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Summer 2010 Issue

Special Feature: Forecasting for the Supply Chain

  • Defining “Demand” for Demand Forecasting by Mike Gilliland
    Demand forecasting is often uncritically based on histories of orders received, shipments/sales, or some combination of the two. As Mike Gilliland explains in this article, the ultimate goal – a measurement of true demand – is elusive and not always amenable to simple formulae based on orders and shipments. What to do? Recognizing the measurement difficulties, Mike suggests we can often derive a proxy for true demand that is close enough to be useful in generating an unconstrained forecast.
  • Choosing Levels of Aggregation for Supply Chain Forecasts by John Boylan
    With this issue, Foresight debuts a new column on supply-chain forecasting. John Boylan, our column editor, will offer his insights on the practical challenges of forecasting and reconciling forecasts across the hierarchical levels of a supply chain.
  • The Value of Forecast Information Sharing in the Supply Chain by Mohammad Ali and John Boylan
    Many studies have pointed to the possibility of substantial benefits from collaboration among supply-chain partners, including information sharing – one form of which is the sharing of forecast information (FIS). In this article, Mohammad Ali and John Boylan report the substantial and specific benefits of FIS found in their study of two large companies: a European supermarket and a U.S. hardware manufacturer.


    1. Worst-Case Scenarios in Forecasting: How Bad Can Things Get? by Roy Batchelor
      Roy Batchelor, Foresight’s Financial Forecasting Editor, explains that conventional business- forecasting models are not set up to tell us about the impacts of extreme events—hence, their worst-case forecasts are liable to be less severe than the worst that plays out in the future. While recognition of this caveat is important in itself, there are ways to model the impacts of extreme events and thus derive a realistic indication of downside risk.
    2. The Keys to the White House: Forecast for 2012 by Allan Lichtman
      The “Keys to the White House” is a forecasting model that has retrospectively predicted the popular-vote winner of every American presidential election from 1860 to 1980, and forecast, well ahead of time, the popular-vote winner of every presidential election from 1984 through 2008. Allan Lichtman, the guru behind the model, writes, “Already, the Keys have produced a relatively secure forecast for the presidential election of 2012. Barring major and unexpected setbacks at home and abroad, Barack Obama will win reelection to another four years in the White House.”
    3. Looking Under the Hood of That Trend by Roy Pearson
      The Spring 2010 issue of Foresight featured Adam Gordon’s presentation of “A DEFT Approach to Trend- Based Foresight.” DEFT is the Drivers, Enablers, Friction, and Turners that underpin a trend and determine its course and longevity. In this article, Roy Pearson offers his perspectives on implementing the DEFT approach and discusses how DEFT can help augment other takes on trend projections.
    4. Book Review by Ira Sohn
      The Next Hundred Million:America in 2050 by Joel Kotkin
    5. Letter to the Editor: Should You Report Forecast Error or Forecast Accuracy? by David Hawitt
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