Optimizing logistics and supply chain management through advanced analytics: Insights from industries
1 International Association of Computer Analysts and Researchers, Abuja, Nigeria.
2 OneAdvanced, UK.
3 Nigeria Inter-Bank Settlement System Plc (NIBSS), Nigeria.
4 Independent Researcher, UK.
Review
International Journal of Scholarly Research in Engineering and Technology, 2024, 04(01), 052–061.
Article DOI: 10.56781/ijsret.2024.4.1.0020
Publication history:
Received on 12 July 2024; revised on 17 August 2024; accepted on 20 August 2024
Abstract:
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.
Keywords:
Advanced Analytics; Supply Chain Management; Logistics Optimization; Predictive Analytics; Emerging Technologies
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Copyright information:
Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0