After successful completion of the course, students are able to:
In this lecture the focus lies on predictive analytics and closed-loop management control systems in the forecasting and budgeting domain predominantly by 1) setting up adequate budgetary planning and control systems in an uncertain business environment and 2) by forecasting future sales volumes and corresponding ROC forecasts with the Rate-Of-Change (ROC) methodology.
The budgetary planning and control systems is a proactive double closed-loop management control system, where in the planning period annual forecasts and budgets are determined, and in the control phases over the year rolling forecasts are made, plan/forecast deviations are derived and deviation dependent corrective and adaptive actions are selected and implemented.
The ROC methodology allows the detection of a cyclical behavior in form of enterprise business cycles and their underlying growth cycles by considering seasonal changes of moving sales totals.
The forecasting accuracy is determined by regressing ROC forecasts on future stock returns.
Imagine, your are hired by a company as an assistant of the chief financial officer (CFO) with three responsibilities: 1) You assist the CFO in setting up an adequate budgetary planning and control system (Management Control System: MCS) in an uncertain business environment. 2) You are in charge of the rolling forecasting tasks where you apply the novel ROC-forecasting methodology. 3) You have to assess the predictive accuracy of ROC-based sales forecasts w.r.t. future stock returns.
In this course you acquire the needed knowledge, skills and competences for performing these tasks by discussing the key concepts according to the scholarly literature, by performing group work in break out sessions, by solving programming problems in the statistics language R and by performing a project assignment as group work.
