Lighthouse Blog

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

As eDiscovery becomes more complex, organizations are turning to hybrid solutions that give them the flexibility to scale projects up or down as needed. Hybrid solutions offer the best of both worlds: the ability to use self-service, spectra for small matters or full-service for large and complex matters. This flexibility is essential in today's litigation landscape, where the volume and complexity of data can change rapidly. Hybrid solutions give organizations the agility to respond quickly and effectively to changing eDiscovery needs. In a recent webinar, I discussed hybrid eDiscovery solutions with Jennifer Allen, eDiscovery Case Manager at Meta, and Justin Van Alstyne, Senior Corporate Counsel, Discovery and Information Governance at T-Mobile. We explored some of the most pressing eDiscovery challenges, including data complexity, staffing, and implementation. We also discussed scenarios that require flexible solutions, keys to implementing new technology, and the future of eDiscovery solutions. Here are my key takeaways from our conversation.Current eDiscovery challengesA hybrid approach can transition between an internally managed solution and a full-service solution, depending on the nuances and unique challenges of the matter. This type of solution can be beneficial in situations where the exact needs of the case are not known at the outset. A few challenges come into play when deciding your approach to a project:Data volume: When dealing with large data sets, being able to scale is critical. If the data for a matter balloons beyond the capacity of an internal team, having experts available is critical to avoid any disruptions in workflows or errors.Data predictability: When it comes to analyzing data, consistency and predictability can greatly inform your approach to analysis. Standard data allows for more flexibility, as there is an expectation that the results will fall within a certain range. However, to ensure accurate representation, caution must be exercised when dealing with complicated big data. It is important to consider variables, potential outliers, and how the data is compiled and presented. Internal capacity: It's important to monitor and manage the internal workload of your team closely. When everyone is already at their maximum capacity, it can be tempting to outsource various tasks to a full-service project manager. Technology can be a more cost-effective and efficient method for filling the gaps.The right talent and knowledge Finding and utilizing the right team in today's competitive labor market can be difficult. A hybrid solution can help with this by providing a scalable way to get the most out of your workforce. With a hybrid solution, you have the option to staff fewer technical positions and provide training on the data or matters your organization most frequently encounters with your existing team. But, if you have a highly complicated data source, you can still staff an expert who knows how to handle that data. An expert can shepherd the data into a solution, do extensive quality control to ensure that you marry up the family relationships correctly, and give confidence that you're not making a mistake.To assuage concerns about the solution being misused, technology partners can provide training and education, and limit access to who can create, edit, or delete projects within the tool. This training helps to upskill your team by teaching them more advanced technology, which leads to more efficient and sophisticated approaches to matters.Flexible solutions for different mattersA hybrid solution can be a great option for a variety of matters, including internal investigations, enforcement matters, third-party subpoenas, and case assessments. These matters can benefit from the flexibility and scalability provided by a hybrid approach.When determining if a matter needs full-service treatment, it's important to consider the specific requirements at hand. Questions around the volume and frequency of data production, the types of data involved, and the necessary metadata and tagging all play a role in determining if a self-service, spectra approach will suffice or if full-service support is needed. It's always important to consider the timeline and potential challenges during the transition. Using experience with similar cases can provide valuable insight into what might work best in your situation.Keys for implementing eDiscovery solutionsThere are a few critical components to keep in mind when evaluating which eDiscovery solutions and tools are right for your business now, and as it grows.Training team: With any new solution or product there may be some trepidation around learning and adoption. Leverage vendor support to answer your questions and help train your team. Keep them involved in your communications with outside counsel and internal teams so you can receive suggestions and assistance if needed. As users get more experience with the software, they will begin to feel empowered and understand how the tool can be used most effectively. Scalability: One of the most significant hurdles to scaling big eDiscovery projects is the amount of data that needs to be processed. With new data sources, tighter deadlines, and more urgency, it can be difficult to keep up with the demand. Using a fully manual process or a project management solution has a greater chance for error or increased cost. A flexible solution can help your team keep up with increasing data volumes while reducing costs and errors. Automation: Automating repetitive tasks and workflows can dramatically speed up data collection and analysis. This can be a huge advantage when investigating large, complex cases. Additionally, automation can help to ensure that data is collected and parsed consistently.Cost-benefit analysis: Through support and training with a self-service, spectra tool, you can work to reduce the number of support requests. This can minimize the time your