Morlidge's Little Book of Operational Forecasting (part 6 of 8)

0

Book CoverNote: Following is an eight-part serialization of selected content from Steve Morlidge's The Little (Illustrated) Book of Operational Forecasting.

The forecasting challenge

It is not possible to forecast any future outcomes precisely.

Only the signal is potentially forecastable – noise is unforecastable in principle.

And all forecasts assume that the future is more or less like the past. But all past data infected by noise, which hides the signal.

And signals can and do change.

The challenge is to spot the patterns of signals hidden in data about the past, to project these in the future and to forecast whether, when and how these patterns will change.

And it is not possible to know in advance whether any particular forecasting technique will work. Sophistication is no guarantee of performance.

The only way is to measure how successful a forecast process has actually been in estimating the signal.

TAKEOUT

In forecasting, there are no marks for style, only results matter.

Graphic6

Coming Next: The measurement challenge

Measuring forecast error is not an end in itself – it only has value to the extent that it helps to improve the quality of forecasts. But, it is surprisingly tricky to measure this because some level of error is unavoidable. This lesson explains why simplistic measures of forecast error cannot be trusted.

Share

About Author

Mike Gilliland

Product Marketing Manager

Michael Gilliland is author of The Business Forecasting Deal (the book), and editor of Business Forecasting: Practical Problems and Solutions. He is a longtime business forecasting practitioner, and currently Product Marketing Manager for SAS Forecasting software. Mike serves on the Board of Directors for the International Institute of Forecasters, and received the 2017 Lifetime Achievement in Business Forecast award from the Institute of Business Forecasting. He initiated The Business Forecasting Deal (the blog) to help expose the seamy underbelly of forecasting practice, and to provide practical solutions to its most vexing problems.

Leave A Reply

Back to Top