Talent Acquisition Metrics And Quality Of Hire For Effective Hiring A Data Driven Approach

Abstract

In the evolving landscape of Human Resource Management, Talent Acquisition (TA) newlinehas emerged as a strategic function essential for driving organisational competitiveness. However, the measurement of hiring effectiveness often remains limited to traditional efficiency metrics, neglecting quality-oriented indicators. This study, titled newlineand#8213;Metrics-Driven Talent Acquisition in IT Organisations: A Data-Driven Analysis of newlineQuality of Hireand#8214;, aims to bridge this gap by developing and empirically evaluating a newlinecomprehensive framework for assessing the Quality of Hire (QoH) through a dataanalytic approach. newlineThe research was conducted in three phases. The first, an exploratory study, examined newlinethe existing TA processes and metrics used by IT organisations, revealing that while newlinefirms actively track operational metrics such as time-to-hire and cost-per-hire, strategic indicators like QoH and predictive analytics are underutilised. The second phase newlinefocused on identifying key drivers influencing QoH through statistical techniques newlinesuch as Chi-Square and ANOVA, analysing relationships between demographic, behavioural, and performance-related variables using real employee data. The findings newlinehighlighted that factors such as performance rating, tenure, education level, job role, newlineand cost of employment significantly impact the QoH metric. newlineIn the third phase, machine learning models, including Decision Tree, R newline