IDEAS home Printed from https://ideas.repec.org/a/rbs/ijbrss/v14y2025i6p53-69.html

Leveraging the power of human resource analytics for enhanced decision making: opportunities and challenges

Author

Listed:
  • Joelle Danielle Ngo Ndjama

    (Vaal University of Technology)

Abstract

The fast-changing technological environment compels organisations to make swift and adaptive strategic choices, necessitating the use of tools and systems that can effectively manage complexities, foresee challenges, and capitalise on opportunities; as a result, there is a growing trend towards the adoption of human resource analytics to improve decision-making processes in the ever-evolving field of human resources. Despite the increasing use of HR metrics and analytics in human resource management, HR professionals have been relatively slow to embrace a data-driven approach, and existing research on data-driven decision-making in HRM often lacks the comprehensive frameworks necessary to provide practical guidance for the effective integration of human resource analytics. Hence, this study aims to explore the utilisation of human resource analytics to improve decision-making processes within organisations, highlighting both the potential benefits and the challenges that may arise. A systematic literature review revealed that the adoption of Human Resource Analytics offers organisations significant benefits, such as enhanced decision-making, better alignment with strategic objectives, improved employee experiences, a stronger competitive advantage, and reduced time expenditures. However, challenges persist, including concerns related to data privacy and security, the quality, integrity, and accuracy of data, a lack of data literacy and skills among employees, and inadequate technological infrastructure. To address data security concerns, HR technology providers must adopt robust security measures, including encryption, firewalls, and intrusion detection systems. Additionally, they should develop user-friendly data management systems and analytical tools that enable HR professionals to derive valuable insights from the data effectively. Key Words:Human resource management, HR analytics, decision making, challenges, opportunities, human capital theory

Suggested Citation

  • Joelle Danielle Ngo Ndjama, 2025. "Leveraging the power of human resource analytics for enhanced decision making: opportunities and challenges," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 14(6), pages 53-69, August.
    • Handle: RePEc:rbs:ijbrss:v:14:y:2025:i:6:p:53-69
    DOI: 10.20525/ijrbs.v14i6.4276
    as

    Download full text from publisher

    File URL: https://ssbfnet.com/ojs/index.php/ijrbs/article/view/4276/2913
    Download Restriction: no
    File URL: https://doi.org/10.20525/ijrbs.v14i6.4276
    Download Restriction: no
    File URL: https://libkey.io/10.20525/ijrbs.v14i6.4276?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Frédéric Rosin & Pascal Forget & Samir Lamouri & Robert Pellerin, 2022. "Enhancing the Decision-Making Process through Industry 4.0 Technologies," Sustainability, MDPI, vol. 14(1), pages 1-35, January.
    2. Kieran Xuereb & Simon Grima & Frank Bezzina & Andre Farrugia & Pierpaolo Marano, 2019. "The Impact of the General Data Protection Regulation on the Financial Services’ Industry of Small European States," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(4), pages 243-266.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Estefania Tobon-Valencia & Samir Lamouri & Robert Pellerin & Alexandre Moeuf, 2022. "Modeling of the Master Production Schedule for the Digital Transition of Manufacturing SMEs in the Context of Industry 4.0," Sustainability, MDPI, vol. 14(19), pages 1-28, October.
    2. Mario Passalacqua & Robert Pellerin & Florian Magnani & Laurent Joblot & Frédéric Rosin & Esma Yahia & Pierre-Majorique Léger, 2025. "Safeguarding worker psychosocial well-being in the age of AI: The critical role of decision control," Post-Print hal-05345071, HAL.
    3. Jonathan Brodeur & Robert Pellerin & Isabelle Deschamps, 2022. "Operationalization of Critical Success Factors to Manage the Industry 4.0 Transformation of Manufacturing SMEs," Sustainability, MDPI, vol. 14(14), pages 1-35, July.
    4. Fuwen Hu & Song Bi & Yuanzhi Zhu, 2024. "Cooperative Game-Based Digital Twin Drives Decision Making: Overall Framework, Basic Formalization and Application Case," Mathematics, MDPI, vol. 12(2), pages 1-22, January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rbs:ijbrss:v:14:y:2025:i:6:p:53-69. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Umit Hacioglu (email available below). General contact details of provider: https://edirc.repec.org/data/ssbffea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.