Effective role resolution in workflow management

Dajun Zeng, J. Leon Zhao

Research output: Contribution to journalArticle

17 Scopus citations


Workflow systems provide the key technology to enable business-process automation. One important function of workflow management is role resolution, i.e., the mechanism of assigning tasks to individual workers at runtime according to the role qualification defined in the workflow model. Role-resolution decisions directly affect the productivity of workers in an organization, and consequently affect corporate profitability. Therefore it is important to develop effective policies governing these decisions. However, there has not been a formal treatment of role-resolution policies in the literature. In this paper, we analyze role-resolution policies used in current workflow practice and propose new optimization-based policies that utilize online batching. Through a computational study, we examine three workflow-performance measures including maximum flow-time, average workload, and workload variation under these policies in different business scenarios. These scenarios vary by overall system load, task-processing-time distribution, and the number of workers. Based on computational results, we obtain the following insights that can help guide the selection of role-resolution policies, (a) As the overall system load increases, the benefit of using batching-based online optimization policies becomes more significant, (b) Processing-time variation has a major impact on workflow performance, and higher variation favors optimization-based policies. (c) Online optimization has the potential to reduce average workload significantly, and to reduce workload variation significantly as well.

Original languageEnglish (US)
Pages (from-to)374-387
Number of pages14
JournalINFORMS Journal on Computing
Issue number3
Publication statusPublished - Jun 2005



  • Online batching
  • Role resolution
  • Workflow management

ASJC Scopus subject areas

  • Computer Science Applications
  • Computational Theory and Mathematics
  • Management Science and Operations Research

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