Abstract
Analysis techniques based on statistical distributions can provide predictive metrics from historically observed trends in a program’s performance. The Rayleigh distribution is a continuous probability distribution that has been historically demonstrated to accurately model large-scale research and development and software development projects. This distribution is the basis of the Rayleigh model, whose shape works particularly well for forecasting software development projects because it can account for the slow ramp-up, peak spending as complexity increases, and a gradual tail-off toward completion. The Rayleigh model relies on accurate and consistent cost and schedule data to fit the distribution, but, because the model is used to fit data that are already collected through traditional project management techniques, there is relatively low additional effort required to realize program benefits, such as early warning of cost overruns and schedule slip. In this study, the predictive ability of the Rayleigh model in evaluating the spending profiles of civil agency IT development programs were evaluated. Using software developed previously by CNA, one completed and one ongoing IT program were analyzed using the Rayleigh model. The predictive ability of the Rayleigh model to estimate final program cost was compared to that of traditional earned value management system (EVMS) methods, with the former found to show earlier and consistent, but more exaggerated, warning indications of cost and schedule slippage. Overall, the Rayleigh model has potential to provide added value to IT program management, especially toward the beginning of a project, when used alongside traditional EVMS metrics.
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Abbreviations
- α :
-
Time parameter
- C(t):
-
Cumulative cost
- D :
-
Cost parameter
- e :
-
Napier’s constant
- t :
-
Time
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Acknowledgment
The authors would like to thank Julianne Nelson, Ph.D., for providing background information on the use and implementation of the XCASA tool to generate Rayleigh models for the analysis as well as Maryann Shane, Ph.D., for providing additional review of the paper.
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Yang, R. et al. (2019). Application of the Rayleigh Model to Predict Information Technology Program Cost and Schedule Performance. In: Adams, S., Beling, P., Lambert, J., Scherer, W., Fleming, C. (eds) Systems Engineering in Context. Springer, Cham. https://doi.org/10.1007/978-3-030-00114-8_15
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DOI: https://doi.org/10.1007/978-3-030-00114-8_15
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