When it comes to e-discovery, many firms have not integrated a fundamental analytics tool—predictive coding. Call CONCORD today! (800) 246-7881 Tania Mabrey and Monica Bay March 22, 2016 Although predictive analytics may be difficult to master, it’s a tool that can greatly improve litigation results. There’s no question that Big Data analytics are dramatically changing […]
Law Departments Aim to Lower Litigation Costs With Efficient E-Discovery
LOWER LITIGATION COSTS? “A single technology tool to support the complete e-discovery workflow simply does not exist.” Ed Silverstein, Law Technology News Corporate legal departments are increasingly like other parts of the business, and are expected to manage costs. This year will find many legal departments trying to control litigation spending on outside counsel, according […]
How algorithms solve all our problems … and create more.
Does Your Computer Need a Law Degree Review of “The Formula: How algorithms solve all our problems … and create more.” Illustration via The Random House Group “The Formula” is a new book by the author of “The Apple Revolution,” Luke Dormehl, which tackles the rise of algorithms and artificial intelligence in art, politics, […]
How to Calculate ROI for E-Discovery (with Calculator)
How to Calculate ROI for E-Discovery (with Calculator) Call CONCORD today (800) 246-7881 March 28, 2014 by Richard Medina In previous posts I talked about doing a business case to see if its worth fixing e-discovery, for example in How to Develop and Implement Your Discovery Readiness Program and Which Part of E-Discovery […]
Electronic Discovery: Native Production vs Bates Numbering
[mp_row] [mp_span col=”12″] [mp_text] Electronic Discovery Native Production vs Bates Numbering  A key advantage of native production is that it spares parties the burden of selecting and collecting from among hundreds of application metadata fields. Each file produced natively carries its peculiar complement of application metadata. System metadata, essential for classifying and sorting large volumes […]
