Industry Experts from Relativity and Insight Optix Discuss Operationalizing Proportionality

By John Patzakis

Industry experts including Relativity eDiscovery attorney David Horrigan, Relativity Product Manager Greg Evans and Insight Optix CEO Mandi Ross addressed utilizing cutting-edge ESI collection processes and technologies to effectuate proportionality in a recent webinar. 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. While proportionality is an often-discussed ideal sought by most legal stakeholders, especially corporate counsel, the discussion focused on how to use processes and best practices to operationally attain this goal.

David Horrigan first provided a detailed analysis of Rule 26(b)(1), and some key case law applying the proportionality rule, including McMaster v. Kohl’s Dep’t Stores, Inc., No. 18-13875 (E.D. Mich. July 24, 2020). Horrigan commented that McMaster generally supports the application of a process that effectively applies proportionality on an operational basis through an iterative exercise to identify relevant custodians, their data sources, applicable data ranges, file types and agreed upon keywords. Such a “targeted, automated and proportional” collection process can be applied to collect only the data that is responsive to this specific criteria.

Mandi Ross explained that proportionality is getting a further boost as George Washington University Law School is sponsoring the development of 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. Mandi is key leader of a team of industry legal and technology exports drafting the GW Law model.

Mandi then outlined her typical workflow applying the aforementioned proportionality heat map in an iterative manner to identify key custodians, data sources, and the potentially relevant data itself. To effectuate this, Mandi noted that “X1 Distributed Discovery and Relativity Collect gives us the ability to understand the story the data tells, using (X1’s) index in-place and also allows us to optimize and target our collection efforts.”

To illustrate Mandi’s point, the webinar then featured a live demonstration showing X1 quickly collecting data across custodians from their laptops, fileservers or other network sources, and seamlessly importing that data into RelativityOne in minutes. Relativity Product Manager Greg Evans 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.”

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, automated and proportional 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.

A recording of the webinar on proportionality can be accessed here.

And a link directly to the demo featuring the X1 and Relativity integration can be accessed here.

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