained that this global phenomenon may have roots in the financial crises of 2008 – 2009, when the economy contracted dramatically, leaving millennials struggling to enter a workforce plagued by an unemployment rate that had soared into the double digits. In the wake of this recession and for years afterward, the balance of power between employers and employees was weighted heavily in favor of employers, with overqualified workers applying to the same jobs, giving employers their pick of quality candidates. Now, this same generation of millennials have been confronted with a pandemic that has caused millions of people to suddenly sever their connections to jobs, employers, and/or geography. Many of these workers may not have felt very connected to where they worked or lived in the first place, but stayed because of their previous experience in a job market that was heavily influenced by the last recession. The pandemic suddenly forced this generation of workers into a situation that ultimately enabled them to make different career choices. And we are certainly seeing them making those choices. As Rossell noted, in addition to this trend among the millennial generation, the pandemic also escalated early retirements for an older generation, while an overall decrease in population growth has led to 400,000 fewer young people entering the labor force every year. These three factors are a perfect labor-shortage storm, with fewer experienced workers, fewer young people entering the labor market, and a generation of mid-career millennials reevaluating their careers and/or employers.McManus pointed out that labor shortage has also had a significant effect on the legal industry generally, and the eDiscovery industry specifically. eDiscovery is a niche industry, which makes it harder to find and retain experienced talent in general. But over the last twelve months, the tighter labor market has significantly exacerbated those issues. There is now a shortage of talent within eDiscovery and the cost of retaining valuable talent has sharply increased over the last nine months, with experienced employees being offered 20% to 40% more in compensation.This trend also affects the broader legal industry. Attrition of associates at law firms was at an unprecedented level in 2021 and the cost of retaining associates skyrocketed. For example, law firm associate compensation grew 11% in November of 2021, year over year, according to a state of the legal market report from the Thomson Reuters Institute. This trend can be expected to continue over the next few years due to the economic factors at play.To combat the worker shortage, McManus warned that employers should expect to not only offer higher compensation, but also include benefits like flexible work arrangements, in order to recruit and retain talented employees. Even prior to the pandemic, Rossell noted, studies showed that flexible work arrangement benefits were worth about 8% of a salary to younger employees. This trend is expected to sustain well into the future, as housing market trends indicate that 30-somethings are moving to larger homes away from large corporate offices and cities.Diversity, Equity, and Inclusion in the WorkforceThere has been a significant emphasis placed on diversity, equity, and inclusion (DE&I) over the past few years across many markets, including the legal industry. Rossell provided a historical perspective, explaining that thirty years ago the consensus from economists was that the labor market was rational and profit-maximizing and thus, discrimination in the labor force could not exist. The theory was that for-profit companies would always be incentivized to hire the best individual for the job, regardless of gender, race, ethnicity, sexual orientation, etc. But in 2004, a groundbreaking economic study on race in the labor market found that people with white-sounding names were 50% more likely to get a call back from an HR professional. This study was the beginning of a sea-change in economics, where organizations slowly realized the economic need for, and importance of, DE&I. In effect, organizations began to slowly understand that there was an economic cost to not hiring the best candidates, and that focusing on DE&I increases profitability, productivity, and growth.This sea-change is represented across the globe. European countries were initially on the forefront of this movement, as evidenced by the 2003 emphasis in Norway to have gender equity represented on corporate boards within the country. The US is now moving even further in that direction. Last year, Nasdaq proposed new board diversity rules and disclosure guidance, including that listed companies should have at least one board member who identifies as a woman, as well as one board member who self-identifies as an underrepresented minority or LGBTQ+.As McManus pointed out, this trend is also represented across the legal industry. There is a continued expectation for more diversity, equity, and inclusion within organizations, law firms, and legal technology supply vendors. Clients want to see diversity, equity, and inclusion represented in the teams they work with on a daily basis. Additionally, the next generation of talented employees is also demanding an equitable environment in which to work. Thus, legal and eDiscovery employers should expect that going forward, they will