Building a PreDiscovery Analytics Maturity Model

by | Jun 6, 2016


Any organization needs objective measurement tools to monitor and evaluate their progress in pursuit of specific operational goals. One way to do this is with a “Maturity Model” – a progress map that allows an organization to have its methods and processes assessed against a clear set of best practice benchmarks. With this tool, progress is indicated one step at a time toward the next particular “maturity level” in the roadmap.

For those of us who are focused on improving performance in the world of eDiscovery, there have been several noteworthy maturity models that can help us map progress in pursuit of operational goals. For example, George Socha and Tom Gelbmann led the effort to create the Electronic Discovery Reference Model (EDRM), which has been a common roadmap to the process workflow for more than a decade. Markus Springer has described a five-stage Big Data maturity model that can be a big help to those who are struggling with the convergence of Information Governance, eDiscovery and Big Data. And as far back as 2011, Gartner was assessing various maturity models for eDiscovery workflow.

We wish to make the case for what we’ll call a “PreDiscovery Analytics Maturity Model” – a model constructed on the premise that there is an important new frontier in our industry: the enormous untapped potential of advanced visual analytics in the eDiscovery workflow to drive early data assessment (EDA) in support of early case assessment (ECA) and case strategy. The key to this premise is that as an industry we are moving away from the step-by-step approach to linear eDiscovery review and moving toward a new approach that begins with the ingestion of data and then relies on powerful software tools, such as advanced visual analytics, to provide earlier insight into the case. Hence, we embrace the idea of “PreDiscovery” as the true engine of the eDiscovery workflow.

Of course, we recognize that the use of analytics in eDiscovery is not new. In the early days, analytics were associated with functions such as de-duplication of files within a data set, email threading and, more recently, predictive coding. Moreover, the concept of a maturity model related to the improved use of analytics has been introduced in other industries.

But we believe there is a great need for an eDiscovery analytics maturity model that identifies a clear progress map, staking out a series of benchmarks in pursuit of a simple goal: how analytics can be used to drive better litigation outcomes for inside and outside counsel. The five levels we envision in this model are Novice, Explore, Analyze, Investigate and Predict. Here is a snapshot of the PreDiscovery Analytics Maturity Model we have constructed:


As a litigation software team, our view is that we’re on the verge of a new generation of eDiscovery software products that will fulfill the promise of analytics in a much bolder way than we previously imagined. These new capabilities include graphical views of data, more transparent reporting metrics, new sophisticated search capabilities, smarter workflows, and advanced data mining tools. We believe that a maturity model such as the one constructed above can be a useful tool for marking an organization’s progress toward the integration of advanced visual analytics throughout the entire eDiscovery workflow – and ultimately help drive better litigation outcomes.


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