Extract from H5’s article “eDiscovery Analytics Use Cases You May Not Know About”
Evolving analytics tools and methods can help expedite review.
Analyze this! No, we’re not talking about the 1999 movie starring Robert DeNiro and Billy Crystal, but rather analytics mechanisms that many organizations are using today to streamline discovery. As these mechanisms become more sophisticated, it pays to keep abreast of the ways in which they can impact a review, including how data can be organized, visualized, identified and reduced.
For example, conceptual clustering can identify groups of topics that might be clearly responsive or non-responsive. Communication visualization maps can identify communication patterns of key parties within a data collection And, of course, predictive coding can train a supervised machine learning algorithm to identify potentially responsive and non-responsive documents based on classifications of other documents.
But there are other use cases for eDiscovery analytics many organizations aren’t taking advantage of that make eDiscovery workflows even more efficient and more cost effective. To improve the efficiency of eDiscovery workflows, organizations can now implement technology with the following analytics features.