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Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE)

  • Author(s): Robert Ferguson, Dennis Goldenson, James McCurley, Robert W. Stoddard, David Zubrow, Debra Anderson
  • Publish Date:
  • Publisher: Software Engineering Institute
  • SEI Identifier: CMU/SEI-2011-TR-026
  • Type: Technical Report
  • Topics: Measurement and Analysis
  • Description: 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.

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.

Cite This Report

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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://resources.sei.cmu.edu/library/asset-view.cfm?AssetID=10039

IEEE

Ferguson. Robert, Goldenson. Dennis, McCurley. James, Stoddard. Robert, Zubrow. David, and Anderson. Debra, "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://resources.sei.cmu.edu/library/asset-view.cfm?AssetID=10039

APA

Ferguson, Robert., Goldenson, Dennis., McCurley, James., Stoddard, Robert., Zubrow, David., & Anderson, Debra. (2011). Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE) (CMU/SEI-2011-TR-026). Retrieved November 22, 2014, from the Software Engineering Institute, Carnegie Mellon University website: http://resources.sei.cmu.edu/library/asset-view.cfm?AssetID=10039

CHI

Robert Ferguson, Dennis Goldenson, James McCurley, Robert Stoddard, David Zubrow, & 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://resources.sei.cmu.edu/library/asset-view.cfm?AssetID=10039

MLA

Ferguson, Robert., Goldenson, Dennis., McCurley, James., Stoddard, Robert., Zubrow, David., & Anderson, Debra. 2011. Quantifying Uncertainty in Early Lifecycle Cost Estimation (QUELCE) (Technical Report CMU/SEI-2011-TR-026). Pittsburgh: Software Engineering Institute, Carnegie Mellon University. http://resources.sei.cmu.edu/library/asset-view.cfm?AssetID=10039