Knowledge-Based Reengineering of Business Processes: Leveraging the Power of Natural Language

  • Alexander Hars


The number of business process reengineering projects in industry and the number of persons involved in such projects has risen rapidly since Hammer and Champy introduced the concept in 1993. As substantial costs are associated with reengineering projects, much effort has been concentrated in developing tools to support BPR projects. In the last three years alone, more than 50 BPR tools have been brought to market. Many of these tools are extensions of tools for Computer-Aided Software Engineering or have been modeled after CASE tools. They therefore face some of the same obstacles, such as step learning curves and acceptance problems (Summer and Ryan, 1994). As a study by Elzinga et al. (1995) showed, participants in BPR projects perceive the lack of user-friendly tools as one of the key problems for more effective BPR projects. One of the reasons for these problems is the generic nature of current tools, which typically incorporate very little knowledge about realistic business situations. In this paper, we show that it is possible to develop a new generation of BPR tools which leverage some of the knowledge contained in natural language. To prove our point, we present a prototype BPR tool which transforms a natural language description of a business process into a process diagram.


Natural Language Business Process Natural Language Processing Semantic Category Business Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Alexander Hars
    • 1
  1. 1.University of Southern CaliforniaUSA

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