Meta Modeling for Business Process Improvement

Conducting business process improvement (BPI) initiatives is a topic of high priority for today’s companies. However, performing BPI projects has become challenging. This is due to rapidly changing customer requirements and an increase of inter-organizational business processes, which need to be considered from an end-to-end perspective. In addition, traditional BPI approaches are more and more perceived as overly complex and too resource-consuming in practice. Against this background, the paper proposes a BPI roadmap, which is an approach for systematically performing BPI projects and serves practitioners’ needs for manageable BPI methods. Based on this BPI roadmap, a domain-specific conceptual modeling method (DSMM) has been developed. The DSMM supports the efficient documentation and communication of the results that emerge during the application of the roadmap. Thus, conceptual modeling acts as a means for purposefully codifying the outcomes of a BPI project. Furthermore, a corresponding software prototype has been implemented using a meta modeling platform to assess the technical feasibility of the approach. Finally, the usability of the prototype has been empirically evaluated

Pattern-Based Semi-Automatic Analysis of Weaknesses in Semantic Business Process Models in the Banking Sector

As banks have realized the need to look on their business in a process-oriented way, they have been engaged in numerous business process optimization or even reengineering (BPR) projects in the last decade 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. In particular, automatic semantic analysis of business processes for different types of weaknesses (i.e. media breaks, redundant consistency checks, or missing or inconsistent information) is yet in its infancy. Value from business process modeling can, however, only be unveiled when time-consuming, mostly manual business process analysis is performed and results in business process optimization. In this paper we develop a methodology for semi-automatic analysis and detection of weaknesses in semantically analyzable business process models. We argue that this contributes to systematically identify possible weaknesses in process models more efficiently and more effectively than manual analysis