Driving police engagement through talent management: Evidence from Abu Dhabi

Abstract

This study examines the relationship between talent management practices and employee engagement, as well as the moderating role of business analytics and the subsequent impact on employee performance within the Abu Dhabi Police. Specifically, the research explores how talent attraction, retention, learning and development, and career management influence employee engagement, which in turn affects job performance. Drawing on social exchange theory, dynamic capability theory, and Aon Hewitt’s employee engagement model, a quantitative research design was employed using a structured questionnaire distributed to senior officers across various departments. A total of 383 valid responses were analyzed using partial least squares structural equation modeling (PLS-SEM) via SmartPLS 3.3.9. The findings reveal that all four dimensions of talent management (talent attraction, talent retention, learning and development, and career management) have significant positive effects on employee engagement. Furthermore, employee engagement strongly and significantly influences employee performance, underscoring its pivotal role in organizational effectiveness. The results of the moderation analysis indicate that business analytics significantly strengthens the relationships between talent attraction, learning and development, and career management and employee engagement, with learning and development and talent attraction showing the strongest moderating effects, whereas the moderating effect on talent retention is statistically insignificant. The model explains 53.8% of the variance in employee engagement, indicating satisfactory predictive power. These findings contribute to the literature by integrating business analytics into the talent management–engagement–performance nexus, particularly within a public sector policing context. Practically, the results highlight the strategic importance of leveraging data-driven and analytics-enabled HRM practices to personalize talent management interventions, enhance perceived fairness, and improve engagement outcomes. Overall, the findings demonstrate that while business analytics enhances most talent management dimensions, its influence is not uniform across all practices, particularly in the case of talent retention. This study provides actionable insights for policymakers and HR leaders seeking to build agile, high-performing, and engaged workforces in dynamic environments.