This article by Scott Anthony at Harvard Business Weekly Publishing is a wonderful example of using analogy for communicating about innovation. The analogy used in the article is between the Major League Baseball draft and the way a company manages innovation.
Because the analogy and its use for innovative thinking is presented so well, I am going to go all recursive on you and use the article as a showcase of the right ways of using analogy for innovation and for communicating about innovation.
The first step in any analogy is pointing out to the audience the relevant correspondences between the concepts:
“Baseball teams have to assemble the best talent possible, just like companies have to bet on the best innovation opportunities. A baseball team chooses between acquiring talent on the free agent market or drafting and building talent. A company chooses between acquisitions or organic growth.“
A good analogy focuses on deep structural correspondences between concepts:
“Acquisitions are expensive, but perceived to be lower risk, because the talent (or idea) has proven itself demonstrably in the marketplace (for baseball, that means success on a major-league diamond). Organic growth is typically cheaper, but perceived to be risky because many times highly touted initiatives or prospects dont pan out.“
What this means is that the author isn’t just drawing correspondences between the elements of the two concepts (e.g., “acquiring talent on the free agent market” = “acquisitions”). He is explaining how elements and the relationships between them in one concept correspond to elements and the relationships between them in the other concept.
These correspondences then lead to certain inferences. Inferences, that are important to the point the author is making about innovation:
“Just as a baseball team doesnt have complete information about what a players true level of ability is on draft day, you dont know the real potential of any one innovation project…. Good teams collect as much data as possible. They have sophisticated models to project how rough performance can project to the major league level.“
Leads to the inference that for companies:
“With a well-organized scouting team, you should gather multiple data points in preparation to draft innovation opportunities.”
By pointing out the correspondences between rich concepts such as the ones being used in the Baseball Analogy article, the audience is then able to make their own inferences using their own detailed knowledge of the concepts in the analogy:
“Of course, the market for companies is more liquid than the market for baseball players. We bet you if you ran the data the absolute best return on investment would be acquiring a hitter who has proven himself at a critical midpoint….Ask yourself: What is the equivalent inflection point in our market?“
It is by working out the inferences resulting from correspondences such as these that innovation is made possible. However, these inferences are not possible unless your audience possesses detailed knowledge of the concepts used in the analogy. I, for one, know next to nothing about the Major League Baseball draft. Consequently, I can follow the analogy made by the author and the points being made but would be absolutely unable to determine an “equivalent inflection point” at which I would be most likely to receive the “absolute best return on investment.”
Using analogy for communicating about innovation or for innovation itself requires knowledge of BOTH the concepts used in the analogy. This knowledge can be provided by the person making the analogy or through personal experience, but acquired it must be for innovation to happen.