A decision tree applied to the grass-roots staffs' turnover problem —take C-R Group as an example

Staff turnover is one of the most pressing problems in enterprises' staff management. The former studies on the problem of staff turnover did not succeed timely in the managing, supervising and preventing of the staff on the production line that have great turnover flow. Taking the staff data of the chain retail stores of the C-R Group as an example, collecting all the information of the staff at some city in east China in 2014, this research established a mining database (N=5277). What's more, it adopted the C4.5 decision tree of a data-mining to research the staffs' turnover situation of the enterprise's stores. Six rules of the turnover of staff in the stores are obtained by calculation, then the results were tested with the non-repetitive verification database (N=1066) by percentage comparison. There were no-significant differences between the two databases to all six rules. According to the result of the research, the reason and precautions of the staff turnover of this enterprise are explored. At the same time, it is recommended that the data mining technology can be further applied and developed in the field of Human Resource Management (HRM).