Authors: Dr. Hemalatha G, Ms. Hemalatha S, Ms. Kanisha. P, Ms. Yakshitha. M
Abstract: The increase in hybrid working scenarios after the pandemic period has brought about new challenges to organizational leadership and the need for new approaches reconciling the two aspects of data analytics and distributed workforce management. This research paper is aimed at presenting the results of analysis of data-driven leadership models applied in hybrid working conditions. The analysis performed within this paper is based on the review of relevant literature in the field (2021-2026) and empirical results of various studies that have been conducted. The main gap found in the existing literature concerns the difference between traditional models of leadership and the needs of hybrid work environment. We suggest a framework combining the concepts of workforce analytics and humanistic approach to leadership, namely the transition from output to outcomes evaluation. The methods applied in our research include the application of ensemble learning algorithms in order to estimate the patterns of employee turnover and productivity and the use of sentiment analysis in order to evaluate employee engagement. It has been proven that organizations adopting data-driven leadership models exhibit much better performance in terms of employee retention and productivity than traditional models of management.
DOI: http://doi.org/10.5281/zenodo.23095472
