Category Archives: ECA

On TAP: Targeted, Automated, and Proportional Collection for Modern e-Discovery

By John Patzakis

Proportionality is now the hottest legal issue in the area of eDiscovery, with the largest number of eDiscovery-related cases in the past year addressing the subject. eDiscovery attorney Kelly Twigger leads a team who produced an excellent analysis of 2020 case law, noting “a big jump to 889 in 2020” of cases addressing proportionality, “which represented nearly a third (31%) of all (eDiscovery) case law decisions last year.” The report notes that “[p]roportionality arguments have become a weapon in arguing scope of discovery and the sharp rise in disputes has illustrated the need for more systematic and standardized approaches to assessing proportionality in cases today.” 

Proportionality-based eDiscovery is a goal that all judges and corporate attorneys want to attain. Under Federal Rule of Civil Procedure 26(b)(1), parties may discover any non-privileged material that is relevant to any party’s claim or defense and proportional to the needs of the case. Lawyers that take full advantage of the proportionality rule can greatly reduce cost, time and risk associated with otherwise inefficient eDiscovery.

Proportionality is getting a further boost as George Washington University Law School is developing an important proportionality benefit-and-burden model that provides a practical structure for assessing claims of proportionality. The model features a heat map mechanism to identify relevant custodians and data sources to enable a more objective application of proportionality, thereby facilitating negotiations and better informing the bench.

The GW Law model is much needed, as while there is keen awareness of proportionality in the legal community, attaining the benefits requires the ability to operationalize workflows as far upstream in the eDiscovery process as possible. For instance, when you’re engaging in data over-collection, which in turn runs up of a lot of human time 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’re losing out on the ability to attain the benefits of proportionality.

An example of a process that effectively applies proportionality on an operational basis would be an iterative exercise to identify relevant custodians, their data sources, applicable data ranges, file types and agreed upon keywords, following the process outlined in  McMaster v. Kohl’s Dep’t Stores, Inc., No. 18-13875 (E.D. Mich. July 24, 2020), and collect only the data that is responsive to this specific criteria. The latest enterprise collection tech from Relativity and X1 enable such detailed and proportional criteria to be applied in-place, at the point of collection. This reduces the data volume funnel by as much as 98 percent from over-collection models, yet with increased transparency and compliance. In other words, a collection process that targeted, automated and proportional, instead of one that is overbroad and manual.

To learn more about these concepts, please tune in on April 13, where attorney David Horrigan of Relativity and Mandi Ross of Prism Litigation Technology will be leading a webinar to discuss the legal and operational considerations and benefits of proportionality. The webinar will also feature a live exercise performing a pre-collection proportionality analysis on remote employee data. You can register here.

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Filed under Best Practices, Case Law, ECA, eDiscovery, eDiscovery & Compliance, Enterprise eDiscovery, ESI, law firm, Preservation & Collection, proportionality

Full Disk Imaging Not Required for eDiscovery Collections

In Fact, Courts and Legal Commentators Disfavor the Practice

By John Patzakis[1]

The collection and preservation of Electronically Stored Information (ESI) in the enterprise remains a significant and costly pain point for organizations. Leading industry research firm Gartner notes that eDiscovery collection and preservation processes “can be intrusive, time consuming and costly.”[2]  And recent court decisions imposing sanctions on corporate litigants who failed to meet their ESI preservation obligations are symptomatic of these pain points.[3]

A key issue regarding collection is that many in the eDiscovery services community standardized on full disk imaging as their default collection practice.  This is problematic for several reasons. For one, full-disk imaging is burdensome because the process often involves service providers traveling out to the individual custodians, which is very disruptive to employees, not to mention time consuming. Additionally, as eDiscovery processing and hosting fees are usually calculated on a per-gigabyte basis, costs are increased exponentially. In a word, this is overkill, with much more effective and efficient options now available.

Full disk images capture every bit and byte on a hard drive, including system and application files, unallocated space and a host of irrelevant user-created data. While full disk images may be warranted in some limited situations, the expense and burden associated with the practice can be quite extensive, particularly in matters that involve multiple custodians.

It is established law that the duty to preserve evidence, including ESI, extends only to relevant information[4]  The vast majority of ESI on a full disk image will typically constitute irrelevant information. As stated by one court, “imaging a hard drive results in the production of massive amounts of irrelevant, and perhaps privileged, information.”[5] The highly influential Sedona Conference notes: “Civil litigation should not be approached as if information systems were crime scenes that justify forensic investigation at every opportunity to identify and preserve every detail.”