team spends on each request and ultimately lowers the cost of providing support. The cost reduction of self-service, spectra tools is often substantial, and it can have a positive snowball effect as your team becomes more skilled at the task. You can reinvest those savings into other business areas with less need for oversight and fewer mistakes. The future state of eDiscovery solutionsThe proliferation of DIY eDiscovery solutions has made it easier for organizations to take control of their data and manage their cases in-house. As AI technology, including continuous active learning (CAL) and technology-assisted review (TAR), continues to evolve, teams will better understand how to handle the growing demands of data and implement hybrid tools. As we move into the future of eDiscovery and legal technology, DIY models will play an increasingly important role in supporting business needs.ediscovery-review; ai-and-analytics; lighting-the-path-to-better-ediscoveryself-service, spectra, blog, ediscovery-review, ai-and-analyticsself-service, spectra; blogself-service, spectrapaige hunt

The goal of Practice Direction 57AD (PD57AD, previously known as the Disclosure Pilot Scheme) is to modernise the UK’s disclosure practice. This transformation is essential because the traditional, manual, and combative approach to disclosure is unsustainable in the face of today’s massive data volumes and ever-evolving data sources. Manually collecting and reviewing millions of documents one-by-one has become prohibitively expensive, impossibly time consuming, and prone to the risk of both under and over disclosure. When you add in the combative approach between opposing parties, the traditional disclosure process becomes a recipe for skyrocketing legal costs, missed deadlines, and data issues that can derail entire matters. Conversely, a more cooperative approach that leverages AI technology can help improve the process—by allowing attorneys to focus their expertise on critical parts of the matter and refining AI tools to better handle data now and for future, related matters.Thus, PD57AD focuses on two pivotal elements to modernise disclosure: cooperation and technology. Specifically, PD57AD requires parties to “liaise and cooperate with the legal representatives of the other parties to the proceedings…so as to promote the reliable, efficient, and cost-effective conduct of disclosure, including through the use of technology.” Similarly, the Disclosure Review Document asks that each party outline how they “intend to use technology assisted review/data analytics to conduct a proportionate review of the data set” and further reminds parties of their duty to cooperate. Through PD57AD, legal teams’ relationships to each other and with technology is changing in a few crucial ways that present opportunities to work smarter, more cost effectively , and with greater agility.The duty to cooperateJudges are increasingly focusing on the language requiring cooperation between parties in PD57AD and will admonish counsel who attempt to use the disclosure process as a tool to punish an opposing party. For instance, in McParland & Partners Ltd v Whitehead, when a dispute arose involving the framing of the issues of disclosure, the judge took the opportunity to broadly remind both parties of the following: “It is clear that some parties to litigation in all areas of the Business and Property Courts have sought to use the Disclosure Pilot as a stick with which to beat their opponents. Such conduct is entirely unacceptable, and parties can expect to be met with immediately payable adverse costs orders if that is what has happened.”As data volumes grow and PD57AD becomes more cemented into the fabric of UK’s disclosure practice, there is a growing intolerance for “weaponised” disclosure practices by courts. Certainly, parties can expect that the days of “data dumping” (i.e., the strategy of over collecting and producing documents to bury the opposing party in data) or conversely, winning burden arguments related to the cost and time of manual review, are over. The duty to leverage technology Instead of this combative approach, courts will expect that parties come together cooperatively to agree on the use of technology to perform targeted disclosure that is both more cost effective and efficient. Indeed, in a cloud-based world, this symbiotic relationship between technology and legal is the only successful path forward for an effective disclosure process. Under this modern approach, the technology used to collect, cull, review, and produce data must be leveraged in such a way that results can be verified by opposing counsel and judges. This means that all workflows and processes must be transparent, defensible, and agreed upon by opposing counsel. Even prior to the implementation of the Disclosure Pilot Scheme in 2018, judges had begun to crack down on parties who attempted to “go it alone” by unilaterally leveraging technology to cull or search data in a non-transparent way, without the consent of opposing counsel and/or without implementing industry standard best practices. For example, in Triumph Controls UK Ltd., the judge explicitly admonished a party for deploying a computer assisted review (CAR) search strategy overseen by “ten paralegals and four associates” rather than a “single, senior lawyer who has mastered the issues in the case” to ensure that the criteria for relevance was consistently applied to effectively teach the CAR technology. He also rebuked the party’s CAR approach because it was not transparent and could not be independently verified. Because these technology best practices were not followed, the judge forced the producing party to go back and cooperatively agree with opposing counsel on an alternative review methodology to sample and re-review a portion of the original dataset. The future of disclosure for counsel and clients The modernisation of the disclosure process through cooperation and technology means that it will be increasingly imperative