The forecasting canon: nine generalizations to improve forecast accuracy

J. Scott Armstrong, University of Pennsylvania

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Reprinted from Foresight: The International Journal of Applied Forecasting, Volume 1, Issue 1, June 2005, pages 29-35. The author has asserted his/her right to include this material in ScholarlyCommons@Penn.

Abstract

Preview: Using findings from empirically-based comparisons, Scott develops nine generalizations that can improve forecast accuracy. He finds that these are often ignored by organizations, so that attention to them offers substantial opportunities for gain. In this paper, Scott offers recommendations on how to structure a forecasting problem, how to tap managers’ knowledge, and how to select appropriate forecasting methods.