Tag Archives: litigation

Dale vs. Deutsche Telekom AG Illustrates the Importance of Effective ECA to Attain Proportionality

By John Patzakis

In Dale v. Deutsche Telekom AG, No. 22 C 3189 (N.D. Ill. Oct. 4, 2024), a class-action antitrust litigation stemming from the 2020 merger between T-Mobile and Sprint, the Court denied the plaintiffs’ motion to expand a proposed custodian list from fifty custodians to sixty, including three in-house attorneys. The court stated that adding the additional custodians would be “out of proportion to the needs of the case.”

Magistrate Judge Jeffrey Cole began the order by quoting Vakharia v. Swedish Covenant Hosp.: “The discovery rules are not a ticket to an unlimited, never-ending exploration of every conceivable matter that captures an attorney’s interest. Parties are entitled to a reasonable opportunity to investigate the facts—and no more.” He also added: “The inescapable reality is that discovery has come to dominate civil litigation…Proportionality, like other concepts, it is not self-defining; it requires a common sense and experiential assessment…In other words, all are agreed that discovery has gotten out of hand over the years and needs to be reigned in.”

The Court’s opinion detailed the ill-fated negotiations between the parties, with a key take-away being the lack of visibility Deutsche Telekom’s in-house counsel had into their own custodians’ data, which stymied their ability to effectively eliminate guess work and limit the number of custodians. This case illustrates that while there is a keen awareness of proportionality in the legal community, realizing the benefits requires the ability to operationalize workflows as far upstream in the eDiscovery process as possible. For instance, when you are engaging in data over-collection, which in turn incurs extensive labor and processing costs, the ship has largely sailed before you are able to perform early case assessments and data relevancy analysis, as much of the discovery costs have already been incurred at that point. The case law and the Federal Rules provide that the duty to preserve only applies to potentially relevant information, but unless you have the right operational processes in place, you are losing out on the ability to attain the benefits of proportionality.

However, traditional eDiscovery services typically involve manual collection, followed by manual on-premises hardware-based processing, and finally manual upload to review. These inefficiencies extend projects by often weeks while dramatically increasing cost and risk with purposeful data over-collection and dozens of manual data handoffs. The good news is that solutions and processes addressing the first half of the EDRM involving collection and processing are now far more automated.

To accomplish the goals of gaining early visibility into your data to foster more intelligent early case assessment, informed discovery negotiations with opposing counsel, and targeted, proportional data collection, corporate legal department should utilize index and search in-place technology. Indexing and search in-place in this context means that a software-based indexing technology (as opposed to an expensive and cumbersome stand-alone hardware appliance) is deployed directly onto the laptop, file server or in the cloud for Microsoft 365 data sources. This indexing occurs without a bulk data transfer of the data. Once indexed, you can search through terabytes of information in seconds, with complex Boolean operators, metadata filters and regular expression searches. Legal teams can iterate and repeat their searches without limitation, which is critical for large data sets.

These capabilities supporting targeted and proportional collection of loose files, emails, and large network file shares and M365 are uniquely provided in the X1 Enterprise Platform.

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Filed under Best Practices, Case Law, eDiscovery, eDiscovery & Compliance, Enterprise eDiscovery, ESI, Information Governance, m365, Preservation & Collection, proportionality

Addressing Critical Information Governance Challenges from Departing Employees

By John Patzakis and Chas Meier

When employees leave an organization, they often leave behind a significant amount of valuable information. This poses major information governance challenges, as companies must decide how to manage litigation holds and retain essential data assets.

A common response to this challenge is to retain departed employees’ laptops, hard drives, or keep their Microsoft 365 or Google Workspace accounts active. However, this approach is both expensive and inefficient. Another often-used method is creating a full disk image of the laptop for archiving. While this preserves data, it is a slow and cumbersome process that can require vast amounts of storage, sometimes reaching petabytes, which becomes both costly and unwieldy. Neither approach offers the ability to gain insights from the data, nor do they allow for intelligent and targeted data extraction, making it difficult to leverage these data assets effectively or comply with legal and regulatory requirements.

To address these challenges, X1 has developed a game-changing workflow utilizing our X1 Enterprise Platform, offering a streamlined and cost-effective solution. With our platform, organizations can process hundreds of laptops and Microsoft 365 accounts in a single day. Leveraging X1’s unique and patented in-place indexing technology, data extraction becomes highly targeted, allowing for efficient responses to litigation holds. This means that each litigation scenario can have a tailored search applied across all relevant data sources simultaneously, enabling precise data extraction.

