Multi-criteria Analysis of Need Factors for Developing a Machine Learning-based System to Track Employees' Digital Activity

Abstract

The necessity of developing a system for Machine Learning (ML)-based employee digital activity monitoring is examined in this study.  The need for developing and using ML-based remote employee monitoring systems in companies is assessed using the benefits associated with them. The development of such a system would require the application of suitable prediction models in addition to Machine learning methodologies and techniques. A Multi-criteria analysis is carried out on a sample of 102 superiors from IT (53 respondents) and non-IT (49 respondents) companies that allow their employees to work remotely, in order to determine the necessity of developing such a system. Applying the Multi-criteria Analytic Hierarchy Process (AHP), it is seen that among the respondents from IT companies, the enhancement of remote employees' job quality is the most significant factor for the development and deployment of this type of system. Conversely, non-IT respondents highlighted increased employee productivity as the primary advantage of the system implementation.