that each party has the requisite legal and technology expertise to meet the requirements of PD57AD. Specifically, each party must have a barrister who understands disclosure law and can guide them through each step of the process in a way that complies with PD57AD. Each party should also have an expert who understands how to implement technology to perform targeted, efficient, and transparent disclosure workflows. As seen from legal decisions emanating around PD57AD, parties without this expertise who attempt to “wing it” will increasingly find themselves facing delayed proceedings, hefty legal costs, and unfavourable judgements by courts. Law firms or corporations that don’t have the requisite expertise internally must look for an external partner that does. This is where an experienced managed review partner can provide a true advantage to both law firms and their clients. Parties should look for a partner who can provide a team of technology experts and experienced barristers, working in tandem and leveraging the industry’s best technology. This team should be ready to jump in at the outset of every matter to understand the nuances of the client’s data, as well as the underlying legal issues at play, so that each step of the disclosure process is performed transparently, defensibly, and efficiently. Over time, a managed review team can become a valuable extension of corporate in-house and law firm teams. This partner can use institutional knowledge, gained by working with the same clients across multiple matters, to create customised, strategic, and automated disclosure workflows. These tailored processes, designed directly for a client’s data infrastructure and technology, can save millions and achieve better outcomes. In turn, law firms can refocus their attention on the evidence that actually matters, while assuring their clients that the disclosure process is contributing to lower legal costs and better overall results.ConclusionUnder the modern approach to disclosure, parties must have someone on their team with the necessary legal and technology expertise to perform the type of targeted, cooperative, and transparent disclosure methodology now required by PD57AD. This partnership between legal and technology is truly the only path forward for a successful disclosure endeavour in the face of today’s more voluminous and complicated datasets. Parties that do not have this expertise should look for an experienced managed review partner who can provide a consistent team of legal and technology experts who can perform each step of the disclosure process efficiently, transparently, and defensibly. ai-and-analytics; ediscovery-reviewreview, ai-big-data, blog, ai-and-analytics, ediscovery-reviewreview; ai-big-data; blogjennifer cowman

Emerging challenges with big data—large sets of structured or unstructured data that require specialized tools to decipher— have been well documented, with estimates of worldwide data consumed and created by 2025 reaching unfathomable volumes. However, these challenges present an opportunity for innovation. Over the past few years, we’ve seen a renaissance in AI products and solutions to help address and evolve past these issues. From smaller players creating bespoke algorithms to bigger technology companies developing solutions with broader applications, there are substantial opportunities to harness AI and rethink how to manage data.A recent announcement of Microsoft’s Syntex highlights the immense possibilities for, and investment in, leveraging AI to manage content and augment human expertise and knowledge. The new feature in Microsoft 365 promises advanced AI and automation to classify and extract information, process content, and help enforce security and compliance policies. But what do new solutions like this mean for eDiscovery and the legal industry?There are three key AI benefits reshaping the industry you should know about:1. Meeting the challenges of cloud and big data2. Transforming data strategies and workflows3. Accelerating through automationMeeting the challenges of cloud and big data Anyone close to a recent litigation or investigation has witnessed the challenge posed by today’s explosion of data—not just volume, but the variety, speed, and uncertainty of data. To meet this challenge, traditional approaches to eDiscovery need to be updated with more advanced analytics so teams can first make sense of data and then strategize from there. Simultaneous with the need to analyze post-export documents, it’s also clear that proactively managing an organization’s data is increasingly essential. Organizations across all industries must comply with an increasingly complex web of data privacy and retention regulations. To do so, it is imperative that they understand what data they are storing, map how that data flows throughout the organization, and have rules in place to govern the classification, deletion, retention, and protection of data that falls within certain regulated categories of data types. However, the rise of new collaboration platforms, cloud storage, and hybrid working have introduced new levels of data complexity and put pressure on information governance and compliance practices—making it impossible to use older, traditional means of information governance workflows. Leveraging automation and analytics driven by AI advances teams from a reactive to proactive posture. For example, teams can automate a classification system with advanced AI where it reads documents entering the organization’s digital ecosystem, classifies them, and labels them according to applicable sensitivity or retention categories implemented by the organization—all of which is organized under a taxonomy that can be searched later. This not only helps an organization better manage data and risks upfront—creating a more complete picture of the organization’s data landscape—but also informs better and more efficient strategies downstream. Transforming data strategies and workflows New AI capabilities give