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Summer 2018


  1. How Big Data Could Challenge Planning Processes across the Supply Chain by Tonya Boone, Ram Ganeshan, and Nada Sanders
    The authors discuss the potential of big data to improve forecasting through better understanding of consumer behavior, upgraded demand-forecasting models, and more efficient supply-chain execution. They also document the major challenges posed for Sales and Operations Planning and propose how these can be anticipated and met head on.
  2. Outcome Prediction in the Practice of Law by Mark Osbeck and Michael Gilliland
    The practice of law requires decisions that must be based on predictions of future legal outcomes, and data scientists are now developing forecasting methods to support the process. In this article, Mark Osbeck and Mike Gilliland first examine the traditional tools lawyers employ along with the limitations that prevent these tools from consistently delivering accurate predictions. They then describe how new data-science approaches, including AI, are starting to alter the way law firms operate.

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