Automatic identification of structural process weaknesses in flow chart diagrams

Abstract

Purpose

Financial institutions have been engaged in numerous business process reengineering (BPR) projects to make their organizations more efficient. However, the success of BPR projects in banks varies significantly and it remains a challenge to systematically discover weaknesses in business process landscapes. Based on the flow chart notation language this paper seeks to argue for the definition of weakness patterns in order to automatically identify potential process weaknesses.

Design/methodology/approach

The authors developed weakness patterns in the flow chart notation language based on design science principles. To systematically derive process weaknesses that can be formalized, they analyzed each element of the flow chart notation as it was used in a real‐life case. They furthermore tested the identified patterns in reality in order to evaluate their validity.

Findings

The authors identified various potential weakness patterns that helped in automatically identifying weaknesses in process models. To some extent these findings are generalizable and transferable to other process modeling languages.

Research limitations/implications

The pattern‐based approach depends upon how well structural weakness patterns are defined and formalized. Identified problems remain “potential” weaknesses until a manual analysis reveals that the identified potential weaknesses are actually real weaknesses or not, e.g. due to law regulations.

Practical implications

Using weakness patterns allows for automatically identifying potential process weaknesses in existing flow chart models. This way, this research helps in improving the so far manual analysis of process model landscapes.

Originality/value

The approach is a new way of looking for process weaknesses through process weakness patterns.

Citation

Winkelmann, A. and Weiß, B. (2011), "Automatic identification of structural process weaknesses in flow chart diagrams", Business Process Management Journal, Vol. 17 No. 5, pp. 787-807. https://doi.org/10.1108/14637151111166187