LZYY(SH:603368) 36氪·2025-12-20 10:27Core Viewpoint - The article highlights the transformation of the pharmaceutical supply chain through AI integration, emphasizing the shift from traditional experience-based methods to data-driven, intelligent decision-making systems [2][11][36]. Group 1: Company Overview - Liuyao Group, established in the 1950s, has evolved from a traditional pharmaceutical distributor to a comprehensive health service group, covering hospitals, retail pharmacies, and B2B clients [2]. - The complexity of Liuyao's supply chain is amplified by the need to manage over ten thousand SKUs, multiple warehouses, and stringent compliance and time constraints [2][4]. Group 2: Supply Chain Challenges - Liuyao faces a "triple constraint" in its supply chain, balancing time, compliance, and cost, where improving one aspect can exacerbate the others [4][5]. - The pharmaceutical industry is under pressure to enhance efficiency and reduce costs due to increasing regulatory demands and market competition [7][10]. Group 3: AI Integration and Transformation - Liuyao has partnered with Huawei Cloud to leverage AI for restructuring its supply chain decision-making processes, focusing on data governance, demand forecasting, and intelligent scheduling [2][11]. - The implementation of a data lake has unified fragmented data, enabling real-time visibility and optimization of supply chain operations [15][21]. Group 4: AI Tools and Their Impact - The Pangu predictive model has improved demand forecasting accuracy to over 89%, directly impacting inventory management and reducing stockout risks [16][21]. - The Tianchou AI solver optimizes complex decision-making scenarios, significantly reducing decision-making time and lowering costs by approximately 20% [21][20]. Group 5: Industry Trends and Future Directions - The article notes a global trend where over 50% of large multinational companies are expected to adopt AI and advanced analytics for supply chain management by 2027 [8]. - In China, over 60% of large enterprises are projected to implement AI and intelligent scheduling systems in their supply chains within the next three years, driven by national policies promoting digital transformation [10][11]. Group 6: Conclusion on Supply Chain Evolution - The shift from experience-based systems to computational systems in supply chains is seen as a critical evolution, enabling companies to predict demand, optimize resources, and enhance operational efficiency [26][36]. - Liuyao's experience serves as a model for the industry, demonstrating that intelligent supply chains can become a new growth engine rather than merely a cost center [36].