A Quantitative Methodology to evaluate the cost of Human Capital acquisition. BioPharma Industry Model

Purpose: - This study introduces a novel quantitative methodology to measure talent efficiency and its direct impact on business financial success, addressing a gap in traditional recruitment cost models. Existing frameworks often focus on static cost-per-hire metrics, neglecting the long-term business impact of recruitment efficiency. By integrating predictive modelling with financial benchmarking, this research provides a strategic tool for workforce planning and talent acquisition optimisation. Aim(s): - The primary aim is to develop a predictive model linking talent efficiency to business financial performance, quantifying the impact of recruitment strategies on profitability and operational success. The secondary aim is to benchmark talent acquisition efficiency across biopharmaceutical firms, identifying best practices that drive financial sustainability. Design/methodology/approach: - The study applies Multiple Linear Regression (MLR) to construct a Cost of Recruitment (CoR) equation, incorporating financial and operational metrics such as Time to Fill (TTF), Bad Hire Replacement (BHR) Costs, and Profit per Employee (PPE). A Data Envelopment Analysis (DEA) model is then used to benchmark talent efficiency across 33 biopharmaceutical firms, identifying high-performing companies. Econometric refinements, including Two-Stage Least Squares (2SLS) estimation, heteroskedasticity correction, and multicollinearity reduction, enhance model reliability. Findings: - The results demonstrate that talent efficiency is a strong predictor of business financial success, with high-efficiency firms achieving greater profitability per employee and improved workforce scalability. The study challenges the assumption that internal hiring is always the most cost-effective, highlighting cases where external recruitment enhances business performance. Limitations of the study: - The analysis is limited to biopharmaceutical firms, requiring further validation across other industries. Future research should incorporate dynamic workforce metrics to refine predictive accuracy. Practical implications: - This model provides HR and executive leadership with a strategic decision-making tool to align talent acquisition investments with financial outcomes, driving cost efficiency and business growth. Originality/value: - By linking talent efficiency with financial performance, this research offers a data-driven framework for optimising workforce strategy, ensuring recruitment decisions contribute directly to business success.