Optimizing Supply Chain Management through Advanced Data Mining Applications

Abstract

In the era of globalization and digital transformation, Supply Chain Management (SCM) has become increasingly complex due to the exponential growth of data generated from various sources. Advanced data mining applications have emerged as pivotal tools for optimizing SCM by extracting actionable insights from vast datasets. This paper explores the integration of sophisticated data mining techniques into SCM processes to enhance decision-making, improve operational efficiency, and increase overall competitiveness. Through an extensive literature review and empirical analysis, the study highlights the significant benefits, challenges, and future directions of leveraging data mining in SCM. The findings indicate that data mining not only facilitates accurate demand forecasting and inventory optimization but also enhances supplier evaluation and logistics management, thereby contributing to a more resilient and agile supply chain.