Effective Personnel Selection and Team Building Using Intelligent Data Analytics

Abstract

Building a successful team is essential for any organization as it enhances creativity, innovation, and productivity. Mismatched staffing is very costly for employers as it can lead to loss of time and resources spent on training and recruitment, loss of productivity, and project failure. Existing personnel selection approaches are focused on determining if the candidates’ skills and personalities fit the job in question. However studies suggest that compatibility of personality traits of team members with respect to the overall team performance must also be considered. This should be done without creating a level of homogeneity and agreeableness which would adversely affect productivity. Factors such as cohesion and consistency between the team members’ personalities are analyzed using the Big Five model to organize and recognize compatible personality traits that would result in more effective teamwork. This research proposed a solution which utilizes intelligent data analytics to provide effective and efficient decision support for personnel selection in order to increase team performance. The result of the proposed research could save significant amount of time and resources by contributing to the increase of employee satisfaction, reducing turnover, and increasing team performance and project success rates.