en.Wedoany.com Reported - On July 1, the new version of the national standard "Data Management Capability Maturity Assessment Model" was officially implemented. This standard is an important foundational national standard in the field of data management, providing a unified reference for enterprises to establish, evaluate, and enhance their data management capabilities, helping organizations transform data resources into manageable, governable, and applicable production factors.
The focus of the new national standard is no longer solely on regulating how enterprises "manage data," but rather on guiding enterprises to genuinely integrate data capabilities into the entire business process, including R&D and design, production and manufacturing, operational management, and supply chain collaboration. For industries such as manufacturing, telecommunications, energy, and finance, data management capabilities now directly impact product R&D efficiency, production scheduling, quality traceability, equipment maintenance, inventory management, customer service, and business decision-making. After the standard's implementation, enterprises can build capabilities around data strategy, data governance, data architecture, data quality, data security, data application, and lifecycle management, using maturity assessments to identify weaknesses.
This means the new national standard will become an important evaluation benchmark for enterprise digital transformation.
Compared to the first version, the new "Data Management Capability Maturity Assessment Model" places greater emphasis on activating data value. The standard guides enterprises to embed data governance into business operations, rather than confining it to institutional documents or information systems. For example, in the production and manufacturing process, if equipment operation data, process parameters, quality inspection results, and supply chain data cannot be managed uniformly, it becomes difficult to support quality analysis, anomaly warnings, and production optimization. In operational management, if sales, finance, inventory, procurement, and customer data have inconsistent definitions, it can affect cost accounting and business decision-making. The new national standard incorporates these capabilities into the maturity assessment framework, helping enterprises leverage data to reduce costs, increase efficiency, and upgrade quality.
The new standard also adds requirements tailored to artificial intelligence. In response to trends such as quality control of training data for large models and multimodal data governance, the standard introduces specific capability clauses to strengthen full lifecycle data management.
This content is particularly critical for the implementation of "AI+." Applications such as large model training, enterprise knowledge bases, intelligent agent systems, industrial visual inspection, predictive equipment maintenance, and intelligent customer service all rely on a data foundation that is high-quality, traceable, authorized, and reusable. If an enterprise's data sources are unclear, labels are inaccurate, permissions are chaotic, and quality is uncontrollable, AI systems will struggle to enter the production environment. By incorporating AI training data quality and multimodal data governance into the capability-building direction, the new national standard extends data management standards from traditional information technology scenarios to AI application scenarios, providing a basis for enterprises to build a usable, trustworthy, and sustainable data foundation.
Fan Kefeng, Deputy Director of the China Electronics Standardization Institute, stated that all indicator modifications and establishments revolve around a single main line: transitioning from "standardizing data management" to "activating data value," enabling data capabilities to truly serve cost reduction, efficiency improvement, quality enhancement, and the high-quality development of the real economy.
Since the release of the first version of the national standard "Data Management Capability Maturity Assessment Model," over 10,000 enterprises and institutions across 33 provincial-level administrative regions in China have conducted capability building and assessments based on the standard, covering more than 20 key industries including manufacturing, telecommunications, energy, and finance. With the official implementation of the new national standard, data management capability assessments will become more aligned with actual business processes, further supporting data element circulation, digital transformation, and AI application deployment.
