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Do Experts' SKU Forecasts improve after Feedback?

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  • Rianne Legerstee

    (Erasmus University Rotterdam)

  • Philip Hans Franses

    (Erasmus University Rotterdam)

Abstract

We analyze the behavior of experts who quote forecasts for monthly SKU-level sales data where we compare data before and after the moment that experts received different kinds of feedback on their behavior. We have data for 21 experts located in as many countries who make SKU-level forecasts for a variety of pharmaceutical products for October 2006 to September 2007. We study the behavior of the experts by comparing their forecasts with those from an automated statistical program, and we report the forecast accuracy over these 12 months. In September 2007 these experts were given feedback on their behavior and they received a training at the headquarters' office, where specific attention was given to the ins and outs of the statistical program. Next, we study the behavior of the experts for the 3 months after the training session, that is, October 2007 to December 2007. Our main conclusion is that in the second period the experts' forecasts deviated lesser from the statistical forecasts and that their accuracy improved substantially.

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Bibliographic Info

Paper provided by Tinbergen Institute in its series Tinbergen Institute Discussion Papers with number 11-135/4.

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Date of creation: 26 Sep 2011
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Handle: RePEc:dgr:uvatin:20110135

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Web page: http://www.tinbergen.nl

Related research

Keywords: model forecasts; expert forecasts; judgmental adjustment; feedback; outcome feedback; performance feedback; cognitive process feedback; task properties feedback;

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  1. Robert C. Blattberg & Stephen J. Hoch, 1990. "Database Models and Managerial Intuition: 50% Model + 50% Manager," Management Science, INFORMS, vol. 36(8), pages 887-899, August.
  2. Franses, Philip Hans & Legerstee, Rianne, 2009. "Properties of expert adjustments on model-based SKU-level forecasts," International Journal of Forecasting, Elsevier, vol. 25(1), pages 35-47.
  3. Sanders, Nada R., 2009. "Comments on "Effective forecasting and judgmental adjustments: An empirical evaluation and strategies for improvement in supply-chain planning"," International Journal of Forecasting, Elsevier, vol. 25(1), pages 24-26.
  4. George Athanasopoulos & Rob J Hyndman, 2011. "The value of feedback in forecasting competitions," Monash Econometrics and Business Statistics Working Papers 3/11, Monash University, Department of Econometrics and Business Statistics.
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  8. Welch, Eric & Bretschneider, Stuart & Rohrbaugh, John, 1998. "Accuracy of judgmental extrapolation of time series data: Characteristics, causes, and remediation strategies for forecasting," International Journal of Forecasting, Elsevier, vol. 14(1), pages 95-110, March.
  9. Flores, Benito E., 2009. "Comments on "Effective forecasting and judgmental adjustments: An empirical evaluation and strategies for improvement in supply-chain planning"," International Journal of Forecasting, Elsevier, vol. 25(1), pages 27-29.
  10. Philip Hans Franses & Rianne Legerstee, 2010. "Do experts' adjustments on model-based SKU-level forecasts improve forecast quality?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 331-340.
  11. Sinan Gönül & Dilek Önkal & Paul Goodwin, 2009. "Expectations, use and judgmental adjustment of external financial and economic forecasts: an empirical investigation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 19-37.
  12. Önkal, Dilek, 2009. "Comments on "Effective forecasting and judgmental adjustments: An empirical evaluation and strategies for improvement in supply-chain planning"," International Journal of Forecasting, Elsevier, vol. 25(1), pages 30-31.
  13. Fildes, Robert & Goodwin, Paul & Lawrence, Michael & Nikolopoulos, Konstantinos, 2009. "Effective forecasting and judgmental adjustments: an empirical evaluation and strategies for improvement in supply-chain planning," International Journal of Forecasting, Elsevier, vol. 25(1), pages 3-23.
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  15. Robert Fildes & Paul Goodwin, 2007. "Good and Bad Judgment in Forecasting: Lessons from Four Companies," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 8, pages 5-10, Fall.
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