And that: “Forensic data collection requires intrusive access to desktop, server, laptop, or other hard drives or media storage devices.”  While noting the practice is acceptable in some limited circumstances, “making a forensic copy of computers is only the first step of an expensive, complex, and difficult process of data analysis . . . it should not be required unless circumstances specifically warrant the additional cost and burden and there is no less burdensome option available.”[6]

This disfavoring of forensic imaging is also reflected in the increased emphasis of proportionality under recent amendment to Federal Rule of Civil Procedure 26(b)(1). The over-arching theme from case law and the Federal Rules is that ESI preservation efforts should be reasonable, proportionate, and targeted to only relevant information, as opposed to being overly broad and unduly burdensome.

Courts do require that ESI be collected in a forensically sound manner, which does not mean a full forensic disk image is required, but generally does entail that metadata is not altered and a documented chain of custody is maintained. More advanced enterprise class technology can accomplish remote searches across multitudes of custodians that are narrowly tailored to collect only potentially relevant information while preserving metadata at the same time. This process is better, faster and dramatically less expensive than manual disk imaging.

In fact, The Sedona principles do outline such an alternative to forensic disk imaging: “Automated or computer-assisted collection involves using computerized processes to collect ESI meeting certain criteria, such as search terms, file and message dates, or folder locations. Automated collection can be integrated with an overall electronic data archiving or retention system, or it can be implemented using technology specifically designated to retrieve information on a case-by-case basis.”

This language maps directly to the capabilities of X1 Distributed Discovery (X1DD), which enables parties to perform targeted search and collection of the ESI of up to thousands of endpoints over the internal network without disrupting operations. The search results are returned in minutes, not weeks, and thus can be highly granular and iterative, based upon multiple keywords, date ranges, file types, or other parameters. This approach typically reduces the eDiscovery collection and processing costs by at least one order of magnitude (90%). This method is sound from an evidentiary standpoint as the collected data is preserved in its native file format with its metadata intact. X1DD features a solid chain of custody and robust logging, tracking and reporting.

And in line with the concepts outlined in the revised Sedona Commentary, X1DD provides a repeatable, verifiable and documented process for the requisite defensibility. 


NOTES:

[1]John Patzakis is the Chief Legal Officer of X1.

[2] “Market Guide for E-Discovery Solutions” Gartner, June 30, 2016

[3] (Matthew Enter., Inc. v. Chrysler Grp. LLC, 2016 WL 2957133 (N.D. Cal. May 23, 2016). (Imposing severe evidentiary including allowing the defense to use the fact of ESI spoliation to rebut testimony from the plaintiff’s witnesses and payment of attorney’s fees incurred by the defendant) Internmatch v. Nxtbigthing, LLC, 2016 WL 491483 (N.D. Cal. Feb. 8, 2016), a U.S. District Court imposed similar sanctions based upon the corporate defendant’s suspect ESI preservation efforts.

[4] Hynix Semiconductor Inc. v. Rambus Inc., 2006 WL 565893 (N.D.Cal. Jan. 5, 2006) at *27. (“The duty to preserve evidence, once it attaches, does not extend beyond evidence that is relevant and material to the claims at issue in the litigation.”)  As noted by the Zubulake court, “Clearly [there is no duty to] preserve every shred of paper, every e-mail or electronic document, and every backup tape…Such a rule would cripple large corporations.”  Zubulake v. UBS Warburg LLC, 220 F.R.D. 212, 217 (S.D.N.Y. 2004) (“Zubulake IV”).

[5] Deipenhorst v. City of Battle Creek, 2006 WL 1851243 (W.D.Mich. June 30, 2006) at *3.  In noting that the “imaging of computer hard drives is an expensive process, and adds to the burden of litigation for both parties,” the Deipenhorst court declined to require the production of  full disk images absent a strong showing of good cause. See also, Fasteners for Retail, Inc. v. DeJohn et al., No 1000333 (Ct. App.Ohio April 24, 2014).

[6] The Sedona Principles, Third Edition: Best Practices, Recommendations & Principles for Addressing Electronic Document Production, 19 Sedona Conf. J. 1 (2018).

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Filed under Authentication, Best Practices, ECA, eDiscovery, ESI, Preservation & Collection

Relativity Highlights Its X1 Integration for ESI Collection

By John Patzakis

Recently, Relativity hosted a live webinar featuring the integration of the X1 Distributed Discovery platform with its RelativityOne Collect solution. This X1/Relativity integration enables game-changing efficiencies in the eDiscovery process by accelerating speed to review, and providing an end-to-end process from identification through production. As stated by Relativity Chief Product Officer Chris Brown: “Our exciting new partnership with X1 highlights our continued commitment to providing a streamlined user experience from collection to production…RelativityOne users will be able to combine X1’s innovative endpoint technology with the performance of our SaaS platform, eliminating the cumbersome process of manual data hand-offs and allowing them to get to the pertinent data in their case – faster.”