legal and data governance teams the freedom to think more holistically about their data and develop strategies and workflows that are updated to address their most pressing challenges. For eDiscovery, this does not necessarily mean discarding legacy workflows (such as those with TAR) that have proven valuable, but rather augmenting them with advanced AI, such as natural language processing or deep learning, which has capabilities to handle greater data complexity and provide insights to approach a matter with greater agility. But the rise of big data means that legal teams need to start thinking about the eDiscovery process more expansively. An effective eDiscovery program needs to start long before data collection for a specific matter or investigation and should contemplate the entire data life cycle. Otherwise, you will waste substantial time, money, and resources trying to search and export insurmountable volumes of data for review. You will also find yourself increasingly at risk for court sanctions and prolonged eDiscovery battles if your team is unprepared or ill-equipped to find and properly export, review, and produce the requested data within the required timeline. For compliance and information governance teams, this proactive approach to data has even greater implications since the data they’re handling is not restricted to specific matters. In both cases, AI can be leveraged to classify, organize, and analyze data as it emerges—which not only keeps it under control but also gives quicker access to vital information when teams need it during a matter.Advanced AI can be applied to analyze and organize data created and held by specific custodians who are likely to be pulled into litigation or investigations, giving eDiscovery teams an advantage when starting a matter. Similarly, sensitive or proprietary information can be collected, organized, and searched far more seamlessly so teams don’t waste time or resources when a matter emerges. This allows more time for case development and better strategic decisions early on.Accelerating through automation Data growth continues to show no signs of slowing, emphasizing the need for data governance systems that are scalable and automated. If not, organizations run the risk of expending valuable resources on continually updating programs to keep pace with data volumes and reanalyzing their key information.The best solutions allow experts in your organization to refine and adjust data retention policies and automation as the organization’s data evolves and regulations change. In today’s cloud-based world, automation is a necessity. For example, a patchwork of global and local data privacy regulations (GDPR, California’s CCPA, etc.) include restrictions related to the timely disposal of personal information after the business use for that data has ended. However, those restrictions often conflict with or are triggered by industry regulations that require companies to keep certain types of documents and data for specific periods of time. When you factor in the dynamic, voluminous, and complex cloud-based data infrastructure that most company’s now work within, it becomes obvious why a manual, employee-based approach to categorizing data for retention and disposal is no longer sustainable. AI automation can identify personal information as it enters the company’s system, immediately classify it as sensitive data, and label it with specific retention rules. This type of automation not only keeps organizations compliant, it also enables legal and data governance teams to support their organization’s growth—whether it’s through new products, services, or acquisitions—while keeping data risk at bay. Conclusion Advancements in AI are providing more precise and sophisticated solutions for the unremitting growth in data—if you know how to use them. For legal, data governance, and compliance teams, there are substantial opportunities to harness the robust creativity in AI to better manage, understand, and deploy data. Rather than be inhibited by endless data volumes and inflexible systems, AI can put their expertise to work and ultimately help to do better at the work that matters. practical-applications-of-ai-in-ediscovery; ai-and-analytics; chat-and-collaboration-data; microsoft-365; lighting-the-path-to-better-information-governancemicrosoft, ai-big-data, cloud-security, blog, record-management, ai-and-analytics, chat-and-collaboration-data, microsoft-365,microsoft; ai-big-data; cloud-security; blog; record-managementmitch montoya

As the corporate workplace continues to evolve—encompassing hybrid work environments, bring your own device policies, and cloud-based storage—companies are well-advised to consider areas of increased vulnerability and whether their policies, procedures, and forensic tools are keeping pace with reality. A hybrid or remote workforce and a more collaborative data infrastructure only exacerbate data risks that were easier to manage when employees were comfortably situated at their desks. Adding even more complexity to these risks are broader labor trends, including “the Great Resignation and Reshuffle” and an aging work force, which are changing staffing and recruiting strategies and impacting knowledge transfer and IP creation.Employee intake and departure: crucial points of data security Two areas likely needing renewed attention are the moments of employee onboarding and offboarding, when a company’s most prized assets—people and data—are on the move. Departing employees present a particular risk as the potential for data exfiltration of IP and other sensitive information, whether intentional or not, is high. Often, employees take corporate IP with them inadvertently, a situation bound to get worse as turnover rates grow (Gartner anticipates a 20% jump in turnover from the pre-pandemic national average).Since people usually take jobs similar to the ones they leave (and often with competitors), taking company data along with their coffee mug and potted plant may