Advanced Analytics in Supply Chain Visibility: A Comparative Review of Techniques for Retail and Consumer Goods
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Advanced Analytics in Supply Chain Visibility: A Comparative Review of Techniques for Retail and Consumer Goods
Authors:
Manykandaprebou Vaitinadin (Independent Researcher) Pondicherry, India, Email:mkprebou1@gmail.com
Abstract: Supply chain visibility (SCV) has become a critical factor in the efficiency and resilience of the retail and consumer goods industries. With increasing complexity in global supply chains, organizations are leveraging advanced analytics techniques, such as machine learning (ML), big data analytics, and artificial intelligence (AI), to improve visibility and enhance decision-making. This paper provides a comparative review of various advanced analytics techniques and their effectiveness in improving SCV within the retail and consumer goods sectors. It discusses key methodologies, challenges, and limitations, while providing insights into future trends. The study also highlights how data-driven analytics solutions enhance operational efficiencies, reduce risks, and improve overall supply chain performance.
Keywords: Supply Chain Visibility, Advanced Analytics, Machine Learning, Big Data, Retail, Consumer Goods, Artificial Intelligence, Predictive Analytics, IoT, Blockchain.