publication of the International Legal Technology Association
Issue link: https://epubs.iltanet.org/i/355985
ILTA WHITE PAPER: JULY 2014 WWW.ILTANET.ORG 22 Benamram, the key to success is to "continue to take lawyer time out of the equation or process." Given attorney time is the most "valuable" asset in a firm, the focus needs to be on increasing their profitability. This means providing tools that streamline their daily tasks. Take the idea of spell check or a metadata scrubber — something we take for granted today. What used to be a human proofreader/editor is now baked into the attorney process. According to Benamram, we need to use examples like these from our "big data past" to predict future tools that will resonate with the profession. OTHER INDUSTRIES LEADING THE WAY In order to think along these lines, we can turn to how IBM utilizes Watson and how it is utilized to solve issues within the health care industry. (Watson is defined by IBM as "a cognitive technology that processes information more like a human than a computer — by understanding natural language, generating hypotheses based on evidence and learning as it goes.") Watson can learn to process patient records and medical literature to ascertain patterns, thereby saving doctors time in diagnosing and treating diseases. It also collates more information as it performs these diagnostics, which creates a vast network of experience and knowledge. Similar to the Watson health care industry example, law firms need to make better connections and diagnostic tools with their legal experience. What used to take years, months or weeks to analyze and solve a legal issue, now takes just days or hours. The ultimate tool would further reduce attorney time and effort and streamline the overall process. These tools will truly affect the way we live and also how we practice law. Here are some examples of "wish list" tools we gathered from our conversations with KM professionals. Are they legal fiction or reality? You decide! • Negotiation Map: Outlines the offer that will prove to produce a positive outcome in closing a deal, with a margin of error built in. • "What I Need to Know" Alerts: Automated alerts to pinpoint "what I need to know" as opposed to reading through reams of data in email, etc. (e.g., associate curses client in an email — red flag — partner will be notified) • Trial Prediction Tool: Analyzes salient milestones of a case, tracks progress and identifies the most likely outcome. • Client Health Index: Tracks the percent of bills and bonuses being paid by a particular client. Based on these findings, predicts how happy the client is and how successful the matter was. Then extrapolates on what a successful client looks like and tries to establish a precedent that KNOWLEDGE MANAGEMENT: MINING FOR GOLD IN BIG DATA