need to track, measure, and demonstrate an inclusive, equitable, and diverse environment in order to attract and retain the best workers.As Rossell pointed out: “(DE&I) matters to the next generation. As talent becomes scarcer and the balance of power shifts away from employers to employees, [the next generation of workers] is going to demand not only a flexible workforce but a diverse and inclusive environment to work in.”As DE&I programs advance, eDiscovery and legal teams will see how diverse hiring contributes to greater innovation and success.AI and Its Role in the Legal IndustryRossell also provided a historical view of technology innovation and its effect on worldwide economies. She noted that artificial Intelligence (AI) technology is the next step in a 200-year-old process that began with the industrial revolution – when advances in machine automation allowed simple machines to perform manufacturing related processes, enabling humans to migrate towards more service-related work. This has now evolved into machines that can now perform some of the work in the service sector, thanks to advancements in AI technology.McManus noted that within the legal industry, lawyers (who are trained to be risk-averse) have traditionally been much slower to adopt this emerging technology. However, the legal industry is also quickly becoming submerged in “big data,” and AI is one of the most effective tools to combat the labor shortages and increased costs that exacerbate the problems caused by massive data volumes. Nowhere is this more evident than in the document review process performed during eDiscovery.“The industry still follows a traditional approach [to document review] with large groups of lawyers reviewing massive volumes of text and that approach is just untenable,” McManus said.The impracticality of that traditional approach is not only due to the increased volume and complexity of data, but also due to labor shortages and increased labor costs. Advancements in AI give newer legal technology tools the capability to help automate and expedite the document review process. This should lead to AI adoption at a much faster pace than we’ve traditionally seen in the legal industry, McManus noted.The Global Regulatory Landscape, Anti-Trust Activity, and What to Look for in the Coming YearsRossell also provided an insightful overview of the dynamic and shifting regulatory landscape from an economist’s perspective. Increased governmental regulation is raising costs in almost every industry and is one of the driving forces behind higher inflation rates. In the United States, the increase in government regulation may be due to the fact that the government’s governing functions have been slowly shifting from the legislative branch to the executive branch. In turn, this shift means that every four years, companies may deal with a complete shift in the regulatory landscape depending on which political party wins the presidential office. These abrupt swings make compliance very costly and put pressure on smaller organizations. Often the only companies that can survive this type of volatility are those big enough to support a department solely dedicated to compliance. Thus, in some ways, increased government regulation is driving the consolidation of companies.At the same time, we are seeing a shift in antitrust policy from an economics perspective. Whereas previously, anti-competition policy was centered around whether consolidation would harm consumers, we’re now seeing a shift to assessing a broader range of harm. Prior to this shift, a merger would be blocked if it would cause higher prices for consumers (i.e., if the merger would cause consumers harm by giving them less choices and therefore raise consumer prices). Now, mergers are blocked for a much broader range of issues that are not just centered solely around consumers, but around society as a whole. For example, a merger might now be blocked if it would be harmful to the environment, to workers, would cause a decline in future competition, etc. This more aggressive governmental regulation worldwide is expected to continue in the coming years. In short, expect anti-competition scrutiny to continue to be broad and aggressive, regardless of changes in political parties and offices.The Future of the Global Data Privacy LandscapeFinally, McManus provided a helpful overview of recent changes to the data privacy landscape, and what to expect in the 2022. Another area where government regulation is expected to continue to increase globally is around data privacy rights and protections for consumers. The EU’s GDPR legislation in 2018 paved the way for data privacy rights, providing a template for governments on how to regulate and protect consumer data privacy. Within a few years, California followed suit, as did a plethora of other governments around the world. This trend is only expected to continue as we move into an increasingly digital world.In the US in 2021 alone, two more states passed comprehensive GDPR-like laws (Virigina and Colorado), while at least 25 other states introduced or had data privacy laws somewhere within the state legislative consideration process. And the US federal government also looks to be increasingly active in this area – with the U.S. House Energy and Commerce Committee voting to give the Federal Trade Commission $1 billion to set up a data privacy bureau. Even China passed a GDPR-like law in 2021, the Personal Information Protection Law, which included not only the risk of huge fines for non-compliance, but also the risk of companies being black-listed by the Chinese government.This focus on data privacy regulation will certainly increase costs for businesses in the coming years, as companies work to stay compliant with a patchwork of global and local data privacy laws and regulations.ediscovery-reviewccpa, gdpr, review, ai-big-data, blog, ediscovery-review,ccpa; gdpr; review; ai-big-data; bloglighthouse

