Breakthroughs and the “Long Tail” of Innovation

To understand how breakthroughs in innovation arise, managers first need to be aware of the different factors that shape the highly skewed distribution of creativity.

Many managers have little understanding of the process of invention. Nor do they possess much insight about the most likely sources of technological and scientific breakthroughs. Specifically, are blockbuster innovations more likely to come from a lone inventor or from a collaborative team? If it’s the latter, does greater diversity on the team help or hurt the group’s chances? And does a deeper understanding of science lead to more breakthroughs, or is such knowledge more likely to result in only incremental progress? To answer such questions, managers first need to understand that invention is essentially a process of recombinant search. That is, I adopt the classic definition of invention as a new combination of components, ideas or processes. At its simplest level, this definition provides an accessible picture of the inventor as a tinker, trying different combinations of materials, gadgets and configurations, and every invention can be thought of as an assemblage of its constituent parts, including the steamship (sailing ship and steam engine), the automobile (bicycle, carriage and internal combustion engine) and Apple Inc.’s iPod (cheap memory, digital music and lightweight battery). The prevailing view is that breakthroughs are impossible to predict, but that’s only partly true. Much of the misconception arises because people tend to focus on just the breakthroughs while ignoring the iterative process of invention and the resulting total distribution of outcomes. When all inventions (that is, all new combinations) are considered, they demonstrate a highly skewed distribution. (See “Histogram of Creativity.”) Almost all inventions are useless; a few are of moderate value; and only a very, very few are breakthroughs. Those breakthroughs constitute the “long tail” of innovation.

Histogram of Creativity

View Exhibit

Every well-sampled distribution of inventive value, creativity or success I have ever observed has demonstrated that highly skewed profile.

Read the Full Article:

Sign in, buy as a PDF or create an account.

References

1. M. Trajtenberg, “A Penny for Your Quotes: Patent Citations and the Value of Innovations,” RAND Journal of Economics 21 (1990): 172-187.

2. D.K. Simonton, “Origins of Genius: Darwinian Perspectives On Creativity” (New York: Oxford University Press, 1999).

3. F.M. Scherer and D. Harhoff, “Technology Policy for a World of Skew-Distributed Outcomes,” Research Policy 29 (2000): 559-566.

4. L. Fleming, S. Mingo and D. Chen, “Brokerage and Collaborative Creativity,” Administration Science Quarterly, forthcoming.

5. A. Taylor and H.R. Greve, “Superman or the Fantastic Four? Knowledge Combination and Experience in Innovative Teams,” Academy of Management Journal 49, no. 4 (2006): 723-740.

6. See L. Fleming, “Lone Inventors As Sources of Breakthroughs: Myth or Reality?” Harvard Business School Working Paper (2006); and K. Dahlin, M.R. Taylor and M. Fichman, “Today’s Edisons or Weekend Hobbyists: Technical Merit and Success of Inventions By Independent Inventors,” Research Policy 33, no. 8 (2004): 1167-1183.

7. T.J. Allen, “Managing the Flow of Technology” (Cambridge, Massachusetts: MIT Press, 1977).

8. This measure is conservative, based on the consideration of non-overlapping three-year periods in the careers of all U.S. inventors. For that data, almost 20% of corporate inventors worked completely alone (see Fleming, “Lone Inventors”).

9. L. Fleming, S. Mingo and D. Chen, “Brokerage”; see also R.S. Burt, “Structural Holes and Good Ideas,” American Journal of Sociology 110 (2004): 349-399.

10. R. Katz and T.J. Allen, “Investigating the Not Invented Here (NIH) Syndrome: A Look at the Performance, Tenure and Communication Patterns of 50 R&D Project Groups,” R&D Management 12 (1982): 7-20.

11. Gatekeepers are also known as “boundary spanners.” See T.J. Allen, “Managing the Flow”; and M.L. Tushman, “Special Boundary Roles in the Innovation Process,” Administrative Science Quarterly 22, no. 4 (1977): 587-605.

12. L. Fleming and M. Marx, “Managing Creativity in Small Worlds,” California Management Review 48, no. 4 (summer 2006): 6-27.

13. O. Sorenson, J.W. Rivkin and L. Fleming, “Complexity, Networks and Knowledge Flow,” Research Policy 35 (2006): 994-1017.

14. A. Hargadon, “How Breakthroughs Happen: The Surprising Truth About How Companies Innovate” (Boston: Harvard Business School Press, 2003); and D. Leonard and W. Swap, “When Sparks Fly: Igniting Creativity in Groups” (Boston: Harvard Business School Press, 1999).

15. L. Fleming, “Recombinant Uncertainty in Technological Search,” Management Science 47, no. 1 (2001): 117-132.

16. J.G. March and H.A. Simon, “Organizations” (Cambridge, Massachusetts: Blackwell Publishers, 1958); R.R. Nelson and S.G. Winter, “An Evolutionary Theory of Economic Change” (Cambridge, Massachusetts: Belknap Press, 1982); and T.E. Stuart and J.M. Podolny, “Local Search and the Evolution of Technological Capabilities,” Strategic Management Journal 17 (summer 1996): 21-38.

17. L. Fleming and O. Sorenson, “Navigating the Technology Landscape of Innovation,” MIT Sloan Management Review 44, no. 2 (winter 2003): 15-23.

18. George Whitesides refers to complex systems as the “natural home of big surprises”; see G.M. Whitesides and G.W. Crabtree, “Don’t Forget Long-Term Fundamental Research in Energy,” Science, February 9, 2007, 796-798.

19. L. Fleming and O. Sorenson, “Science As a Map in Technological Search,” Strategic Management Journal 25 (2004): 909-928.

20. O. Sorenson and L. Fleming, “Science and the Diffusion of Knowledge,” Research Policy 33, no. 10 (2004): 1615-1634.