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A Frequency-Based Algorithm for Workflow Outlier Mining

  • Yu-Cheng Chuang
  • PingYu Hsu
  • MinTzu Wang
  • Sin-Cheng Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6485)

Abstract

The concept of workflow is critical in the ERP (Enterprise Resources Planning) system. Any workflow that is irrationally and irregularly designed will not only lead to an ineffective operation of enterprise but also limit the implementation of an effective business strategy. The research proposes an algorithm which makes use of the workflow’s executed frequency, the concept of distance-based outlier detection, empirical rules and Method of Exhaustion to mine three types of workflow outliers, including less-occurring workflow outliers of each process (abnormal workflow of each process), less-occurring workflow outliers of all processes (abnormal workflow of all processes) and never-occurring workflow outliers (redundant workflow). In addition, this research adopts real data to evaluate workflow mining feasibility. In terms of the management, it will assist managers and consultants in (1) controlling exceptions in the process of enterprise auditing, and (2) simplifying the business process management by the integration of relevant processes.

Keywords

ERP BPM Workflow mining Data mining Outlier detection 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Yu-Cheng Chuang
    • 1
  • PingYu Hsu
    • 1
  • MinTzu Wang
    • 2
  • Sin-Cheng Chen
    • 1
  1. 1.Department of Business AdministrationNational Central UniversityTaiwan
  2. 2.Department of Information ManagementTechnology and Science Institute of Northern TaiwanTaiwan

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