seem justified (I wrote this stuff, so it’s mine)—or simply inconsequential. Cloud storage services such as Dropbox, Box, or Google Drive, and collaborative apps such as Microsoft Teams or Slack make it all the easier to appropriate files, lending credence to a feeling of personal data ownership. No matter how it happens, the escape into the wild of proprietary items such as source code, strategy documents, contact lists, and financial information exposes the company to untold risk, including the danger of running afoul of any number of privacy regulations if personal data is exfiltrated from its protected environment—an additional headache for the company if things go south. Are current entry and exit protocols enough? Although most companies have entrance and exit protocols usually siloed as HR and IT functions, the recent surge in employee turnover has put those very teams under pressure as they face their own personnel and budget deficits. Further, responsibilities have become less defined at a time when offboarding tasks—many now carried out at a distance—should be fortified to include proactive data monitoring and oversight, activities such teams may not be equipped to handle. The challenge, of course, is the growing complexity of the data landscape. Knowing what information is where, who accesses it, and for what purpose becomes more difficult to track as software and storage options grow, yet this is key to keeping important data protected. Data security: start training early and reinforce often Onboarding procedures can play a key role in keeping data where it belongs and helping employees navigate through and understand their responsibilities in this increasingly intricate data terrain. First, a sound onboarding protocol can ensure that new employees aren’t bringing troublesome data into the environment. No company wants to deal with the fallout of being in possession of some other company’s IP or sensitive information. More importantly, onboarding offers the most opportune time to clearly communicate expectations regarding data management and safety—information that should be reinforced with frequent (and up to date) training that emphasizes data protection and ownership. It's easy to forget as time goes on what data may be confidential or sensitive, and even easier to forget that data belongs to the business, not the employee. In short, data awareness should be instilled as part of the company culture right from the start. Seize the moment: identify and monitor offboarding risksThe recent and ongoing workplace disruption calls for a hard look at offboarding data risks and an evaluation of potential vulnerabilities to protect data before an employee leaves the company, bolster the exit protocols to have in place when they do, and have the proper forensic and analytic tools to handle data monitoring and address potential wrongdoing. Most companies do have standard offboarding checklists that address employee assets, data access, and preservation obligations as they leave the company. But there’s more to data protection at this crucial moment than ticking off boxes. Expand and optimize the offboarding checklistSavvy companies implement a more proactive, programmatic approach that begins earlier, with monitoring procedures that include defensible and repeatable processes to guard against the exfiltration of company data while helping to fortify the company’s position in case of a breach. A few important things to consider as part of the offboarding process:Know which employees warrant departure attention. Develop risk profiles with business stakeholders to identify which classes of employees, whether based on role, circumstance of departure, seniority, or access to sensitive information could present an exfiltration risk.Understand the company’s data landscape. Make sure there are mechanisms in place for tracking where sensitive data and IP may reside and when such data has been accessed.Explore activity and assets with the employee prior to their departure. An expert, friendly review of a departing employee’s recent computer activity with the employee, including an audit of their recent network activities, use of peripherals, cloud uploads, and email sends, can reveal and help mitigate potential trouble.Preserve employee devices and data as warranted with state-of-the-art forensic tools. Forensic preservation is critical to ensuring valid evidence down the line, especially since investigations today regularly involve new and novel devices, data sources, and artifacts that must be diagnosed and understood.Document all offboarding information. A paper trail of findings during the exit procedure is important if further analysis is recommended or necessary and will be crucial for subsequent investigation, if it comes to that. Have a plan if there is evidence of wrongdoing. Part of any data security effort is having an action plan to execute if there are signs of a breach. Preservation, collection, and a forensic analysis may be required should legal action ensue. ConclusionThe recent upheaval in employee turnover along with more collaboration tools and storage options present increasing risk for today’s enterprise. Companies that acknowledge new vulnerabilities and leverage opportunities to revamp outdated policies and protocols are better positioned to stop data exfiltration before it becomes a problem. The best solution: Implement robust onboarding and offboarding solutions that include data monitoring, reporting, and forensic analysis to enable a quick pivot to actionable remediation steps if trouble is brewing. digital-forensics; information-governancedeparting-onboarding-employee, blog, risk-management, digital-forensics, information-governancedeparting-onboarding-employee; blog; risk-managementdaniel black

