Optimizing Retail Operations, Inventory Management and Sales Forecasting with Big Data and AI in China

Abstract

The retail industry in China is rapidly evolving due to rising consumer demand, increasing competition, and technological disruptions. To stay ahead, retailers need to optimize their operations, inventory management, and sales forecasting. This paper examines how big data and artificial intelligence (AI) can be leveraged to transform retail processes and boost performance. We provide an overview of China's retail landscape, key retail optimization challenges, and present big data/AI solutions for inventory control, demand forecasting, personalized promotions, pricing optimization, and supply chain efficiency. Our analysis suggests that data-driven AI systems can significantly improve inventory turns, forecast accuracy, product availability, markdown optimization, and operational efficiency. However, success requires integrating AI into core retail processes, strong data governance, continuous improvement cycles, and organizational change management. This paper provides retail executives with an AI transformation framework, best practices, and case studies of leading Chinese retailers using big data and AI to optimize operations. The insights can help retailers revamp processes, enhance productivity, reduce costs, and provide better customer service.