[Sponsored Article] Managing Perishable Inventories in Retailing: Replenishment, Clearance Sales, and Segregation LI, Qing | YU, Peiwen | WU, Xiaoli Operations Research, Vol. 64, No. 6, November–December 2016, pp. 1270–1284 Retail products such as food items and pharmaceuticals are perishable. For them, matching supply with uncertain demand is a challenge. Retailers sometimes run out of stock, which leads to revenue loss, and they sometimes have to throw away items that have passed their expiration dates. It was found that four main supermarkets in Hong Kong discard approximately 87 tons of food per day, most of which end up in landfills. Therefore, in addition to the obvious financial importance for retailers, better management of perishable goods is critical to the environment. In an attempt to avoid revenue loss and to better match supply and demand, many retailers use clearance sales to sell items that are reaching their expiration dates at a reduced price. While this is a good idea, there is no scientific guidance on its actual implementation. In particular, when should items be put on clearance sales and how many? How to coordinate clearance sales and replenishment? A recent study by Qing Li, Peiwen Yu, and Xiaoli Wu, investigated the joint replenishment and clearance sales of products with a finite lifetime. They showed that the optimal policy was very complex and required the full age information of the products, which is not available in the current barcodes. Therefore, the optimal policy is hard to implement. They came up with two novel heuristics. They categorized perishables into two classes: those with a remaining lifetime of two periods or more, and those of one period. They tested two methods that required only partial age information: the first with only information about the total inventory, and the second with information on the number of items with one period of lifetime remaining, as well as the total inventory. They found that the second method was significantly better than the first, and almost as good as the optimal strategy. In addition, whenever the inventory level of the products with a one-period remaining lifetime is low enough, they should all be cleared because when the new shipment arrives, customers will choose the new items first and it is very likely that the old items will go unsold. These findings have important implications for retail operations. Retailers should pay close attention to the class of inventory with a one-period remaining lifetime on their shelves. That information can make a significant difference, but the value of the information about other age classes is only incremental. The authors believe that “business analytics can make a big difference” in this field; and while they hope their work has opened additional pathways of inquiry, further studies in this field are required.