A Data-driven Analysis of Employee Promotion: The Role of the Position of Organization

Abstract

In the era of big data and industry 4.0, the mode of human resource management (HRM) will be changed. As the role of talents rises, enterprises need to pay more attention to human capital. Meanwhile, intelligent production also urges intelligent HRM. Based on the accumulation of data, enterprises should use big data and artificial intelligence technologies to analyze employees, predict the future, and support businesses. Thus, the paper attempts to put forward ideas on data-driven solution to the promotion issue in HRM, and focus on the influence from the position of organization. The data come from a state-owned enterprise in China. Here the features of organizational position are chosen to analyze employee promotion and forecast employee prospect. From the analysis based on statistics and networks, as well as the prediction based on machine learning, we find that structural position plays a more critical role than geographic position. Besides, employees can benefit from working in the place where special experience is available, where mobility is more stable, or where resource is more abundant. But organizations should be concerned with the fair development of workers. The experimental results also validate that the prediction model is practical and effective.