0683 Business Intelligence in Supply Chains 1 (BI 1)
ao.Univ.Prof. Dr. Alexander Prosser
Contact details
Weekly hours
Language of instruction
11/20/23 to 11/27/23
Registration via LPIS
Notes to the course
Day Date Time Room
Friday 12/01/23 09:00 AM - 05:00 PM TC.-1.61
Saturday 12/02/23 09:00 AM - 05:00 PM LC.-1.038
Friday 12/15/23 09:00 AM - 05:00 PM LC.2.064 PC Raum

Implementation of a CO2 (generally, greenhouse gas GHG) accounting tool. The tool used will be the SAP Footprint Manager.

Learning outcomes

Students will understand the concept of carbon footprint reporting and the underlying data management capabilities. They will understand current and already planned future requirements both in the EU and the U.S. with a particular view to auditing requirements in this field as part of “non-financial reporting”. This knowledge will come in useful in future positions managing national or transnational supply chains.

Students will learn how to research specific details in these requirements for a given supply chain and how to implement them in a product specifically designed to handle footprint management and reporting.

Students will learn how to implement their supply chain and to map it to CO2 equivalents in a specific tool and how to derive the necessary reports to meet the auditing requirements.

Students will also learn to leverage relative financial and CO2 advantages in alternative sources depending on the CO2 reporting requirements of their market.

Attendance requirements

According to the examination regulation full attendance is intended for a PI.

Teaching/learning method(s)

Students have to research specific requirements in the applicable legal base of the supply chain (U.S./EU/third country without any GHG accounting requirements), to implement their supply chain in a specific tool and to map the GHG requirements to that model and also to make optimal decisions based on the requirements of the target market.


Assessment will be based on the case studies to be implemented.


Grading scale:

(1) Excellent: 90% - 100%

(2) Good: 80% - <90%

(3) Satisfactory: 70% - <80%

(4) Sufficient: 60% - <70%

(5) Fail: <60%


Prerequisites for participation and waiting lists



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Recommended previous knowledge and skills

Availability of lecturer(s)

Last edited: 2023-07-21