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Using Prizes to Foster Innovation May 22, 2011

Posted by keithsawyer in Enhancing creativity.
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Steve Lohr’s “Unboxed” column in today’s New York Times provides several examples of how prize competitions have spurred innovation–starting with Britain’s 1714 prize of 20,000 pounds (nearly $4.5 million today) to anyone who could figure out how to determine  a ship’s longitude (see the fascinating book Longitude for the full story).

If you like Lohr’s article and you’d like to learn more, I recommend The McKinsey Prize Report (I was interviewed for the report), published in 2010. It provides good advice about how and when prize competitions work and when they don’t, and a comprehensive list of recent prize competitions designed to foster innovation.

Harnessing the Wisdom of Crowds July 24, 2009

Posted by keithsawyer in Innovative networks.
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We’ve heard a lot about collective intelligence, Web 2.0.  Internet-based examples abound: Wikipedia, Google, Threadless.  Thomas Malone and colleagues have written a new article proposing an analytic framework to help us think about these networks, what they call the “building blocks” or “genes” of collective intelligence.  Of course, I wanted to see how their framework compares to my own “collaborative web” model from Group Genius.  Based on a study of 250 examples of web communities, here’s what they propose.

The four building blocks are answers to these questions: Who is doing the task? Why? What is being done? How?  How these questions are answered determines which “gene” it is.

The Who question has two genes: (1) Hierarchical organization determines who.  (2) Crowd gene: Anyone can participate.

The Why question has three genes: (1) Money (2) Intrinsic motivation of the task (3) fame or reputation.

The What question has two genes: (1) Create something new; (2) Select among alternatives.

The How question has two genes for each of the what genes, depending on whether it is independent or collective.  For “Create” the two genes are Collect independent contributions and Collaborate together.  For “Select” the two genes are Group decisions (Aggregate individual group decisions by voting or consensus etc.) and Individual decisions, through markets or social networks.

Then continuing the biological analogy, they analyze specific examples of web-based collaboration and call them “genomes.”

This is a useful way of breaking down different web-based communities, although I found it not very surprising or new.  The key thing that’s missing from this model is what I think is the biggest challenge facing such communities: What is the right degree of central control and structure?  Communities with no central structure are usually a huge mess.  Linux succeeds only because of a strong central guiding body, led by Linus Torvalds.  The model presented in this article seems most appropriate for tasks where no central control is necessary, where small items are created that don’t need to coordinate with each other in complex systems (in Wikipedia each entry stands alone; with Threadless, each t-shirt design is independent).  But with Linux, everything has to work together.  That’s a key variable missing from this model, but I have no doubt Malone and colleagues are aware of this and are thinking about it. (The 7/19/2009 NYTimes article by Steve Lohr, where Prof. Malone was interviewed, explicitly addresses this topic.)  Perhaps another paper will emerge from the same research study.

*Thomas W. Malone, Robert Laubacher, and Chrysanthos Dellarocas. February 2009.  Harnessing Crowds: Mapping the Genome of Collective Intelligence.

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