Predictive Effectiveness of Recruitment and Selection Practices on Employee Performance and Retention

Ms.R. JAVI PRABHA

MBA ,NET, Assistant Professor, School of Management Dhanalakshmi Srinivasan University (yazhini.s)

Abstract:The alignment between human resource acquisition frameworks and operational business strategy stands as a defining pillar of long-term sustainable institutional performance. This extensive study presents an empirical evaluation of the predictive effectiveness of advanced recruitment and selection protocols on twin core organizational endpoints: employee performance metrics and post-onboarding retention dynamics. Utilizing data collected across listed mid-to-large-cap corporations from 2022 to 2026, this research examines the shift from traditional heuristic hiring modalities toward analytical, structured selection technologies. Through a structured multi-dimensional panel data framework capturing detailed candidate screening histories, behavioral assessment architectures, psychometric test evaluations, and multi-stage panel interviewer scorecards, we isolate specific selection vectors that act as key high-fidelity indicators of future workplace excellence. The findings indicate that while psychometric profile clustering provides high predictive alignment with baseline role competency and task adherence, the deployment of interactive structured behavioral interviewing and situational task modeling offers a significantly more robust, statistically valid forecast of organizational citizenship behavior, agile problem-solving capacity, and mid-to-long-term tenure commitment. Furthermore, quantitative structural equation modeling demonstrates that early tenure attrition is heavily mediated by information asymmetry experienced during the talent pipeline initialization stage. Organizations that incorporate realistic job previews (RJPs) alongside standardized algorithmic screening platforms show an average 27.4% reduction in first-year involuntary turnover and a corresponding 18.2% elevation in localized annual key performance index metrics. Ultimately, this report outlines an integrated predictive model that treats candidate sourcing not as an isolated transactional administrative protocol, but as an ongoing data-driven predictive calibration engine designed to secure structural human capital advantages.

Keywords: Recruitment optimization, Predictive selection frameworks, Employee retention kinetics, Structural Equation Modeling, Human Capital Yield, Strategic HRM Analytics.