Data-driven HRM and the role of HR Analytics.

 

As time has gone on, HR's job has evolved from an administrative one to one that is increasingly strategic. The advancement of technology has been one of the main forces behind this transition.

HRM has gradually evolved, with data collection, storing, and processing playing a major role. Even now, experts and professionals have questioned whether HR's shift to a more strategic role has been successful over the previous few decades. The capacity to generate reliable information about people-related issues and make fact-based, strategic HRM decisions has proven to be one barrier. Beatty (2015)

The exponential rise in data volume, the increasing efficiency of data storage, and the processing speed are all contributing factors to the ongoing acceleration of technological growth. While social media and mobile devices are becoming ubiquitous in our daily lives, software is rapidly moving to the cloud.

The management of human resources (HRM) is one area where such developments have historically been significant and are likely to continue. These trends are altering organizations' organization and management and giving them new possibilities in analytics and forecasting. Becker, Huselid and Ulrich (2001)

The development of HRM has evolved almost hand in hand with the technological progress. Data, its storing, processing and utilisation have played a central role throughout HRM’s gradual evolution from the basic administrative duties to more recently support the data-driven decision-making, and associated with it strategic role of HR in contemporary organizations. However, throughout past decades both academics and practitioners have been concerned and often sceptical about the speed and ultimate success of HR in this evolution. Recently, there is a growing belief that HR analytics offer a possible solution to ensure and improve the data-driven HRM and, at last, to help HRM achieve its strategic potential. Bhargava, Power and Sun ( 2007)

Enhancing knowledge of HR analytics and its application was the goal of this thesis. The potential links between HR analytics and HRM measurement and decision-making were also looked at. This investigation was conducted to determine whether and how HR analytics relate to the more general notion of data-driven HRM. Borckbank ( 2015)

Findings

The findings show that adoption of advanced HRA is hampered by both technological and human barriers, including the use of antiquated information systems, extremely rudimentary HR procedures, and poor data quality. This presents additional hurdles for the HR function's ability to use data analytics and fulfil its position as a business partner.Boudreau and Ramstad (2007) Other issues include a lack of analytical and business expertise, a reluctance to move beyond reporting, misunderstandings about business development, and a typical compliance-oriented HR culture. Although scepticism was frequent, HR experts saw potential usefulness in BD, while senior executives expect no significant breakthroughs in HRA. The findings suggest that in order to provide and comprehend HR-related data for business-related decision making, there is a need for more collaboration with data analysts and HR specialists. Moreover, organisational restructuring and cultural transformation can be necessary.in addition to getting over BD-related technological challenges, for it to influence HR procedures. The use of HRAs and the change in the HR function's role appear to be closely related, and they may even reinforce one another.Dahlbom, P., Siikanen, N., Sajasalo, P. and Jarvenpää, M. (2020)

Originality

he exploratory data on HRA within a sample of some of the biggest Finnish firms is provided and theorised in this study. It suggests that BD and HRA utilisation are still in their infancy and that there may be a connection between HRA and the role transition of the HR function in organisations. 

Burns and Burgress,(2012)

REFERENCES

• Beatty, R. 2015. HR analytics and metrics: scoring on the business scorecard. In Ulrich, D., Schiemann, A. & Sartain, L. eds. The rise of HR. Wisdom from 73 thought leaders. HR Certification Institute. Alexandria, VA. Ch. 285-294.

• Becker, B., Huselid, M. & Ulrich, D. 2001. The HR Scorecard: Linking people, strategy and performance, Harward Business School Press: Boston.

• Bhargava, H., Power, D. J., & Sun, D. 2007. Progress in Web-based decision support technologies. Decision Support Systems, 43: 1083–1095.

• Borckbank, W. 2015. HR´s role in a world of pervasive information. In Ulrich, D., Schiemann, A. & Sartain, L. eds. The rise of HR. Wisdom from 73 thought leaders. HR Certification Institute. Alexandria, VA. Ch. 295-302

• Boudreau, J. & Ramstad, P. 2007. Beyond HR. The new science of human capital. Harward Business School Press; Boston.

• Burns, A. & Burgress, J. 2012. Doing blog research: the computational turn. ARC Centre of Excellence for Creative Industries and Innovation. Queensland University of Technology, Australia.

• Carlson K. & Kavanagh, M. 2015. In Kavanagh, M., Thite, M. & Johnson, R. eds. Human resource information systems. Third edition. SAGE Publications: Thousand Oaks, California.

• Dahlbom, P., Siikanen, N., Sajasalo, P. and Jarvenpää, M. (2020), "Big data and HR analytics in the digital era", Baltic Journal of Management, Vol. 15 No. 1, pp. 120-138. https://doi.org/10.1108/BJM-11-2018-0393