Category Archives: Best Practices

Federal Judge: Custodian Self-Collection of ESI is Unethical and Violates Federal Rules of Civil Procedure

By John Patzakis

In E.E.O.C. v. M1 5100 Corp., (S.D. Fla. July 2, 2020), Federal District Judge Matthewman excoriated defense counsel for allowing the practice of unsupervised custodian ESI self-collection, declaring that the practice “greatly troubles and concerns the court.” In this EEOC age discrimination case, two employees of the defendant corporation were permitted to identify and collect their own ESI in an unsupervised manner. Despite no knowledge of the process the client undertook to gather information (which resulted in only 22 pages of documents produced), counsel signed the responses to the RFP’s in violation of FRCP Rule 26(g), which requires that the attorney have knowledge and supervision of the process utilized to collect data from their client in response to discovery requirements.Gavel and books

This notable quote from the opinion provides a very strong legal statement against the practice of ESI custodian self-collection:

“The relevant rules and case law establish that an attorney has a duty and obligation to have knowledge of, supervise, or counsel the client’s discovery search, collection, and production. It is clear to the Court that an attorney cannot abandon his professional and ethical duties imposed by the applicable rules and case law and permit an interested party or person to ‘self-collect’ discovery without any attorney advice, supervision, or knowledge of the process utilized. There is simply no responsible way that an attorney can effectively make the representations required under Rule 26(g)(1) and yet have no involvement in, or close knowledge of, the party’s search, collection and production of discovery…Abdicating completely the discovery search, collection and production to a layperson or interested client without the client’s attorney having sufficient knowledge of the process, or without the attorney providing necessary advice and assistance, does not meet an attorney’s obligation under our discovery rules and case law. Such conduct is improper and contrary to the Federal Rules of Civil Procedure.”

In his ruling, Judge Matthewman stated that he “will not permit an inadequate discovery search, collection and production of discovery, especially ESI, by any party in this case.” He gave the defendant “one last chance to comply with its discovery search, collection and production obligations.”  He then also ordered “the parties to further confer on or before July 9, 2020, to try to agree on relevant ESI sources, custodians, and search terms, as well as on a proposed ESI protocol.” The Court reserved ruling on monetary and evidentiary sanctions pending the results of Defendants second chance efforts.

A Defensible Yet Streamlined Process Is Optimal

EEOC v. M1 5100, is yet another court decision disallowing custodian self-collection of ESI and underscoring the importance of a well-designed and defensible eDiscovery collection process. At the other end of the spectrum, full disk image collection is another preservation option that, while being defensible, is very costly, burdensome and disruptive to operations. Previously in this blog, I discussed at length the numerous challenges associated with full disk imaging.

The ideal solution is a systemized, uniform and defensible process for ESI collection, which also enables targeted and intelligent data collection in support of proportionality principles. Such a capability is only attainable with the right enterprise technology. With X1 Distributed Discovery (X1DD), parties can perform targeted search and collection of the ESI of hundreds 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%), thereby bringing much needed feasibility to enterprise-wide eDiscovery collection that can save organizations millions while improving compliance by maintaining metadata, generating audit logs and establishing chain of custody.

And in line with the Judge’s guidance outlined in EEOC v. M1 5100, X1DD provides a repeatable, verifiable and documented process for the requisite defensibility. For a demonstration or briefing on X1 Distributed Discovery, please contact us.

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Filed under Best Practices, Case Law, collection, eDiscovery, ESI, Uncategorized

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

True Proportionality for eDiscovery Requires Smart Pre-Collection Analysis

By John Patzakis

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. However attorneys representing enterprises are essentially flying blind on this analysis when it matters most. Prior to the custodian data being actually collected, processed and analyzed, attorneys do not have any real visibility into the potentially relevant ESI across an organization. This is especially true in regard to unstructured, distributed data, which is invariably the majority of ESI that is ultimately collected in a given matter.proportionality

If accurate pre-collection data insight were available to counsel, that game-changing factor would enable counsel to set reasonable discovery limits and ultimately process, host, review and produce much less ESI.  Counsel can further use pre-collection proportionality analysis to gather key information, develop a litigation budget, and better manage litigation deadlines. Such insights can also foster cooperation by informing the parties early in the process about where relevant ESI is located, and what keywords and other search parameters can identify and pinpoint relevant ESI.

The problem is any keyword protocols are mostly guesswork at the early stage of litigation, as, under outdated but still widely used eDiscovery practices, the costly and time consuming steps of actual data collection and processing must occur before meaningful proportionality analysis can take place. When you hear eDiscovery practitioners talk about proportionality, they are invariably speaking of a post-collection, pre-review process. But without requisite pre-collection visibility into distributed ESI, counsel typically resort to directing broad collection efforts, resulting in much greater costs, burden and delays.

X1 recently hosted a webinar featuring prominent industry experts including attorney David Horrigan of Relativity, Mandi Ross of Prism Litigation Technology and Ben Sexton of JND eDiscovery, addressing the issues of remote ESI collection and proportionality. David Horrigan outlined in succinct detail the legal concepts of proportionality under the Federal Rules, the Sedona Principles and as applied in case law. Mandi Ross explained how she applies proportionality when advising lawyers and judges through custodian interviews, coupled with detailed keyword search term analysis based upon the matter’s specific claims and defenses. She noted that technology such as X1 greatly enables the application of her practice in real time: “The ability to index in place is a game changer because we have the ability to gain insight into the data and validate custodian interview data without first requiring that data to be collected.”

The webinar also featured a live exercise performing a pre-collection proportionality analysis on remote employee data with X1 Distributed Discovery. The panelists provided comments and insights contrasting what they saw with the outdated, costly, and time consuming process involving manual data collection and subsequent migration into a hardware processing appliance. The later process negates counsel’s ability to conduct any meaningful application of proportionality, without first incurring significant expense and loss of time. A recording of the webinar can be accessed here.

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