On July 15, 2022, the mandatory Disclosure Pilot Scheme (PD51U) was officially approved and will operate on a permanent basis within the Business and Property Courts (BP&C) of England and Wales. Originally implemented in 2019 on a temporary pilot basis, it was extended twice and had been set to expire in December of 2022. Its approval means that on October 1, 2022, the pilot will end, and the scheme will officially be known as Practice Direction (PD) 57AD “Disclosure in the Business and Property Courts.”This approval is no surprise to those familiar with the modern disclosure process in the UK. PD51U was originally implemented to address the key issues associated with standard disclosure under Civil Procedure Rule (CPR) 31, such as unwieldly costs and the insurmountable scale of disclosure due to ever-growing corporate data volumes. As per UTB LLC v Sheffield United, the pilot was meant to effect a “culture change” in the reasonableness and proportionality of disclosure requests by streamlining the process in a variety of ways. One of the most notable is through the encouragement of leveraging technology (such as technology assisted review or TAR) and data analytics for document review—even going so far as to mandate the use of TAR in cases where the document count exceeds 50,000.Over the last two years, this push toward implementing more technology to streamline the disclosure process has proven to be a wise one. With a worldwide shift to cloud-based infrastructures and remote working, corporate data volumes have exploded and will only continue to grow. Therefore, the traditional means of disclosure review, wherein a team of reviewers looks at each electronic document one-by-one, is quickly becoming untenable. Utilising technology to streamline review is more imperative than ever and will only grow in importance as data volumes continue to balloon. What 57AD does not mean, however, is that solicitors faced with disclosure need to be data science or technology experts. It simply means that it will become increasingly important for solicitors who are not comfortable with disclosure technology to find a solid managed review partner that can help streamline the disclosure process with technology and meet Practice Direction 57AD requirements. Below are key attributes to look for when seeking such a partner.Look for a managed review partner with expertise on the Disclosure Review Document (DRD)The DRD is meant to facilitate an agreement between parties about what constitutes proportional disclosure, and how to achieve that goal in a cost-effective manner. To do so, it requires parties to identify the key issues of the case and then detail the method of disclosure for each issue, with five methods from which to choose.[1] Each method can have severe impacts on the cost of a matter, as well as the overall outcome of the case for clients. It is vital that someone with in-depth disclosure expertise is involved in the negotiation and completion of this document. Some managed review vendors may be able to provide staffing and project management when it comes to disclosure document review but will not have experts available and capable to provide advice on effective disclosure strategy, including DRD assistance. Without this expertise, a party may find itself agreeing to disclosure methods that significantly balloon budgets or even worse, result in harmful outcomes for clients. Look for a managed review partner who has developed strong defensible workflowsOne of the hallmarks of and impetuses for PD 51U (soon to be PD 57AD) was to streamline the disclosure process in the face of ever-growing and unprecedented data volumes. Understanding when and how to leverage technology to cull and prioritise data for review, as well as how to leverage TAR, is imperative. However, the technology and workflows can seem overwhelming, especially to those who don’t perform disclosure often. Thus, it is essential to find a managed review partner who has access to the best review technology and knows how to leverage that technology to achieve the best results in every type of matter. It is also important that that managed review partner has developed strong defensible workflows for data reduction that can be customised to meet the individual needs of each client.Look for a managed review partner who thinks outside of the traditional linear review approachWhile it may seem simpler to fall back on traditional approaches to the disclosure document review process (i.e., hiring many reviewers to read and categorize each document), it is important to remember that PD 57AD was enacted because that approach is quickly becoming too burdensome for parties. The traditional approach also opens parties up to risk, when reviewers cannot effectively review the volume of documents within the time frames required for disclosure. Today’s larger data volumes and more complicated data increase the risk that human reviewers will miss important documents that were required to be disclosed, or conversely, that they will disclose harmful or sensitive documents that should not have been disclosed. Forward-thinking managed review partners have anticipated this change and have invested in technology and human expertise that can defensibly minimise document volumes so that a discrete number of subject matter experts can look at prioritised categories of pertinent documents, maximizing the value of human review. In this way, a managed reviewer partner can help solicitors move away from an outdated approach to review, while streamlining the disclosure process, keeping litigation budgets in check, minimising risk, and achieving better outcomes. Look for a partner who will help prepare bespoke briefing documentation, right from the outsetWhen a matter needs to scale up quickly and on short notice, the painstaking process of adding new reviewers can explode budgets—not only because of the additional overhead, but also because of the churn and inefficiency created by inconsistent work product from inexperienced, new reviewers. A good managed review partner will prepare for and minimise this churn from the outset, by creating customised briefing documentation that enables new reviewers to roll onto matters