The framework of talent analytics using big data
Document Type
Article
Publication Date
1-18-2022
Abstract
Purpose: 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. Design/methodology/approach: 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. Findings: 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. Practical implications: 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. Originality/value: 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.
Citation Information
Saputra, Arnold; Wang, Gunawan; Zhang, Justin Zuopeng; and Behl, Abhishek, "The framework of talent analytics using big data" (2022). UNF Faculty Research and Scholarship. 54.
https://digitalcommons.unf.edu/unf_faculty_publications/54