Next Article in Journal
A Durkheimian Theorization of Scottish Suicide Rates, 2011–2017
Previous Article in Journal
‘I Respect You but I Am Not Willing to Be You’: Critical Reflections of Western Teaching of Social Work to Students in China—What Can be Learned Both Ways?
Previous Article in Special Issue
Integrating Social Scientific Perspectives on the Quantified Employee Self
Open AccessArticle

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

Essex Business School, University of Essex, Essex SS1 1LW, UK
Author to whom correspondence should be addressed.
Soc. Sci. 2019, 8(10), 273;
Received: 29 July 2019 / Revised: 5 September 2019 / Accepted: 11 September 2019 / Published: 29 September 2019
(This article belongs to the Special Issue Big Data and Employee Wellbeing)
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. View Full-Text
Keywords: big data; talent analytics; human resources management big data; talent analytics; human resources management
Show Figures

Figure 1

MDPI and ACS Style

Nocker, M.; Sena, V. Big Data and Human Resources Management: The Rise of Talent Analytics. Soc. Sci. 2019, 8, 273.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop