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.
How do you build a forecast when you have no historical data? This is a recurring challenge for businesses that update their product offerings, and a recurring question in online forecasting discussion groups (e.g. this one on LinkedIn). The bad news is that you probably can't expect to achieve highly
While fancy new forecasting models will always be of interest to researchers, there is plenty of really interesting and practical new work being led by forecasting practitioners. Last month Steve Morlidge (who spent 30 years at Unilever, now with CatchBull), shared his promising new approach on the “Avoidability of Forecast
Forecasting Support Systems (FSS) – essentially, decision support systems for forecasters – are being given increasing scrutiny in forecasting circles, including our recent half-dozen articles in Foresight. Additionally this year, there has been a special issue of the International Journal of Forecasting focused on the topic. Keith Ord and
