Big Data Analytics in Supply Chain Information Systems: Improving Operational Efficiency and Predictive Accuracy

Abstract

Big Data Analytics (BDA) has become a transformative force in supply chain management, enabling organizations to derive actionable insights from diverse and voluminous data. By integrating advanced analytical techniques, companies can enhance operational efficiency, bolster predictive accuracy, and improve overall decision-making. This paper provides a comprehensive review of BDA applications within supply chain information systems, covering fundamental concepts, tools, and techniques while examining key challenges such as data quality, security, and organizational change management. Through an exploration of real-world case studies and best practices, the paper emphasizes the crucial role BDA plays in driving innovation and resilience across global supply networks. It concludes with recommendations on effective implementation strategies, alongside insights into future directions—particularly the rise of autonomous decision-making and digital twin technologies. The findings underscore BDA’s potential to reshape supply chain processes, offering a competitive advantage to organizations willing to adopt and invest in data-driven capabilities.