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2.3.1 A Practical Program of Research to Measure Systems Engineering Return on Investment (SE‐ROI)
Author(s) -
Honour Eric C.
Publication year - 2006
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2006.tb02744.x
Subject(s) - categorization , computer science , return on investment , identification (biology) , quality (philosophy) , measure (data warehouse) , process (computing) , risk analysis (engineering) , process management , data mining , artificial intelligence , engineering , business , philosophy , botany , epistemology , production (economics) , biology , economics , macroeconomics , operating system
Past analysis has shown that there is a quantifiable correlation between the amount, types and quality of systems engineering efforts used during a program and the success of the program. For any given program, an amount, type and quality of systems engineering effort can be selected from the quantified correlations. The optimal nature of these selections, however, has not yet been explored. An ongoing project, Systems Engineering Return on Investment (SE‐ROI), aims to quantify the correlations by gathering data on current and completed programs. This paper describes the practical program of research being used in the SE‐ROI project and the current state of that development. The research program involves defining categorization sufficient to explore the correlations, implementing that categorization onto data sheets, gathering data from real programs through a personal interview process with the program leaders, and then performing statistical work to reveal the correlations. The project expects to achieve practical results in the form of (a) statistical correlation of SE methods with project success, to understand how much of each SE method is appropriate under what conditions, (b) leading indicators that can be used during a project to assess the project's expected future success and risks, and (c) identification of good SE practices that are appropriate to generate success under different conditions. 1