For example, one company with over two dozen active litigation holds has employed X1’s solution, allowing them to save detailed keyword search routines crafted by their counsel. These searches can be quickly and programmatically applied not only to data on specific laptops but also to archived PSTs and associated Microsoft 365 accounts. Once the targeted data is extracted, the company repurposes the laptops for new employees, resulting in significant cost savings—estimated to be in the millions—and a reduction in storage requirements.

Beyond managing litigation holds, another core benefit of X1’s solution is its ability to extract key data assets from departed employees to retain within the company’s knowledge base. This capability is especially valuable for law firms, consulting firms, and organizations that rely heavily on high-end knowledge professionals. For instance, one law firm uses X1’s workflow to rapidly search large, archived PST files from departed attorneys to identify and separate key data related to ongoing matters. This ensures that crucial information remains accessible to the firm or is appropriately transferred to the attorney’s new firm. Additionally, vital legal and business insights from retained documents and emails are quickly mined and reviewed, enhancing the firm’s overall knowledge management.

Client Example:
Overview: A major pharmaceutical retailer uses X1 within Relativity to perform 50 data collections weekly, covering both Mac and PC environments. The system allows them to repurpose laptops from departed employees within days instead of months, leading to substantial savings.
Integration: The company eliminated the need for traditional eDiscovery tools to remediate laptops, opting instead for X1’s more efficient approach.
Time and Cost Savings: This shift has saved the company millions by:
1. Reducing the reliance on costly traditional eDiscovery tools.
2. Minimizing the risk and cost associated with retaining unnecessary data.
3. Reintroducing millions of dollars’ worth of computer equipment back into circulation.
4. Completing these processes in one-tenth the time it would have traditionally taken, vastly improving operational efficiency.

Conclusion:
In today’s fast-paced and data-driven world, organizations face numerous challenges when it comes to managing and retaining data from departed employees. Traditional methods, such as retaining physical devices or creating full disk images, are not only costly and time-consuming but also fail to provide the flexibility and insight needed to effectively manage information assets. X1’s innovative solutions, particularly its patented in-place indexing technology, offer a modern, scalable, and efficient alternative. By enabling targeted data extraction, streamlining the process for litigation holds, and supporting knowledge retention, X1 empowers organizations to manage data governance with precision and agility.

For companies navigating complex data environments, especially those utilizing BYOD policies, X1 Enterprise Platform ensures compliance while protecting privacy. By implementing X1’s advanced platform, organizations can not only reduce costs and save valuable time but also gain a strategic advantage in managing their information governance needs. We invite you to explore how X1 can transform your data management processes and help you stay ahead in the ever-evolving digital landscape.

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X1 Achieves Unmatched Throughput and Results in Several Recent M365 eDiscovery and Information Governance Engagements

By John Patzakis and Chas Meier

As discussed previously on this blog, X1 and our active enterprise customers believe X1 Enterprise Collect is the best solution available to address M365 data sources as well as on-premises sources such as laptops and file shares. In recent weeks, our customers and partners have executed several projects on a massive scale and have captured and documented X1’s performance metrics.

No other solution in the industry can index data across the enterprise as fast or as scalable as the X1 Enterprise platform, including Microsoft Purview Premium. When compared to Microsoft Purview, with its built-in architectural constraints and throttling limitations, X1 can index nearly eight times the daily volume of Purview or any other competitive “connector” technology can achieve in the market. X1’s distributed index-in-place methodology, combined with horizontal scaling of our index hosts, make X1 the only solution truly capable of handling the rapid indexing, identification, searching and collecting/remediation of mass data sets in the TB’s or PB’s across the modern enterprise. X1 effectively addresses cloud and on-premises data sources in a unified manner, including distributed endpoints, network file shares, M365 data sources including Mail, OneDrive, Teams, and SharePoint, as well as other cloud data sources.

In several recent large-scale eDiscovery and information governance projects, X1 Enterprise Collect, on average, was able to collect and index M365 data (MS Mail [including archived mail and modern attachments] Teams, One Drive and SharePoint) at a rate of approximately 350 GB per day. This is nearly 8 times faster than Microsoft Purview, with its documented throughput limitations at 2GB per hour. X1 can achieve even faster throughput by scaling out virtual cloud computing resources.

