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Do experts' adjustments on model-based SKU-level forecasts improve forecast quality?

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Author Info

  • Philip Hans Franses

    (Econometric Institute, Erasmus University, Rotterdam, The Netherlands)

  • Rianne Legerstee

    (Econometric Institute, Erasmus University, Rotterdam, The Netherlands)

Abstract

Model-based SKU-level forecasts are often adjusted by experts. In this paper we propose a statistical methodology to test whether these expert forecasts improve on model forecasts. Application of the methodology to a very large database concerning experts in 35 countries who adjust SKU-level forecasts for pharmaceutical products in seven distinct categories leads to the general conclusion that expert forecasts are equally good at best, but are more often worse than model-based forecasts. We explore whether this is due to experts putting too much weight on their contribution, and this indeed turns out to be the case. Copyright © 2009 John Wiley & Sons, Ltd.

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File URL: http://hdl.handle.net/10.1002/for.1129
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Bibliographic Info

Article provided by John Wiley & Sons, Ltd. in its journal Journal of Forecasting.

Volume (Year): 29 (2010)
Issue (Month): 3 ()
Pages: 331-340

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Handle: RePEc:jof:jforec:v:29:y:2010:i:3:p:331-340

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Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966

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Cited by:
  1. Davydenko, Andrey & Fildes, Robert, 2013. "Measuring forecasting accuracy: The case of judgmental adjustments to SKU-level demand forecasts," International Journal of Forecasting, Elsevier, vol. 29(3), pages 510-522.
  2. Philip Hans Franses & Rianne Legerstee & Richard Paap, 2011. "Estimating Loss Functions of Experts," Tinbergen Institute Discussion Papers 11-177/4, Tinbergen Institute.
  3. Philip Hans Franses & Chia-Lin Chang & Michael McAleer, 2011. "Analyzing Fixed-event Forecast Revisions," Working Papers in Economics 11/25, University of Canterbury, Department of Economics and Finance.
  4. Goodwin, Paul & Sinan Gönül, M. & Önkal, Dilek, 2013. "Antecedents and effects of trust in forecasting advice," International Journal of Forecasting, Elsevier, vol. 29(2), pages 354-366.
  5. Rianne Legerstee & Philip Hans Franses, 2014. "Do Experts’ SKU Forecasts Improve after Feedback?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(1), pages 69-79, 01.
  6. Legerstee, R. & Franses, Ph.H.B.F. & Paap, R., 2011. "Do experts incorporate statistical model forecasts and should they?," Econometric Institute Research Papers EI2011-32, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  7. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2014. "Golden Rule of Forecasting: Be conservative," MPRA Paper 53579, University Library of Munich, Germany.
  8. Rianne Legerstee & Philip Hans Franses & Richard Paap, 2011. "Do Experts incorporate Statistical Model Forecasts and should they?," Tinbergen Institute Discussion Papers 11-141/4, Tinbergen Institute.
  9. Philip Hans Franses & Rianne Legerstee & Richard Paap, 2011. "Estimating Loss Functions of Experts," Tinbergen Institute Discussion Papers 11-177/4, Tinbergen Institute.
  10. Rianne Legerstee & Philip Hans Franses, 2011. "Do Experts' SKU Forecasts improve after Feedback?," Tinbergen Institute Discussion Papers 11-135/4, Tinbergen Institute.
  11. Bert de Bruijn & Philip Hans Franses, 2012. "Managing Sales Forecasters," Tinbergen Institute Discussion Papers 12-131/III, Tinbergen Institute.
  12. Chia-Lin Chang & Bert de Bruijn & Philip Hans Franses & Michael McAleer, 2013. "Analyzing Fixed-Event Forecast Revisions," Tinbergen Institute Discussion Papers 13-057/III, Tinbergen Institute.
  13. Bert de Bruijn & Philip Hans Franses, 2012. "Managing Sales Forecasters," Tinbergen Institute Discussion Papers 12-131/III, Tinbergen Institute.
  14. Franses, Philip Hans & Legerstee, Rianne, 2013. "Do statistical forecasting models for SKU-level data benefit from including past expert knowledge?," International Journal of Forecasting, Elsevier, vol. 29(1), pages 80-87.

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