DECISION SUPPORT TOOL FOR RETAIL SHELF SPACE OPTIMIZATION

Abstract

Efficient allocation of shelf space and product assortment can significantly improve a retailer's profitability. This paper addresses the problem from the perspective of an independent franchise retailer. A Category Management Decision Support Tool (CMDST) is proposed that efficiently generates optimal shelf space allocations and product assortments by using the existing scarce resources, resulting in increased profitability. CMDST utilizes two practical integrated category management models that maximize the total net profit in terms of decision variables expressing product assortment, shelf space allocation, review period, and order quantity. The implementation of the models demonstrates their robustness and that the net profit can be significantly increased when compared to the current industry practice.