Page 17 - Azerbaijan State University of Economics

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

their personal data is being misused, it can erode their trust and confidence in the
organisation [Roberts DR. 2013; S. Chatterjee and S. Mousumi, 2023] In the backdrop
of above discussion, it can be strongly asserted that employee engagement and
retention have been widely examined aspects in the arena of HR Analytics,
highlighting the potential of data-driven approaches in lowering the employee
turnover rate and improving their efficiency [Roberts DR. 2013].

Workforce Planning and Optimisation
Various scholarly investigations undertaken in the domain of HR Analytics have
accentuated the critical role of data in workforce planning and optimisation decision
making [Momin WYM, Mishra K. 2015; Bajaj NA. 2025; Huselid MA. 2018]. The
findings of these studies emphasised that organisations could harness the power of
predictive analytics, scenario planning, and advanced data modelling techniques to make
an accurate estimate of future workforce requirements. Such methodologies enable
businesses to optimise staffing levels, ensuring that available resources are neither
underutilised nor overburdened, while also facilitating strategic mobility of workforce
[Nalla NNR. 2024; Kishnani N. 2019; Yuan J. 2019; Falletta SV, Combs WL 2020].

By using advanced analytics techniques, organisations can get an idea about the
possible skill gaps, align future staffing requirement with objectives of the business,
and ensure the placement of the right people in the right job [Huselid MA. 2018;
Worth CW. 2011; Chaturvedi V. 2016]. For example, a study undertaken by Falletta
& Combs (2020) [Falletta SV, Combs WL. 2020] revealed that predictive models can
be utilised to forecast future staffing requirements, taking into consideration the
factors including employee turnover, retirement trends, and expansion of business.

Furthermore, the research highlights the potential of using employee data, including
performance level, skills, expertise and career aspirations, to find the talented
workforce, doing succession planning, and ensuring strategic workforce mobility
[Rombaut E, Guerry MA. 2017]. The adaptability of a data-driven approach to talent
management may assist organisations in retaining and developing their top
performers, while also sustaining a responsive and multifaceted workforce.

Employee Capacity Building and Skill Development Initiatives
The application of data analytics in measuring and evaluating the effectiveness of existing
training and development programs and identifying the knowledge and skill gaps among
employees has been extensively investigated by the research community [Chauhan R,
Mishra AK. 2025; Ramamurthy KN, Singh M, Davis M, Kevern JA, Klein U, Peran M.
2015; Dixit R, Sinha V. 2020; Falletta SV, Combs WL.2020]. It has been suggested by
the researchers that organisations could employ learning analytics to monitor the impact
of training on employee performance [Barbar K, Choughri R, Soubjaki M. 2019; Mushtaq

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