HRD Professionals' Experience Utilizing Data Analytics in the Training Evaluation Process
In the past, Human Research Development (HRD) professionals have faced barriers of gaining access to the data they need to conduct higher level evaluations. However, recent technological innovations have presented opportunities for them to obtain this data, and consequently, apply new approaches for the training evaluation process. One approach being used is the application of data analytics. Because organizations have begun to embrace its use, recent research activities in the literature have focused on the promotion of analytics versus the practical application of analytics in the organization. This study investigated how HRD professionals utilize data analytics in the training evaluation process. It contributes to the body of research on the practical application of analytics in determining training effectiveness. The Unified Theory of Acceptance and Use of Technology (UTAUT) and Sociomateriality served as the theoretical framework for understanding how HRD professionals use data analytics in the training evaluation process. To address the research objective, a qualitative descriptive design was employed to investigate the phenomenon of lived experience, how HRD professionals use data analytics in the training evaluation process. Data were collected through semi-structured interviews with six (6) participants who were front and center in the organization’s transition to the analytics tool, Metrics That Matter (MTM), for evaluating training initiatives. The thematic analysis approach was applied. The study findings suggest three factors that influenced HR professionals to use human resource analytics, while revealing four ways they used those analytics in the training evaluation process. More importantly, findings from this study will provide training departments and HRD professionals recommendations for expanded job role and/or function descriptions, as well as best practices for incorporating data analytics in the training evaluation process.