Electronic Discovery Best Practices Update

I found time recently to make several updates to EDBP.com, the collection of electronic discovery best practices for legal services. There are several additions and revisions, but the primary ones were made to step-one, Litigation Readiness, and step-seven, C.A.R. (computer assisted review).

May be freely used without changesI received input on Litigation Readiness from a practicing attorney who prefers to remain anonymous. He correctly pointed out that the statements on this page pertaining to third-party certification of ESI destruction went too far, especially considering how most large organizations necessarily have to delete data everyday to keep functioning. The revisions make clear that an outside expert audit of ESI destructions to solidify protection under Rule 37(e) only applies to exceptional large-scale data purges.

More input on this collection of pre-suit best practices are welcome. This page is still in its early formative stage. You can contribute anonymously, as done here, or can receive credit for any significant contributions. Links to excellent articles on the subject are also appreciated. Please send me suggestions. Remember, EDBP is focused solely on attorney work, the practice of law, and not on technology per se. The non-legal e-discovery work performed by other members of a e-discovery team are not included in EDBP. This differentiates this work-flow model from its much older, big brother.

EDBP_5-9Portions of the CAR best practices pages are now fairly well articulated, with several recent additions made. But your input on computer assisted review issues is also invited, especially on the Review Quality Controls section of CAR. That still has a long way to go.

The next step of Protections has not been written-up at all. When completed it will include best practices for the legal tasks of Redaction, Privilege Logs, Confidentiality Agreements and Orders, and Clawback Agreements and Orders. By the way at a recent CLE I attended in Pittsburgh both Judge Frank Maas and Judge John Facciolla said it was borderline malpractice not to have a clawback order entered in a case with serious ESI.

I divide the CAR best practices into a primary page, that just has a short introduction, and the sub-pages where most of the content resides:

I recently added several revisions and citations in the Predictive Coding page, including a summary of a recent article by Warwick Sharp, Ten Essential Best Practices in Predictive Coding (Today’s General Counsel, May 2013). Warwick, who I don’t think I’ve ever met, is a co-founder of Equivo and VP. His suggestions were all good and warranted inclusion on EDBP. I also added to this page a discussion of the difference between a control set and a training set, something that I touched upon in my most recent robot animation, Robots From The Not-Too-Distant Future Explain How They Use Random Sampling For Artificial Intelligence Based Evidence Search.

I also added citations to two excellent white papers from KPMG. They were added to both the Predictive Coding and Review Quality Control pages, where there is anyway some overlap. The best and most recent KPMG white paper was by Manfred Gabriel entitled Quality Control For Predictive Coding In e-Discovery (2013). The predecessor paper, The Case For Statistical Sampling In e-Discovery (2012), by multiple KPMG authors, Chris Paskach, Michael Carter, and Phil Strauss, was also very good.

I know Manfred, who is now a principal at KPMG, from presenting together at Legal Tech a few years back with Jason R. Baron on advanced review techniques. Unlike many lawyers who claim expertise in CAR, including especially predictive coding, Manfred has far more than just theoretical knowledge. Like Maura Grossman and myself, Manfred is hands-on in the digital world of document review. He is not only a review expert, he is an SME in the field of anti-trust law. Manfred Gabriel actually drives the CAR, and supervises many big projects. That is the only way to really understand these complex processes. Manfred and I seem to agree on all things predictive coding (although we agree to disagree on the proper role of EDBP’s big red-square!), so I was pleased to see he has now made a written contribution to the field with his Quality Control paper.

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