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Systems engineering leading indicators for assessing program and technical effectiveness

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  • Donna H. Rhodes
  • Ricardo Valerdi
  • Garry J. Roedler

Abstract

This paper discusses a 3‐year initiative to transform classical systems engineering (SE) measures into leading indicators, including the resulting guidance information that has been developed and future research directions. Systems engineering leading indicators are measures for evaluating the effectiveness of the systems engineering activities on a program in a manner that provides information about impacts that are likely to affect the system or program performance objectives. A leading indicator may be an individual measure, or collection of measures, that is predictive of future system performance before the performance is realized. Contrary to simple status oriented measures typically used on most projects, leading indicators are intended to provide insight into the probable future state, allowing projects to improve the management and performance of complex programs before problems arise. This paper discusses the motivations and collaborative development of the SE leading indicators. It defines the leading indicator construct, introduces the initial set of 13 indicators, and provides guidance for implementation, analysis, and interpretation of these indicators. The initial set of indicators, developed through a collaboration of industry, government, and academia, has recently undergone validation through pilot studies and surveys. This work serves as a foundation for industry implementation and for further research to improve and expand the set of indicators, including development of a better understanding of how to best implement and use the leading indicators in a given program context. © 2008 Wiley Periodicals, Inc. Syst Eng

Suggested Citation

  • Donna H. Rhodes & Ricardo Valerdi & Garry J. Roedler, 2009. "Systems engineering leading indicators for assessing program and technical effectiveness," Systems Engineering, John Wiley & Sons, vol. 12(1), pages 21-35, March.
    • Handle: RePEc:wly:syseng:v:12:y:2009:i:1:p:21-35
    DOI: 10.1002/sys.20105
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    Cited by:

    1. Li Zheng & Claude Baron & Philippe Esteban & Rui Xue & Qiang Zhang, 2017. "Mapping Systems engineering leading indicators with leading indicators in construction industry projects," Post-Print hal-01709556, HAL.
    2. Michael W. Grenn & Shahram Sarkani & Thomas Mazzuchi, 2014. "The Requirements Entropy Framework in Systems Engineering," Systems Engineering, John Wiley & Sons, vol. 17(4), pages 462-478, December.
    3. Ricardo Valerdi & Matthew Dabkowski & Indrajeet Dixit, 2015. "Reliability Improvement of Major Defense Acquisition Program Cost Estimates—Mapping DoDAF to COSYSMO," Systems Engineering, John Wiley & Sons, vol. 18(5), pages 530-547, October.
    4. Justin W. Eggstaff & Thomas A. Mazzuchi & Shahram Sarkani, 2014. "The Development of Progress Plans Using a Performance‐Based Expert Judgment Model to Assess Technical Performance and Risk," Systems Engineering, John Wiley & Sons, vol. 17(4), pages 375-391, December.
    5. Li Zheng & Claude Baron & Philippe Esteban & Rui Xue & Qiang Zhang, 2017. "Considering the systems engineering leading indicators to improve project performance measurement," Post-Print hal-01710579, HAL.
    6. Li Zheng & Claude Baron & Philippe Esteban & Rui Xue & Qiang Zhang, 2017. "A framework to improve performance measurement in engineering projects," Post-Print hal-01709535, HAL.
    7. Thomas Walworth & Mike Yearworth & Laura Shrieves & Hillary Sillitto, 2016. "Estimating Project Performance through a System Dynamics Learning Model," Systems Engineering, John Wiley & Sons, vol. 19(4), pages 334-350, July.

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