Abstract
We’ve covered a lot of material up to this point, and some of it was perhaps new in concept and maybe even took a couple of passes to fully absorb.
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- 1.
For example, the Cynefin framework can be a helpful start in considering levels of complexity and associated effects on the assessment of uncertainties. See: Kurtz, Cynthia F., and David J. Snowden (2003). “The new dynamics of strategy: Sense-making in a complex and complicated world” (PDF), IBM Systems Journal, 42(3): 462–83.
- 2.
For an example of this sentiment expressed in the context of innovation, see: Katila, Riitta, “Too Many Experts Can Hurt Your Innovation Projects”, Harvard Business Review, December 7, 2017. https://hbr.org/2017/12/too-many-experts-can-hurt-your-innovation-projects
- 3.
While the degree of lateralization of the brain assumed by the original left-/right-brained theory has been shown to be overstated, the labels for describing associated personality traits still often resonate and so are used here.
- 4.
Plattner, Hasso, Meinel, Christoph, and Leifer, Larry J., eds. Design Thinking: Understand-Improve-Apply (Understanding Innovation) (Springer-Verlag, 2011).
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© 2018 Steven Flinn
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Flinn, S. (2018). Organizing for Data-to-Learning-to-Action Success. In: Optimizing Data-to-Learning-to-Action. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-3531-7_10
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DOI: https://doi.org/10.1007/978-1-4842-3531-7_10
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