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Stock keeping unit fill rate specification

Author

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  • Teunter, R.H.
  • Syntetos, A.A.
  • Babai, M.Z.

Abstract

The fill rate is the most widely applied service level measure in industry and yet there is minimal advice available on how it should be differentiated on an individual Stock Keeping Unit (SKU) basis given that there is an overall system target service level. The typical approach utilized in practice, and suggested in academic textbooks, is to set the individual service levels equal to the targeted performance required across an entire stock base or a certain class of SKUs (e.g., in ABC classification). In this paper it is argued that this approach is far from optimal and a simple methodology is proposed that is shown (on real life datasets) to be associated with reductions in stock investments. In addition, the new approach is intuitive, very easy to implement and thus highly likely to be positively received by practitioners and software manufacturers.

Suggested Citation

  • Teunter, R.H. & Syntetos, A.A. & Babai, M.Z., 2017. "Stock keeping unit fill rate specification," European Journal of Operational Research, Elsevier, vol. 259(3), pages 917-925.
    • Handle: RePEc:eee:ejores:v:259:y:2017:i:3:p:917-925
    DOI: 10.1016/j.ejor.2016.11.017
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    References listed on IDEAS

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    Cited by:

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    2. Achkar, Victoria G. & Brunaud, Braulio B. & Pérez, Héctor D. & Musa, Rami & Méndez, Carlos A. & Grossmann, Ignacio E., 2024. "Extensions to the guaranteed service model for industrial applications of multi-echelon inventory optimization," European Journal of Operational Research, Elsevier, vol. 313(1), pages 192-206.
    3. van Donselaar, Karel & Broekmeulen, Rob & de Kok, Ton, 2021. "Heuristics for setting reorder levels in periodic review inventory systems with an aggregate service constraint," International Journal of Production Economics, Elsevier, vol. 237(C).
    4. Sun, Yimeng & Qiu, Ruozhen & Sun, Minghe, 2024. "A robust optimization approach for inventory management with limited-time discounts and service-level requirement under demand uncertainty," International Journal of Production Economics, Elsevier, vol. 267(C).
    5. Ye, Yuan & Lu, Yonggang & Robinson, Powell & Narayanan, Arunachalam, 2022. "An empirical Bayes approach to incorporating demand intermittency and irregularity into inventory control," European Journal of Operational Research, Elsevier, vol. 303(1), pages 255-272.
    6. Bruzda, Joanna, 2020. "Demand forecasting under fill rate constraints—The case of re-order points," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1342-1361.
    7. De Bock, Koen W. & Coussement, Kristof & Caigny, Arno De & Słowiński, Roman & Baesens, Bart & Boute, Robert N. & Choi, Tsan-Ming & Delen, Dursun & Kraus, Mathias & Lessmann, Stefan & Maldonado, Sebast, 2024. "Explainable AI for Operational Research: A defining framework, methods, applications, and a research agenda," European Journal of Operational Research, Elsevier, vol. 317(2), pages 249-272.

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