Authors: Gururaj S N, Dr. Jayanthi R
Abstract: The study aims to evaluate the preparedness of Human Resource (HR) managers for data-driven decision-making by analysing the impact of data literacy, organisational support, and the adoption of HR analytics technologies on the efficacy of decision-making. This paper examines how HR managers may successfully incorporate data insights into strategic and operational activities, acknowledging the growing significance of analytics and artificial intelligence in human resource management. A quantitative study approach was used, using data gathered from 384 HR experts across public, private, multinational, start-up, and non-governmental organisations. A structured questionnaire with a 5-point Likert scale assessed four constructs: data literacy among HR managers, organisational support, the adoption of HR analytics technologies, and the efficacy of data-driven decision-making. Statistical studies were performed with SPSS and AMOS, including descriptive statistics, correlation, regression, and structural equation modelling to investigate the connections among the variables. The findings indicated substantial positive correlations across all variables, showing that HR managers with enhanced data literacy, more organisational support, and broader use of analytics technologies had superior decision-making skills. The results indicate that data literacy immediately improves analytical proficiency, organisational support creates a conducive climate for analytics integration, and advanced tools boost predicted precision and operational performance. The study indicates that fostering data literacy and technological adaptation in HR professionals, supported by a culture of evidence-based decision-making, is crucial for organisational flexibility and sustained performance. It underscores that preparing HR managers for data-driven decision-making is not only a technical adjustment but a strategic transformation that establishes HR as an essential collaborator in attaining enduring organisational performance and competitiveness.
DOI: https://doi.org/10.5281/zenodo.20391964
