2024中央企业数据资产化及数据资产入表场景建设白皮书

Industry Investment Rating - The report does not explicitly provide an industry investment rating [1] Core Views - Data is considered the "oil of the 21st century" and a core element of economic development in the digital economy era [6] - Data, as a production factor, can significantly enhance production efficiency when combined with other factors, creating a "multiplier effect" [7] - The integration of data into financial statements is a significant theoretical innovation in China's economic field, marking a shift from being "on the verge" to "inevitable" [9] - Central enterprises' data assets have immense potential and value in the digital economy era due to their extensive coverage, cross-industry integration, and high data quality [22][23] Policy Background and Significance - The 19th CPC Central Committee's Fourth Plenary Session in 2019 first included data as a production factor, reflecting its increasing importance in economic activities [7] - The "Data Twenty Articles" emphasize the need to promote data compliance, efficient circulation, and empowerment of the real economy, marking a significant step in data assetization [7] - The establishment of the National Data Bureau in 2023 further underscores the strategic importance of data in reshaping global economic structures [7] Central Enterprises' Data Assetization Challenges - Data Value Mining: Central enterprises face challenges in effectively mining and utilizing the rich commercial value embedded in their data assets [25] - Data Governance: The vast scale and diversity of data assets make governance complex, requiring robust systems for data standards, quality, and security [26] - Data Security Risks: High data security risks due to sensitive information such as trade secrets and personal data necessitate stringent security measures [27] - Accounting Complexity: The lack of clear paths for data asset formation and cost allocation poses significant challenges for accounting treatment [28] Central Enterprises' Data Assetization Path - Data Scenarioization: Identifying key business scenarios and data needs to lay the foundation for data resourceization and value realization [33] - Data Resourceization: Transforming raw data into reusable data resources through processes like cleaning, integration, and storage [35] - Data Value Realization: Discovering and leveraging the potential value of data through analysis, product development, and trading [36] Central Enterprises' Data Assetization Solutions - A dual-layer "Pagoda" value model is proposed, focusing on scenario-based data assetization and integration into financial statements [37] - The solution emphasizes the importance of data governance, cost allocation mechanisms, and the establishment of independent data management departments [38] Data Assetization Services - Services cover multiple key areas of data assetization, including value planning, resource management, and intelligent accounting [64] - Different service levels (basic, standard, advanced) are available to meet varying enterprise needs [65]