Predicting Employee Performance and discovering its correlation with various work environment factors

Abstract

Major source of judgement for human resource managers is the performance of its employees in company. Many methods of evaluating and predicting the employee performance has evolved over recent period. In any organisation, employees play a major role in the success or failure of the organisation. Today, every organisation is taking innumerable measures to improve the performance of their employees. They try to use brute force approach and expect an increase in performance of employees. This also leads them to false predictions and estimations of their success goals when it is concerned to productivity of employees. Their primary goal is to achieve their goals on time, by improving employee productivity and efficiency. There are many research going on for applying machine learning to solve the concerned problem. Many classification algorithm are worked upon to predict the future performance rating of a particular employee. There is not much information available on what parameters are actually responsible for this performance rating of the employee. This paper is about the machine learning methods which helped in finding the factors that are responsible for the performance rating of an employee and also predict their future performance rating based on certain conditions. These conditions are dependent on the work environment of an employee and there concerned priorities about work. Upon discovering the factors responsible, the research gives a study about recommendations to be given to an employee or the organisation on how they can improve the metrics and increase employee productivity.