T/BIAIM 0028-2024 Industrial identification data element analysis model requirement
T/BIAIM 0028-2024 Industrial identification data element analysis model requirement
Basic Information
Scope
Main technical content: In addition to the standard normative elements (scope, normative reference documents, terms and definitions, etc.), the main content of the standard includes production data element analysis models, storage data element analysis models, logistics data element analysis models, sales data element analysis models, after-sales data element analysis models, and data element asset entry value chain models. Among them: (1) The production data element analysis model specifically includes technical requirements for data analysis of time elements, production yield elements, material elements, and quality elements involved in production sites, operation sites, and related fields. (2) The storage data element analysis model includes technical requirements for data analysis of inventory entry elements, inventory exit elements, and in-warehouse data elements, as well as storage data management strategies. (3) The logistics data element analysis model includes technical requirements for data analysis of basic data elements and business data elements. (4) The sales data element analysis model includes technical requirements for data analysis of basic data elements, regional data elements, product data elements, and channel data elements. (5) The after-sales data element analysis model includes technical requirements for data analysis of operational management data elements, personnel management data elements, inventory management data elements, work order statistics data elements, revenue statistics data elements, and customer report data elements. (6) The data element asset entry value chain model includes technical requirements for resource utilization, resource productization, and product assetization. (7) The data element asset value evaluation method includes data asset value evaluation methods based on data resource classification and grading, data product life cycle, and data asset behavior.