This thesis demonstrates the performance analysis and optimization of SAP’s Integrated Business Planning solution. SAP IBP is powered by SAP HANA in-memory technology. This supply chain planning solution combines capabilities for sales and operations, demand, response, supply planning, and inventory optimization.
There are many different customers with different data sets and unique planning models, so it is quite a challenge to fit every customer’s requirement. In this thesis, I will present the methods used to analyze and improve the performance of SAP IBP.
I have tried many performance measurement tools (SAT, STAD, SUPA, Load Runner, ARIES, Fiddler, EPM) during the writing of this thesis. I present the usage of these tools on sample measurements, to show what they are capable of. Usability wise, the automated methods turned out to be the best, the manual measurements were only useable while verifying unusual results.
The thesis reveals that the automated performance measurement program I developed is the most optimal solution out of all the tools.
Overall five performance measurement programs were made, which measure the IBP Excel add-in’s response time in certain areas, by calling the backend’s services. The test data for the measurements comes from a separated package called Test Data Containers.