Performance evaluation of employees using Bayesian belief network model

It is a generally acknowledged fact that employee performance evaluation is a critical managerial tool for any organisation. In the global economy, the modern industrial and commercial organisation needs to develop effective methods for assessing the performance of their human resources. In this study, a Bayesian belief network (BBN) model is developed to evaluate the performance of an employee considering the dependencies and correlations between the criteria. The capabilities of the proposed approach are demonstrated on the lumber assembly section of a furniture manufacturing company in Bangladesh. Kendall's rank correlation coefficient is used to identify the correlation between the criteria. The results indicate that the proposed BBN-based model can explicitly quantify uncertainties and handle the complex relationships between the criteria better when compared with existing performance evaluation methods. The proposed model is also capable of assessing the credibility of multiple experts and ranking employees for different purposes such as reward, improvement, training, promotion, termination, compensation, etc.