Issue link: https://epubs.iltanet.org/i/13683
REDUCE DOCUMENT REVIEW COSTS THROUGH TEXT ANALYTICS concepts. No input from the end user is needed. The search engine builds subsets of conceptually related documents (clusters) based on the information contained within the documents in the case. Reviewers gain increased insight into their data sets by using clustering early in the review process. This insight can lead to better prioritization of batches for review. Additionally, clustering imposes organization on the review process that improves review speeds by allowing a reviewer to evaluate all documents responsive to a particular concept at one time. For example, a reviewer is assigned 1,200 e-mail messages from a custodian. Using a linear approach, the reviewer might read these messages in sequential order by date. A clustering workflow will group the e-mail messages into clusters by topic, and the reviewer can then sort by date to see the topic timeline. A cluster of personal communications could quickly be reviewed or reassigned to a lower priority, or, conversely, a cluster of e-mail messages discussing the details of a business deal could be assigned to a higher priority review team. If a reviewer can identify documents that serve as examples of issues in the case, she can train the concept engine to create groups of conceptually similar documents based on her examples. This type of classification, sometimes called categorization, allows the reviewer to define her own concepts within the documents. Assignments can then be made to team members who have the best understanding of those concepts. COST CONTAINMENT IS THE BOTTOM LINE It is becoming increasingly important for legal professionals to present cost-effective solutions to their clients. To combat the high costs of e-discovery and maintain a competitive edge, these professionals must look to improve the document review process. Using concept search and classification features available in text analytics search technology is an effective way to increase review speeds and reduce a client’s litigation spend. ILTA Quality Control One of the benefits of using text analytics technology during review is enhanced quality control. Often, at the end of a review process, the case team will have identified a set of privileged documents. Prior to document production and finalizing the privilege log, the case team can compare the documents tagged for privilege with conceptually similar documents as a quality control mechanism. Text analytics software can locate documents within the data set that are conceptually similar to those already tagged by the case team for privilege. Reviewers can double-check the conceptually similar results to ensure that no privileged documents were missed, thus demonstrating that they have taken significant measures to ensure the protection of their client’s privileged information. ILTA www.iltanet.org Case/Matter Management 27