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The application of big data technology in each link of the supply chain can reduce the cost of each link, optimize the allocation of resources, and increase the benefits of enterprises. This paper builds a supply chain cost control program based on big data at three levels: pre-prediction, mid-control and post analysis. It analyzes the feasibility of inventory management program based on CPFR, combines inventory optimization elements based on supply chain coordination, and proposes sales inventory optimization program for supply chain coordination to optimize inventory resources. Combine the time series model and multiple regression model, unite the CPFR concept, synthesize the CPFR sales combination forecasting model, and design and form the resource optimization scheme for real-time adjustment of supply chain inventory based on sales forecast. Analyze and validate the forecasting effect of the combination forecasting model, forecast product sales on a weekly basis, and calculate product safety inventory and remaining inventory. Analyze the effect of enterprise supply chain cost control based on big data sales forecast. The proportion of procurement cost in the enterprise’s supply chain cost to revenue shows a decreasing trend, falling to 0.5107 in 2023, and the gross profit margin shows an increasing trend, growing to 0.5366 in 2023, which controls its cost and improves its gross profit. It shows that the enterprise uses big data technology to optimize the supply chain resources in the process of supply chain cost control, and the cost control effect is better.