Group data modeling support for business process reengineering.

Abstract

In the aggressive business environment of today, organizations are being forced to explore new opportunities for creating a competitive advantage. The call is going out for organizations to reengineer themselves and to become more lean. Information systems/technology is a critical enabler in the reengineering process. To fully take advantage of this technology, an organization must develop an accurate enterprise-wide data model. Data modeling is a challenging, complex task which requires a vast knowledge of an enterprise and a tremendous amount of effort to complete. This dissertation explores the development of a systems prototype to support the data modeling process in a group environment. Background literature is presented from many sources addressing the systems development process, different approaches to data modeling, strategies for involving users (subject matter experts) in the development process, and concepts relating to business process reengineering. The systems development research approach is applied to the domain. A prototype system is developed, based on the IDEF1X data modeling methodology, and tested in an Electronic Meeting Systems (EMS) environment. EMS provide an environment in which meetings are more effective by introducing structure and technology into the meeting process. The prototype system allows multiple participants to contribute to the modeling process in parallel. GroupSystems for Windows, from Ventana Corporation, is also used in the modeling activity. Additionally, the prototype provides a means to export data into an IDEF1X CASE tool for further analysis and development. The research blends methodology, techniques, and tools to assist subject matter experts in data model development in support of business process reengineering efforts. Research contributions include a prototype system for developing data models in a group setting that can be further enhanced and evaluated, insights into the prototype and evaluation process, and new knowledge of the group dynamics of developing data models with large groups of subject matter experts. Based on the perceptions and feedback from participants and systems analysts involved in the evaluation and testing of the prototype and the methods to support the modeling effort, the use of an EMS environment for data modeling results in shorter development times and more robust data models.