Last year, Magistrate Judge Andrew Peck of the U.S. District Court for the Southern District of New York issued the first judicial opinion recognizing predictive coding, also known as technology-assisted review, as a legitimate e-discovery tool. Since that opinion, the focus of the e-discovery world has been on predictive coding, seen by many as a more accurate way to identify relevant electronically stored information (ESI) for discovery than the predecessor technology, keyword searching. Other federal and state courts have followed Peck's lead.

However, the cost effectiveness of an ESI production plan can vary considerably depending on such factors as the importance of the issues, size of dataset and resources of the parties. Specifically, keyword searching can be substantially less costly than predictive coding. And three recent cases demonstrate that keyword searching remains a defensible e-discovery plan.

In one case involving nearly 20 million electronic documents, the court upheld keyword searching as a method for the first phase of identifying relevant documents, with predictive coding then applied to the remainder, over objections from the plaintiffs who argued the keyword search may have eliminated relevant ESI. In a second case, the court reversed its earlier order requiring the parties to use predictive coding and agreed that keyword searching was acceptable due to the relatively small amount of ESI in question. In the third case, the court rejected the defendant's claim that keyword searching would produce too many documents requiring manual review and therefore be too costly.