Digital White Papers

84 WWW.ILTANET.ORG | ILTA WHITE PAPER LITIGATION AND PRACTICE SUPPORT The New Path to Ediscovery Success: Business Intelligence following are the estimated savings for those excluded documents for the entire project, including collection, processing, hosting, project management and litigation support, review, review quality control and supervision: This analysis demonstrates the effectiveness of targeting the collection and using TAR to reduce the costs of the project. While these techniques may not be the right fit for every case, the metrics they provide on potential savings is very helpful in future decisions and provides instructive BI about when and how to use them. Strategic Workflows = Money Saved The art of ediscovery involves picking the right workflow for each case. This requires understanding the costs and benefits of the workflows. BI can demonstrate how successful an approach has been as well as inform future decisions about similar workflows. For example, many projects now use analytics to put as many responsive documents into human review as possible while avoiding the review of nonresponsive documents (this is known as TAR 2 or continuous active learning). In a TAR 2 project, analytics predict which unreviewed documents are most likely to be responsive, and those documents are batched for human review. As humans then tag the documents responsive or nonresponsive, the system continues to learn and refine results to beer predict which documents should be reviewed. The result of this workflow is full review of the required responsive documents and a remaining set of unreviewed documents that are predicted nonresponsive. To demonstrate the usefulness of this approach we first use metrics to analyze how well the process increases responsiveness of documents reviewed compared to the overall set of data. Here, where the overall set of data was only 25 percent responsive, the TAR 2 review successfully focused the review on the responsive documents, and only a small percentage (13 percent) of nonresponsive documents were reviewed. SAVINGS $1,600,000 $1,400,000 $1,200,000 $1,000,000 $800,000 $600,000 $400,000 $200,000 $0 PROJECT COST TAR REVIEW METADATA FILTERING EXCLUDED BY TARGETED COLLECTION In a TAR 2 project, analytics predict which unreviewed documents are most likely to be responsive, and those documents are batched for human review. As humans then tag the documents responsive or nonresponsive, the system continues to learn and refine results to better predict which documents should be reviewed.

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