The webinar featured a live demonstration showing X1 quickly collecting data across multiple custodians and seamlessly importing that data into RelativityOne in minutes. Relativity Collect currently supports Office 365 and Slack sources, and Relativity Product Manager Greg Evans noted that “this X1 integration will now enable Relativity Collect to also reach emails and files on laptops, servers,” and other network sources. The webinar outlined how the Relativity/X1 integration streamlines eDiscovery processes by collapsing the many hand-offs built into current EDRM workflows to provide greater speed and defensibility. Evans also said that new normal of web-enabled collections of remote custodians and data sources was a major driver for the Relativity/X1 alliance, as “remote collections now represent 90 percent of all eDiscovery collections happening right now.”

Adam Rogers, of Complete Discovery Source, a customer of both X1 and RelativityOne, highlighted a recent major multi-national litigation where the X1 and Relativity integration was critical to the success of the project. Adam noted that the effort would have taken about 30 days utilizing traditional methods, “but with this X1 and Relativity integration, we cut it down to 3 days, because with X1, we were able to index everything in-place, search, analyze and categorize that data right away, and then release that data to Relativity for review.”

The live demonstration performed by Greg Evans highlighted in real time how the integration improves the enterprise eDiscovery collection and ECA process by enabling a targeted and efficient search and collection process, with immediate pre-collection visibility into custodial data. X1 Distributed Discovery enhances the eDiscovery workflow with integrated culling and deduplication, thereby eliminating the need for expensive and cumbersome electronically stored information (ESI) processing tools. That way, the ESI can be populated straight into Relativity from an X1 collection.

The X1 and Relativity integration addresses several pain points in the existing eDiscovery process. For one, there is currently an inability to quickly and remotely search across and access distributed unstructured data in-place, meaning eDiscovery teams have to spend weeks or even months to collect data as required by other cumbersome solutions. Additionally, using ESI processing methods that involve appliances that are not integrated with the collection will significantly increase cost and time delays.

So in terms of the big picture, with this integration providing a complete platform for efficient data search, eDiscovery and review across the enterprise, organizations will save a lot of time, save a lot of money, and be able to make faster and better decisions. When you accelerate the speed to review and eliminate over-collection, you are going to have much better early insight into your data and increase efficiencies on many levels.

A recording of the X1/Relativity integration webinar can be accessed here.

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Lawson v. Spirit Aerosystems: Federal Court Blasts “Bloated” ESI Collection, Rendered TAR Ineffective

By John Patzakis

Technology Assisted Review (TAR), 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 TAR are often undercut by the over-collection and over-inclusion of Electronically Stored Information (ESI) into the TAR process. These challenges played out in spades in the recent decision in Lawson v. Spirit Aerosystems, where a Kansas federal judge issued a detailed ruling outlining the parties’ eDiscovery battles, use of Technology Assisted Review (TAR), and whether further TAR costs should be shifted to the Plaintiff. The ex-CEO of Spirit Aerosystems brought his suit accusing Spirit of unlawfully withholding $50 million in retirement benefits over his alleged violation of a non- compete agreement.

Lessons Learned from New Technology-Assisted Review Case Law ...

The Lawson court outlined two ways in particular how ESI over-collection can detrimentally impact TAR. First, 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 TAR 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 TAR are erased by eDiscovery costs associated with overly aggressive ESI inclusion on the front end. Per the judge in Lawson, “the TAR set was unnecessarily voluminous because it consisted of the bloated ESI collection” due to overbroad collection parameters.

The court also outlined how the TAR 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 TAR. As noted by Lawson court, “the ‘richness’ of the dataset…can also be a key driver of TAR expenses. This is because TAR is not as simple as loading the dataset and pushing a magic button to identify the relevant and responsive documents. Rather, the parties must devote the resources (usually a combination of attorneys and contract reviewers) necessary to “educate” or “train” the predictive algorithm, typically through an ongoing process…” According to the courts’ decision, the inefficiencies in the process resulted in an estimated TAR bill of $600,000 involving the review of approximately 200 GBs of data. This is far too expensive for TAR to be feasible as a standard litigation process, and the problems all started with the “bloated” ESI collection.

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, including the Plaintiff in Lawson, who will, per the courts’ ruling, incur at least a substantial amount of the TAR bill under the cost-shifting order. 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 TAR.

Ideally, an effective and targeted collection capability can enable parties to ultimately process, host, review and produce less ESI.  This capability should enable a pre-collection early case assessment capability (ECA) to 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 TAR 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 hundreds 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 collection and ECA process: much more accurate and feasible technology assisted review.

