The purpose of this paper is to examine the evolution of the concept of human resource analytics (HRA) and propose an operational framework demonstrating the sources generating data for HRA, as well as the impact of HRA on multiple levels in the organization.
A review of literature was conducted to present the existing body of knowledge and build upon for the development of an operational framework for successful implementation of HRA as a human resources (HR) process.
Building upon the existing literature, this paper presents an operational HRA framework, positioning HRA as an analytical process through integrating advanced statistical methodology. HRA presents a tool to obtain evidence-based analytical results for improving people-related performance, operational effectiveness, and ultimately the impact of the business strategy. By using HR big data, HRA impacts multiple organizational levels, from individual employees to HR functions and the organizational strategy.
While research on data analytics has recently flourished across various management fields, this has not been the case for the broader field of HR. This is especially a growing concern as the lack of understanding of the basics and fundamentals of people analytics in the field of HR may delay the effective implementation and operationalization of HRA and present additional barriers impacting on-going HR activities, as well as HR’s role as a strategic business partner. HR practice may greatly benefit from gaining an understanding of HRA and the multi-levels of impact it may have on the organization.
This paper explores various concepts related to HRA by examining terms such as “HR metrics” vs “HR” and “HR big data” vs “big data.” Furthermore, the comprehensive HRA operational framework presented in this paper provides HR professionals and researchers with a better understanding of HRA in the age of data analytics and artificial intelligence.
