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With the acceleration of globalization and the increasingly fierce competition in the market, demand forecasting and inventory management in supply chain management have become particularly important. Traditional supply chain management methods are difficult to cope with the complex and changing market demand, resulting in the frequent occurrence of inaccurate forecasts, excessive or insufficient inventory, and other problems. This paper aims to explore the application of intelligent technology in supply chain demand forecasting and inventory management, focusing on analyzing how technologies such as big data, artificial intelligence, and machine learning can improve forecasting accuracy and inventory management efficiency. Through the analysis of actual cases, this paper demonstrates the implementation effect of intelligent demand forecasting technology and proposes corresponding inventory management optimization strategies. The study shows that intelligent supply chain management can not only effectively reduce operating costs, but also improve service levels, thus enhancing the competitiveness of enterprises in a dynamic market environment
Shijie Luo (Sat,) studied this question.
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