METHODOLOGICAL APPROACH TO COMPREHENSIVE ASSESSMENT OF THE EFFECTIVENESS OF REMOTE WORK MANAGEMENT IN IT-COMPANIES

Abstract

The article substantiates methodological approaches to assessing the effectiveness of remote work management in IT companies under conditions of widespread digitalization and hybrid employment models. The study systematizes three generalized approaches to evaluation: result-oriented (KPI/OKR-based), process-behavioral (discipline, engagement, communication patterns), and integrated approaches combining quantitative metrics with qualitative feedback tools. Particular attention is paid to the risks of metric over-optimization, distortion of employee behavior, and the necessity of balancing speed and quality indicators in engineering work. A comparative analysis of foreign and Ukrainian IT companies demonstrates that the most mature management systems integrate development flow metrics (lead time, cycle time, WIP, release frequency), quality indicators (defect rate, rework share, code review outcomes), and HR analytics (engagement, eNPS, turnover, burnout risks). The research emphasizes the importance of transparency, trust-based organizational culture, and regular calibration of performance criteria in distributed teams. The paper proposes a multidimensional model of remote work management effectiveness that includes five functional blocks: performance outcomes, quality metrics, process sustainability, team collaboration, and human capital well-being. To ensure comparability of heterogeneous indicators, a weighted integral index based on normalized stimulators and de-stimulators is developed. The proposed model allows organizations to integrate engineering, managerial, and HR data into a unified evaluation system and to adapt weighting coefficients according to strategic priorities. The practical significance of the research lies in the possibility of applying the proposed methodological framework for designing performance management systems in fully remote and hybrid IT companies. The results may serve as a basis for further empirical testing and econometric modeling of relationships between productivity, quality, costs, and employee well-being in digital work environments.