EmReSys: AI-based Efficient Employee Ranking and Recommender System for Organizations

According to Jorge Paulo Lemann, “the greatest asset of a company is its people.” An organization consists of many areas where technologies supporting decision-making, i.e., artificial intelligence, can assist organizations in organization aspects, business strategies, and people management. The objective of decision-making technologies is not based on subjective factors but on objective data analysis. One such application area is to provide incentives to employees without any human interaction or intervention. It is an organization’s job to find good employees and recognize their efforts by offering incentives. However, handpicking potentially outstanding employees in a workplace where biases have penetrated gets perplexing. To overcome this barrier, EmReSys, an employee recommendation System for large-scale organizations, is developed, which does not require any human interaction to recognize personnel potential. It uses Machine Learning (ML) techniques to recommend the employee for promotion, increment, etc. The EmReSys system is installed at the edge network to perform ML tasks efficiently and the communication is established via the 5G network. The suggested method automates the procedure using a Support Vector Machine (SVM), an ML technique with a 98.9% accuracy.