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Winter 2018

Special Feature: Misconceptions, Missteps, and Bad Practices in S&OP, Parts 1-3

Chris Gray and John Dougherty— authors of the pathbreaking book Sales & Operations Planning – Best Practices— review their firsthand experience with S&OP practices in organizations, attempting to flush out what they’ve found to be among the most blatant misconceptions and missteps, the sort that do real harm to the potential of S&OP. In parts 1 and 2, Chris and John discussed 11 common misconceptions, missteps, and bad practices in S&OP. In the final segment they emphasize the danger of excessive automation of the planning processes. This peril has at least two sources: one is the temptation to develop the supply plan (which attempts to ensure that overall resource capabilities are adequate to meet total market demand) by simply aggregating the detailed production schedules for individual items (a bottom-up approach); the second is to rely on advanced planning systems to the extent that requisite human judgment and leadership are marginalized.


  1. Incorporating Leading Indicators into your Sales Forecasts by Nikolaos Kourentzes and Yves Sagaert
    Using leading indicators for business forecasting—in contrast to macroeconomic forecasting—has been relatively rare, partly because our traditional time-series methods do not readily allow incorporation of external variables. Nowadays, however, we have an abundance of potentially useful indicators, and there is evidence that utilizing relevant ones in a forecasting model can significantly improve forecast accuracy and transparency.
  2. How to Respond to a Forecasting Sceptic by Paul Goodwin
    Recent high-profile events have led to scepticism about forecasting. So what underlies this scepticism about forecasting, and what can be done to challenge it? There appear to be several causes, but perhaps the most fundamental is a misunderstanding of what a forecast is.
  3. The M4 Competition: Interview with Spyros Makridakis
  4. Beware of Standard Prediction Intervals for Causal Model Forecasts by Len Tashman
    We’re all well aware that point forecasts are subject to a degree of error, and so we frequently report the forecast with a margin for error around it; that is, we present a prediction interval (PI). Much has been written about our prediction intervals often being too narrow to reflect the confidence we have in the forecast— for several reasons—and this is especially so when we forecast from regression and other causal models.
  5. Principles of Business Forecasting: Review of the Second Edition by Stephan Kolassa
    Keith Ord and Robert Fildes have prepared a second edition of their business forecasting textbook, taking Nikolaos Kourentzes on board as an additional coauthor. The first edition was reviewed both in Foresight (Kolassa, 2012) and in the International Journal of Forecasting (Sloboda, 2014). How does the second edition, henceforth PBF2, compare?
  6. Book Review by Oliver Schaer and Simon Spavound
    Forewarned: A Sceptic’s Guide to Prediction by Paul Goodwin
    This book clinically examines the issues surrounding forecasters having failed to predict the outcomes of notable events, and presents illuminating insights into the limitations of predictions made by humans, as well as by machines and their interpreters.

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