seamlessly, without a heavy lift from the client or review manager. Documentation like term glossaries for niche cases (for example, medical inquiries) that are kept in a central repository will help case teams quickly scale up and onboard new reviewers at short notice, while minimizing the churn and risk often thought of as inevitable when adding new reviewers. Look for a partner who has developed ways to ensure quality work from review teamsInconsistent or incorrect decisions from review teams creates additional work, which can decimate budgets. Even when data volumes are culled to more manageable levels, inaccurate review work product can still open clients up to risk, especially when sensitive data is involved. Look for managed review partners who have systems in place to ensure the accuracy of the review team from the outset. For example, some managed review providers will rigorously “test” the work product of review teams, directly after training has finished. This testing process can ensure that each reviewer assigned to the team understands the subject matter and review process, and that from the start of the matter their work product aligns with the case team’s direction. This type of quality control, started at the reviewer selection process, can greatly reduce risk while keeping budgets under control. Look for a managed review partner who ensures value for money in terms of candidatesIn a traditional approach, first pass review for relevance, privilege, and issues are undertaken by UK-based paralegals, with proven experience in reviewing and redacting documents together with a law degree, LPC/GDL, or NALP certification. However, these reviewers can be expensive, and billed at exorbitant hourly rates. Forward-thinking managed review partners often have partnerships with reviewers who have been admitted to Bars outside of the UK, providing an added layer of experience offered at a reduced cost. This complies with the overall message of PD 57AD, in that it offers a reliable basis for costs which promotes the cost-effective and efficient conduct of disclosure. [1] Model A – No order for disclosure; Model B – Limited disclosure; Model C – Request-led, search-based disclosure; Model D – Narrow search-based disclosure (with or without narrative documents); Model E – Wide search-based disclosureediscovery-reviewreview, blog, ediscovery-review,review; blogjennifer cowman

As legal teams expand their responsibilities and business impact throughout their organizations, there’s a delicate balance legal professionals must strike in their roles: be better partners and balance risk.To tease out this complex and dynamic relationship, Megan Ferraro, Associate General Counsel of eDiscovery and Information Governance at Meta, recently joined as a guest on Law & Candor.Highlights from that conversation are below.The legal function's bigger roleLegal departments are playing a more significant part in strategy and innovation because the role of in-house counsel has changed greatly in the past few decades. There's been a considerable shift in forward-thinking companies from viewing legal as a blocker to more of a strategic partner.Successful legal teams are partnering internally to ensure attorneys across their organization get early signals to address potential inquiries in litigation or investigations. Additionally, companies are now hiring in-house teams to fill roles where those legal partners can identify and assess legal risk early on.In-house counsel have become advocates for why legal deserves a seat at the table at all company levels, which contributes to the overall success of the business.A great example of how legal is partnering with other parts of their organizations to drive innovation is through the role of product counsel at technology companies. The most effective product counsel have a deep understanding of product goals early, which helps them to identify and address legal issues more quickly and accurately. By working closely with the product team through development, updates, and deployment, they also serve as a conduit between legal and product teams to help advance projects and address potential risks.Critical risks for legal teams todayOne of the most significant challenges for in-house legal teams is keeping up with the pace of their organization’s growth—whether it’s developing products and services, forging unique partnerships, or adopting new technology and software.Often, business teams do not appreciate how even the slightest difference in facts can contribute to different outcomes in the law. Managing the expectations of the business regarding the time it takes to do legal analysis is extremely important.It's normal to take the time to think about these challenging issues. An important adage for the business to remember is that the law is not “Minute Rice.”The balancing act between risk and innovationWeighing risk and innovation requires that you keep pace with changes throughout the organization, including pivots in strategic priorities, with a variety of stakeholders. Staying ahead of these developments and allowing counsel enough time to evaluate potential impacts is key to understanding if the benefits are worth the risk, and if not, how to adjust a business plan accordingly.Along with providing the guidance stakeholders need to assess risk and make decisions, legal teams also frequently manage how organizational data is stored and accessed with IT departments. If other teams throughout the business do not have the information they need, they can't move as fast to help the company innovate. How long to keep data, what format it is in, and who can access it are all questions that can have a huge impact on innovation.Cross-functional collaborationIn-house counsel are increasingly working with other leaders in their organizations to inform strategic decisions, but having a seat at the table requires listening and staying connected to “clients” within the business. Strategic priorities can change very often, especially in a fast-paced environment.Knowing not just what these priorities are but how the business interprets them and what success means to the company will contribute to the most successful legal partners for balancing risk factors and supporting innovation.To listen to the full conversation and hear more stories from the legal technology revolution, check out Law & Candor.ai-and-analytics; information-governanceblog, risk-management, ai-and-analytics, information-governanceblog; risk-managementlighthouse

