Predicting Employee Career Development based on Employee Personal Background and Education Status

Recruiting and retaining high-potential employees is quite critical for enterprises to maintain competitive advantages in modern knowledge-intensive economy. In this paper, we attempt to identify existing talents who have development potentials based on their personal backgrounds and education statuses through data analysis and a prediction model. Our research is based on data that are collected from a large state-owned enterprise. Statistical analysis method is utilized to discover the correlations between the employee career development and their personal backgrounds and education statuses. Besides, data mining used in the proposed prediction model is to forecast the potential employee career development. From the results, our research provides a reliable and practical way to use personal background and education status features forecast employee career development potential and find out significant factors affecting employee career development.