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Systems engineering leading indicators for assessing program and technical effectiveness
Author(s) -
Rhodes Donna H.,
Valerdi Ricardo,
Roedler Garry J.
Publication year - 2008
Publication title -
systems engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.474
H-Index - 50
eISSN - 1520-6858
pISSN - 1098-1241
DOI - 10.1002/sys.20105
Subject(s) - performance indicator , context (archaeology) , set (abstract data type) , construct (python library) , computer science , performance measurement , work (physics) , systems engineering , engineering , risk analysis (engineering) , management science , process management , operations research , business , mechanical engineering , paleontology , marketing , biology , programming language
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