Retail benefits of dynamic expiry dates—Simulating opportunity losses due to product loss, discount policy and out of stock

Abstract

When setting an expiry date on fresh food products producing companies have to buffer against two major uncertainties. The initial number of microbes is unknown in practice, and will be variable. Moreover the storage and transport temperatures until consumption will be uncertain and variable too, which will make microbial growth uncertain and variable. In order to cope with these two uncertainties, expiry dates are set at a rather cautious level, resulting into high numbers of product losses or out of stock (lost sales) at retail. In this paper we propose a so-called dynamic expiry date (DED) as an alternative for the fixed expiry date (FED) as applied nowadays. On the basis of a quality decay model that describes the growth of the number of microbes as a function of time and temperature, the expiry date can be dynamically adjusted depending on the measured temperature profile along the distribution chain and the initial number of microbes on the product. We present computer simulation experiments that quantify the effect of a dynamic expiry date on product losses and out of stock at retail outlets. For this purpose, a logistics simulation model of a Dutch pork supply chain was developed. Simulation results show that the DED concept is a promising concept. We predict that a dynamic expiry date decreases opportunity losses by almost 80%. Moreover, advantages are higher when having lower shelf temperatures. Therefore, implementing DED may be an incentive for retailers to optimize their climate control.