Legal teams approaching a Hart-Scott-Rodino (HSR) Second Request may hold false assumptions about what is and isn’t possible with document review. Often these appear as necessary evils—compromises in efficiency and precision are inevitable given the unique demands of Second Requests. But, in fact, these compromises are only necessary in the context of legacy technology and tools. Using more current tools, legal teams can transcend many of these compromises and do more with document review than they thought possible.Document review during an HSR Second Request is notoriously arduous. Legal teams must review potentially millions of documents in a very short timeframe, as well as negotiate with regulators about custodians and other parameters that could change the scope of the data under review.Up until recently, legal teams’ ability to meet these demands was limited by technology. It wasn’t possible to be precise and thorough while also being extremely quick. As a result, attorneys adopted certain conventions and concessions around the timing of review steps and how much risk to accept.Technology has evolved since then. For example, tools powered by advanced artificial intelligence (AI) utilize deep learning models and big data algorithms that make review much faster, more precise, and more resilient than legacy tools. However, legacy thinking around how to prepare for Second Requests remains. Many attorneys and teams remain beholden to the constraints imposed on them by tools of the past. New review tools enable new approaches and benefits, eliminating these constraints. Here’s a look at three of the most common myths surrounding document review during Second Requests and how they’re proven false by modern review tools.Myth 1: Privilege review must come after responsive reviewThe classic approach to reviewing documents during a Second Request is to start by creating a responsive set and then review that set for privileged documents. This takes time— an extremely precious commodity during a Second Request—but these steps are unavoidable with legacy tools. The linear nature of legacy review models requires responsive review to happen first because supporting privilege review over an entire dataset simply is not a feasible task over potentially millions of records. Tools leveraging advanced AI, however, are well suited to support scalable privilege analysis with big data. Rather than save privilege review for later, legal teams can conduct privilege review simultaneously with responsive review. This puts documents in front of human reviewers sooner and shaves invaluable hours off the timeline as a whole.Myth 2: Producing privileged documents to regulators is inevitableInadvertently disclosing privilege documents to federal agencies is so common the Federal Rules of Civil Procedure give parties some latitude to do so without penalty. Even so, the risk remains of inadvertent disclosure during a Second Request that will invite additional questions and scrutiny from regulators and undermine the deal.Although advanced AI tools cannot eliminate the possibility of inadvertent disclosure, these automated solutions can vastly reduce it. In one recent Second Request, a tool using advanced AI was able to identify and withhold 200,000 privilege documents that a legacy tool had failed to catch. This spared the client from costly exposure and clawbacks.Myth 3: There’s no time to know the details of what you’re producingWith massive datasets and very little time to review, legal teams get used to producing documents without fully knowing what’s in them. This can cause surprise and pain down the line when regulators ask for clarification about information the team isn’t prepared to address.With advances in technology, teams can gain more clarity using tools that identify key documents. These tools conduct powerful searches of both text and document attributes, using complex and dynamic search strings managed by linguistic experts. Out of a million or more documents, key document identification can surface the one or two thousand that speak precisely to attorneys’ priorities, efficiently helping counsel prepare for testimony and other proceedings.What’s your Second Request strategy?Second Requests will always be intense. Advancements in eDiscovery technology prove the limits of the past don’t apply today. With technology moving beyond legacy tools, it is time for teams to move beyond legacy thinking as well.For more detail about how advancements in technology help teams meet the demands of Second Requests, download our eBook.antitrust; ediscovery-review; ai-and-analyticsreview, hsr-second-requests, blog, antitrust, ediscovery-review, ai-and-analytics,review; hsr-second-requests; blogkamika brown

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