Formulating the data-flow perspective for business process management

Sherry X. Sun, J. Leon Zhao, Jay F. Nunamaker, Olivia R.Liu Sheng

Research output: Contribution to journalArticlepeer-review

164 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)374-391
Number of pages18
JournalInformation Systems Research
Issue number4
StatePublished - Dec 2006


  • Data-flow anomalies
  • Data-flow specification
  • Data-flow verification
  • Dependency analysis
  • Process data diagram
  • Workflow modeling

ASJC Scopus subject areas

  • Management Information Systems
  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Library and Information Sciences


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