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Spare-Parts Forecasting: A Case Study at Hewlett-Packard

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Listed:
  • Jerry Z. Shan
  • Julie Ward
  • Shelen Jain
  • Jose Beltran
  • Feridoun Amirjalayer
  • Young-Wook Kim

Abstract

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. Copyright International Institute of Forecasters, 2009

Suggested Citation

  • Jerry Z. Shan & Julie Ward & Shelen Jain & Jose Beltran & Feridoun Amirjalayer & Young-Wook Kim, 2009. "Spare-Parts Forecasting: A Case Study at Hewlett-Packard," Foresight: The International Journal of Applied Forecasting, International Institute of Forecasters, issue 14, pages 40-47, Summer.
    • Handle: RePEc:for:ijafaa:y:2009:i:14:p:40-47
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    Cited by:

    1. Baecke, Philippe & De Baets, Shari & Vanderheyden, Karlien, 2017. "Investigating the added value of integrating human judgement into statistical demand forecasting systems," International Journal of Production Economics, Elsevier, vol. 191(C), pages 85-96.
    2. Mirko Kremer & Enno Siemsen & Douglas J. Thomas, 2016. "The Sum and Its Parts: Judgmental Hierarchical Forecasting," Management Science, INFORMS, vol. 62(9), pages 2745-2764, September.

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