Nocker, Manuela and Sena, Vania (2019) Big Data and Human Resources Management: The Rise of Talent Analytics. Social Sciences, 8 (10). p. 273. DOI https://doi.org/10.3390/socsci8100273
Nocker, Manuela and Sena, Vania (2019) Big Data and Human Resources Management: The Rise of Talent Analytics. Social Sciences, 8 (10). p. 273. DOI https://doi.org/10.3390/socsci8100273
Nocker, Manuela and Sena, Vania (2019) Big Data and Human Resources Management: The Rise of Talent Analytics. Social Sciences, 8 (10). p. 273. DOI https://doi.org/10.3390/socsci8100273
Abstract
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.
Item Type: | Article |
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Additional Information: | Special Issue "Big Data and Employee Wellbeing" |
Uncontrolled Keywords: | big data; talent analytics; human resources management |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Essex Business School |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 26 Nov 2019 18:25 |
Last Modified: | 30 Oct 2024 21:11 |
URI: | http://repository.essex.ac.uk/id/eprint/25652 |
Available files
Filename: socsci-08-00273-v2.pdf
Licence: Creative Commons: Attribution 3.0