34 Pages Posted: 28 Oct 2014 Last revised: 17 Jul 2017
Date Written: July 14, 2017
We study how inventory managers can fully utilize point-of-sales (POS) data for the design of inventory auditing and replenishment strategies that account for the existence of phantom inventories. Events such as spoilage, expiration, employee theft, and customer shoplifting reduce available inventories in retail stores without these reductions being reflected in inventory records. As a result, inventory records often include phantom inventories, i.e., units of good present on inventory records but not actually available for sale. These phantom inventories cause replenishment delays and stockouts which ultimately hurt service levels. The optimal policy in the presence of phantom inventories is complex. We analyze the structure of the problem using tools from discrete mathematics and dynamic programming to derive a simple policy which performs close to the optimal policy and rarely acts sub-optimally. We propose a simple policy based on a threshold on the estimated fraction of demand to be met on a given day conditional on the POS data up to that day, a statistic that we refer to as the daily expected service level. Our policy is easy to compute and interpret, and can thus offer an attractive solution for inventory managers.
Keywords: shelf availability, inventory-record inaccuracy, POMDP, optimal replenishment, retail analytics
JEL Classification: C11, D81
Suggested Citation: Suggested Citation
Bassamboo, Achal and Moreno, Antonio and Stamatopoulos, Ioannis, Inventory Auditing and Replenishment Using Point-of-sales Data (July 14, 2017). Available at SSRN: https://ssrn.com/abstract=2515147 or http://dx.doi.org/10.2139/ssrn.2515147