HR 애널리틱스 개념적 틀 제안
A Conceptual Framework for HR Analytics
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초록
HR 분야에서 HR 애널리틱스의 중요성은 날이 갈수록 부각되고 있다. HRA는 기존 HR 실무와 학문 체계의 한계점을 보완하는 접근방식이며, 최근 컴퓨터 연산능력의 비약적 발전으로 빅데이터 처리 기술이 활발하게 도입되면서, HRA 적용 역시 가속화되고 있다. HRA는 실무 현장과 학계에서 주목받고 있는 개념임에 틀림없으나, 학문적으로 독자적인 제 위상을 갖지 못하고 있다는 다수 선행 연구의 지적이 존재한다. 이에 이 연구에서는 HRA라는 현상을 담아낼 수 있는 개념적 틀을 개발하고자 하였으며, HRA 개념적 틀은 어떻게 설계될 수 있는가? HRA 개념적 틀에 따라 국내외 선행연구 사례를 분류, 요약할 수 있는가? 등을 연구문제로 삼았다. 연구결과, 선행연구들이 HRA를 절차, 통계, 시스템 관점으로 해석하고 있음을 확인하고, 이를 종합하여 HRA 개념적 틀을 구안하였다. 구안된 HRA 개념적 틀은 HR 관행과 애널리틱스 투입, 절차, 산출의 합성으로 표현할 수 있었다. 개념적 틀의 실무적인 세분화 예시로써 투입되는 데이터는 속성 및 관계적 데이터, 개인, 양자, 집단 및 조직 데이터, 횡단 및 종단적 데이터로 구성되고, 통계 분석 개념의 절차는 기술적, 진단적, 예측적 및 처방적 분석과 개별 통계분석기법으로 구성되며, 활용 개념의 산출은 설명, 예측, 분류, 탐지, 추천 등으로 구성할 수 있었다. 또한, 이렇게 개발된 개념적 틀을 렌즈로 삼아 국내외 선행 연구 사례를 분류하고 고찰하였다. 마지막으로 연구의 과정에서 얻은 통찰과 한계점을 바탕으로 HRD 실무자와 향후 연구자에게 제언하였다.
Abstract
The value of analytics in the HR area is growing all the time. HRA is a method of supplementing existing HR practices and academic systems, and its use is growing in tandem with the trend of adopting big data processing technology as a result of the rapid advancement of computing power. HRA is clearly a trendy topic in the field and in academia, however a lot of earlier research has pointed out that it does not have an independent academic status. So, this research attempted to establish a conceptual framework that can capture the phenomenon of HRA, as well as how to design an HRA conceptual framework. The central question of this paper was "Can you use...research cases?" As a consequence of the research, it was proven that earlier studies had classified HRA based on procedures, statistics, and systems, and that a conceptual framework for HRA had been developed by combining them. Analytics data input consists of attribute and relational data, individual, dyad, group and organizational data, and cross-sectional and longitudinal data, and the statistical analysis concept's procedure consists of descriptive, diagnostic, predictive, and prescriptive analytics, as well as each statistical analysis techniques, and the usage concepts consists of explanation, prediction, classification, detection, and recommendation. previous study cases were also classified and analyzed utilizing the developed conceptual framework as a lens. Finally, suggestions were offered to HRD practitioners and researchers based on the insights and limits of this study.
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