Peer to Peer Magazine

51 WWW.ILTANET.ORG RICKY BROOMAN Richard (Ricky) Brooman is a Litigation Support Specialist at Saul Ewing LLP. In this capacity, he consults internal and external clients on best practices for e-discovery and information governance and manages all phases of the EDRM for litigation matters. Ricky is also a member of ILTA's Business Management Content Coordinating Team. Contact him at rbrooman@ saul.com. KRIS WASSERMAN Kris Wasserman is a 10-year veteran of the e-discovery industry with experience as a litigation support project manager and solutions architect with multiple technology start-ups. He has a passion for leveraging cutting-edge technology to build effective solutions for mitigating legal risk, reducing costs and streamlining efficiencies associated with managing large- scale discovery. Contact Kris at kris. wasserman@discovereq.com. Evolution of the E-Discovery Project Manager FEATURES Technology: Into the Maze Just as technology complicates maers, so too can it help solve complex e-discovery scenarios. Future e-discovery project managers will leverage technology to devise workflows that facilitate an understanding of IoT data sets to extract relevant information and present it in a digestible fashion. While humans might not be able to accurately track the dissemination of IoT information — not to mention collect, analyze and review the data — our machines can certainly learn to execute such tasks. Just as machines have created the IoT maze, they will assist in untangling the pieces. In particular, e-discovery PMs will work with programmers to build programs that understand IoT data clusters and identify where to focus collection efforts. Information pulled from an IoT device will not be presented as a nicely formaed email, but rather as a series of ones and zeros (or whatever new machine language is developed in years to come) that will likely be encrypted in such a way that only the two machines talking to each other will understand. Thus, e-discovery experts must program the machines to collaboratively decrypt and present the data in an accurate, succinct manner. As machine learning and quantitative analysis technologies make connections faster than humans can keep up with, it will be ever more important to have requisite experts on hand to continuously train, evaluate and quantify the results from IoT systems. Metrics Make Sense of It All How does the future e-discovery PM present the growing, diverse IoT data in a meaningful fashion? Metrics. And dashboards. Why? Because numbers are simple and do not lie, and dashboards paint an understandable picture of the data. For generations, humans have relied on metrics to understand everything from currency and temperature to finance and quantum physics. Metrics in e-discovery are no exception. Everything from data sizes and reviewer run rates to cohesion values and recall rates are metric-based. The future e-discovery PM will rely heavily on metrics to paint a picture of a project's status, direction, timeliness and cost. If you want metrics in a highly visible and organized fashion, the dashboard is an e-discovery project manager's current and future best friend. Dashboards are becoming common, and reliance on them will continue to grow in the IoT era. Sometimes a quick reference tool and other times a visual analytics engine for big data sets, the dashboard will continue to evolve, becoming more specialized to depict metrics across the life cycle of the litigation maer. We've Got You As we collectively grow beyond e-discovery adolescence into adulthood with IoT, we are slowly inching toward working smarter, not harder. As the volume of data continues to grow in size and complexity, new technology-driven solutions will be developed and machines will play a greater role in e-discovery. These solutions, however, will require a hands-on team of seasoned e-discovery project managers who are masters within a particular subvertical of the e-discovery spectrum. We will need more than just one Superman — we need the Super Team. P2P

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