A DEA-based decision analytics framework for product deletion in the luxury goods and fashion industry

Abstract

Traditionally, product deletion is a reactive decision driven by low sales volume and profit margin. However, the complexities involved in product management and consumer behavior volatilities make it necessary to account for a broad range of financial and non-financial factors. Besides, proactive product deletion may be required for a company to reduce the risk of draining resources, adjust to the market changes, and stay competitive. This study develops an analytics-based product deletion decision framework that considers multidimensional measurements, from finance to supply chain and competitive considerations. For this purpose, an innovative application of Data Envelopment Analysis (DEA) is explored within a novel framework. Input from a luxury goods company is used to evaluate the applicability of the tool. In the case study, the developed framework identified 41 out of 74 products for deletion consideration from which, two received a higher priority for possible deletion. The results provide insights into a deeper analysis of product deletion decisions showing that short-term financial perspectives should not stall managers. The study also provides recommendations for further research on modeling and implementation of product deletion decisions in practice. The developed method can be further validated and tested in other industries to contribute to this understudied topic.