Lecturer: Walter Schwaiger
In this lecture the focus lies on the design of Management Control Systems (MCS) and Decision Support Systems (DSS) surrounded by an uncertain business environment predominantly by 1) considering Double Closed-Loop Management Control Systems (e.g. Balanced Scorecard), 2) using predictive analytics methods in the corporate planning, forecasting and budgeting domain (e.g. ROC-based forecasting) and in the risk management (e.g. scorecard modeling in predictive maintenance domain), and 3) applying optimization procedure in the decision supporting systems e.g. Minimum Exceedance Probability (MEP) approach in the investment decision domain and the stochastic dynamic control theory in the Sales & Operations Planning (S&OP) domain.
Objectives and competences:
In this course, students develop a deep understanding of the topics described in the syllabus. In addition, students are enabled to use this newly gained knowledge in practice. More detailed information can be found in the sections “syllabus outline” and “intended learning outcomes”.
Intended learning outcomes:
After successful completion of the course, students are able to …
· … design double-closed loop management control systems in the PDCA modelling language that is adequate for capturing uncertainty in the business environment
· … discuss advantages and disadvantages of Traditional Budgeting, Beyond Budgeting, Activity-Based Budgeting and Continuous Budgeting within a solid foundation
· … calculate Enterprise Business Cycles and corresponding Growth Cycles with the Rate-Of-Change (ROC)-forecasting approach
· … calculate accurate predictions by using the scorecard modelling approach
· … analyse more difficult systemic relationships with structural equations models
· … determine optimal investment decisions by using the Minimum Exceedance Probability-optimization… determine optimal Sales & Operations Planning (S&OP) decisions by using the stochastic control theory