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Spring 2011


  1. Projecting Success: Don’t Forget the Base Rate by Paul Goodwin 
    Suppose that you make an outrageously extreme forecast, such as predicting a quadrupling within a year of the demand for your company’s product, or the successful implementation of a technology that within three years makes road accidents impossible. Your friends give you strange looks and think you may have been working too hard. You catch your colleagues mocking your prediction in the coffee room.
  2. Financial Forecasting: Accuracy versus Profitability by Roy Batchelor
    In a perfect world, forecast accuracy would be a reliable guide to the monetary value of the forecast; more accurate forecasts would be more profitable. But who lives in a perfect world? In real life, accuracy and monetary value do not necessarily correspond and, as Roy shows, can move in opposite directions. His examples reveal disconnections between accuracy and profitability among financial forecasters and how the same might occur among sales forecasters. To better explain this situation, Roy distinguishes between (a) the small movements in a target variable that occur ordinarily, and (b) the large changes that occur only occasionally. His point is similar to that made by Wil Gorr’s accompanying article in this issue on forecasting exceptional demands (p. 22): not only might we need different models to forecast exceptional vs. ordinary demand, but also different forecast-accuracy metrics. This clearly is a lesson worth attending to.
  3. Forecasting Exceptional Demand: Not the Same as Forecasting Ordinary Demand by Wilpen Gorr [Includes Forecaster in the Field: Wilpen Gorr]
    Many forecasting models designed to track and forecast trend and seasonality do well enough for ordinary demand conditions but are challenged by exceptional patterns such as sudden large jumps and turning points. Wil Gorr proposes a framework for exceptional-demand situations that is based on Receiver Operating Characteristics (ROC) analysis, in which models for exceptional demand forecasts work as a team with models to forecast ordinary demands. The ROC framework gives less emphasis to traditional forecast accuracy metrics such as the MAPE in favor of metrics to distinguish between real and false signals of exceptional demand.
  4. Getting Your Forecasting and Planning Fundamentals Right: A Pharmaceutical Case Study by Alec Finney, Martin Joseph and Hannah Kurth 
    This new article illustrates how the audit process plays out within an organization. It provides two accounts based on a case study of a global biotechnology specialty-care group based in Paris, France.Alec and Martin’s story presents the auditors’ viewpoint. It describes the way the audit and subsequent analysis probed beneath the surface to reveal not only consensus views but polarized and outlying views. Hannah’s story is the internal view at the company, describing the challenges faced, how the interviews were received, and how the recommendations were presented to management. She concludes with an assessment of the benefits that accrued.
  5. Predicting the Results of the 2010 Midterm Elections: Judgment, Econometrics, and Prediction Markets by Alfred Cuzán
    Alfred Cuzán offers his postmortem on forecasts made for the midterm elections for the U.S. House of Representatives. His evaluation compares the judgment of three experts, six statistical models, and one (betting) prediction market. It seems like the best political forecasts emerge when forecasters place their bets. However, this issue of Foresight contains a related article on corporate prediction markets (p. 35), where the challenges of implementation are arguably greater than those in election markets.
  6. Forecast Accuracy Measurement: Two Commentaries by Jim Hoover and Mark Little
  7. Book Review by Marcus O’Connor
    Being Wrong: Adventures in the Margin of Error by Kathryn Schulz
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