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    Investigating critical success factors in agile systems development projects

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    Date
    2012
    Author
    Wagener, Ruhan Pieter
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    Abstract
    This study investigates the critical success factors involved in agile systems development projects. Various systems development methodologies and project management methodologies are presented with their underlying principles, strengths and weaknesses. Thereafter the critical success factors adopted from the work of Chow and Cao (2007) are presented. A positivistic research paradigm was chosen for data collection and analysis. The survey method was chosen for data collection. A questionnaire was sent to multiple respondents in a predominantly agile work environment, which resulted in a total of 129 respondents in various business sectors. The results were analysed by implementing multiple correlation and regression statistics as well as descriptive statistics. The results show that there are in fact 16 critical success factors that have a direct impact on the success of agile systems development projects. Agile systems development methodologies have been increasing in use during the last 3 years, and most organisations are implementing some form of project management methodology. The first recommendation is based on the findings that strong customer involvement and the appropriate management of the agile process with a satisfactory amount of documentation resulted in greater process success. Therefore, organisations should encourage these critical success factors when implementing an ASDM as this has a positive effect on the project outcome. The appropriate management of the agile process with a satisfactory amount of documentation, the application of good design practices and technical knowledge to a project, and a cooperative organizational culture instead of hierarchical are three of the key critical success factors that were positively related to the success of the product. By focussing on these critical success factors, the success of the entire project can be predicted.
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    http://hdl.handle.net/10394/9251
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    • Natural and Agricultural Sciences [2778]

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