The results obtained from this talent analysis offer many opportunities in growing and advancing a company’s talents that are not yet realized.
Abhishek Behl, Assistant Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India.
Arnold Saputra, Bina Nusantara University, Jakarta Barat, Indonesia.
Gunawan Wang, Bina Nusantara University, Jakarta Barat, Indonesia.
Justin Zuopeng Zhang, University of North Florida, Jacksonville, Florida, USA.
The era of work 4.0 demands organizations to expedite their digital transformation to sustain their competitive advantage in the market. This paper aims to help the human resource (HR) department digitize and automate their analytical processes based on a big-data-analytics framework.
The methodology applied in this paper is based on a case study and experimental analysis. The research was conducted in a specific industry and focused on solving talent analysis problems.
This research conducts digital talent analysis using data mining tools with big data. The talent analysis based on the proposed framework for developing and transforming the HR department is readily implementable. The results obtained from this talent analysis using the big-data-analytics framework offer many opportunities in growing and advancing a company’s talents that are not yet realized.
Big data allows HR to perform analysis and predictions, making more intelligent and accurate decisions. The application of big data analytics in an HR department has a significant impact on talent management.
This research contributes to the literature by proposing a formal big-data-analytics framework for HR and demonstrating its applicability with real-world case analysis. The findings help organizations develop a talent analytics function to solve future leaders’ business challenges.
Published in: The TQM Journal
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