Workforce Analytics: Need of the Modern Organisations

Authors

  • Dr. Nandini Srivastava Professor, MRIIRS Author
  • Dr. Farhat Mohsin Associate Professor, FMS, MRIIRS Author

DOI:

https://doi.org/10.61841/5s6ctm61

Keywords:

Work Force Analytics, HR Analytics, Talent Management, Performance and Compensation

Abstract

With the growth in industry and complexities in the corporate jobs, the volume of data has increased manyfold. Over the last 20 years, the companies have realized the importance of data and its interpretation in the effective management of business operations. Almost all organizations, in some way or other, are increasingly adopting analytics in the day-to-day activities of the organization. The scope of analytics is not confined to marketing and finance; rather, now the data available for HR to report has also increased and gained importance. Fields like talent acquisition, management, performance, compensation, etc., have started utilizing analytics for better results; however, most of the companies have yet to even realize the need for the use of analytics in the field of HR. According to a report published, most companies have not understood the value of their analytics investments, with only 12% of organizations currently using talent data to effectively influence business decisions and 70% of organizations expecting to increase the resources that they dedicate to talent analytics in recent times. The aim of this paper is to understand the rise of HR analytics over the last few years. This paper focuses on the role of stakeholders involved in HR, who have developed and positioned HR analytics as a necessary solution to existing and upcoming challenges 

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References

[1] Beer, M. (2015). HRM at a Crossroads: Comments on “Evolution of Strategic HRM Through Two

Founding Books: A 30th Anniversary Perspective on Development of the Field.” Human Resources

Management, 54(3), 417-421.

[2] Benders, J., & Van Veen, K. (2001). What's in a fashion? Interpretive viability and management fashions.

Organization, 8(1), 33-53.

[3] Deloitte. (2015). Global Human Capital Trends 2015. Leading in the new world of work. Retrieved from

https://www2.deloitte.com/content/dam/Deloitte/at/Documents/human-capital/hc-trends-2015.pdf

[4] Deloitte. (2016). Global Human Capital Trends 2016. The new organization: different by design.

[5] Retrieved from http://www.workdayrising.com/pdf/Deloitte_GlobalHumanCapitalTrends_2016_3.pdf

[6] Aral, S., Brynjolfsson, E., Wu, L. (2012). Three-way complementarities: Performance Pay, human

resource analytics and information technology. Management Science, Vol. 58, pp. 913–931.

[7] Bailey, T. (1993). Discretionary effort and the organization of work: Employee participation and work

Reform since Hawthorne, working paper, Columbia University, New York.

[8] Bersin, J. (2013): Big Data in Human Resources: Talent Analytics (HR Analytics) Comes of Age. Source:

https://www.forbes.com/sites/joshbersin/2013/02/17/bigdata-in-human-resources-talent-analytics-comesofage/#280ea53f4cd0 2018.02.20 02. 20

[9] Fink, A. A. (2017): Getting results with talent analytics. People + Strategy Journal, Vol. 40, No. 3.

[10] Gartner. (2012). Workforce Analytics, retrieved October 14, 2012, from http://www.gartner.com/itglossary/workforce-analytics/.

[11] Harris, J. G., Craig, E., Light, D. A. (2011). Talent and analytics: New approaches, higher ROI. Journal

of Business Strategy, Vol. 32, pp. 4–13

[12] Hota, J.R. (2011). Business Analytics: A Tool for Organizational Transformation. CSI Communications,

35(3), 21-22.

[13] Kaur, J., & Fink, A. A. (2017): Trends and practices in talent analytics. Society for Human Resource

Management (SHRM)-Society for Industrial Organizational Psychology (SIOP) Science of HR White

Paper Series. Source: http://www.siop.org/SIOP SHRM/2017%2010_SHRM-SIOP%20Talent%20

Analytics.pdf 2018.02.20

[14] Marler, J. H. & Boudreau, J. W. (2017): An evidence-based review of talent analytics. The International

Journal of Human Resource Management, Vol. 28, No. 1, pp. 3–26

[15] Robinson, A. (2012). Predictive Analytics: Data Driven Decision Making, HRMAC Summit, retrieved

October 30, 2012, from http://www.hrmac.org/summit2012/Anne%20Robinson%20-

20Predictive%20Analytics%20-%20Data-Driven%20Decision%20Making.pdf.

[16] Rouse, M. (2012). Workforce Analytics, retrieved October 10, 2012, from http://searchfinancialapplications.techtarget.com/definition/workforce-analytics.

[17] Stone, D.—Deadrick, D.—Lukaszewski, K.—Johnson, R. (2015): The influence of technology on the future of human resource management. Human Resource Management Review, Vol. 25, pp. 216–231

[18] Waber, B. (2013): HR Analytics: How Social Sensing Technology Will Transform Business And What IT Tells Us about the New World of Work. New Jersey: Pearson Education, Inc.

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Published

31.07.2020

How to Cite

Srivastava, N., & Mohsin, F. (2020). Workforce Analytics: Need of the Modern Organisations. International Journal of Psychosocial Rehabilitation, 24(5), 4410-4418. https://doi.org/10.61841/5s6ctm61