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Prerna Ahuja, Meenu Gupta, Jinesh Jain, Kiran Sood, Luan Vardari: HR Analytics Research
Landscape (2003–2024): A Systematic, Bibliometric, and Content Analysis

INTRODUCTION
The growing complexity and competitive nature of contemporary business necessitate
a shift in human resource management (HRM) from intuition and experience-based
practices to data-driven decision-making. Human resource analytics has emerged as a
transformative field relying on vast data and advanced analytics [Ben-Gal HC. 2019].
This shift has led to the rapid growth of HR analytics to improve employee
productivity and ultimately enhance organisational performance [Polyakova A,
Kolmakov V, Pokamestov I. 2020]

HR analytics encompasses a broad spectrum of activities, ranging from analysing
employee turnover and absenteeism, forecasting human resource requirements, and
assessing the effectiveness of training programs [Lawrance N, Petrides G, Guerry MA.
2021]. By applying statistical methods, predictive modelling, and data visualisation
techniques, HR professionals can gain deep insights into workforce dynamics, identify
grey areas, improve them and make informed decisions [Dahlbom P, Siikanen N,
Sajasalo P, Jarvenpää M. 2019]. This data-driven approach has the potential to
transform HR from a primarily administrative function to a strategic partner in
achieving the organisation's long-term goals [Wang N, Katsamakas E., 2019].

However, the successful implementation and utilisation of HR analytics is not without
its challenges [Hota J. 2021]. The limited data literacy, inadequate technological
infrastructure, and lack of analytical skills among HR professionals are presenting
challenges for the effective adoption of HR analytics. Additionally, concerns around
data privacy, ethics, and the potential for algorithmic bias must be carefully navigated.
Organisations face hurdles in developing robust data management systems, acquiring
the necessary analytical skills, and addressing data privacy issues [Cayrat C, Boxall
P. 2022; Hamilton RH, Sodeman WA. 2019].

The existing literature on HR analytics has explored a range of topics, including the
drivers and barriers to adoption, the applications of analytics in various HR domains,
and the potential benefits that can be derived from adopting these practices. A
comprehensive understanding of the current state of HR analytics research is essential
for guiding future scholarly and practitioner efforts in this evolving field. Moreover,
it is necessary to examine the full potential of HR analytics and propose best practices
for its implementation in diverse organisational settings [Zebua NDK, Santosa NTA,
Putra NFD. 2024; Kakkar H, Kaushik S. 2019; Bala, R., Singh, S., & Sood, K.,
Grima.S 2025,]. This study aims to offer a comprehensive and systematic overview
of existing research in HR analytics. To meet this objective, the study adopts a triadic
approach, combining systematic literature review (SLR), bibliometric analysis, and
content analysis to highlight contextual insights and thematic challenges related to HR

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