A Decision Analysis Framework for the Identification and Performance Preservation of Strategic Products in the Supply Chain

Abstract

This study develops a decision-making framework for the identification and performance preservation of strategic products using a non-parametric analysis of items within the product portfolio. Methods: Data Envelopment Analysis (DEA) and the sensitivity analysis of Inverted Data Envelopment Analysis (IDEA) are adapted to explore a new application area in growth product management. A field study from the retail sector of a developing economy is conducted to evaluate the method’s practicality. Results: This study suggests that the power of suppliers, product shelf life, and the ratio of sales to inventory are important supply chain considerations in identifying strategic products accommodated in Slow-Moving Consumer Goods (SMCG) supply chains. Conclusions: The field study shows that sensitivity analysis, in the new application area, provides insights for the identification and performance preservation of strategic items in a product portfolio. Data-driven solutions tailored to the operational needs of the case company and its different product categories conclude this article.