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Multi-item sales forecasting with total and split exponential smoothing

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  • J W Taylor

    (University of Oxford)

Abstract

Efficient supply chain management relies on accurate demand forecasting. Typically, forecasts are required at frequent intervals for many items. Forecasting methods suitable for this application are those that can be relied upon to produce robust and accurate predictions when implemented within an automated procedure. Exponential smoothing methods are a common choice. In this empirical case study paper, we evaluate a recently proposed seasonal exponential smoothing method that has previously been considered only for forecasting daily supermarket sales. We term this method ‘total and split’ exponential smoothing, and apply it to monthly sales data from a publishing company. The resulting forecasts are compared against a variety of methods, including several available in the software currently used by the company. Our results show total and split exponential smoothing outperforming the other methods considered. The results were also impressive for a method that trims outliers and then applies simple exponential smoothing.

Suggested Citation

  • J W Taylor, 2011. "Multi-item sales forecasting with total and split exponential smoothing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 555-563, March.
  • Handle: RePEc:pal:jorsoc:v:62:y:2011:i:3:d:10.1057_jors.2010.95
    DOI: 10.1057/jors.2010.95
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    References listed on IDEAS

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    Cited by:

    1. Chethana Dharmawardane & Ville Sillanpää & Jan Holmström, 2021. "High-frequency forecasting for grocery point-of-sales: intervention in practice and theoretical implications for operational design," Operations Management Research, Springer, vol. 14(1), pages 38-60, June.
    2. Liang Qiao & Doudou Liu & Xueliang Yuan & Qingsong Wang & Qiao Ma, 2020. "Generation and Prediction of Construction and Demolition Waste Using Exponential Smoothing Method: A Case Study of Shandong Province, China," Sustainability, MDPI, vol. 12(12), pages 1-12, June.
    3. Mun, Mak Kit & Chong, Choo Wei, 2018. "Forecasting Movie Demand Using Total and Split Exponential Smoothing," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 52(2), pages 81-94.

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