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Predictive HR analytics and talent management: a conceptual framework

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  • R. Navodya Gurusinghe
  • Bhadra J. H. Arachchige
  • Dushar Dayarathna

Abstract

Digitisation, new technologies and artificial intelligence demand organisations for new ways of working with a different skill set to accomplish strategic objectives. HR analytics is the scientific solution enabling organisations to make significant human capital and strategic business decisions and thereby gain a competitive advantage. However, theory-based relationships in HR analytics adoption is meagre. Further, there is a paucity of HR analytics literature on the role of contextual factors that affect organisations in building predictive HR analytics (PHRA) capability. Addressing this gap, we develop a conceptual framework through the lens of the Technological-Organisational-Environmental (TOE) framework and Resource-based theory to examine the relationships among the antecedents and consequences of PHRA capability considering talent management under the moderating effect of a data-driven culture. This paper is possibly the first study to propose a theoretical model to examine the effect of PHRA capability on talent management outcomes.

Suggested Citation

  • R. Navodya Gurusinghe & Bhadra J. H. Arachchige & Dushar Dayarathna, 2021. "Predictive HR analytics and talent management: a conceptual framework," Journal of Management Analytics, Taylor & Francis Journals, vol. 8(2), pages 195-221, April.
    • Handle: RePEc:taf:tjmaxx:v:8:y:2021:i:2:p:195-221
    DOI: 10.1080/23270012.2021.1899857
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    Cited by:

    1. Shuo Tian & Hangeng Zhao & Xiaobo Xu & Rongchao Mu & Qiang Ma, 2022. "Knowledge chain integration of design structure matrix‐based project team: An integration model," Systems Research and Behavioral Science, Wiley Blackwell, vol. 39(3), pages 462-473, May.

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