Abstract

Effective supplier management is essential in the apparel industry for optimizing supply chain efficiency and ensuring profitability. This study applies Data Envelopment Analysis (DEA), using MATLAB software, to evaluate yarn suppliers' performance by considering a range of input variables—such as raw material costs, transportation expenses, engineering support, serviceability, and lead time—as well as output variables, including scrap rate, profit, and warranty offerings. By categorizing suppliers into efficient and inefficient frontiers, the DEA model identifies benchmarks and highlights best practices from top-performing suppliers on the efficient frontier. These efficient suppliers demonstrate optimal resource utilization, superior engineering support, and high standards of cost-effectiveness and product reliability, providing added value in service and warranty commitments. In contrast, inefficient Decision-Making Units (DMUs) gain insights into areas for improvement, such as cost control, product quality, service enhancement, and warranty responsiveness. This DEA approach enables a detailed efficiency analysis, equipping apparel companies with actionable insights for selecting and managing yarn suppliers to build a resilient and competitive supply chain. The study underscores DEA’s utility as a strategic decision-making tool, empowering companies to drive supply chain effectiveness, achieve cost savings, and remain adaptable to evolving market demands.

Keywords: Supplier Management, Data Envelopment Analysis (DEA), Supply Chain Efficiency, Apparel supply chain, Performance Evaluation.