Over the past few years, there has been a significant increase in the number of tools available to attorneys to analyze and review electronically stored information (“ESI”) that has been collected from clients or produced by opposing parties. While courts and attorneys continue to become

Over the past few years, there has been a significant increase in the number of tools available to attorneys to analyze and review electronically stored information (“ESI”) that has been collected from clients or produced by opposing parties. While courts and attorneys continue to become comfortable with the use of tools like technology-assisted review, email threading, document clustering, and document categorization to facilitate the actual review of documents, there are a host of top-down methods for analyzing the document population as a whole that can provide helpful insight that would be difficult, if not impossible, to obtain through a document-by-document analysis.

On November 10, 2016, Law360 released an article entitled Data Analytics: How Parties Are Using Tools Beyond TAR that outlined a number of case studies where these “big data” tools can directly assist in identifying potential areas of interest or gaps in available ESI.


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As part of its Working Group on Electronic Document Retention & Production, the Sedona Conference recently released a “TAR Case Law Primer” that analyzes court decisions that directly or indirectly touch upon issues involving technology-assisted review (“TAR”).

The primer begins with a brief summary of Da Silva Moore v. Publicis Groupe, 287 F.R.D. 182 (S.D.N.Y. 2012), the first published opinion agreeing that TAR is an “acceptable way to search for relevant ESI in appropriate cases.” Id. at 183. Although this opinion approved the use of TAR in that case under the particular facts and issues before the court, many parties were still unclear regarding the method of implementing TAR, the appropriate level of involvement by opposing parties (if any), and whether an agreement must be reached regarding technical specifics of the TAR process.
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In Hyles v. New York City, 10 Civ. 3119 (AT)(AJP) (S.D.N.Y. Aug. 1, 2016), the court addressed the question of whether the City could be “forced” to use technology assisted review (predictive coding) to identify discoverable information when the City itself preferred to use keyword searching. “The short answer [was] a decisive ‘NO.’”

After consulting with an e-discovery vendor, Plaintiff’s counsel in this case “proposed that the City should use TAR as a ‘more cost-effective and efficient method of obtaining ESI from Defendants.’” “The City declined, both because of cost and concerns that the parties, based on their history of scope negotiations, would not be able to collaborate to develop the seed set for a TAR process.”  The issue was referred to U.S. Magistrate Judge Andrew Peck for resolution.
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