A decision support system for retail assortment planning

Abstract

PurposeBecause increasing product variety in retail conflicts with limited shelf space, managing assortment and shelf quantities is a core decision in this sector. A retailer needs to define the assortment size and then assign shelf space to meet consumer demand. However, the current literature lacks not only information on the comprehensive structure of the decision problem, but also a decision support system that can be directly applied to practice in a straightforward manner. The paper aims to discuss these issues.Design/methodology/approachThe findings were developed and evaluated by means of explorative interviews with grocery retail experts. An optimization model is proposed to solve the problem of assortment planning with limited shelf space for data sets of a size relevant in real retail practice.FindingsThe author identifies the underlying planning problems based on a qualitative survey of retailers and relates the problems to each other. This paper develops a pragmatic approach to the capacitated assortment problem with stochastic demand and substitution effects. The numerical examples reveal that substitution demand has a significant impact on total profit and solution structure.Practical implicationsThe author shows that the model and solution approach are scalable to problem sizes relevant in practice. Furthermore, the planning architecture structures the related planning questions and forms a foundation for further research on decision support systems.Originality/valueThe planning framework structures the associated decision problems in assortment planning. An efficient solution approach for assortment planning is proposed.