Improving Managerial Efficiency Through Analyzing and Mining Resigned Staff Data

Abstract

Reducing the resigned staff number has become a significant challenge in many companies. Nevertheless, resignation can in many cases help companies to establish a 'survival of the fittest' culture that can provide companies with competitive advantages. However, a high percentage of resigned staff will have a negative impact on a company's daily operation and, in worst cases, will cause organizational breakdown. Analyzing the factors that influence the resigned staff could enable solutions to be found to prevent such incidences occurring in companies. In this paper, a data analytical method has been employed based on a China Construction Bank Hangzhou sub-branch to find whether the salary standard could have a significant effect on the rate of resignation. Through this work we could improve the contingency plan to reduce the resignation percentage and build a more reasonable human resource management system.