Machine Learning in Supply Chain Planning– When Art & Science Converge

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Spring 2019

Journal of Business Forecasting Volume 38 | Issue 1 | Spring 2019

As ever, when new technology promises to revolutionize your business, it is nothing without the tried and true processes needed to support it. This issue offers readers a non-nonsense, practical guide to machine learning, and a clear road map for adopting it in your organization. Written by a leading expert in the field, Hank Canitz (Logility), the lead article details what AI, machine learning and predictive analytics are, and what it really takes to leverage them as a tool for growth. In this issue, you’ll learn what new skills are required to support this technology, and how to engage in effective change management to facilitate widespread acceptance and adoption. You’ll also find invaluable tips to present a business case for machine learning to senior leadership to secure the investment required.

Other highlights of this issue include engaging Customer Service for better forecasting and S&OP, which, Pat Bower, (Sr. Director of Supply Chain Planning & Customer Service at Combe Inc,) argues is an obvious and yet overlooked source of insight. What’s more, we bring you very modern lessons from an old-school supply chain problem - that of the Newsboy. Delving into the differences between Walmart and Amazon, Dr. Larry Lapide (MIT) uses the Newsboy problem to reveal the supply chain challenges facing these two retail giants.

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