IS 515: Process Management & Analytics
Contents
Business processes are the structural core of every modern enterprise. In this course, we will cover the fundamentals of business process management (BPM) by introducing students to relevant concepts and methods for modelling, analysing, implementing, and controlling processes. We will put particular focus on data-driven BPM methods (process analytics). The overall course goals are that students recognize the influence of data-driven business process management on corporate success and are able to use analytical methods to discover and evaluate optimization potential for business processes. The lectures will be accompanied by exercise sessions, where the concepts and methods will be practically applied through text-based exercises, manual computations, standard process mining tools as well as light-weight programming. In addition, students will have to participate in a case study, where they will apply process mining methods in a practical business case.
Learning outcomes
Upon successful completion of this course, students will be able to:
- Design and improve business processes using suitable methods
- Analyze properties of process models and event logs
- Apply and compare the most important methods of process discovery and conformance checking
- Suggest data-based process optimizations
- Explain how business processes can be supported by information technology
Necessary prerequisites
Students may not take IS 515 if they took IS 514
Recommended prerequisites
Fundamentals of enterprise modelling (e.g., IS 401, IS 405); some knowledge in Python is helpful, but not required
| Forms of teaching and learning | Contact hours | Independent study time |
|---|---|---|
| Lecture | 2 SWS | 4 SWS |
| Exercise class | 2 SWS | 4 SWS |
| Case Study Presentation | 0 SWS | 5 SWS |
| ECTS credits | 6 |
| Graded | yes |
| Workload | 180h |
| Language | English |
| Form of assessment | Written exam (60 min, 80%), group assignment (20%) |
| Restricted admission | yes |
| Further information | Limited to 60 participants |
Examiner Performing lecturer |  | Prof. Dr. Jana-Rebecca Rehse Prof. Dr. Jana-Rebecca Rehse |
| Frequency of offering | Fall semester |
| Duration of module | 1 semester |
| Range of application | M.Sc. MMM, M.Sc. WiPäd, M.Sc. VWL, M.Sc. Wirt. Inf., MMDS |
| Preliminary course work | – |
| Program-specific Competency Goals | CG 1, CG 2 |
| Literature | Dumas, M. et al: Fundamentals of Business Process Management (2nd edition), Springer, 2018 Van der Aalst, W.: Process Mining – Data Science in Action (2nd edition), Springer, 2016 Seminal literature and additional papers will be provided during the lectures. |
| Course outline | Business Process Management Lifecycle Process Modeling Process Model Analysis Process Elicitation & Modeling Quality Process Discovery Process Mining Methodology Conformance Checking Process Enhancement Process Quality & Simulation Process Redesign Process Automation Operational Process Support |