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Big Data and Human Resources Management: The Rise of Talent Analytics


  • Manuela Nocker

    () (Essex Business School, University of Essex, Essex SS1 1LW, UK)

  • Vania Sena

    () (Essex Business School, University of Essex, Essex SS1 1LW, UK)


The purpose of this paper is to discuss the opportunities talent analytics offers HR practitioners. As the availability of methodologies for the analysis of large volumes of data has substantially improved over the last ten years, talent analytics has started to be used by organizations to manage their workforce. This paper discusses the benefits and costs associated with the use of talent analytics within an organization as well as to highlight the differences between talent analytics and other sub-fields of business analytics. It will discuss a number of case studies on how talent analytics can improve organizational decision-making. From the case studies, we will identify key channels through which the adoption of talent analytics can improve the performance of the HR function and eventually of the whole organization. While discussing the opportunities that talent analytics offer organizations, this paper highlights the costs (in terms of data governance and ethics) that the widespread use of talent analytics can generate. Finally, it highlights the importance of trust in supporting the successful implementation of talent analytics projects.

Suggested Citation

  • Manuela Nocker & Vania Sena, 2019. "Big Data and Human Resources Management: The Rise of Talent Analytics," Social Sciences, MDPI, Open Access Journal, vol. 8(10), pages 1-19, September.
  • Handle: RePEc:gam:jscscx:v:8:y:2019:i:10:p:273-:d:271925

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    References listed on IDEAS

    1. David J. Teece & Gary Pisano & Amy Shuen, 1997. "Dynamic capabilities and strategic management," Strategic Management Journal, Wiley Blackwell, vol. 18(7), pages 509-533, August.
    2. Erik Brynjolfsson & Lorin M. Hitt, 2000. "Beyond Computation: Information Technology, Organizational Transformation and Business Performance," Journal of Economic Perspectives, American Economic Association, vol. 14(4), pages 23-48, Fall.
    3. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," Boston University - Department of Economics - Working Papers Series dp-297, Boston University - Department of Economics.
    4. Daron Acemoglu & Pascual Restrepo, 2017. "Robots and Jobs: Evidence from US Labor Markets," NBER Working Papers 23285, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Carolyn Axtell & Mark Taylor & Bridgette Wessels, 2019. "Big Data and Employee Wellbeing: Walking the Tightrope between Utopia and Dystopia," Social Sciences, MDPI, Open Access Journal, vol. 8(12), pages 1-5, November.

    More about this item


    big data; talent analytics; human resources management;

    JEL classification:

    • A - General Economics and Teaching
    • B - Schools of Economic Thought and Methodology
    • N - Economic History
    • P - Economic Systems
    • Y80 - Miscellaneous Categories - - Related Disciplines - - - Related Disciplines
    • Z00 - Other Special Topics - - General - - - General


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