Indian Journal of Science and Technology
DOI: 10.17485/ijst/2019/v12i4/141063
Year: 2019, Volume: 12, Issue: 4, Pages: 1-7
Original Article
Mohammad Ibraigheeth* and Syed Abdullah Fadzli
Faculty of Informatics and Computing, Universiti Sultan ZainalAbidin, 21300 Kuala Terengganu, Malaysia; [email protected], [email protected]
*Author for correspondence
Mohammad Ibraigheeth
Faculty of Informatics and Computing, Universiti Sultan ZainalAbidin, 21300 Kuala Terengganu, Malaysia.
Email: [email protected]
Objectives: To identify the most common success factors through reviewing a set of software project reports and case studies. Methods/Statistical Analysis: In order to fully understand reasons behind the project success, the reasons behind project failure and the definition of failure itself are discussed. Furthermore, case studies of successful and failed software projects are described. This paper also investigates techniques that have been developed to increase software project success rate and decrease probable failures. Findings: Six common factors reported in various studies and reports are selected to construct a success factors list. Factors that affect the project success or failure are identified for each project through content reviewing and analysis. Multiple reports and sources were reviewed for some projects to assure the accurate identification. We note that each of the identified success factors is common in at least four projects of this sample, and there is no project success for single factor. The frequencies of success factors for our data which contains 236 software projects are founded. The median number of projects for each factor is 103; with minimum of 72 and maximum of 131. For the investigated projects, the better project had significantly more success factors. We note that there is no successful project had just one success factor; all projects had multiple factors that led to their success. Application/Improvements: The constructed success factors list will be used in further research to develop prediction models that can be applied early through software development process in order to avoid project failure risks.
Keywords: Project Performance, Software Project Failure, Software Project Success, Success Factors, Success Rate
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