Abstract: With the continuous expansion of the power grid construction investment scale, the correlation between the electrical equipment market scale and the power grid material procurement demand continues to strengthen. In the era of big data, the data-driven prediction method is utilized to integrate the power grid procurement plan prediction and the electrical equipment market scale prediction, so as to promote the interconnection and efficient application of information between the supply and demand.It can effectively promote the development of the electrical equipment market from the demand market to the dynamic balance of supply and demand market, accelerate the extension of the industry supply chain to suppliers, reduce the production cycle and production cost of suppliers, and improve the lean production level of suppliers.In the meantime, it helps to promote the lean and intelligent level of material management for the power grid enterprises, eliminate the deviation between the procurement plan and the actual demand by accurately predicting the material demand scale, and reduce the risks of project progress delay or inventory backlog caused by the deviation of material procurement scale. Through the analysis and selection of available models, an ecological enabling interactive platform based on big data in the supply chain will be built. On the premise of data resource security and compliance utilization, the global data resources of material procurement will be integrated and a data-asset management system will be built, aiming to improve the procurement management level internally and enable the transformation and upgrading of upstream and downstream enterprises in the supply chain externally, so as to improve the modernization level of the supply chain of the electrical equipment industry chain and serve the construction of the national unified market for electrical equipment.