Is Your Company Choosing the Best Innovation Ideas?

Generating good innovation proposals from within the ranks of the organization is only the beginning. The more difficult part is creating a selection process that identifies which ideas to implement.

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Managers who are new to the field of corporate innovation will quickly find that there is no dearth of advice or resources on how to turn corporations into fountains of creative ideas. Books and journals abound with techniques for helping employees overcome old mental models and “think outside of the box.” The goal of these approaches is to generate vast numbers of unconventional ideas to improve the existing business or uncover new opportunities. However, as veteran leaders of innovation campaigns know, the problem for most large organizations usually isn’t a shortage of ideas. The real challenge is figuring out how to ferret out the good ones.

In large organizations, senior managers need to delegate major parts of the selection process to lower-level managers. But delegating critical decisions comes with risks. In the case of asking subordinates to filter innovation proposals, the company may end up promoting ideas senior management doesn’t deem worthy; alternatively, it may not pursue projects top management would have promoted had they known about them. Therefore, it’s essential for senior managers to understand the mechanisms at work when their staff evaluates one another’s ideas, so that executives can hone in on the ideas that will make a real difference to the organization as they move through the innovation funnel. This article, based on research on more than 10,000 innovation proposals from within a large multinational corporation, examines what happens when ideas are screened through a large organization. Based on my research, I describe seven variables, or setscrews, that senior managers can adjust to their particular context to ensure that the most promising innovation proposals — and only those — stand a good chance of being implemented.



1. In its most general form, this insight on the skewed distribution of breakthrough ideas was reported by Alfred Lotka as early as 1926. See A. Lotka, “The Frequency Distribution of Scientific Productivity,” Journal of the Washington Academy of Sciences 16, no. 12 (1926): 317-324. More recently, these insights have been applied to improve our understanding about corporate innovation more specifically. See L. Fleming, “Breakthroughs and the ‘Long Tail’ of Innovation,” MIT Sloan Management Review 49, no.1 (2007): 69-74.

2. For a review, see H. Lamm and G. Trommsdorff, “Group versus Individual Performance on Tasks Requiring Ideational Proficiency (Brainstorming): A Review,” European Journal of Social Psychology 3, no. 4 (1973): 361-388.

3. Recent experimental studies in the field of operations research support this conclusion. For details, see K. Girotra, C. Terwiesch and K.T. Ulrich, “Idea Generation and the Quality of the Best Idea,” Management Science 56, no. 4 (April 2010): 591-605.

4. The data on ideas I deploy for analysis are limited to observations that can, at least in theory, be tracked to an individual inside the company’s central personnel database, and have no major missing information otherwise.

5. Note that the “costs” of implementation can be twofold. The company will incur direct costs when implementing a bad (that is, unprofitable) idea, and it will face opportunity costs when not implementing a good (or profitable) idea. Both types of errors (so-called false positives and false negatives) jointly create the total costs of idea implementation. When balancing selection and implementation costs, the manager must find an optimum for her or his corporation.

6. For more information, see M.G. Reitzig and O. Sorenson, “Intra-Organizational Provincialism,” Working paper, Toronto, February 12, 2010, and M.G. Reitzig, “Hierarchies, Polyarchies, and Endogenous Screening,” August 6, 2010,

7. For the basics, see M.B. Brewer, “In-group Bias in the Minimal Intergroup Situation: A Cognitive Motivational Analysis,” Psychological Bulletin 86, no.1 (1979): 307-324.

8. Depending on the actual statistical model; for more information, see Reitzig and Sorenson, “Provincialism,” and Reitzig, “Hierarchies.”

9. In this case the bias is driven by an informational transfer problem, and not by other behavioral particularities of the subjects.

10. For further reading, see M. McPherson, L.S. Lovin and J.M. Cook, “Birds of a Feather: Homophily in Social Networks,” Annual Review of Sociology 27, no. 1 (2001): 415-444.

11. A detailed manual inspection of a random sample of about 200 idea descriptions confirms this large-scale empirical finding.

12. Think of it as follows: You can say (1) that an idea makes $1 million more per year for the company; or (2) that the company has a problem, which unless fixed will cost the company $1 million per year. The first statement is positively worded. Chances are, it will pass the selection. The second one, saying exactly the same thing in terms of content, stands a worse chance because it is not framed positively.

13. For further reading, see D.R. Forsyth, L.E. Zyzniewski and C.A. Giammanco, “Responsibility Diffusion in Cooperative Collectives,” Personality and Social Psychology Bulletin 28, no. 1 (2002): 54-65.

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