IS 515: Process Management & Analytics

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 learningContact hoursIndependent study time
Lecture2 SWS4 SWS
Exercise class2 SWS4 SWS
Case Study Presentation0 SWS5 SWS
ECTS credits6
Graded yes
Form of assessmentWritten exam (60 min, 80%), group assignment (20%)
Restricted admissionyes
Further informationLimited to 60 participants
Performing lecturer
Prof. Dr. Jana-Rebecca Rehse
Prof. Dr. Jana-Rebecca Rehse
Frequency of offeringFall semester
Duration of module 1 semester
Range of applicationM.Sc. MMM, M.Sc. WiPäd, M.Sc. VWL, M.Sc. Wirt. Inf., MMDS
Preliminary course work
Program-specific Competency GoalsCG 1, CG 2
LiteratureDumas, 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 outlineBusiness 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