Summary
Large and global companies in South Korea have begun adopting HR analytics to make evidence-based decisions about people, yet frameworks and empirical evidence to guide adoption remain scarce. This chapter asks which approaches and techniques are common and important, what two illustrative cases can teach, and which organizational issues (policy, governance, culture) decide whether analytics spreads beyond a single team.
The chapter draws on the authors’ own HR analytics projects in several companies, combining elements of case study, phenomenology, literature review, and document analysis. This summary is written from the authors’ final manuscript.
We review common misunderstandings and barriers such as silos, mistrust, and data access, the problems a standalone analytics team faces, and three families of techniques: text mining, social network analysis, and machine learning. Two cases follow: developing director and team-leader competencies through text mining, and talent management through a digital learning platform. We conclude that expanding HR analytics takes careful planning by the analytics team to win collaboration and buy-in from business units, and leadership attention to policy, governance, and culture around using and sharing data.
Citation
Yoon, S. W., Chae, C., Kim, S., Lee, J., & Jo, Y. (2020). Human resource analytics in South Korea: Transforming the organization and industry. In D. H. Lim, S. W. Yoon, & D. Cho (Eds.), Human resource development in South Korea (pp. 159–180). Springer. https://doi.org/10.1007/978-3-030-54066-1_9
Citation
@online{2020,
author = {},
title = {Human Resource Analytics in {South} {Korea:} {Transforming}
the Organization and Industry},
date = {2020-10-29},
url = {https://chadchae.github.io/posts_publication/2020-10-29-hr-analytics-south-korea-chapter/hr-analytics-south-korea-chapter.html},
langid = {en}
}