Changing the paradigm for business forecasting (Part 5 of 12)

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Implications for the Offensive Paradigm

The worldview promulgated by the Offensive paradigm is that if we only had MORE – more data, more computational power, more complex models, more elaborate processes – we could eventually solve the business forecasting problem. But this just doesn’t seem to be the case.

Operating within the Offensive paradigm, we would expect the focus on MORE would generate MORE accurate forecasts. But it doesn’t.

You can always cherry pick instances where a particular technique, with a particular dataset, under particular conditions, generate forecasts over a particular time period that are particularly good. Paul Goodwin’s article points out several of those

Changing the Paradigm for Business Forecasting

For over a half century we have been operating within a paradigm that, to a large extent, esteems complexity in forecasting. Yet we are now facing the evidence that complexity isn’t working like we need it to be – it’s no longer substantially improving our forecasts. The Offensive paradigm may have run its course.

Kuhn says that a discredited paradigm does not just go away without a fight. The transition can take a long time, and the old one does not go away until it is replaced by something new. He quotes the physicist Max Planck, “[A] new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.”

I’m certainly not wishing ill health on followers of the Offensive paradigm! But Planck has a point.

Copernicus published his heliocentric theory – placing the Sun rather than the Earth at the center of the universe – in the early 1500’s. But it took over a century before it was generally accepted and replaced the geocentric paradigm. Isaac Newton’s ideas were not generally accepted for over 50 years.

Why the Attraction for the Offensive Paradigm

So why the continuing attraction for the Offensive paradigm? Green and Armstrong took a look at that, too, in a section of their paper headed, “Why simplicity repels and complexity lures.”

They suggest that the popularity of complexity may be due to incentives:

  • Some people are reassured by complexity.

If you are consulting for a company, and suggest a forecasting method that is intuitive, reasonable, and simple, the client might ask why am I paying you? I could do that myself!

  • There may be resistance to simple methods.

A 1972 paper stated that “Few people would accept the naïve no-change model even if it were clearly shown to be more accurate.”*

A 2012 paper found that senior academics resisted overwhelming evidence that simple methods provide forecasts that are more accurate than those from complex ones.**

  • Complexity can be persuasive.

In the famous “Dr. Fox” study from 1973, a complex lecture was given high ratings even though the content was nonsense. Respondents said that while they did not understand everything Dr. Fox said, the guy knew his stuff.***

In 1980 Armstrong did a similar study using simple and complex versions of papers with identical content. The academic reviewers rated the papers more highly when written in more complex ways.****

Another experiment in 2012 used two versions of an abstract, one which included a sentence from an unrelated paper that contained an algebraic equation. 200 reviewers, all of whom had post graduate degrees in the subject matter, judged the abstract with the nonsense mathematics to be of higher quality.*****

  • You may be able to advance your career by writing in a complex way.

Software developed by MIT students randomly selects common complex words and applies grammar rules to produce research papers on computer science. At least 120 such computer generated papers have been published in peer reviewed journals.

  • To support decision maker's plans

If you are providing forecasts for someone who already knows what they want to do, you can always concoct a model that generates forecasts to justify their decision.


*Juster, F.T. (1972). An evaluation of the recent record in short-term forecasting. Business Economics, 7(3), 22-26.

**Hogarth, R.M. (2012). When simple is hard to accept. In Todd, Gigerenzer, & Group (Eds.), Ecological Rationality: Intelligence in the World (pp. 61-79).

***Naftulin, D.H., Ware, J.E., Jr., & Donnelly, F.A. (1973). The Doctor Fox lecture: a paradigm of educational seduction. Journal of Medical Education, 48, 630-635.

****Armstrong, J.S. (1980). Unintelligble management research and academic prestige. Interfaces, 10(2), 80-86.

*****Eriksson, K. (2012). The nonsense math effect. Judgment and Decision Making 7(6), 746-749.

[See all 12 posts in the business forecasting paradigms series.]

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About Author

Mike Gilliland

Product Marketing Manager

Michael Gilliland is a longtime business forecasting practitioner and formerly a Product Marketing Manager for SAS Forecasting. He is on the Board of Directors of the International Institute of Forecasters, and is Associate Editor of their practitioner journal Foresight: The International Journal of Applied Forecasting. Mike is author of The Business Forecasting Deal (Wiley, 2010) and former editor of the free e-book Forecasting with SAS: Special Collection (SAS Press, 2020). He is principal editor of Business Forecasting: Practical Problems and Solutions (Wiley, 2015) and Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning (Wiley, 2021). In 2017 Mike received the Institute of Business Forecasting's Lifetime Achievement Award. In 2021 his paper "FVA: A Reality Check on Forecasting Practices" was inducted into the Foresight Hall of Fame. Mike initiated The Business Forecasting Deal blog in 2009 to help expose the seamy underbelly of forecasting practice, and to provide practical solutions to its most vexing problems.

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