Civil Litigation Discovery Legal Topics

Speeding Up E-Data Review

It’s impossible for counsel to look at every single document that’s part of a large-scale e-data review—doing so would be prohibitively costly and time-consuming. But it’s also unacceptable to blindly produce documents to the opposing party. You can safeguard clients without excessive expense by taking time at the beginning of the case to make some determinations about how to conduct the review. Try one of these four ways to speed up e-data review.

  1. Meeting and conferring with opposing counsel. You can use meet-and-confer meetings to help refine the scope of the review. At a minimum, discuss with opposing counsel the search terms and document custodians or locations that can be used to focus review on the most likely documents and reach agreement with opposing counsel on those terms. See, e.g., Pyle v Selective Ins. Co. of Am. (WD Pa, Sept. 30, 2016, No. 2:16-cv-335) 2016 US Dist Lexis 140789, *5 (party ordered to confer and come to agreement on search terms opponent will use to review email archives). You should also discuss the use of advanced search technology and the possible inclusion of predictive coding and other artificial intelligence solutions. Both the federal and California rules require the parties to discuss issues relating to discovery of electronically stored information (ESI) when the parties meet and confer. See Fed R Civ P 26(f)(2), (f)(3)(C); Cal Rules of Ct 3.724(8).
  2. Using artificial intelligence for document review. Cases involving large quantities of ESI are prime candidates for artificial intelligence technology (known by many names including predictive coding, computer-assisted review, technology-assisted review, and machine learning) that can supplement or even supplant human review. Courts are beginning to accept the use of predictive coding. In the seminal decision on this issue, Da Silva Moore v Publicis Groupe (SD NY 2012) 287 FRD 182, 191, the court held that “[w]hile this Court recognizes that computer-assisted review is not perfect, the Federal Rules of Civil Procedure do not require perfection,” and found that predictive coding was allowable in the specific circumstances in that case. See also Rio Tinto v Vale S.A. (SD NY 2015) 306 FRD 125, 127 (if producing party wants to use technology-assisted review for document review, courts will allow it). But see Hyles v New York City (SD NY, Aug. 1, 2016, No. 10 Civ. 3119 (AT)(AJP)) 2016 US Dist Lexis 100390, *9 (court cannot order city to use technology-assisted review in production of ESI when city prefers keyword searching).
  3. Dividing up e-data. After refining the scope of review and reducing the volume of data, counsel must decide who will review which parts of the data. Depending on the type of case, reviewers might review data based on the custodian (i.e., review an individual’s documents) or the issues of the case. Breaking up the data into small manageable groups, known as “batches,” allows reviewers to better understand the data and give feedback on what they encounter. This information can help set the direction of the review.
  4. Using tags and issue codes. Tags and issue codes are created within a litigation support database to categorize or group documents. Tags and issue codes can be used interchangeably or separately. Tags are typically radio button or check box options that are the electronic equivalent of a yellow sticky note. Issue codes are typically an additional field in the database. Tags tend to be easier for a reviewer to use because they require only a simple click, whereas an issue code requires clicking into a field and selecting a code from a drop-down list. Some common tags that a reviewer might use are “privileged,” “responsive,” and “hot.” Technology allows “bulk coding” of tags. For example, emails showing the sender and recipient as the attorney and client can be easily bulk coded as attorney-client privileged communications.

For much more on ESI, turn to CEB’s California Civil Discovery Practice, chap 4 and Internet Law and Practice in California, chap 20A. And to find out about the competence requirements in handling ESI, view CEB’s program Electronically Stored Information and the Ethical Duty of Competence.

Other CEBblog™ posts on e-data:

© The Regents of the University of California, 2017. Unauthorized use and/or duplication of this material without express and written permission from this blog’s author and/or owner is strictly prohibited.

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