E-Discovery

Recently, I began work on a complex litigation case that had millions of documents to review with many moving parts and quick deadlines that made completing assignments daunting, to say the least. We determined that simply running targeted searches to find this evidence was not the best approach, in part because the issues were broadly defined and had multiple subparts, and in part because of the sheer number of documents in the database (over 2.5 million records). As an alternative, we decided to utilize technology assisted review or “TAR” (also known in the industry as predictive coding). What follows is my impression of the tool.

This is Part One of a continuing series on ESI basics. In this series, we will cover some of the terms used most often on the tech-side of e-discovery. Whether this is an introduction to you, or a refresher, and whether you are an attorney, member of an in-house team, or data analyst, we think this information may come in handy in your practice.

Two of the most compelling discovery sanction cases of the past year are Klipsch Group., Inc. v. ePRO E-Commerce Ltd. and Ronnie Van Zant, Inc. v. Pyle, both decided in the Second Circuit. In the first, the court awarded $2.68 million in discovery sanctions in a case valued at a mere $20,000. In the second, the court issued an adverse inference when a defendant failed to preserve text messages held by a non-party. The implications of both decisions appear far-reaching and critically important for those involved in the discovery process.     

There was a time when the only data you needed to collect in response to a discovery request was corporate email. Fast forward to present day. Employees are conducting business with smartphones, via social media and with the assistance of wearable technology. As a result, responding to e-discovery requests has become increasingly challenging.

In the modern workplace, companies are beset with a multitude of challenges regarding ownership and use of devices such as laptops, mobile phones, tablets, and others, and the information on or accessed by them. It has become increasingly common for companies to follow a model called BYOD, or “Bring Your Own Device,” where an employee purchases their own device and the company pays for either all or partial service. While there are clear advantages to this type of business model, there are drawbacks that should be considered when drafting company policies.