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Article

Data-driven approaches in recruitment and personnel selection

Dmytro Zelenyi
Abstract

The purpose of the present study was to investigate the impact of data-driven approaches on the efficiency of recruitment processes in Ukrainian companies. The study was conducted based on a meta-analysis of 87 scientific publications for 2016-2024. Using the Glass-Hedges methodology, the study determined the effectiveness of various analytical tools, with the highest scores demonstrated by predictive analytics with an average effect of 0.82 and CV screening systems with an indicator of 0.75. An expert survey of 24 industry professionals using the Delphi method revealed the priority of accuracy in predicting hiring success with a consensus level of 92% and speed of candidate processing with an 88% rate. Analysis of the practical aspects of implementation based on in-depth interviews with 38 HR directors identified key challenges in technical integration and staff training. The study of the specific features of implementing innovative approaches showed the highest level of digitalisation of recruitment in the IT sector (92.4%) and large companies (87.3%), which correlates with the amount of investment in relevant technologies. The developed predictive models based on the analysis of 78 thousand candidate records and 4.3 thousand completed hiring cycles showed the greatest efficiency of the XGBoost algorithm with an 89.4% accuracy of hiring success prediction and a ROC-AUC of 0.92. Comparative analysis of the effectiveness of automated CV screening systems revealed the advantage of hybrid solutions with a selection accuracy of 92.3% and a processing speed of 620 CVs per hour, while reducing the cost of processing one CV to USD 1.5. An assessment of key performance indicators showed a 43.7% reduction in time-to-hire and a 22.1% increase in quality-of-hire in companies with a data-driven approach compared to the control group, accompanied by a 20.6% increase in retention rates. The integrated assessment of the effects of analytical tools showed the highest efficiency index in the operational component (0.89) and process automation (0.88) with an economic effect (ROI) of 245% and 278%, respectively, which confirmed the feasibility of implementing data-driven approaches in recruiting for Ukrainian companies

Keywords

predictive analytics; automated systems; optimisation algorithms; labour market

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Received 05.02.2025, Revised 29.04.2025, Accepted 05.06.2025

Retrieved from Vol. 12, No. 1, 2025

Suggested citation

Zelenyi, D. (2025). Data-driven approaches in recruitment and personnel selection. Economics, Entrepreneurship, Management, 12(1), 69-82. https://doi.org/10.56318/eem2025.01.069

https://doi.org/10.56318/eem2025.01.069

Pages 69-82

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