Harnessing Advanced Data Mining to Optimize Supply Chain Management

Abstract

In today’s globalized, digitally driven economy, the torrent of data flowing through supply chains presents both a challenge and an opportunity. This paper examines how cutting-edge data mining techniques can be woven into Supply Chain Management (SCM) to turn raw information into strategic advantage. By synthesizing insights from a broad literature review and supporting them with empirical analysis, we demonstrate that advanced mining methods enable more accurate demand forecasting, dynamic inventory control, and rigorous supplier performance evaluation. We also explore their impact on logistics planning and overall operational agility. Finally, we discuss the principal obstacles—such as data quality, integration complexity, and scalability—and outline promising avenues for future research. Our findings confirm that when properly applied, data mining transforms SCM into a more resilient, responsive, and competitive function.