Daily indexing volumes for endpoints and on-premises file shares vary due to the performance characteristics of each machine, but X1 indexes and searches endpoints in parallel yielding extremely high aggregate daily indexing and collection throughput.

Detailed documentation on these metrics and a further briefing on these engagements can be provided upon request.

X1 achieves such scalability through a decentralized approach that does not rely on the M365 or Purview search Index, which has known issues with the number of file types supported, consistency of search results, accuracy, and throughput. X1’s approach enables a very scalable, accurate, defensible, and robust indexing and data collection at unmatched speeds.

In addition to greatly reducing risk, X1’s capabilities also enable massive cost savings. X1 Enterprise Collect significantly streamlines the eDiscovery workflow by bringing targeted collection results directly into the review platform, thereby eliminating over collection, over processing, and over importing just to cull. X1 will populate ESI (Electronically Stored Information) straight into Relativity from an X1 collection without multiple hand offs, extensive project management and inefficient data processing.

The ability to collect data directly and transparently from custodian laptops, desktops, M365 and other cloud sources into a RelativityOne/Relativity workspace is a game-changer that enables legal and compliance teams to begin review in hours rather than weeks. As facts become known and collection focus changes, X1 allows teams to pivot and respond in hours. With the ability to efficiently take multiple bites of the apple, X1 enables teams to start fast and stay agile.

For a demonstration of the X1 Enterprise Collect Platform, contact us at sales@x1.com. For more details on this innovative solution, please visit www.x1.com/x1-enterprise-collect-platform.

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Filed under Best Practices, Cloud Data, Corporations, ECA, eDiscovery, eDiscovery & Compliance, Enterprise eDiscovery, ESI, Information Governance, MS Teams, OneDrive, Preservation & Collection, SharePoint

Key to Improving Predictive Coding Results: Effective ECA

Predictive Coding, when correctly employed, can significantly reduce legal review costs with generally more accurate results than other traditional legal review processes. However, the benefits associated with predictive coding are often undercut by the over-collection and over-inclusion of Electronically Stored Information (ESI) into the predictive coding process. This is problematic for two reasons.

The first reason is obvious, the more data introduced into the process, the higher the cost and burden. Some practitioners believe it is necessary to over-collect and subsequently over-include ESI to allow the predictive coding process to sort everything out. Many service providers charge by volume, so there can be economic incentives that conflict with what is best for the end-client. In some cases, the significant cost savings realized through predictive coding are erased by eDiscovery costs associated with overly aggressive ESI inclusion on the front end.

The second reason why ESI over-inclusion is detrimental is less obvious, and in fact counter intuitive to many. Some discovery practitioners believe as much data as possible needs to be put through the predictive coding process in order to “better train” the machine learning algorithms. However this is contrary to what is actually true. The predictive coding process is much more effective when the initial set of data has a higher richness (also referred to as “prevalence”) ratio. In other words, the higher the rate of responsive data in the initial data set, the better. It has always been understood that document culling is very important to successful, economical document review, and that includes predictive coding.

Robert Keeling, a senior partner at Sidley Austin and the co-chair of the firm’s eDiscovery Task Force, is a widely recognized legal expert in the areas of predictive coding and technology assisted review.  At Legal Tech New York earlier this year, he presented at an Emerging Technology Session: “Predictive Coding: Deconstructing the Secret Sauce,” where he and his colleagues reported on a comprehensive study of various technical parameters that affect the outcome of a predictive coding effort.  According to Robert, the study revealed many important findings, one of them being that a data set with a relatively high richness ratio prior to being ingested into the predictive coding process was an important success factor.

To be sure, the volume of ESI is growing exponentially and will only continue to do so. The costs associated with collecting, processing, reviewing, and producing documents in litigation are the source of considerable pain for litigants. The only way to reduce that pain to its minimum is to use all tools available in all appropriate circumstances within the bounds of reasonableness and proportionality to control the volumes of data that enter the discovery pipeline, including predictive coding.

Ideally, an effective early case assessment (ECA) capability can enable counsel to set reasonable discovery limits and ultimately process, host, review and produce less ESI.  Counsel can further use ECA to gather key information, develop a litigation budget, and better manage litigation deadlines. ECA also can foster cooperation and proportionality in discovery by informing the parties early in the process about where relevant ESI is located and what ESI is significant to the case. And with such benefits also comes a much more improved predictive coding process.

