Orange Legal Technologies’ Automated Predictive Review Service helps corporate legal departments and their outside counsel conduct the critical electronic discovery task of document review by providing advanced predictive coding technologies and expert reviewer assistance to accelerate the electronic discovery process.
What is Automated Predictive Review?
Commonly referred to as predictive coding or technology-assisted review, automated predictive review leverages predictive coding technologies and expert reviewer assistance to accelerate the electronic discovery review process by assessing and predicting document responsiveness, privilege and issue relation prior to the conduct of manual document review. When employed as a part of the overall electronic discovery process, automated predictive review enhances the efficiency of document reviews by providing accuracy and consistency while reducing the time and cost associated with manual first pass document review.
Why is Automated Predictive Review relevant?
The task of document review is the most costly and time consuming of the electronic discovery tasks and may comprise upwards of 60% of the overall cost of projects employing a fully manual document review approach. (1) However, with the advent of predictive coding technologies, industry research indicates that document reviews can be conducted in a more efficient and efficient manner when they leverage automated predictive review as part of the overall review process. Recent results from the Text Retrieval Conference (TREC) as well as the eDiscovery Institute show that automated predictive review is at least as accurate and usually more consistent than having teams of reviewers read every document. (2,3) This proven accuracy and consistency when coupled with the decreased time and talent required for an automated review makes automated predictive review a relevant and reliable approach to streamlining first pass document reviews.
How does the Automated Predictive Review process work?
Automated predictive review is initiated with a series of random document samples from the reviewable (post processing) document collection. These random samples are then reviewed and judged as responsive or non-responsive by an assigned matter expert. After the expert marks several sets of random samples as responsive or non-responsive, predictive coding technology is able to “predict” which of the documents in the remainder of the reviewable data set will in fact be responsive. Based on actual attorney reviews, this automated predictive review approach has resulted in more than 90% of predicted responsive documents being confirmed as responsive during final manual attorney review. (5)
Where does Automated Predictive Review fit in the Electronic Discovery Process?
The decision to employ automated predictive review is usually made during the project scoping phase of electronic discovery projects. This decision results in the development and implementation of an electronic discovery workflow that combines traditional electronic discovery tasks to include collection, analytics (early case assessment) processing, review and production with the advanced evidence-based document categorization capability of automated predictive review. While elements of predictive coding technology may be applied during data set ingestion and early case assessment tasks, automated predictive review (predictive coding and expert review assistance) is primarily implemented after the processing phase and prior to the manual review phase of electronic discovery.
When employed in conjunction with Orange Legal Technologies’ OneO® Discovery Platform (analytics, processing, review) and expert professional services (collection and forensics, project management and managed attorney review), automated predictive review provides clients with advanced technology and approaches to significantly reduce the time and cost associated with electronic discovery.
Why Orange Legal Technologies for Automated Predictive Review?
As a leading provider of electronic discovery technology and services, Orange Legal Technologies has worked with some of the world’s most well known corporations and law firms and has been recognized in leading analyst and media publications from such organizations as Gartner (6), IDC (7), The 451 Group (8), and Forbes magazine (9). While our background is proven and our capabilities complete, the most important benefit that our clients share with us about our services is that we allow them to conduct electronic discovery while reducing their time, cost and risk. Simply stated, we provide complete and completely affordable electronic discovery support that allows our clients to focus on the law, not the technology.
To learn more, contact us.
(1) David Degnan, Accounting for the Costs of Electronic Discovery. Minnesota Journal of Law, Science & Technology, 2011;12(1):151-190.
(2) Maura R. Grossman & Gordon V. Cormack, Technology-Assisted Review in E-Discovery Can Be More Effective and More Efficient Than Exhaustive Manual Review, XVII RICH. J.L. & TECH. 11 (2011).
(3) Herbert Roitblat, Anne Kershaw & Patrick Oot, Document Categorization in Legal Electronic Discovery: Computer Classification vs. Manual Review, eDiscovery Institute (2011).
(4) Andrew Peck, Search Forward, Law Technology News (October 1, 2011).
(5) Herb Roitblat, Visualize A New Concept in Document Decisioning, OrcaTec LLC (2012).
(6) Gartner “Magic Quadrant for E-Discovery Software (Gartner RAS Core Research Note G00212221)” John Bace, Debra Logan. 2011.
(7) IDC MarketScape: The Worldwide Standalone Early Case Assessment Applications 2011 Vendor Analysis (Doc # 229928) V. Tero. 2011.
(8) The 451 Group “Orange Goes For An Open Source Mid-Level eDiscovery Niche with the PurpleBox” N. Patience, D. Horrigan. 2011.
(9) Forbes Magazine “E-Discovery Moves to the Cloud” with Bret Laughlin. Ben Kerschberg. 2011.