Abstract:    On the one hand, big data makes it possible to integrate more complementary resources in a wider range, and the supply capacity of manufacturing services is increasingly concentrated; on the other hand, big data also provides more forms of realization and access to meet service needs, and the demand for manufacturing services is increasingly heterogeneous; how to respond to the triple impact of data enabling on the supply side, demand side and matching of manufacturing servicization determines the success or failure of manufacturing services. 
    From the supply side, the existing research emphasizes the improvement of data enabling and the realization of some improvements, such as real-time response speed, adaptive flexibility and the possibility of large-scale personalized manufacturing. However, how data enabling affects the implementation environment and implementation process of these improved capacity states of enterprises is still unclear, and it is not clear how data enabling can maximize its benefits under the business model on the demand side of manufacturing enterprises. 
   From the perspective of "supply-demand" matching, the driving path of data enabling on the servicization of manufacturing enterprises in Midea is analyzed by the framework of business model innovation (BMI) with the help of the grounded theory (GT). The driving process and the management practice and the influences of data enabling on the business model innovation and servicization of the manufacturing enterprises are deeply analyzed and clarified, which results in the corresponding proposition. The research shows that: (1) the linkages between the data enabling and the servicization of manufacturing enterprises are constitute by the concurrent of the strategic orientation, the data feature utilization and multi-agent real-time interaction, which is followed by resource utilization as the common medium and ended in the three dimensions of value creation, value delivery and value capture. (2) the dynamic driving process of data enabling on the servicization of manufacturing enterprises is characterized in "Data Enabling - Industrial Digitization Capability, Product Data Utilization Capability, Customer Value Interaction Capability Enhancement - Combination of Industrial Servicization, Customer Servicization and Value Servicization". The construction of enterprise-customer-upstream and downstream multi-agent participation in the interactive environment is conducive to the service transformation of manufacturing enterprises and the matching of demand and supply in the context of interactive development and transmission. 
    The introduction of the demand side in the business model innovation expands the roles of data enabling in the servicization of manufacturing enterprises and provides theoretical guidance with "supply-demand" matching as the core for manufacturing enterprises servicization. It expands the connotation of data enabling, demonstrates the industrial digitization ability, product data utilization ability and customer value interaction ability of data enabling. The research is helpful to form a process explanation of service to manufacturing enterprises, enrich the theoretical connotation of service and business model innovation, and answer the specific ability required by manufacturing enterprises. The object of data enabling is expanded from supply side to demand side, and its influence on the matching of the two is taken as the direct reason of service transformation. The situation, path and mechanism of service theory of manufacturing enterprises are improved, and the important role of enterprise-customer-upstream and downstream multi-agent environment construction in manufacturing service is emphasized.

Key words: data enabling, business model, servicization, dynamic capability, grounded theory