I've never been much of a fan of forecasting approaches to intermittent demand. In situations like intermittent demand (or other areas where we have little hope of reasonably accurate forecasts), my thinking is "why bother?" If we can't expect to solve the problem with forecasting, we need a different approach. The general issue of dealing with a highly unpredictable future was addressed brilliantly in one of my favorite articles of all time, “Living in a world of low levels of predictability,” by Spyros Makridakis and Nassim Taleb (International Journal of Forecasting 25 (2009) 840-844.
[Sidenote: Join me live in New York City, December 6-7, to hear from Spyros and Nassim at the M5 Conference. I'm looking forward to an amazing event, with two days of presentations and discussion of the M5 Forecasting Competition. Check out the link for agenda and incredible list of speakers providing results, analysis, and commentary.]
Intermittent Demand Forecasting (IDF)
For me, intermittent demand is not so much a forecasting problem as an inventory management problem. As Makridakis and Taleb point out, just because you can't solve a problem with forecasting, doesn't mean there aren't other ways to address it. This same kind of mindset -- this openness to look beyond just throwing models at a problem -- is displayed in the new book Intermittent Demand Forecasting: Content, Methods and Applications by John Boylan and Aris Syntetos. I also appreciate their recognition of the meaningful environmental benefit of better managing our inventories.
From the description:
The first text to focus on the methods and approaches of intermittent, rather than fast, demand forecasting
Intermittent Demand Forecasting is for anyone who is interested in improving forecasts of intermittent demand products, and enhancing the management of inventories. Whether you are a practitioner, at the sharp end of demand planning, a software designer, a student, an academic teaching operational research or operations management courses, or a researcher in this field, we hope that the book will inspire you to rethink demand forecasting. If you do so, then you can contribute towards significant economic and environmental benefits.
No prior knowledge of intermittent demand forecasting or inventory management is assumed in this book. The key formulae are accompanied by worked examples to show how they can be implemented in practice. For those wishing to understand the theory in more depth, technical notes are provided at the end of each chapter, as well as an extensive and up-to-date collection of references for further study. Software developments are reviewed, to give an appreciation of the current state of the art in commercial and open source software.
Thanks to John and Aris for this very important (and much needed!) contribution to our handling of the IDF problem. Find my full review of the book in a forthcoming issue of Journal of Business Forecasting.
