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Explore the intersection of innovation, learning, and learning spaces, understanding knowledge construction, expertise, and the challenges of disruptive innovation. Learn about diffusion processes, managing disruptive technologies, and embracing failure as part of the learning process.
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Innovation, Learning, and Learning Spaces ELI web seminar October 2008 Malcolm Brown, Dartmouth College
“If I’d have asked my customers what they wanted, they would have told me ‘A faster horse.’ ” attributed to Henry Ford
QuickReview http://www.nap.edu/books/0309070368/html/
Findings • Knowledge is constructed • Expertise / competency = • factual matrix or manifold • conceptually organized • retrieval and application
Expertise: range and limits where are the knights? where are the rooks?
Findings • Knowledge is constructed • Expertise / competency = • factual matrix or manifold • conceptually organized • retrieval and application • Student control of learning
How did we get here? We’ve innovated
It feels like innovation No formula Adoption to rapidly changing circumstances Working with teams Often handed odds & ends Funding can be uncertain New ideas not always received well
But is it innovation? What does it “look” like? Feel like? How does it work? How can we be better at it? What are all the moving parts?
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Version 2: Innovation = Idea
“The best way to get a good idea is to get a lot of ideas.” Linus Pauling
Implementation “The elaboration of idea into function… [is] ‘the one that takes up the most time and involves the hardest work.’ ” Berkun, Myths of Innovation, p. 13
Also… Innovation ≠ Serendipity Percy Spencer (1896–1970)
Innovation Epiphany ≠ = + lots of hard work, trial and error, research, etc. etc. etc. etc.
Thought “Every innovation is difficult.” Christensen, Innovator’s Dilemma, p. 154
What influences diffusion following Rogers, Diffusion of Innovations Relative advantage Compatibility Ease of use Trialability Observability
Analyzing diffusion’s prospects Example 1 very high relative advantage compatibility somewhat low
Analyzing diffusion’s prospects Example 2 modest relative advantage ease of use very low
Analyzing diffusion’s prospects Example 3 very high relative advantage very high compatibility ease of use OK
Analyzing diffusion’s prospects Example 4 moderate/high relative advantage somewhat low compatibility trialability low
Thought “If, at first, the idea is not absurd, then there is no hope for it.” Albert Einstein
“I can’t waste my time on this stuff.” Disney exec on Pixar, c. 1987 (NYT review)
www.wired.com/cars/futuretransport/magazine/16-01/ff_100mpg “…we just cannot divert ourselves from the business at hand.” — GM vice chair
“Search doesn’t matter. Portals do.” Yahoo execs, 1998
Sustaining vs. disruptive Sustaining innovation Disruptive innovation Incremental improvement Established paradigm Valued by current customers Predictable Underperform New paradigm “I didn’t ask for this” Unpredictable
Disruption is hard following Christensen, Innovator’s Dilemma Limited market capacity for disruption Disruptive tech won’t fit Our orgs our less flexible than we want to believe Failure and iterative learning are keys Reluctance to invest in disruption
Managing for disruption following Christensen, Innovator’s Dilemma, p. 113–114 Align disruptive tech with the right customers so there’s tangible demand Align to small, independent units for small growth Fail early and inexpensively Search for markets not technological breakthroughs
Thought “If I have a thousand ideas and only one turns out to be good, I am satisfied.” Alfred Bernhard Nobel