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    Factor reduction and clustering for operational risk in software development

    Access Status
    Fulltext not available
    Authors
    Mohd-Rahim, F.
    Wang, C.
    Boussabaine, H.
    Abdul-Rahman, H.
    Wood, Lincoln
    Date
    2014
    Type
    Journal Article
    
    Metadata
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    Citation
    Mohd-Rahim, F. and Wang, C. and Boussabaine, H. and Abdul-Rahman, H. and Wood, L. 2014. Factor reduction and clustering for operational risk in software development. The Journal of Operational Risk. 9 (3): pp. 53-88.
    Source Title
    The Journal of Operational Risk
    ISSN
    1744-6740
    School
    School of Information Systems
    URI
    http://hdl.handle.net/20.500.11937/45082
    Collection
    • Curtin Research Publications
    Abstract

    Software development failures frequently emerge as a result of the failure to understand and identify risks. The aim of this paper is to identify the most salient risk factors present during a software development project's life cycle, in terms of their occurrence likelihood and impact on cost overrun. A questionnaire was sent to 2000 software development companies, IT consultancy and management companies and web development companies in the United Kingdom, United States, mainland Europe, Canada, Australia, India, China, Japan and other Asian countries, asking respondents to evaluate a number of risk factors. Because many factors were closely related, we applied a factor reduction and clustering process to the results to allow a smaller number of crucial risk factors to be identified. The three main clusters of risk factors we identified are feasibility studies, project team management and technology requirements. While a feasibility study may be unlikely to take place, it can have a significant impact on project outcomes. In contrast, project team management is likely to occur but has a relatively small impact on outcomes in comparison with technology requirements. Professionals will need to apply checks and balances to these factors and generate risk mitigation plans to reduce the severity of project failures. Our results allow them to connect the probability of risk factor occurrence and overall impact, so they can focus their limited resources on reducing the most pertinent risks in their projects.

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