The Value of RFID Technology Enabled Information to Manage Perishables

We address the value of RFID technology enabled information to manage perishables in the context of a supplier that sells a random lifetime product subject to stochastic demand and lost sales. The product's lifetime is largely determined by the time and temperature history in the supply chain. We compare two information cases to a Base case in which the product's time and temperature history is unknown and therefore its shelf life is uncertain. In the first information case, the time and temperature history is known and therefore the remaining shelf life is also known at the time of receipt. The second information case builds on the first case such that the supplier now has visibility up the supply chain to know the remaining shelf life of inventory available for replenishment. We formulate these three different cases as Markov decision processes, introduce well performing heuristics of more practical relevance, and evaluate the value of information through an extensive simulation using representative, real world supply chain parameters

Grocery omnichannel perishable inventories: performance measures and influencing factors

Purpose- Perishable inventory management for the grocery sector has become more challenging with extended omnichannel activities and emerging consumer expectations. This paper aims to identify and formalize key performance measures of omnichannel perishable inventory management (OCPI) and explore the influence of operational and market-related factors on these measures. Design/methodology/approach- The inductive approach of this research synthesizes three performance measures (product waste, lost sales and freshness) and four influencing factors (channel effect, demand variability, product perishability and shelf life visibility) for OCPI, through industry investigation, expert interviews and a systematic literature review. Treating OCPI as a complex adaptive system and considering its transaction costs, this paper formalizes the OCPI performance measures and their influencing factors in two statements and four propositions, which are then tested through numerical analysis with simulation. Findings- Product waste, lost sales and freshness are identified as distinctive OCPI performance measures, which are influenced by product perishability, shelf life visibility, demand variability and channel effects. The OCPI sensitivity to those influencing factors is diverse, whereas those factors are found to moderate each other's effects. Practical implications- To manage perishables more effectively, with less waste and lost sales for the business and fresher products for the consumer, omnichannel firms need to consider store and online channel requirements and strive to reduce demand variability, extend product shelf life and facilitate item-level shelf life visibility. While flexible logistics capacity and dynamic pricing can mitigate demand variability, the product shelf life extension needs modifications in product design, production, or storage conditions. OCPI executives can also increase the product shelf life visibility through advanced stock monitoring/tracking technologies (e.g. smart tags or more comprehensive barcodes), particularly for the online channel which demands fresher products. Originality/value- This paper provides a novel theoretical view on perishables in omnichannel systems. It specifies the OCPI performance, beyond typical inventory policies for cost minimization, while discussing its sensitivity to operations and market factors

Perishable Items in Multi-Level Inventory Systems

This master thesis studies a two-echelon distribution system for perishable items with two non identical retailers. Each location is managed following a standard continuous (R, Q) ordering policy. The demand occurs solely at the retailers and follows independent Poisson processes. Customers are backordered when the retailer is out of stock. The items are considered as fixed lifetime perishables. Whenever an item perished, it is discarded from the stock. The model includes fix transportation time and the allocation policy at the central warehouse is a First-Come-First-Serve one. This kind of system is very complicated and therefore hard to study. In this master thesis, we focus on a simulation study of 48 different problems with both a FIFO and a LIFO issuing policy at the retailers. The goal of this study is therefore to optimize the values of R in (R, Q) ordering policies considering that the items are perishables. To do so, we try to optimize the values of the reorder points at every location. We also try to find some general behaviour of the system and we compare the FIFO and the LIFO best found solution. More than 1000 hours of computer-time were used for this study. For every problem, we conducted an optimization process to find better values of the reorder points at every location. For the FIFO case, an average cost reduction of more than 20% was found. It exists a good opportunity in term of cost savings while taking into account the perishable characteristic of the items. Another finding of our study is that the LIFO case has good performance comparing to what expected. On average, the costs increase is only 7% while considering a LIFO issuing policy instead of a FIFO one. Moreover, the values of the reorder points for the FIFO best found solution are still the same than the LIFO best found solution in 70% of the problems studied

The Value of Demand Information in Omni-Channel Grocery Retailing

As e-commerce reaches one of the last strongholds of traditional fulfillment, how can grocers leverage the omni-channel trend and stay competitive in today’s changing market landscape? To improve operating outcomes and address food waste concerns, this study investigates various scenarios in which the grocery retailer accepts online orders in advance. We examine the value of advance demand information through a Markov Decision Process-based model, in terms of changes to expected profits, outdating, freshness, and several inventory and service performance metrics. Our results indicate that when the demand lead time is longer than the replenishment lead time, close to 20% safety stock reduction on average can be achieved, leading to a 15% decrease in product deterioration and 26% less outdating. In some cases, we also find that it is possible to profitably offer discounted prices in exchange for the customer’s future demand information

On order policies with pre-specified order schedules for a perishable product in retail.

This paper studies a retail inventory system for a perishable product, based on a practical setting in Dutch retail. The product has a fixed shelf life of three days upon delivery at the store and product demand has a weekly pattern, which is stationary over the weeks, but varies over the days of the week. Items of varying age occur in stock. However, in retail practice, the age-distribution is often unknown, which complicates order decisions. Depending on the type of product or the size of the supermarket, replenishment cycle lengths may vary. We study a situation where a store is replenished either three or four times a week on pre-specified days. The research aim is to find practical and efficient order policies that can deal with the lack of information about the age distribution of items in stock, considering mixed LIFO and FIFO withdrawal. Reducing potential waste goes along with cost minimization, while the retailer aims at meeting a cycle service level requirement. We present four new heuristics that do not require knowledge of the inventory age-distribution. A heuristic, based on a constant order quantity for each order moment, often generates least waste and lowest costs. However, this requires a few minutes of computation time. A new base stock policy appears second best