可复制的主数据管理路径：一家老牌酒企的数字化实践

Core Insights - The article discusses the challenges faced by a traditional liquor company (referred to as Company Y) due to fragmented data across multiple business lines, which hindered its digital transformation efforts. The company initiated a master data management project to streamline data processes and enhance decision-making efficiency [1][20]. Group 1: Company Challenges - Company Y experienced issues stemming from its diversified operations, leading to complex systems and inefficient decision-making processes. For instance, marketing struggled with customer segmentation due to duplicate customer codes, while procurement faced increased costs from inconsistent supplier data [2][8]. - The company had over ten information systems, including EAS, WMS, and sales systems, which resulted in data chaos, such as duplicate customer codes and inconsistent material specifications [8][20]. Group 2: Master Data Management Strategy - To address these challenges, Company Y collaborated with Yixin Huachen to implement a five-step strategy: "single source of truth, data validation, unified coding, data sharing, and historical cleansing" [2][20]. - The first step involved identifying data ownership, assigning specific departments to manage different types of master data, such as customer data by the sales department and supplier data by the procurement department [4][5]. Group 3: Implementation Steps - The project established strict data validation rules to ensure data quality, including mandatory fields and standardized formats for supplier codes and material specifications [9][10]. - A unified coding system was developed to eliminate multiple codes for the same item, ensuring each object had a unique identifier [11][13]. - The project facilitated data sharing by integrating the master data management system with various business systems, allowing real-time data synchronization [14][17]. Group 4: Historical Data Cleansing - A comprehensive historical data cleansing process was conducted to remove duplicates and non-compliant data, resulting in a significant reduction in the number of customer, material, and personnel records [15][18]. - The cleansing process allowed for accurate statistics on dealer customers and improved data quality across the organization [15][20]. Group 5: Results and Insights - Following the implementation of the master data management project, Company Y achieved significant improvements, such as reducing customer code duplication from 15% to 0% and increasing material specification accuracy from 70% to 95% [19][20]. - The project highlighted that master data management is not merely a technical solution but requires cross-departmental consensus and ongoing data quality management [20][22].