Among data challenges that businesses and their law firms face, those surrounding mergers and acquisitions are arguably some of the most daunting. Fast-paced and demanding, the high-stakes M&A process is like an amped-up litigation and investigation combined, with specific M&A data requirements, massive document productions, fact-finding imperatives, and more.To add a bit of drama, inflationary pressure and fears of a recession could cool M&A activity, while the impacts of the pandemic continue to make regulatory reaction to the M&A landscape unpredictable, especially as to whether an HSR Second Request will be in the offing. If there is Second Request, document requirements ramp up and so does heightened scrutiny from regulatory agencies, especially in light of the 2021 Executive Order on Promoting Competition in the American Economy. “Providing heightened scrutiny to a broader range of relevant market realities is core to fulfilling our statutory obligations under the law.” – FTC, 2021Know as much as you can, as soon as you canIn a Second Request (as with any legal matter), the more you know and the sooner you know it, the better. Since technology assisted review (TAR), continuous active learning (CAL), and other eDiscovery technology has largely usurped a linear responsive review process, there is often less need for attorneys to review the majority of the documents that get produced to the government. This is good news for attorneys, who are faced with ever-growing data volumes that would be nearly impossible to tackle using a linear document review process, while still meeting the tight substantial compliance timeframe in a typical Second Request. However, less human review during the eDiscovery process elevates the need for counsel to find a way to uncover key information within the documents for fact development, witness kits, or expert support.From a data standpoint, what fact-finding can be done early using human expertise, technology, and a specific search workflow? The sophisticated analytics tools available today make any number of assessments possible, even before data is collected. Basic data characteristics gleaned from metadata can reveal important information: email domains, recipients, BCCs, timestamps—such metadata is fodder for data analytics tools that can reveal custodians, relationships, timelines, communications patterns and more, all necessary information in regulatory matters. Companies that have found a way to have previously-assessed characteristics live with a document (think privilege, PII, confidentiality status) are really ahead of the game.Let’s also not forget that evidence of anti-competitive behavior is really what Second Requests are all about. Although there are plenty of market facts and figures to be scrutinized, communications among people who are knowledgeable about the proposed deal could tell an “interesting” story. Common words and phrases casually bandied about (“dominant player,” “sticky customers”) can be laden with meaning to regulators or attorneys, throwing up red flags for further investigation. Company data stores can thus either be a gold mine or a land mine—and it helps counsel tremendously if they have the information on hand to prepare for either circumstance. Finding key documents: a surgical strike, not a data dumpIdentifying key information requires a precise approach and assessment —it’s not something that can be accomplished with a keyword list created during a brainstorming session. Keywords can’t help much if you don’t know exactly what you’re looking for. Rather, finding key documents today can be an elevated process—one that is technology-enabled and executed by a nimble team that can leverage linguistic expertise, proven search algorithms and processes, and proprietary technology to quickly pinpoint and deliver a highly-curated set of documents on target topics. As key information is uncovered, further fact-finding can be curtailed or expanded. A team can adapt to any change in priorities, custodians, subjects, and/or time frames as a regulator changes the focus of the review. This reduces the amount of time counsel must spend going through documents, keeping costs in check, and providing the best ROI.Between the initial filing and receipt of a Second Request, especially when there is little doubt that the Second Request will be issued, a team executing key document identification can help kick off the fact-finding and development process with whatever data is available—before any responsiveness review has even begun.And even when no Second Request is issued, a team of experts executing key document identification can play a significant role. In support of an initial filing, they can help identify 4(c) and 4(d) documents that are required as part of the disclosure and get the best instance or latest version of important documents. This is especially helpful in situations where executives or others involved in the deal have massive data populations and don’t know where the relevant documents are. ConclusionIdentifying key documents is a critical part of a Second Request. If client and counsel are well-prepared—armed with the ability to leverage expertise and advanced technology to find key documents from the get-go—the most challenging hurdles can often be overcome, enabling timely compliance, and avoiding potential complications that could delay resolution—or even kill the deal. antitrust; ediscovery-reviewantitrust, ediscovery-reviewhsr-second-requests; bloglighthouse