X1 Distributed Discovery (X1DD) uniquely fulfills this requirement with its ability to perform pre-collection early case assessment, instead of ECA after the costly, time consuming and disruptive collection phase, thereby providing a game-changing new approach to the traditional eDiscovery model.  X1DD enables enterprises to quickly and easily search across thousands of distributed endpoints from a central location.  This allows organizations to easily perform unified complex searches across content, metadata, or both and obtain full results in minutes, enabling true pre-collection ECA with live keyword analysis and distributed processing and collection in parallel at the custodian level. To be sure, this dramatically shortens the identification/collection process by weeks if not months, curtails processing and review costs from not over-collecting data, and provides confidence to the legal team with a highly transparent, consistent and systemized process. And now we know of another key benefit of an effective ECA process: much more accurate predictive coding.

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Filed under ECA, eDiscovery

LTN: Social Media Evidence Even More Important than email and “Every Litigator” Needs to Address It

legaltech-news-thumbBrent Burney, a top eDiscovery tech writer of Legaltech News, recently penned a detailed product review of X1 Social Discovery after his extensive testing of the software. (Social Media: A Different Type of E-Discovery Collection, Legaltech News, September 2016). The verdict on X1 Social Discovery is glowing, but more on that in bit. Burney also provides very remarkable general commentary on how social media and other web-based evidence is essential for every litigation matter, noting that “email does not hold a flicker of a candle to what people post, state, admit and display in social media.” In emphasizing the critical importance of social media and other web-based evidence, Burney notes that addressing this evidentiary treasure trove is essential for all types and sizes of litigation matters.

Consistent to that point, there is a clear dramatic increase in legal and compliance cases involving social media evidence. Top global law firm Gibson Dunn recently reported that “the use of social media continues to proliferate in business and social contexts, and that its importance is increasing in litigation, the number of cases focusing on the discovery of social media continued to skyrocket.” Undoubtedly, this is  why Burney declares that “every litigator should include (X1 Social Discovery) in their technical tool belt,” and that X1 Social Discovery is “necessary for the smallest domestic issue all the way up to the largest civil litigation matter.” Burney bases his opinion on both the critical importance of social media evidence, and his verdict on the effectiveness of X1 Social Discovery, which he lauds as featuring an interface that “is impressive and logical” and providing “the ideal method” to address social media evidence for court purposes.

From a legal commentary standpoint, two relevant implications of the LTN article stand out. First, the article represents important peer review, publication and validation of X1 Social Discovery under the Daubert Standard, which includes those factors, among others, as a framework for judges to determine whether scientific or other technical evidence is admissible in federal court.

Secondly, this article reinforces the view of numerous legal experts and key Bar Association ethics opinions, asserting that a lawyer’s duty of competence requires addressing social media evidence. New Hampshire Bar Association’s oft cited ethics opinion states that lawyers “have a general duty to be aware of social media as a source of potentially useful information in litigation, to be competent to obtain that information directly or through an agent, and to know how to make effective use of that information in litigation.” The New York State Bar similarly weighed in noting that “A lawyer has a duty to understand the benefits and risks and ethical implications associated with social media, including its use as a … means to research and investigate matters.” And the America Bar Association recently published Comment [8] to Model Rule 1.1, which provides that a lawyer “should keep abreast of changes in the law and its practice, including the benefits and risks associated with relevant technology.”

The broader point in Burney’s article is that X1 Social Discovery is enabling technology that provides the requisite feasibility for law firms, consultants, and other practitioners to transition from just talking about social media discovery to establishing it as a standard practice.  With the right software, social media collections for eDiscovery matters and law enforcement investigations can be performed in a very scalable, efficient and highly accurate process. Instead of requiring hours to manually review and collect a public Facebook account, X1 Social Discovery can collect all the data in minutes into an instantly searchable and reviewable format.

So as with any form of digital investigation, feasibility (as well as professional competence) often depends on utilizing the right technology for the job.  As law firms, law enforcement, eDiscovery service providers and private investigators all work social discovery investigations into standard operating procedures, it is critical that best practices technology is incorporated to get the job done. This important LTN review is an emphatic punctuation of this necessity.

 

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