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Predicting Demand from Sales Data in the Presence of Stockouts

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  • William E. Wecker

    (University of Chicago)

Abstract

The effect of stockouts on prediction accuracy is analyzed. The forecasting bias that results and the effect on the prediction error variance are explored and are seen to depend on the frequency of stockouts, the coefficient of variation of demand, and the serial correlation of demand.

Suggested Citation

  • William E. Wecker, 1978. "Predicting Demand from Sales Data in the Presence of Stockouts," Management Science, INFORMS, vol. 24(10), pages 1043-1054, June.
    • Handle: RePEc:inm:ormnsc:v:24:y:1978:i:10:p:1043-1054
    DOI: 10.1287/mnsc.24.10.1043
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    Cited by:

    1. Anna‐Lena Sachs & Michael Becker‐Peth & Stefan Minner & Ulrich W. Thonemann, 2022. "Empirical newsvendor biases: Are target service levels achieved effectively and efficiently?," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1839-1855, April.
    2. Vasudaven, M. & Nair, M. G. & Sithole, M. M., 1996. "On estimation for censored autoregressive data," Statistics & Probability Letters, Elsevier, vol. 31(2), pages 97-105, December.
    3. Gah-Yi Ban, 2020. "Confidence Intervals for Data-Driven Inventory Policies with Demand Censoring," Operations Research, INFORMS, vol. 68(2), pages 309-326, March.
    4. Adam J. Mersereau, 2015. "Demand Estimation from Censored Observations with Inventory Record Inaccuracy," Manufacturing & Service Operations Management, INFORMS, vol. 17(3), pages 335-349, July.
    5. Gen Sakoda & Hideki Takayasu & Misako Takayasu, 2019. "Data Science Solutions for Retail Strategy to Reduce Waste Keeping High Profit," Sustainability, MDPI, vol. 11(13), pages 1-30, June.
    6. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2022. "Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1283-1318.
    7. Perera, H. Niles & Hurley, Jason & Fahimnia, Behnam & Reisi, Mohsen, 2019. "The human factor in supply chain forecasting: A systematic review," European Journal of Operational Research, Elsevier, vol. 274(2), pages 574-600.
    8. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2019. "Retail forecasting: research and practice," MPRA Paper 89356, University Library of Munich, Germany.
    9. Opher Baron & Iman Hajizadeh & Joseph Milner, 2011. "Now Playing: DVD Purchasing for a Multilocation Rental Firm," Manufacturing & Service Operations Management, INFORMS, vol. 13(2), pages 209-226, April.
    10. Georgia Perakis & Melvyn Sim & Qinshen Tang & Peng Xiong, 2023. "Robust Pricing and Production with Information Partitioning and Adaptation," Management Science, INFORMS, vol. 69(3), pages 1398-1419, March.
    11. Aditya Jain & Nils Rudi & Tong Wang, 2015. "Demand Estimation and Ordering Under Censoring: Stock-Out Timing Is (Almost) All You Need," Operations Research, INFORMS, vol. 63(1), pages 134-150, February.
    12. Boone, Tonya & Ganeshan, Ram & Jain, Aditya & Sanders, Nada R., 2019. "Forecasting sales in the supply chain: Consumer analytics in the big data era," International Journal of Forecasting, Elsevier, vol. 35(1), pages 170-180.
    13. Steven Nahmias, 1994. "Demand estimation in lost sales inventory systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 41(6), pages 739-757, October.
    14. Hakan Uslu & Larry Teeter, 2017. "Shutdown Decision of Firms Based on Variable Costs and Demand," The American Economist, Sage Publications, vol. 62(1), pages 43-65, March.
    15. Lau, Hon-Shiang & Hing-Ling Lau, Amy, 1996. "Estimating the demand distributions of single-period items having frequent stockouts," European Journal of Operational Research, Elsevier, vol. 92(2), pages 254-265, July.
    16. Narendra Agrawal & Stephen A. Smith, 1996. "Estimating negative binomial demand for retail inventory management with unobservable lost sales," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(6), pages 839-861, September.

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