Author

Mike Gilliland
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Product Marketing Manager

Michael Gilliland is a longtime business forecasting practitioner and formerly a Product Marketing Manager for SAS Forecasting. He is on the Board of Directors of the International Institute of Forecasters, and is Associate Editor of their practitioner journal Foresight: The International Journal of Applied Forecasting. Mike is author of The Business Forecasting Deal (Wiley, 2010) and former editor of the free e-book Forecasting with SAS: Special Collection (SAS Press, 2020). He is principal editor of Business Forecasting: Practical Problems and Solutions (Wiley, 2015) and Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning (Wiley, 2021). In 2017 Mike received the Institute of Business Forecasting's Lifetime Achievement Award. In 2021 his paper "FVA: A Reality Check on Forecasting Practices" was inducted into the Foresight Hall of Fame. Mike initiated The Business Forecasting Deal blog in 2009 to help expose the seamy underbelly of forecasting practice, and to provide practical solutions to its most vexing problems.

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Preview of INFORMS Conference

The INFORMS Conference on Business Analytics and Operations Research kicks off April 15 in Huntington Beach, CA. I had a chance to preview a presentation by Glenn Bailey, Sr. Director of Operations Research at Manheim (the $3B wholesaler auto auctioneer). Glenn's talk is on "The Need for Speed: Responsive Predictive Analytics,"

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Editorial comment: Forecast accuracy vs. effort

Let's end 2012-Q1 with a graphic editorial comment: Forecast Accuracy vs. Effort Using a naïve model will achieve a certain level of forecast accuracy. That accuracy may be high if the demand is smooth and stable, or low if the demand is erratic. But you achieve this level of accuracy with virtually no

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Deadly sin #5: Senior management meddling

The March 28 edition of APICS extra features an article by Fred Tolbert on "The Seven Deadly Sins of Sales Forecasting." Although I have some objection to his Deadly Sin #1: Using Shipment History (and will discuss the objection in a forthcoming guest-post on the Institute of Business Forecasting blog),

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