Abstract
In addition to the efforts of academic researchers, there is a lot of interesting and important new work being done by industry forecasting practitioners. Among these are Martin Joseph and Alec Finney, who studied the application of statistical process control (SPC) methods during long careers at the pharmaceutical company, AstraZeneca.
In this article, Joseph and Finney extend the ideas of quality thought leader Donald Wheeler into business forecasting and planning. While Wheeler's book, Understanding Variation: The Key to Managing Chaos, is not about business forecasting, its scathing critique of management reporting and misinterpretation of data delivers a valuable lesson on the application of SPC methods to business decision making. Joseph and Finney build upon this lesson.
The objective of SPC is to distinguish "normal" variation in the output of a process from a signal that the process is changing-and possibly out of control. The authors show how process behavior charts (PBCs) can be extended from their original applications in quality control to time series of sales histories and forecasts.
A key observation is that most companies manage their businesses by means of tabular reports. Yet tables of data, rather than graphical visualizations, can leave the important information (upon which decisions need to be made) indistinguishable from the unremarkable. PBCs provide a means to make this distinction.
The authors provide practical guidance on how to create appropriate charts (e.g., when there is trend in the data, as often observed when forecasting sales). They also show how to identify signals in the data, so that the forecaster will know when to act and when to avoid overreacting. They present three vignettes of situations that regularly occur in S&OP meetings and discuss how the PBCs provide a crucial context for deciding whether new actions are needed.