4873 Kurs III - Business Projekt Teil 1
Univ.Prof. Dr. Isabella Grabner, Ass.Prof. Dr. Otto Janschek
Weekly hours
Language of instruction
02/11/19 to 02/17/19
Registration via LPIS
Notes to the course
Day Date Time Room
Monday 02/25/19 09:00 AM - 01:00 PM D5.1.001
Monday 03/04/19 09:00 AM - 01:00 PM D5.1.003
Monday 03/11/19 08:00 AM - 05:00 PM Extern
Tuesday 03/12/19 08:00 AM - 02:00 PM Extern
Monday 03/18/19 09:00 AM - 01:00 PM D5.1.003
Monday 03/25/19 09:00 AM - 01:00 PM D5.1.003
Friday 03/29/19 08:00 AM - 10:00 AM D5.1.002
Monday 04/01/19 09:00 AM - 01:00 PM D5.1.003

BUSINESS PROJECT: Predictive Analytics in Corporate Planning

Predictive Analytics in Corporate Planning is a hot topic both for practitioners and academics. While some predict the demise of the financial controller as a result of increased automation and application of advanced analytical tools, the picture is far from clear once you start looking for use cases or best practices. While predictive analytics has made inroads in production, logistics and marketing departments, many finance departments are still watching from the benches. While better forecasting tools have always been of interest, implementing advanced automated procedures in their planning and forecasting process holds challenges on several levels.

Together with our project partner OMV, the leading Austrian oil and gas group, we will conduct a comparative study of firms from several industries. Crucial questions are, among others: Which KPIs do these firms use on group level and how are these predicted? Which type of forecasts (timing, period, organizational level, detailed vs. aggregate are implemented? What are the forecasts used for (adjust plans versus target setting)? How is forecast quality measured and how is the forecast improved? Which tools are used and how are they implemented (IT-departments vs. consultants vs. data scientists vs. controllers)?

Based on this comparison, we will derive recommendations for OMV. The project will be an ideal starting point for a Master or Bachelor Thesis in this field (possibly, in cooperation with our partner firm).


  • Students interested in budgeting, forecasting and predictive analytics will be part of a research-focused consulting project and learn how to do a practically relevant research study. Students will get unique real world insights into firms' planning and forecasting processes and will have the opportunity to interview finance and accounting managers in large and successful Austrian firm.
  • Students will be able to develop and train their team-working and leadership skills. According to the “IfU Business Project Approach“ which has been awarded the Austrian State Price for teaching (Ars Docendi) 2016,  five Master Students will take the role of team leaders and lead small teams of Bachelor students. The experienced challenges of leadership will be discussed in class and all students (Bachelor and Master students) will have the opportunity to get invaluable „learning by doing“ leadership experience for their future career.


Learning outcomes

After completing this class students will be able to:

  • describe and discuss applications of predictive analytics in corporate planning and forecasting
  • conduct systematic literature reviews
  • critically read and make sense of research articles
  • structure complex business problems
  • design and implement research projects


Apart from that, completing this course will contribute to students' abilities to:

  • organize and manage a large-scale project in the field of strategic management and management control
  • pursue the project management (PM) activities and master the use of various PM tools
  • structure complex and ill-defined problems
  • apply theoretical knowledge from different fields to find creative hands-on solutions to real-life business problems.
Attendance requirements

In order to successfully pass this course, your absence is limited to 20% of our appointments.

Teaching/learning method(s)
  • Coachings
  • Group discussions about research papers
  • Group assignments
  • Individual assigments
  • Practitioner feedback

The final grade of the course will depend on:

• final presentations and accompanying documentation including peer evaluation: 30%
• interim presentation I and II: 20% each
• Retz introductory presentation & discussion: 10%
• Project management objectives-reporting: 10%
• participation: 10%

Availability of lecturer(s)
The kick-off event of our project will take place in Retz (lower Austria). Participation is compulsory! More information will follow in due course.
Last edited: 2019-01-30