Quality Metrics for Business Process Modelling

Adil Sylqa

Master's thesis

Abstract:

In the field of Business Informatics today more and more importance is given to business process models since it serves as a foundation for communication between the stakeholders in the software development process. In the field of software engineering, quality metrics have proven to be an industry changer in terms of good programming practices and software design. This paper shows similarities found between software applications and business process designs and stresses out the potential of quality metrics in BPM.To have a competitive edge in the process oriented approach it is necessary for these models to have very good quality metrics so we can measure and create easy to understand, unambiguous and less error prone models. The current existing metrics although measure different complexity values within a model, there is not a clear standard that captures process clarity in both visual and mathematical way. In the practical part of this thesis we define a new potential metric (Compound Complexity) that can grasp and measure in a more rounded way the different quality aspects of a business process model through the use of BPMN notation. The case study presented in this paper, shows that Compound Complexity when presented with two almost identical models, can differentiate between the less and the more complex one. The results show there are measurements that can describe a large portion of process clarity and understanding in a quantifiable metric, however there is still more empirical research that needs to be done in order to validate Compound Complexity as a sophisticated quality metric.

Keywords

Business Process Modelling, BPM, Quality Metrics, Complexity Metrics, BPMN

Language used: English

Date on which the thesis was submitted / produced: 22. 3. 2016

Thesis defence

• Supervisor: Ing. Josef Pavlíček, Ph.D.

Czech University of Life Sciences Prague

Faculty of Economics and Management

Master programme / field:
Systems Engineering and Informatics / Informatics