Galorath Article “applying Earned Value Management To Software Intensive Programs Part 1
The new Galorath paper on performance based earned value went live on the DACS site today. It is so important to have viable estimates as the basis of plans for earned value to be valuable. For paper with figures see Applying Earned Value Management To Software Intensive Programs Final The paper’s introduction follows:
By Robert P Hunt (Galorath Incorporated), Paul J. Solomon (Performance-Based Earned Value), and Dan Galorath (Galorath Incorporated)
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Often, traditional earned value approaches do not deal sufficiently with the idiosyncrasies of software intensive programs. However, successful management of software intensive programs can be achieved by focusing on establishing the requirements, developing a reliable baseline estimate for cost and schedule, selecting effective software metrics, applying Performance-Based Earned Value® (PBEV), and using analytic processes to project cost and schedule based on actual performance.
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Introduction
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The Department of Defense estimates that software now accounts for 40% of all research, development, test and evaluation (RDT&E) spending[1]. Software intensive projects that achieve their original cost and schedule projections are rare. Many information technology projects have been declared a disaster area by commercial and government managers. These projects have been too costly, too late, and often don’t work right. Applying appropriate technical and management techniques can significantly improve the current situation.
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Inaccurate estimates can threaten project success causing poor project implementations, the shortcutting critical processes, and emergency staffing to recover schedule.   The lack of well defined project requirement and specifications may result in significant growth in cost and schedule.  Symptoms of this growth may include constantly changing project goals, frustration, customer dissatisfaction, cost overruns, missed schedules, and the failure of a project to meet its objectives.
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PMI published an analysis of several government defense and intelligence agency large-scale acquisition programs that experienced significant cost and schedule growth. This analysis shows that several critical factors need to be addressed in the pre-acquisition phase of the acquisition cycle. The principal causes of growth on these large-scale programs can be traced to several causes related to overzealous advocacy, immature technology, lack of corporate technology roadmaps, requirements instability, ineffective acquisition strategy, unrealistic program baselines, inadequate systems engineering, and work-force issues.[2]
This paper will discuss some key element associated with:
- Establishing a process for requirements definition and developing the cost and schedule baseline
- Developing a reliable cost and schedule baseline,
- Identifying critical software management metrics,
- Applying Performance-Based Earned Value (PBEV), and
- Using an analytic process (such as SEER Control; formerly called Parametric Project Monitoring and Control (PPMC)) to project cost and schedule based on actual performance.
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[1]Page 134, Trillions For Military Technology; John A.Alic, Palgrave MacMillian, 2007
[2]PMI Project Management Journal, March 2008; “Best Project Management and Systems Engineering Practices in the Preacquisition Phase for Federal Intelligence and Defense Agencies” by Steven R. Meier
This article was originally published in the Software Tech News, Volume 12, No. 1, April 2009. Â The web site for more information about this publication is www.softwaretechnews.com
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
Related posts:
- Galorath Article “Applying Earned Value Management To Software Intensive Programs Part 2
- Applying Earned Value Management to Software Intensive Programs Part 4
- Applying Earned Value Management to Software Intensive Programs Part 3
- Performance Based Earned Value
- Improving Earned Value With Statistics
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