Big Data Driven Supply Chain Optimization
Abstract
With the digital transformation of the global economy and the rapid development of information technology, big data has become a key driving force in supply chain optimization. The introduction of big data technology provides new perspectives and solutions for traditional supply chain management, especially in improving decision-making efficiency, reducing operating costs, and enhancing supply chain agility. This article reviews the application of big data in supply chain optimization based on existing research literature, and analyzes its practices in different fields, including demand forecasting, inventory management, transportation optimization, supplier management, and more. Meanwhile, this article summarizes the challenges that currently exist in the application of big data in supply chain optimization, such as data privacy, security issues, and the complexity of real-time data processing. In addition, this paper also puts forward the development direction of future big data research in the field of supply chain, focusing on the application prospects of cutting-edge technologies such as intelligent supply chain, edge computing and cross enterprise data sharing. This study provides valuable theoretical basis for further understanding the application and future trends of big data in supply chain optimization, and provides reference for academia and business practice.
