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Evaluating Count Prioritization Procedures for Improving Inventory Accuracy in Retail Stores

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DeHoratius, Nicole ; Holzapfel, Andreas ; Kuhn, Heinrich ; Mersereau, Adam J. ; Sternbeck, Michael:
Evaluating Count Prioritization Procedures for Improving Inventory Accuracy in Retail Stores.
In: Manufacturing & service operations management : M & SOM / Institute for Operations Research and the Management Sciences. 25 (2022) 1. - S. 288-306.
ISSN 1526-5498 ; 1523-4614

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Volltext Link zum Volltext (externe URL):
https://doi.org/10.1287/msom.2022.1119

Kurzfassung/Abstract

We compare several approaches for generating a prioritized list of products to be counted in a retail store, with the objective of detecting inventory record inaccuracy and unknown out-of-stocks. Our study evaluates these approaches using data from inventory audits we conducted at European home and personal care retailer dm-drogerie markt. We consider both "rule-based" approaches, which sort products based on heuristic indices, and "model-based" approaches, which maintain probability distributions for the true inventory levels updated based on sales and replenishment observations. Our results support arguments for both rule-based and model-based approaches. We find that model-based approaches provide versatile visibility into inventory states and are useful for a broad range of objectives, but that rule-based approaches are also effective as long as they are matched to the retailer's goal. We find that "high-activity" rule-based policies that favor items with high sales volumes, inventory levels, and past errors are more effective at detecting inventory discrepancies. A "low-activity" rule-based policy based on low recorded inventory levels, on the other hand, is more effective at detecting unknown out-of-stocks. Our approach can be replicated at other retailers interested in customized optimization of their counting programs.

Weitere Angaben

Publikationsform:Artikel
Schlagwörter:inventory; retail
Sprache des Eintrags:Englisch
Institutionen der Universität:Wirtschaftswissenschaftliche Fakultät > Betriebswirtschaftslehre > ABWL, Supply Chain Management & Operations
DOI / URN / ID:10.1287/msom.2022.1119
Open Access: Freie Zugänglichkeit des Volltexts?:Ja
Peer-Review-Journal:Ja
Verlag:Institute for Operations Research and the Management Sciences
Die Zeitschrift ist nachgewiesen in:
Titel an der KU entstanden:Ja
KU.edoc-ID:27376
Eingestellt am: 18. Jun 2021 12:26
Letzte Änderung: 29. Aug 2023 15:01
URL zu dieser Anzeige: https://edoc.ku.de/id/eprint/27376/
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