Formulating the Data-Flow Perspective for Business Process Management

Workflow technology has become a standard solution for managing increasingly complex business processes. Successful business process management depends on effective workflow modeling and analysis. One of the important aspects of workflow analysis is the data-flow perspective because, given a syntactically correct process sequence, errors can still occur during workflow execution due to incorrect data-flow specifications. However, there have been only scant treatments of the data-flow perspective in the literature and no formal methodologies are available for systematically discovering data-flow errors in a workflow model. As an indication of this research gap, existing commercial workflow management systems do not provide tools for data-flow analysis at design time. In this paper, we provide a data-flow perspective for detecting data-flow anomalies such as missing data, redundant data, and potential data conflicts. Our data-flow framework includes two basic components: data-flow specification and data-flow analysis; these components add more analytical rigor to business process management.

• 저널Information Systems Research · 17(4) · 374–391
• 토픽Business Process Modeling and Analysis · Management Information Systems
• DOI10.1287/isre.1060.0105
• 저자Sherry Sun, J. Leon Zhao, Jay F. Nunamaker, Olivia R. Liu Sheng