Application of machine learning models in employee selection and performance management

Abstract

In today’s world of intense business competition and a continuously evolving landscape with globalization and new age technological breakthrough, it is important for organisations to utilize their internal resources to the maximum by focusing on people management and having systems that help companies achieve their business targets. With regards to this, human resources can be a key asset to attain sustainable competitive advantage which can help businesses leap ahead of their competitors. An organization's employee selection and performance management processes are extremely important for the company’s success. In today’s modern world, these processes are rapidly changing with integration with modern technological systems into the same. Machine learning and AI are being increasingly used to assist in hiring and performance management procedures. Some examples are instead of manually sorting the applications beginning with the resume shortlisting and screening process, AI and machine learning algorithms use natural language processes to analyze resumes and sort applications based on job requirements. Similar applications have come up in employee performance evaluation as well. Machine learning models refer to the methods in the Artificial Intelligence system which are either used for prediction of an output or trend analysis, with a given set of input data. These are covered under majorly 2 areas of classification and/or regression. We aim to explore both potential applications in the above-mentioned topics. This report aims to implement applications of machine learning in employee performance and employee selection processes and gain insights from the same. It also looks at other potential new age use-cases that can be explored and implemented in employee selection and employee performance.