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This review paper explores the transformative role of advanced analytics in optimizing logistics and supply chain management, offering insights into industry applications, best practices, and future trends. As global supply chains become increasingly complex, integrating advanced analytics—encompassing data mining, predictive analytics, machine learning, and big data—has emerged as a critical driver of efficiency, cost reduction, and enhanced decision-making. The paper discusses how various industries, including manufacturing, retail, healthcare, and transportation, leverage advanced analytics to address specific challenges and improve overall supply chain performance. Additionally, it highlights the best practices for successful implementation, such as aligning analytics initiatives with business objectives, investing in the right technology infrastructure, and fostering a culture of data-driven decision-making. The paper also addresses the challenges and barriers to implementation, including technological, organizational, and regulatory hurdles. Finally, it examines emerging technologies like AI, IoT, and blockchain, poised to revolutionize supply chain management further. It identifies key opportunities for growth in areas such as sustainability, risk management, and customization. The paper concludes by emphasizing the importance of advanced analytics in shaping the future of logistics and supply chain strategies, offering recommendations for industry stakeholders to harness these technologies effectively.
Adeniran et al. (Sun,) studied this question.