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.