Objective decision support tools for IT project managers
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Date
2015-09-04
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Towson University. Department of Computer and Information Sciences
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There are no restrictions on access to this document. An internet release form signed by the author to display this document online is on file with Towson University Special Collections and Archives.
There are no restrictions on access to this document. An internet release form signed by the author to display this document online is on file with Towson University Special Collections and Archives.
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Abstract
The definition of a project is a temporary endeavor undertaken to create a unique product, service, or result. In terms of the Information Technology industry, projects are generally aimed at developing or acquiring new or modified information systems hardware or software, or both. The literature claims that less than half of all IT projects are completed successfully. The Project Management Body of Knowledge (PMBOK) published by the Project Management Institute indicates that the "planning" process group accounts for approximately 48% of all project management processes. The literature reveals that a major reason that IT projects fail or are cancelled is that they frequently go over schedule. Thus, schedule estimation is vital to the planning process; but it is well known that project uncertainty is typically very high in the early stages of a project, which is where accurate planning is particularly crucial. Additionally, analysis of the PMBOK shows that the highly subjective "expert judgment" technique is relied on much more than other tools and techniques, perhaps adding to the uncertainly and inaccuracy in the early project stages. This research focuses on proposing objective tools and techniques to increase certainty and accuracy in the early project stages, concentrating on the primary research question "Can project determination and time / schedule estimation be improved by using objective tools and techniques?". This question is answered by attacking three sub-questions in three separate steps. In the first step, a framework is proposed for estimating an objective project schedule in the proposal preparation stage, and its effectiveness is demonstrated on an example project scenario. Function point analysis, probability, and project management techniques are used to reduce project risk by taking into account the uncertainty associated with project schedule estimation in this very early project stage. The second step uses the above framework to address the issue of refining / verifying the previous schedule when the project reaches the planning stage. With the availability of design documents at this stage, additional detail is available to allow the function point analysis to be done with the more accurate Adjusted Function Point (AFP) count as opposed to the Unadjusted Function Point (UFP) used in the first step. The example project scenario from the first step is carried forward and extended to illustrate the usage of the framework in this step. The final step develops a methodology using a decision tree-based framework to provide an objective technique for the early-stage comparison of software development project types. The process utilizes cost estimation based on the probabilistic project schedule from the previous newly-developed framework, expected monetary value, possibilistic success rate, and the decision tree approach to introduce more objectivity into deciding, during the early project stages, which software development type should be used. The methodology is illustrated by example, and one notable result is that the software development type selected using the project management viewpoint (relying on expected monetary value) may not be the one that would be selected from the typical business management point of view (governed by net present value).