People Management & Analytics (E)
Niveau
Master
Learning outcomes of the courses/module
The participants:
• know key concepts and application areas of people management and analytics.
• understand data structures, metrics, and analytical approaches in the HR context.
• apply statistical and analytical methods to HR-related questions.
• analyze HR data in terms of quality, informative value, and decision relevance.
• evaluate opportunities, risks, as well as ethical and legal implications of people analytics.
• develop data-driven solutions for HR-related challenges (e.g., recruiting, retention, performance).
• design and implement people analytics projects in organizations.
• know key concepts and application areas of people management and analytics.
• understand data structures, metrics, and analytical approaches in the HR context.
• apply statistical and analytical methods to HR-related questions.
• analyze HR data in terms of quality, informative value, and decision relevance.
• evaluate opportunities, risks, as well as ethical and legal implications of people analytics.
• develop data-driven solutions for HR-related challenges (e.g., recruiting, retention, performance).
• design and implement people analytics projects in organizations.
Prerequisites for the course
None
Course content
• Introduction & Foundations (people management in a data-driven context; role of people analytics; business value & decision support)
• Data in Human Resource Management (data sources; data quality; HR metrics; integration and preparation of people data)
• Methods & Models (descriptive, diagnostic, and predictive analytics; statistical foundations; causality vs. correlation)
• People Analytics Process (problem definition; hypotheses; data analysis; interpretation; implementation and scaling)
• HR Controlling & Reporting (metrics systems; dashboards; visualization; data-driven decision-making)
• Fields of Application (recruiting; talent management; retention; performance management; workforce planning)
• Organization & Implementation (project management; roles and competencies; change management; integration into HR processes)
• Culture & Leadership (data-driven organization; feedback culture; acceptance of analytics; decision-making behavior)
• Ethics, Law & Data Protection (privacy; fairness; bias; transparency; regulatory requirements)
• Advanced Analytics in HR Contexts (predictive analytics; AI applications; text and network data; use cases)
• Data in Human Resource Management (data sources; data quality; HR metrics; integration and preparation of people data)
• Methods & Models (descriptive, diagnostic, and predictive analytics; statistical foundations; causality vs. correlation)
• People Analytics Process (problem definition; hypotheses; data analysis; interpretation; implementation and scaling)
• HR Controlling & Reporting (metrics systems; dashboards; visualization; data-driven decision-making)
• Fields of Application (recruiting; talent management; retention; performance management; workforce planning)
• Organization & Implementation (project management; roles and competencies; change management; integration into HR processes)
• Culture & Leadership (data-driven organization; feedback culture; acceptance of analytics; decision-making behavior)
• Ethics, Law & Data Protection (privacy; fairness; bias; transparency; regulatory requirements)
• Advanced Analytics in HR Contexts (predictive analytics; AI applications; text and network data; use cases)
Recommended specialist literature
• Ferrar, J., & Green, D. (2021). Excellence in people analytics: How to use workforce to create business value. London, UK: Kogan Page.
• Ghatak, R. (2022). People Analytics: Data to decision. Singapore: Springer.
• Guenole, N., Ferrar, J., & Feinzig, S. (2017). Power of people: Learn how successful organization use workforce analytics to improve business performance. Upper Saddle River, NJ: Pearson.
• Loscher, G. (2021). Quick Guide People Analytics: Wie Sie das Personalmanagement verändern können. Wiesbaden: Springer.
• Reindl, C., & Krügl, S. (2023). People Analytics in der Praxis: Mit Datenanalyse zu besseren Entscheidungen im Personalmanagement. Freiburg: Haufe-Lexware.
• Ghatak, R. (2022). People Analytics: Data to decision. Singapore: Springer.
• Guenole, N., Ferrar, J., & Feinzig, S. (2017). Power of people: Learn how successful organization use workforce analytics to improve business performance. Upper Saddle River, NJ: Pearson.
• Loscher, G. (2021). Quick Guide People Analytics: Wie Sie das Personalmanagement verändern können. Wiesbaden: Springer.
• Reindl, C., & Krügl, S. (2023). People Analytics in der Praxis: Mit Datenanalyse zu besseren Entscheidungen im Personalmanagement. Freiburg: Haufe-Lexware.
Assessment methods and criteria
Exam
Presentation
Presentation
Language
English
Number of ECTS credits awarded
3
Semester hours per week
Planned teaching and learning method
The course is based on an e-learning concept that incorporates a didactically aligned combination of online and in-person phases. During the online phases, an inductive learning approach is applied, fostering the independent acquisition of knowledge and the completion of tasks. The in-person phases follow a deductive approach, in which learning processes are guided and deepened, and content is systematically delivered through lectures as well as practical examples.
Semester/trimester in which the course/module is offered
2