Golden Rule of Forecasting: Be Conservative

50 Pages Posted: 15 Aug 2015

See all articles by J. Scott Armstrong

J. Scott Armstrong

University of Pennsylvania - Marketing Department

Kesten C. Green

University of South Australia - UniSA Business School; Ehrenberg-Bass Institute for Marketing Science

Andreas Graefe

Macromedia University of Applied Sciences

Date Written: March 1, 2015

Abstract

This article proposes a unifying theory, or Golden Rule, of forecasting. The Golden Rule of Forecasting is to be conservative. A conservative forecast is consistent with cumulative knowledge about the present and the past. To be conservative, forecasters must seek out and use all knowledge relevant to the problem, including knowledge of methods validated for the situation. Twenty-eight guidelines are logically deduced from the Golden Rule. A review of evidence identified 105 papers with experimental comparisons; 102 support the guidelines. Ignoring a single guideline increased forecast error by more than two-fifths on average. Ignoring the Golden Rule is likely to harm accuracy most when the situation is uncertain and complex, and when bias is likely. Non-experts who use the Golden Rule can identify dubious forecasts quickly and inexpensively. To date, ignorance of research findings, bias, sophisticated statistical procedures, and the proliferation of big data, have led forecasters to violate the Golden Rule. As a result, despite major advances in evidence-based forecasting methods, forecasting practice in many fields has failed to improve over the past half-century.

Keywords: analytics, bias, big data, causality, checklists, combining, elections, index method, judgmental bootstrapping, structured analogies, uncertainty

Suggested Citation

Armstrong, J. Scott and Green, Kesten C. and Graefe, Andreas, Golden Rule of Forecasting: Be Conservative (March 1, 2015). Available at SSRN: https://ssrn.com/abstract=2643546 or http://dx.doi.org/10.2139/ssrn.2643546

J. Scott Armstrong (Contact Author)

University of Pennsylvania - Marketing Department ( email )

700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States
215-898-5087 (Phone)
215-898-2534 (Fax)

HOME PAGE: http://marketing.wharton.upenn.edu/people/faculty/armstrong.cfm

Kesten C. Green

University of South Australia - UniSA Business School ( email )

GPO Box 2471
Adelaide, SA 5001
Australia
+61 8 83012 9097 (Phone)

HOME PAGE: http://people.unisa.edu.au/Kesten.Green

Ehrenberg-Bass Institute for Marketing Science ( email )

Australia

HOME PAGE: http://www.marketingscience.info/people/KestenGreen.html

Andreas Graefe

Macromedia University of Applied Sciences ( email )

Sandstrasse 9
Munich, Bavaria 80337
Germany

HOME PAGE: http://www.andreas-graefe.org

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