The development history of China's big data is relatively short, and it has only been ten years so far.
Although the application level of big data in real life is not high, some achievements have been made in the supply chain. Various kinds of data will be generated in the actual operation of the supply chain. If these data can be effectively classified and used, the "bullwhip effect" of the operation of the supply chain can be also effectively improved. Thus this paper proposes the development of a supply chain collaborative inventory management model and application framework using big data. In this study, we analyzed the supply chain of beer industry, which is the most prominent consumption industry with "bullwhip effect", and further established a big data collaborative inventory management model for the supply chain of beer industry based on system dynamics. We used the Vensim software for simulation and sensitivity test and after appling our model, we found that the inventory fluctuations of the participants in the beer industry supply chain became significantly smaller, which verified the effectiveness of the model.
Our study can be also applied to the possible problems of the large data supply chain collaborative inventory management model, and gives certain countermeasures and suggestions.