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Filed under Best Practices, Case Law, Case Study, collection, ECA, eDiscovery, Enterprise eDiscovery, ESI

How to Implement an Effective eDiscovery Search Term Strategy

By Mandi Ross and John Patzakis

A key Federal Rules of Civil Procedure provision that greatly impacts eDiscovery processes is Rule 26(f), which requires the parties’ counsel to “meet and confer” in advance of the pre-trial scheduling conference on key discovery matters, including the preservation, disclosure and exchange of potentially relevant electronically stored information (ESI). With the risks and costs associated with eDiscovery, this early meeting of counsel is a critically important means to manage and control the cost of eDiscovery, and to ensure relevant ESI is preserved.

A very good authority on the Rule 26(f) eDiscovery conference is the “Suggested Protocol for Discovery of Electronically Stored Information,” provided by then Magistrate Judge Paul W. Grimm and his joint bar-court committee. Under Section 8 of the Model Protocol, the topics to be discussed at the Rule 26(f) conference include: “Search methodologies for retrieving or reviewing ESI such as identification of the systems to be searched;” “the use of key word searches, with an agreement on the words or terms to be searched;” “limitations on the time frame of ESI to be searched;” and “limitations on the fields or document types to be searched.”x1-collection-img

Optimizing the process of developing keyword searches, however, is no easy task, especially without the right technology and expertise. The typical approach of brainstorming a list of terms that may be relevant and running the search on a dataset to be reviewed results in a wide range of inefficiencies. Negotiations over proper usage of search terms may become onerous and contentious. Judges are often tasked with making determinations regarding the aptness of the methodology, and many are reluctant to do so. Thus, the use of outside expertise leveraging indexing in place technology is beneficial in building an effective and comprehensive search term strategy.

The courts agree. In Victor Stanley v. Creative Pipe, U.S. District Court Judge Paul Grimm explains, “Selection of the appropriate search and information retrieval technique requires careful advance planning by persons qualified to design effective search methodology.”

Building a sound search strategy is akin to constructing a building. First, lay the foundation with a clear understanding of the claims and defenses of the case and the types of documents that will support a legal strategy. Once a solid foundation is built, the structure of language, logical expressions, and metadata are blended as necessary to create the appropriate set of robust Boolean searches. These searches then target the retrieval of responsive documents, and consistently achieve a staggering 80 percent reduction in data volumes to be reviewed.

It’s quite simple. If a document does not contain the defined language, then the document is unlikely to be relevant. The best way to find the language specific to the claims and defenses is to create a linguistic narrative of the case. This not only helps construct a roadmap for a comprehensive strategy designed to reduce the volume of data, it also creates a thorough categorization system for organization and prioritization of review. The approach is straightforward, flexible, and adaptive to client objectives, whether during early case assessment, linear or technology-assisted review, or anything in between.

The narrative search approach includes the following steps:

  1. Issue Analysis: Create an unambiguous definition of each issue that characterizes the claims being made and the defenses being offered.
  2. Logical Expression Definition: Define the specific expressions that encapsulate each issue. There may be multiple expressions required to convey the full meaning of the issue.
  3. Component Identification and Expansion: Distill each logical expression into specific components. These components form the basis for the expansion effort, which is the identification of words that convey the same conceptual meaning (synonyms).
  4. Search Strategies: Determine the appropriate parameters to be used for proximity, as well as developing a strategy for searching non-standard, structured data, such as spreadsheets, non-text, or database files.
  5. Test Precision and Recall: In tandem with the case team, review small sample sets to refine the logical expression statements to improve precision and recall.

The effectuation of this process requires the right technology that enables its application in real time. The ability to index data in place is a game changer, as it provides legal teams early insight into the data and validates search term sampling and testing instantly, without first requiring data collection. This is in contrast to the outdated, costly, and time-consuming process involving manual data collection and subsequent migration into a physical eDiscovery processing platform. The latter process negates counsel’s ability to conduct any meaningful application of search term proportionality, without first incurring significant expense and loss of time.

X1 Distributed Discovery 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 search analytics with live keyword analysis and distributed processing and collection in parallel at the custodian level. This dramatically shortens the identification/collection process by weeks if not months, curtails processing and review costs by not over-collecting data, and provides confidence to the legal team with a highly transparent, consistent and systemized process.

Led by an experienced consulting team that leverages cutting-edge technology, this innovative narrative methodology, created by the experts at Prism Litigation Technology, enriches common search terms by adding layers of linguistic and data science expertise to create a fully defensible, transparent, and cogent approach to eDiscovery. For more on this workflow, please see the white paper: Don’t Stop Believin’: The Staying Power of Search Term Optimization.


Mandi Ross is the CEO of Prism Litigation Technology (www.prismlit.com)

John Patzakis is Chief Legal Officer and Executive Chairman at X1 (www.X1.com)

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