Reviewing Potentially Relevant Data

Reviewing potentially relevant data

One portion of the e-discovery process that is frequently ignored is the plan for eventually reviewing potentially relevant data that has been collected in response to a specific legal need. E-mail systems and file servers in even small companies may contain hundreds of thousands (if not millions) of documents. Only a small fraction of them are likely to be relevant to a particular dispute.

An e-discovery strategy that adequately identifies and preserves potentially relevant ESI is not operating efficiently if it does not include a plan for reducing the amount of this data that must then be reviewed. Our law firm of Squire Sanders & Dempsey ("Squire Sanders") has addressed this need through its "Intelligent Discovery" initiative, which seeks to reduce client costs by limiting-to the greatest extent possible-the amount of time devoted to human review of large data populations.

Traditional discovery processes often involve a "linear" review in which each document (that is, piece of potential evidence) is individually classified as to its relevance. This process is time-consuming and expensive. For very large populations of ESI, the potential costs of this exercise can approximate the true economic value of the matter in dispute. In addition, because of the amount of material that must be reviewed, key evidence might not be seen by the legal team until well after important strategy decisions have been made.