Guest Blogger: Len Tashman previews Summer 2009 issue of Foresight


The Summer 2009 issue of Foresight is now available, and features a section on “Rethinking the Ways We Forecast.” Here is Editor Len Tashman’s preview:

Are traditional forecasting tools suitable for predicting complex systems like the economy and the global climate? Basically, no, argue David Orrell and Patrick McSharry: such tools are based on equations that model a system’s components but ignore its emergent properties, the global effects arising from those components. They call this the reductionist approach. All models, they assert, make simplifying assumptions, but the reductionist
approach makes the wrong assumptions.

David and Patrick then describe key elements for more effective modeling of complex systems, including agent-based models, network analysis, nonlinear dynamics, and scenarios. These models shift the emphasis from the point forecasts most often demanded by business decision makers to the assessment of risks in what the future may bring.

The section continues with two commentaries. Roy Batchelor illustrates the difference between a simple macroeconomic-forecasting model (representing the reductionist approach) and a complex-system model, and compares the virtues of the two viewpoints. Roy’s concern is that specific complex-systems models for the economy may be unwieldy and unstable, complexifying without improving forecasting.

Robert Fildes and Paul Goodwin note that the complex-systems models are untried in the arena of economics and that we need to explore whether these models are better applied individually or together. They reinforce the Orrell-McSharry thesis that point forecasts are overemphasized and misapplied but argue that they are unavoidable in the business world. Robert and Paul conclude with their own scenario on the future of forecast modeling.

This special feature wraps up with David and Patrick’s responses to the commentaries. They emphasize that complex-systems models need not be complex and that many biological applications of these models are relatively simple, indeed simpler than many current models in use.

In your editor’s view, the section reveals essential agreement among forecasters that there is much room for rethinking and refining our current approaches to forecasting, placing greater emphasis on risk assessment and preparation for uncertain futures.


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.

Leave A Reply

Back to Top