Leveraging Machine Learning to Enhance the Efficiency of Retail Supply Chains

Vidushi Sharma

doi:10.5281/zenodo.14715773

Leveraging Machine Learning to Enhance the Efficiency of Retail Supply Chains

Author(s)	Vidushi Sharma
Country	United States
Abstract	The retail industry is undergoing a digital transformation, with technological advancements playing a pivotal role in reshaping supply chain management. One such technology that holds substantial promise is machine learning (ML), which is being increasingly adopted to enhance the efficiency of retail supply chains. This paper investigates how machine learning can improve various supply chain functions, such as demand forecasting, inventory management, logistics optimization, and supplier relationship management. The research aims to answer the question: How can machine learning technologies optimize the operational performance of retail supply chains and address the inefficiencies inherent in traditional methods? The study utilizes a mixed-methods approach, incorporating case studies of retailers that have implemented ML solutions and analyzing quantitative data related to supply chain performance. The findings suggest that ML models, such as neural networks, decision trees, and reinforcement learning, significantly improve demand forecasting accuracy, reduce inventory holding costs, optimize delivery routes, and enhance supplier reliability. Specifically, retailers reported a 15-25% improvement in demand forecasting accuracy, a 10-12% reduction in inventory holding costs, and a 12-15% decrease in transportation costs. These improvements lead to better customer satisfaction, lower operational costs, and more resilient supply chains. The paper concludes by emphasizing the importance of integrating machine learning into retail supply chains to maintain a competitive edge in an increasingly dynamic market. It also highlights challenges, such as high implementation costs and data quality, that need to be addressed for widespread ML adoption, especially among small and medium-sized retailers.
Keywords	Machine Learning, Retail Supply Chain, Efficiency, Demand Forecasting, Inventory Optimization, Route Optimization, Anomaly Detection
Field	Engineering
Published In	Volume 11, Issue 2, July-December 2020
Published On	2020-07-08
Cite This	Leveraging Machine Learning to Enhance the Efficiency of Retail Supply Chains - Vidushi Sharma - IJAIDR Volume 11, Issue 2, July-December 2020. DOI 10.5281/zenodo.14715773
DOI	https://doi.org/10.5281/zenodo.14715773
Short DOI	https://doi.org/g82qst

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Leveraging Machine Learning to Enhance the Efficiency of Retail Supply Chains

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