Designing efficient assortments: A branch-and-bound method to optimise volume and satisfaction

Abstract

Category assortments are a key driver of retailer success. When a customer’s preferred product is unavailable, retailers must provide viable alternatives or risk losing the customer. This paper presents an analytical method that uses a survey-based approach where consumers make hypothetical (albeit not conjoint) choices. The objective is to identify how delisting a stock-keeping unit (SKU) will affect overall sales; the extent to which customers will abandon the store; and overall satisfaction with the store. Such knowledge will help retailers make the best delisting decisions and help both retailer and brands with their category management negotiations. It can also identify possible gaps for the brand, such as which alternatives in the competition’s portfolio have low substitutability and hence should perhaps be added to the brand’s product portfolio. This approach also allows brands to test new concepts and evaluate how adding a new (concept) SKU will affect sales of other SKUs and overall sales and profitability. The data are then modelled using a branch-and-bound algorithm. This approach can easily be implemented at the store level and allows for the optimisation of multiple objectives.