Organizations continually seek to leverage new and innovative ways to increase the likelihood of software project success. The meaning of project success varies widely across literature, yet most definitions declare a project successful if it delivers within budget, on time, with acceptable quality, and meets overall stakeholder objectives. Mature enterprises define project-specific success criteria based on organizational needs and have increasingly been leveraging Agile or lightweight development methodologies over traditional heavyweight methods, such as waterfall, to increase their rate of software project success. Selecting development methodologies to drive project success is largely heuristic, and there is no standard set of criteria nor rulesets available for project managers to readily apply to facilitate those decisions. This research paper summarizes the vast findings in the literature regarding software project success characterization for Agile and traditional projects and offers a framework to measure, assess, and predict the likelihood of meeting project success criteria based on user-defined project factors and success criteria. Data on software project factors and outcomes from the International Software Benchmarking Standards Group is analyzed to determine the statistical influence of known Agile critical success factors on the budget, time, quality, and stakeholder goal dimensions of project success, resulting in a prediction model and decision framework. The proposed Agile Success Estimation Framework for Software Projects addresses the lack of integrated Agile suitability and estimation tools to assist project managers and organizations in making informed decisions on the selection of Agile over other methodologies.
|Advisor:||Grenn, Michael, Etemadi, Amir|
|School:||The George Washington University|
|School Location:||United States -- District of Columbia|
|Source:||DAI-A 81/2(E), Dissertation Abstracts International|
|Subjects:||Engineering, Information Technology, Management|
|Keywords:||Agile, Development methodology, Predictive model, Project management, Project success, Software|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be