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Behavioral Economics and the Design of Systems Engineering Measures
Author(s) -
Brown Barclay
Publication year - 2013
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2013.tb03033.x
Subject(s) - measure (data warehouse) , perspective (graphical) , unintended consequences , computer science , field (mathematics) , work (physics) , affect (linguistics) , analytics , interpretation (philosophy) , behavioral economics , management science , data science , risk analysis (engineering) , psychology , epistemology , artificial intelligence , economics , engineering , mathematics , microeconomics , mechanical engineering , medicine , philosophy , communication , database , pure mathematics , programming language
The design of measures is an art and a science. Taking a systems thinking perspective in designing a measure requires considering how the measure will be used, what it means, what kind of behavior it will produce, and the results of that behavior. Treating the implementation of a measure as a move in a game can give new insights into what will happen when the measure is introduced. Measures may be ignored if it is not clear what they mean, or if there are no standards or goals for the measure. Measures that are published, evaluated and used to determine performance levels of people and groups, and which have standards, norms and goals, in turn affect behavior and are subject to gaming. It is these measures which must be analyzed for unintended, or worse yet, adverse consequences. Short of finding perfect measures, the practice of balancing measures can be used to mitigate such consequences. In theory there is no difference between theory and practice. In practice there is . (Yogi Berra) In pursuing a comprehensive approach to the measurement of systems engineering and systems development work, we must face difficulties in both theory and practice. The central questions we must answer are, What should we measure? How should we measure it? What does it mean? How will measuring this affect behavior? Most work in the area of measures focuses on the first two questions. The field of data analytics and interpretation focuses on the third, and the field of behavioral economics is interested in the fourth. This paper will present some key ideas about how measures can be designed and conducted, applying some insights from these diverse fields. Part I will focus on current practice, as assessed in a series of informal interviews conducted by the author in 2011–2012 with several active, senior practitioners in systems engineering measurement, mostly in the aerospace and defense industry. The goal was to understand how systems engineering is measured in current practice and how those measures are used. Part II looks at the question of how measures are designed, their component parts and how meaning for measures can be determined. In Part III the focus is on unintended consequences of applying measures—the behavioral economics perspective. Some guidelines will be suggested for the successful design of measures that avoid or minimize unintended consequences. This paper aims at suggesting a new way of thinking about and designing measures and does not claim to present an explicit solution to any or all measurements needs. In fact, it is likely that the topic of measurement will appear more problematic after understanding what follows, than before.