In order to do business, we have to use predictions of various sorts. These range from seat-of-the-pants guesses to the results of sophisticated modeling. In every case, the key to effective forecasting is to understand the uncertainty in the forecast. Ways to do this are the subject of this article.

For many years I taught the senior-level forecasting course in the college of business at the University of Tennessee. In that class, we covered many different techniques for massaging the data to obtain forecasts. Regardless of the complexity of the technique used, the limiting factor in every forecast was always the noise in the data themselves. The various techniques would provide exact values, but these values would only be as good as the uncertainty in the source material.

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