HR analytics and ethics

The systematic application of analytical methods on human resources (HR)-related (big) data is referred to as HR analytics or people analytics. Typical problems in HR analytics include the estimation of churn rates, the identification of knowledge and skill in an organization, and the prediction of success on a job. HR analytics, as opposed to the simple use of key performance indicators, is a growing field of interest because of the rapid growth of volume, velocity, and variety of HR data, driven by the digitalization of work processes. Personnel files used to be in steel lockers in the past. They are now stored in company systems, along with data from hiring processes, employee satisfaction surveys, e-mails, and process data. With the growing prevalence of HR analytics, a discussion around its ethics needs to occur. The objective of this paper is to discuss the ethical implications of the application of sophisticated analytical methods to questions in HR management. This paper builds on previous literature in algorithmic fairness that focuses on technical options to identify, measure, and reduce discrimination in data analysis. This paper applies to HR analytics the ethical frameworks discussed in other fields including medicine, robotics, learning analytics, and coaching.