JOURNAL ARTICLE

Whole‐brain thinking in systems architecting

Tony Di CarloBehrokh KhoshnevisFirdaus E. Udwadia

Year: 2008 Journal:   Systems Engineering Vol: 12 (3)Pages: 265-273   Publisher: Wiley

Abstract

Abstract This position paper explores the role of whole‐brain thinking in the context of systems architecting. Brain research indicates that the brain is dual and that each of its hemispheres interprets the world differently; the concept is commonly referred to as right‐brain and left‐brain thinking, or sometimes R‐mode and L‐mode for short. L‐mode denotes step‐by‐step linear thinking. R‐mode is integrative and holistic. It pays to extend this to systems architecting. For example, there may be two ways to look at complexity, analytically and holistically. Step‐by‐step analysis is well suited for low‐dimensional complexity. As complexity increases methodical analytical skills become overwhelmed and we are bogged down, maybe even forced into complacent partial representation—tunnel vision. Learning to “see” the complex may benefit from a shift from the analytical to the holistic, from L‐mode to R‐mode thinking, or a better blending of the two. We begin with a cursory review of brain theory and applications thereof in drawing, management and creativity theory, and then follow up with observations of blended L/R‐mode thinking in the context of systems architecting. Our hope is to distill from these sources whole‐brain mental strategies that may be relevant to systems architects. © 2008 Wiley Periodicals, Inc. Syst Eng

Keywords:
Creativity Context (archaeology) Systems thinking Cognitive science Mode (computer interface) Vertical thinking Representation (politics) Computer science Parallel thinking Psychology Artificial intelligence Epistemology Human–computer interaction Creative thinking Divergent thinking Convergent thinking Social psychology Political science Philosophy

Metrics

4
Cited By
0.79
FWCI (Field Weighted Citation Impact)
20
Refs
0.85
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Systems Engineering Methodologies and Applications
Physical Sciences →  Engineering →  Control and Systems Engineering
Complex Systems and Decision Making
Social Sciences →  Decision Sciences →  Management Science and Operations Research
Technology Assessment and Management
Physical Sciences →  Engineering →  Safety, Risk, Reliability and Quality

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