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The Role of Big Data Analytics in Optimizing Retail Inventory Management

Author(s)

Zhankun Yang

Affiliation(s)

Tianjin University of Commerce, Tianjin, China

Abstract

Against the backdrop of the rapid development of the retail industry, this paper reviews the key role of big data analytics in optimizing inventory management. By analyzing the research background and significance, the paper reveals the challenges faced by traditional inventory management, such as demand uncertainty and supply chain complexity, as well as the potential of big data as a data-driven solution. The paper first reviews the retail inventory management theory, including basic concepts, traditional optimization methods and their limitations. Subsequently, the basic characteristics, analysis methods and commercial applications of big data analysis technology are outlined, emphasizing that it improves the efficiency of demand forecasting, supply chain coordination and inventory control through predictive analysis and real-time processing. Finally, the specific role of big data analysis in retail inventory optimization, such as reducing costs, improving responsiveness and sustainability, is discussed. This paper provides a theoretical framework and practical inspiration for retail practitioners and scholars to promote the industry's transformation to intelligence.

Keywords

Big Data Analysis; Retail Inventory Management; Demand Forecasting; Supply Chain Optimization; Inventory Control

References

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