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Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE)

Technical Report
The method of quantifying uncertainty 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.
Publisher

Software Engineering Institute

CMU/SEI Report Number
CMU/SEI-2011-TR-026
DOI (Digital Object Identifier)
10.1184/R1/6582698.v1

Abstract

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.

Part of a Collection

2017 SEI Year in Review Resources

Cite This Technical Report

Ferguson, R., Goldenson, D., McCurley, J., Stoddard, R., Zubrow, D., & Anderson, D. (2011, December 1). Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE). (Technical Report CMU/SEI-2011-TR-026). Retrieved May 26, 2024, from https://doi.org/10.1184/R1/6582698.v1.

@techreport{ferguson_2011,
author={Ferguson, Robert and Goldenson, Dennis and McCurley, Jim and Stoddard, Robert and Zubrow, David and Anderson, Debra},
title={Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE)},
month={Dec},
year={2011},
number={CMU/SEI-2011-TR-026},
howpublished={Carnegie Mellon University, Software Engineering Institute's Digital Library},
url={https://doi.org/10.1184/R1/6582698.v1},
note={Accessed: 2024-May-26}
}

Ferguson, Robert, Dennis Goldenson, Jim McCurley, Robert Stoddard, David Zubrow, and Debra Anderson. "Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE)." (CMU/SEI-2011-TR-026). Carnegie Mellon University, Software Engineering Institute's Digital Library. Software Engineering Institute, December 1, 2011. https://doi.org/10.1184/R1/6582698.v1.

R. Ferguson, D. Goldenson, J. McCurley, R. Stoddard, D. Zubrow, and D. Anderson, "Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE)," Carnegie Mellon University, Software Engineering Institute's Digital Library. Software Engineering Institute, Technical Report CMU/SEI-2011-TR-026, 1-Dec-2011 [Online]. Available: https://doi.org/10.1184/R1/6582698.v1. [Accessed: 26-May-2024].

Ferguson, Robert, Dennis Goldenson, Jim McCurley, Robert Stoddard, David Zubrow, and Debra Anderson. "Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE)." (Technical Report CMU/SEI-2011-TR-026). Carnegie Mellon University, Software Engineering Institute's Digital Library, Software Engineering Institute, 1 Dec. 2011. https://doi.org/10.1184/R1/6582698.v1. Accessed 26 May. 2024.

Ferguson, Robert; Goldenson, Dennis; McCurley, Jim; Stoddard, Robert; Zubrow, David; & Anderson, Debra. Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE). CMU/SEI-2011-TR-026. Software Engineering Institute. 2011. https://doi.org/10.1184/R1/6582698.v1