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Technology Maturity Assessments and Confidence Intervals

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  • Wanda Peters
  • Steven Doskey
  • James Moreland

Abstract

The research presented in this paper examines the accuracy of technology maturity assessments at a key decision point in the acquisition life cycle. This study utilizes statistical means to quantify the confidence interval of technology maturity determinations and established confidence intervals for various population sizes using a Monte Carlo simulation. The study identified with a 95% confidence that there are no significant differences in the standard deviation or the confidence interval ranges of heritage developments and new developments at a key decision point. The significance of this finding is the margin of error, which is derived from the standard deviation and used to compute confidence intervals, measures accuracy. One challenge facing the field of system engineering is the ability to accurately measure technology maturity when transitioning from formulation to implementation. Correctly assessing the technology maturity of a development is crucial for the organization's ability to manage performance, cost, and schedule. The findings from this research have the potential for minimizing inaccurate maturity determinations, which could lead to reductions in unsatisfactory technical performance and programmatic overruns.

Suggested Citation

  • Wanda Peters & Steven Doskey & James Moreland, 2017. "Technology Maturity Assessments and Confidence Intervals," Systems Engineering, John Wiley & Sons, vol. 20(2), pages 188-204, March.
    • Handle: RePEc:wly:syseng:v:20:y:2017:i:2:p:188-204
    DOI: 10.1002/sys.21389
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    References listed on IDEAS

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    1. Robert Shishko & Donald H. Ebbeler & George Fox, 2004. "NASA technology assessment using real options valuation," Systems Engineering, John Wiley & Sons, vol. 7(1), pages 1-13.
    2. Weiping Tan & Jose Ramirez‐Marquez & Brian Sauser, 2011. "A probabilistic approach to system maturity assessment," Systems Engineering, John Wiley & Sons, vol. 14(3), pages 279-293, September.
    3. Eileen McConkie & Thomas A. Mazzuchi & Shahram Sarkani & D. Marchette, 2013. "Mathematical properties of System Readiness Levels," Systems Engineering, John Wiley & Sons, vol. 16(4), pages 391-400, December.
    4. Daniel R. Katz & Shahram Sarkani & Thomas Mazzuchi & Edmund H. Conrow, 2015. "The Relationship of Technology and Design Maturity to DoD Weapon System Cost Change and Schedule Change During Engineering and Manufacturing Development," Systems Engineering, John Wiley & Sons, vol. 18(1), pages 1-15, January.
    5. Nazanin Azizian & Thomas Mazzuchi & Shahram Sarkani & David F. Rico, 2011. "A framework for evaluating technology readiness, system quality, and program performance of U.S. DoD acquisitions," Systems Engineering, John Wiley & Sons, vol. 14(4), pages 410-426, December.
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    Cited by:

    1. Klessova, Svetlana & Engell, Sebastian & Thomas, Catherine, 2022. "Assessment of the advancement of market-upstream innovations and of the performance of research and innovation projects," Technovation, Elsevier, vol. 116(C).
    2. Svetlana Klessova & Sebastian Engell & Catherine Thomas, 2022. "Assessment of the advancement of market-upstream innovations and of the performance of research and innovation projects," Post-Print hal-03636260, HAL.

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