Facilitating organisational learning through causal mapping techniques in IS/IT project risk management

  • Authors:
  • Abdullah J. Al-Shehab;Robert T. Hughes;Graham Winstanley

  • Affiliations:
  • School of Computing, Mathematical and Information Sciences, University of Brighton, Brighton, UK;School of Computing, Mathematical and Information Sciences, University of Brighton, Brighton, UK;School of Computing, Mathematical and Information Sciences, University of Brighton, Brighton, UK

  • Venue:
  • WM'05 Proceedings of the Third Biennial conference on Professional Knowledge Management
  • Year:
  • 2005

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Abstract

Information System and Information Technology (IS/IT) development and implementation have become more difficult with the rapid introduction of new technology and the increasing complexity of the marketplace. IS/IT projects often encounter a range of problems that can be described as failure. Thus, learning from an analysis of past projects and from the issues contributing to failure is becoming a major stage in the risk management process. In IS/IT projects, it is common for groups of stakeholders to participate in planning and management. One important element in these activities is risk assessment, that is, the identification of potential risks and their interrelationships throughout the project lifecycle. The ability to visualise cause and effect risk networks and the capability for interactive network building and modification have the potential for individual and group risk identification, justification and prediction. In this paper we introduce Causal Mapping as a method of accomplishing this, and describe two experiments: one carried out with a group of masters-level students and a second with practitioners from a government organization who had experienced an IS/IT project failure. These two exploratory experiments have demonstrated the potential (and also some of the problems) of the approach in identifying problem areas in past projects, through the collaborative construction of cause and effect maps that allow project participants to visualise their perceptions.