Summer 2009 Issue

Special Feature: Rethinking the Ways We Forecast

  • Preview by Len Tashman, Editor
    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.
  • A Systems Approach to Forecasting by Patrick McSharry and David Orrell
    The practice and profession of computer-based numerical forecasting have reached a crossroads. Forecasting tools and availability of high-quality data have improved enormously in recent decades, but not forecast quality. In areas including weather forecasting, genetics and, particularly, economics – as shown by our failure to predict the current financial crisis – we have become increasingly aware of the limits of prediction. It’s clear we need to change the way we make forecasts and the questions we attempt to address. To move forward, we should adopt a systems approach.
  • Commentaries:
    • Why Do We Need Complexification? Roy Batchelor
    • Are We Ready for a New Approach? Paul Goodwin and Robert Fildes
    • Reply to Commentaries, Patrick McSharry and David Orrell


    1. Spare Parts Forecasting: Case Study at HP by Jerry Shan, Julie Ward, Shelen Jain, Jose Beltran, Feridoun Amirjalayer, and Young-Wok Kim
      Spare parts generate high sales margins and improve customer loyalty by extending the useful life of base products. Forecasting and managing the spare-parts business is challenging, however, due in no small measure to short life cycles and long support life for the base products. At Hewlett-Packard, the Replacement Parts Business (RPB) was challenged by shortages that drove customers to competing parts suppliers. To deal with this threat, an HP team refined the company’s forecasting methodology. This paper describes the business issues involved and the forecasting processes developed. Of particular methodological interest is their approach to (a) choosing between monthly and quarterly forecasts, (b) adjusting the historical data for price/promotion effects, and (c) combining regression and time-series forecasts.
    2. How to Track Forecast Accuracy to Guide Forecast Process Improvement by Jim Hoover
      While considerable attention has been paid to the measurement of forecast accuracy for individual items at particular points in time, issues around an aggregated forecastaccuracy metric and its tracking over time still present opportunities for discussion. Jim Hoover talks about why organizations have neglected the task of tracking forecast accuracy and offers a step-by-step guide for getting back on the track.
    3. Sales and Operations Planning: Simpler, Better, and Needed More than Ever by Bob Stahl
      Sales and Operations Planning (S&OP) has become perhaps the most significant innovation of this generation for forecast process improvement, bringing demand people and supply people together in a structured series of steps. But the effective uses of Simpler, Better, and Needed More than Ever S&OP are not widely understood, and while practitioners need to hear what is working, it is imperative for them to learn what is not working, and why, and how companies are correcting the problems. In this inaugural column, Bob Stahl lays the foundation for understanding what the executive component of S&OP is – and where it fits in the organizational hierarchy.
    4. Software Review by Tom Yokum
      Sparklines: The Tom Thumb of Statistical Graphs
    5. Forecasting Intelligence Column: Free and Easy Access to Monthly Forecasts, by Roy Pearson {Free article}
    6. Book Review by Peter Sephton {Free article}
      The Drunkard’s Walk: How Randomness Rules Our Lives by Leonard Mlodinow

Additional information


Complete Issue, Special Feature, Special Feature 1, Special Feature 2, Article 1, Article 2, Article 3, Article 4, Article 5, Article 6, Article 7, Article 8, Article 9, Free Article, Free Article 1, Free Article 2, Free Article 3