Big Data-driven Warehousing Process Optimization Scheme for Express Delivery Company - Qin, Xin Sheng (Journal of Innovative Studies, 2022)
Warehouse management has never been more complex than it is today. historically logistics and supply chains have produced large quantities of high value data. for many organizations optimizing this data, analyzing it, and learning from it, is a challenge due to the lack of effective data statistical analysis methods and tools, so these data have not been effectively utilized. This paper takes Cainiao company of China as an example to analyze the status of the inbound and outbound express warehousing process. taking the operation data of the Cainiao company at a university as a sample to research the deep-seated causes of low efficiency disordered management. the logistics big data cluster analysis method is used to mine the inbound and outbound operations and then the optimization schemes are proposed.