The good news is that we are finally at a point in the evolution of eDiscovery where virtually everyone agrees on the need for content analytics to make collection and review faster and less expensive.  This news is tempered, however, by a lack of understanding of what content analytics are and how they work.  Until there are some standard ways of understanding how analytics work from both IT and legal perspectives, they will not become ubiquitous.


Content analytics are necessary because there is simply too much digital information for human reviewers to read efficiently.  Without analytics, the cost of legal review will cripple litigious organizations.  Plus, these analytics promise to feed other use-cases, too - storage optimization, knowledge management, compliance, security, and privacy.


A good analytics tool will offer at least some of the following features:  near deduplication, conceptual clustering, automated tagging, social network analysis, vizualization, and machine learning.  As these features are put together, there are many problems that organizations can solve, such as Early Case Assessment (ECA) to make more informed legal decisions earlier so as to save significant costs.


The issue that I hear most often from end-users, though (and this is both IT and legal end-users) is that there is no prescription on analytics.  Case law is murky and no organization wants to be the pioneer in advanced use of analytics.  I'm interested in more perspectives on the use of analytics.  Email me with any thoughts that you have...and Thanks!