E-Discovery

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E-Discovery in California

E-Discovery in Federal Courts in California

By Benedict Y. Hur and Matthew M. Werdegar. They are partners at Keker & Van Nest in San Francisco whose practice includes complex litigation. They frequently deal with e-discovery issues.

The rules of civil procedure are supposed to be “construed and administered to secure the just, speedy, and inexpensive determination of every action and proceeding.” (Fed. R. Civ. P. 1.) Yet, as anyone who has been tasked with handling discovery in complex litigation knows, the judicial system has been slow to adjust to the explosion of electronically stored information (ESI) and the corresponding jump in e-discovery costs.

Despite various attempts at reforming the e-discovery process over the past decade, studies indicate that discovery continues to account for the bulk of the cost of civil litigation. Indeed, according to one survey, it is responsible for 70 percent of total litigation costs in cases that do not go to trial. Litigants can spend upwards of $18,000 to collect, process, and review a gigabyte of data. And in large cases, potentially responsive data can measure in the hundreds or thousands of gigabytes.

Yet the potential costs of not properly managing e-discovery also are enormous. Courts have not been shy about imposing sanctions for misconduct related to e-discovery. In late 2013, for example, a federal judge issued sanctions of almost $1 million for e-discovery mismanagement. (In re Pradaxa Prods. Liab. Litig., 2013 WL 6486921 (S.D. Ill.).) And last year another federal court considered terminating sanctions for e-discovery violations in a trade secrets case; ultimately, the judge settled on a spoliation instruction. (Quantlab Techs. Ltd. v. Godlevsky, 2014 WL 651944 (S.D. Tex.).)

Fortunately, relief from this scourge may soon arrive at a court near you. Over the past three years, more than two dozen federal courts, including the Northern and Southern Districts of California, have used their local rule-making powers to enact new e-discovery model orders and guidelines. These rules generally call for phased discovery of ESI, limits on email discovery, limits on the obligation to preserve and collect certain categories of ESI, increased cooperation between litigants on e-discovery, and cost-shifting provisions to further discourage overreaching. (At present, the most comprehensive materials can be found on the website for the Northern District; see cand.uscourts .gov/eDiscoveryGuidelines.)

Some of the rules impose new burdens on litigants. But they also create new opportunities for attorneys to conduct e-discovery in a more rational and cost-efficient framework. Courts are now willing to entertain creative proposals for reigning in e-discovery – provided they are tailored to the circumstances of the case and transparently describe what ESI will and will not be covered.

To take advantage of the new rules, you must do your homework at the outset of a case:
– Familiarize yourself with the local rules and guidelines of the court in question.
– Realistically assess the risk the litigation poses and your own discovery needs.
– Understand where your client’s data resides, how much there is, and how much effort it will take to collect the information.

Based on this information and the circumstances of the case, the plan could include limits on the sources of noncustodial ESI that must be preserved and collected, and limits on email discovery.

It is also important to understand what the new rules do not address – and develop a plan for handling those issues as well. For example, predictive coding is a relatively new tool to manage e-discovery costs, using computer algorithms to determine which documents are relevant based on a review of test documents by humans. The technology has the potential to curb costs by drastically reducing the amount of data requiring human review. But few courts have addressed the use of predictive coding and other emerging e-discovery tools.

The key to effectively using them, then, is to negotiate early and transparently with opposing counsel. Your opponent needs to know what data you plan to search, how you intend to search, and who (or what) will determine responsiveness.

Although this may require disclosing more information than you are used to, courts so far have conditioned their approval of predictive coding on such transparency. (See Moore v. Publicis Groupe, 287 F.R.D. 182 (S.D.N.Y. 2012).)

1 thought on “E-Discovery

  1. International Post author

    I love the sentence in this article: Know your data. I think this is really at the heart of the matter, or every matter in the context of eDiscovery, actually. Full disclosure: I am a linguist/language expert who has worked in eDiscovery for many, many years now and I’ve come to believe a few things: 1) The conversation of “managing costs” almost always co-occurs with discussions of the sheer quantity of data/ESI that is the centerpiece of today’s complex litigation. Data quantity shouldn’t be the driving factor in our conversations about discoverable ESI and proportionality, when the problem we face is one of data quality. How do we stop focusing on the exclusion of data to reduce quantity (i.e. manage costs) and start focusing on the inclusion of data to ensure the most qualitatively robust, relevant ESI? 2) The legal field needs to regularly consult those of use with language/lingusitic expertise (NLP-ers, Computational Linguists, Corpus Linguists, Language Variationists, etc), who understand how relevancy is concretely expressed through language and linguistic patterns of communication, and who can leverage this expertise in a way that translates to principled methodologies in an eDiscovery context. Methodologies that can be reasonably implemented. Methodologies that do not involve educated guesswork and arbitrary, intuition-based processes for figuring out how relevancy qua language plays out in ESI. And finally 3) Technology does not make up for the fact that the *right* teams need to be assembled to address the changes to the FRCP with respect to proportionality specifically, and eDiscovery workflow processes generally. The right experts who understand the complexity of working with unstructured text (this is not simply an IT issue) and people like myself who have worked with large collections of natural language in a research capacity and who understand the benefits and limitations of technology, such as predictive modeling. I have truly come to believe that eDiscovery issues are not ones that will be solved by technology alone, but by people who understand the nature of ESI as complex language data, who are able to understand this in a legal framework, and who can employ principled methods and consult expert tools in the most expeditious way possible. Expert tools used by expert teams. All of it hinging on that one crucial element, or the ability to “know your data.”

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