Once is Not Enough: The Case for Using an Iterative Approach to Choosing and Applying Selection Criteria in Discovery

Culling using selection criteria is used to manage otherwise overwhelming volume of data in litigation discovery.[1] Courts and experts are endorsing the emerging best practice of iterative measurement of selection results, borrowing from established and effective data management practices outside of the litigation setting. By insisting on this practice, in-house counsel and their advisers can both contain the cost of discovery and reduce or eliminate the risk of challenge to the search and selection methodology.

The use of search terms and other selection criteria (e.g., date restrictions or other filters) by parties in litigation at each and every stage of discovery, from preservation to collection to privilege review, is commonplace. The courts and other experts recognize this practice as a necessary alternative to the impossible task of reviewing every possible document in the overwhelmingly large collections of electronic data subject to consideration. And, over time, the process for choosing and applying search terms has evolved as parties, the bench and the bar have looked for better and more cost effective methods to handle discovery. But as the use of selection criteria has become an indispensable tool in the e-discovery toolkit, its application has come under increasing scrutiny by opposing parties and the courts in order to ensure that appropriate search criteria are being used and that responsive materials are not systematically missed in the rote application of search terms. In the last couple of years, there have been several high profile e-discovery cases that dealt with the choice of search terms and their application.[2]

As these cases show, there can be significant risks – of both increased discovery costs and various discovery sanctions – if a litigant fails to properly calibrate its selection criteria.

The good news is that a reasonable, defensible, best practice approach to using selection criteria and cost-effective discovery are not mutually exclusive. An iterative approach to calibrating selection criteria will not only be easier to defend from attack by opposing parties, but in many cases will reduce the overall cost of discovery by eliminating more irrelevant documents from processing and review. Corporate counsel don’t have to choose between containing discovery costs and increasing the defensibility of their process – with the iterative approach to selection criteria, they can do both.

Why Search at All?
The goal for producing parties is to carve from the overall universe of electronic documents a relevant subset of documents for review and ultimate production in a legally defensible and reasonable manner. Litigants faced with document requests quickly realize that there is an impossible volume of data that must be assessed. In most cases, the entirety of electronic documents cannot be produced without some level of selection and review. Neither the producing party nor the requesting party would be able to handle the volume, the effort might not be proportionate to the value of the matter, and the production of non-responsive, unrelated business information might be harmful to producing parties.

This task is usually accomplished by selecting documents via some search mechanism. This is not new. From the beginning of discovery, counsel and parties have been making choices of where and what to search for responsive documents. What text searchable electronic documents have done is abstracted the process.[3] A party may choose to look at one custodian’s files over another because they are more likely to have responsive documents. A party may not open a filing cabinet or box because the label indicates it does not have any documents of value — a reasonable decision. However, applying search terms to a large volume of data does not necessarily have that same effect – especially if the party does not know the effectiveness of those criteria.

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Source: edrm.net
By: Gene Eames, David J. Kessler and Andrea L. D’Ambra