Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE)
Difficulties with estimating the costs of developing new systems have been well documented, and are compounded by the fact that estimates are now prepared much earlier in the acquisition lifecycle, before there is concrete technical information available on the particular program to be developed. This report describes an innovative synthesis of analytical techniques into a cost estimation method that models and quantifies the uncertainties associated with early lifecycle cost estimation.
The method described in this report synthesizes scenario building, Bayesian Belief Network (BBN) modeling and Monte Carlo simulation into an estimation method that quantifies uncertainties, allows subjective inputs, visually depicts influential relationships among program change drivers and outputs, and assists with the explicit description and documentation underlying an estimate. It uses scenario analysis and design structure matrix (DSM) techniques to limit the combinatorial effects of multiple interacting program change drivers to make modeling and analysis more tractable. Representing scenarios as BBNs enables sensitivity analysis, exploration of scenarios, and quantification of uncertainty. The methods link to existing cost estimation methods and tools to leverage their cost estimation relationships and calibration. As a result, cost estimates are embedded within clearly defined confidence intervals and explicitly associated with specific program scenarios or alternate futures.
This report is related to the following area(s) of work:
Measurement and AnalysisTechnical Report
CMU/SEI-2011-TR-026
December 2011
Cite This Report
SEI:
Ferguson, Robert; Goldenson, Dennis; McCurley, James; Stoddard, Robert; Zubrow, David; & Anderson, Debra. Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE) (CMU/SEI-2011-TR-026). Software Engineering Institute, Carnegie Mellon University, 2011. http://www.sei.cmu.edu/library/abstracts/reports/11tr026.cfm
IEEE:
R. Ferguson, D. Goldenson, J. McCurley, R. Stoddard, D. Zubrow, and D. Anderson, "Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE)," Software Engineering Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, Technical Report CMU/SEI-2011-TR-026, 2011. http://www.sei.cmu.edu/library/abstracts/reports/11tr026.cfm
APA:
Ferguson, R., Goldenson, D., McCurley, J., Stoddard, R., Zubrow, D., & Anderson, D. (2011). Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE) (CMU/SEI-2011-TR-026). Retrieved May 25, 2013, from the Software Engineering Institute, Carnegie Mellon University website: http://www.sei.cmu.edu/library/abstracts/reports/11tr026.cfm
CHI:
Ferguson, Robert, Dennis Goldenson, James McCurley, Robert Stoddard, David Zubrow, and Debra Anderson. Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE) (CMU/SEI-2011-TR-026). Pittsburgh, PA: Software Engineering Institute, Carnegie Mellon University, 2011. http://www.sei.cmu.edu/library/abstracts/reports/11tr026.cfm
MLA:
Ferguson, R., Goldenson, D., McCurley, J., Stoddard, R., Zubrow, D., & Anderson, D. 2011. Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE) (Technical Report CMU/SEI-2011-TR-026). Pittsburgh: Software Engineering Institute, Carnegie Mellon University. http://www.sei.cmu.edu/library/abstracts/reports/11tr026.cfm
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