I’ve just been reading a fascinating new doctoral dissertation by a recent Ph.D. from Washington University’s Olin School of Business: Chihmao Hsieh, now a professor at the University 0f Missouri. He asks a fascinating question about innovation: what is the structure of successful new ideas? If that sounds abstract, I’ll try to explain by drawing on some of the research from my book GROUP GENIUS.
First, creativity researchers know that all new ideas are combinations of existing ideas. That’s why psychological studies of “conceptual combination” are so important–what happens when people combine words like “pony” and “chair” and what they say a “pony chair” looks like.
Second, innovations today are always combinations of previous ideas, products that are already out there, being used every day.
So the question “What is the structure of good ideas” is really a question about these combinations. If only there were some way to evaluate the combinations that form new ideas–perhaps we could count up the number of previous ideas that the new idea is based on? Perhaps we could measure how those new ideas are related to each other?
Hsieh’s dissertation is exciting because he has figured out a way to measure the relatedness of all of the component ideas in a new idea. He started with a database of all patents granted between 1975 and 1999. For each patent, this database indicates which previous patents are cited, and which later patents cite it. Using this huge database, and applying some fancy mathematical tools, it’s possible to calculate the relatedness of any two patents (essentially, you count how many of the same other patents that both of these patents cite). Then, for each patent, Hsieh figured out the overall relatedness of all of the patents that it cited. The key question is: which level of internal relatedness is most likely to result in a successful patent?
He measured the success of a patent by counting how many times later patents cite it, and here’s what he found: the most successful patents have an intermediate degree of relatedness. And he found something else interesting: patents that cite more other patents are more successful.
I’m excited by this research because it reinforces what psychologists have discovered about creativity: good ideas involve certain kinds of combinations among existing concepts and ideas. But it’s very hard to look inside the brain and observe these connections in action. Hsieh’s clever use of patent data provides us with a window into what successful innovation looks like. The key lesson for all of us is to learn as much as you can about the ideas that are already out there; that’s the only way you’ll be able to come up with that unique new combination that no one else has ever thought of.