Research Projekt "Business Value of Business Intelligence"

The competence center in Data Science & Business Analytics carries out the research project “Business Value of Business Intelligence” in cooperation with SAP Germany and the University of the Western Cape (UWC) in South Africa. Business Intelligence comprises methods, processes and systems for the collection, preparation and analysis of data. From this data, information and knowledge are derived to support the strategic and operative decision making as well as support the targeted use of resources.

To make the use of Business Intelligence for companies more transparent and to optimize the deployment of the BI solution is the overall target of the research project.

In daily business, the deployment of BI is often missing the orientation on the company processes. Therefore, the use and support through BI technologies is impalpable. This fact points out the need for a reference process model which helps to measure the interactions between Business Intelligence and company success. The project is based on the hypothesis, that the business value of BI can be measured in application reference to the Corporate Performance Management processes. CPM is a holistic management concept for performance measurement and control of companies. Just after connecting CPM with BI, a higher business value can be achieved.

The research project is carried out with the University of the Western Cape to facilitate intercultural collaboration and comparison. Furthermore, the collaboration with SAP Germany enables a high practical relation.


First, a connectional framework has been developed as a basis for the project. The framework is a holistic reference process model for Corporate Performance Management. The model depicts transparently the Corporate Performance Management processes over all company regarding Levels, from the company environment to the transactional business processes.

Second, a total of 7 Critical Success Factors of Business Intelligence and Corporate Performance Management have been elaborated. In a Germany wide study, the exact interrelationships have been analyzed and direct relationships identified (see figure).

Based on the research results, a BI assessment as well as a CPM assessment have been developed. To start, with the CPM assessment the current development of the company management is evaluated and needs for action are identified. Afterwards, the current development of BI is evaluated. This is based on the statistically proven model and enables focusing on the BI areas which actually help to improve the specific previously identified potentials of development in CPM. Therefore, it is not necessary to analyze the whole BI landscape to improve a specific CPM area. The measures for improvement can focus on the specific BI areas which actually help to improve specific CPM areas. Afterwards, recommended actions are deviated describing how a targeted implementation and improvement of Business Intelligence can support the success of the company management.


  • K. Hartl and O. Jacob, „Using Data Mining Techniques for Information System Research Purposes - An Examplary Application in the Field of Business Intelligence and Corporate Performance Management Research”, NextTech Conference Proceedings, Venice, 2016.
  • K. Hartl and O. Jacob, „The Role of Data Quality in Business Intelligence - An empirical study in German medium-sized and large companies”, 21st International Conference on Data Quality (ICIQ), 2016, Article 4.
  • K. Hartl, O. Jacob, F.H. Lien, A. Budree and L. Fourie, „The Impact of Business Intelligenc on Corporate Performance Management”, 49th Hawaii International Conference on System Sciences, 2016, 5041-5051.
  • K. Hartl and O. Jacob, „Determing the Business Value of Business Intelligence with Data Mining Methods”, NextTech Conference Proceedings, Nice, 2015, 87-91.
  • F.H. Lien Mbep, O. Jacob and L. Fourie, „The Impact of Business Intelligence on Corporate Performance Management”, BUSTECH Conference Proceedings, 2015, pp. 6-14. 
  • O. Jacob und F.H. Lien, „Ganzheitliches Referenzprozessmodell für das Corporate Performance Management”, HNU Working Paper, Nr. 23, 2012.


Karin Hartl View Profile

Research Assistant / Centre for Data Sciene and Business Analytics

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