Data Science in HR

Data Science in HR can be defined as the data-driven and goal-oriented method of examining employee processes, challenges, engagement, performance, turnover, as well as ways to derive actions in the HR context. Data Science in HR is sometimes referred to as People Analytics or Workforce Analytics.

Essentially, Data Science in HR leads to better decision making through the application of statistical methods and other data interpretation techniques. Therefore, Data Science in HR can also be defined as an approach to using statistical insights from employee data to make evidence-based HR management decisions. With Data Science in HR, smarter, more strategic, and data-driven employee decisions are more tangible, and this applies to the entire employee lifecycle – from making better hiring decisions to managing performance more effectively to improving employee retention.

In the research work of the chair, procedures for the analysis of HR issues by statistical methods are developed as well as corresponding analysis projects are carried out in cooperation with companies. The focus is also on the question of how Data Science in HR can contribute to a more discrimination-free work in HR management.

In the research project ADVICE, funded by the Volkswagen Foundation, the findings from the HR context are transferred to the student life cycle and investigated which data-driven procedures and statistical analysis can be used for student counseling.

The basic procedures and theories of data management and analysis are the subject of the bachelor lecture “Data Management and Analytics“. A contextualization of statistical data analysis in relation to HRM issues takes place in the lecture “People Analytics”.



Selected publications

Selected talks