Joint Product Design and Dynamic Assortment Optimization: Integrating Strategic and Tactical Revenue Management

Abstract

Revenue management decisions often have both strategic and tactical components. Strategic decisions happen first and set the broad and long-term operational context in which tactical decisions are frequently and repeatedly made, often on a weekly or daily basis. We consider a joint optimization of both strategic and tactical decisions. Specifically, we examine a setting in which the strategic decision is to choose product designs (e.g., price, capacity, return eligibility, and other characteristics) and the tactical decision involves the dynamic assortment optimization over a selling season. Our formulation has many applications, including optimizing products' return eligibility and determining product discounts. We formulate an optimization problem that combines the impact on the expected revenue of both strategic and tactical decisions. To determine the product design, we reformulate the choice-based deterministic linear program, solve its continuous relaxation, and round the resulting solution. By using value function approximations, we obtain a dynamic assortment policy whose expected revenue is at least a constant fraction of the choice-based deterministic linear program, for every product design decision. Combining these two results, we show that our approach provides an approximate solution to the joint optimization with performance guarantees. Numerical experiments based on real transaction data from a major U.S. retailer show that our method has 95%-97% effectiveness, which represents a 10%-13% advantage over methods that fail to fully integrate strategic and tactical decisions. The experiments also demonstrate the prominent role of product design, which explains 85.4% of the total variation of empirically observed effectiveness across different methods.

Keywords: strategic decision, tactical decision, product design, dynamic assortment optimization