A replenishment policy for a perishable inventory system based on estimated aging and retrieval behavior

So far the literature on inventory control for perishable products has mainly focused on (near-) optimal replenishment policies for a stylized environment, assuming no leadtime, no lot-sizing, stationary demand, a first in first out retrieval policy and/or product life time equal to two periods. This literature has given fundamental insight in the behavior and the complexity of inventory systems for perishable products. In practice, many grocery retailers have recently automated the inventory replenishment for non-perishable products. They recognize they may need a different replenishment logic for perishable products, which takes into account e.g. the age of the inventory in the system. Due to new information technologies like RFID, it now also becomes more economically feasible to register this type of information. This paper suggests a replenishment policy for perishable products which takes into account the age of inventories and which requires only very simple calculations. It will be shown that in an environment, which contains important features of the real-life retail environment, this new policy leads to substantial cost reductions compared with a base policy that does not take into account the age of inventories

Inventory replenishment in retail : the efficient full service strategy

In this paper we compare two inventory replenishment strategies for retailers and evaluate their effect on service levels, average inventory and the number of order lines. The first inventory replenishment strategy we consider is the Full Service strategy which is currently applied by many retailers and orders at a review period if either a case pack fits onto the shelves or the minimum reorder level is reached. This strategy is compared to an Efficient Full Service strategy where an order is placed only if at areview period the inventory position drops below the minimum reorder level; then as many case packs are ordered as possible taking into account the limited shelf space. This modified strategy will be compared with the current strategy. We will derive approximations for the key performance indicators and use simulation based on empirical data for thousands of SKU’s at multiple stores from a European retailer to quantify the improvement potential of the new strategy and to evaluate our approximations. The results show that, on average, inventory can be reduced with 22% and the number of handled order lines can be reduced with 17% when applying the Efficient Full Service strategy, while guaranteeing the same target customer service level. The approximations for the average inventory and the number of order lines perform very well at the store level and perform well at the SKU level. We also show that these approximations can be used as good indicators for the improvement potential of the new replenishment strategy

Static versus dynamic safety stocks in a retail environment with weekly sales patterns

Sales in European retail environments typically follow a weekly pattern having high sales at the end of the week and low sales at the start of the week. In this paper we compare two different ways of setting safety stock norms in a retail environment with weekly sales patterns. The first option is to set a single safety stock norm, which is constant throughout the week. The second option is a safety stock norm which is dynamic since it depends on the weekday. The inventory is controlled periodically and a lost sales environment is assumed. We study the impact of the dynamic safety stock on the inventory holding and shortage costs as well as on drivers of handling costs like the number of orderlines and the workload balance, since earlier research has shown that handling costs are relatively large for retailers. We use a full factorial experiment and simulation to evaluate both inventory replenishment strategies