It’s not about you

If you’re trying to make yourself more creative, maybe you’re focusing too much on yourself. The way to become more creative is to look outwards, to embed yourself more effectively in innovative social networks that I call “collaborative webs”.

That’s the message emerging from an interdisciplinary group of psychologists, cognitive scientists, and computer scientists. They have different names for what happens when groups generate ideas–distributed cognition, embodied cognition, or social cognition. In my 2006 book Explaining Creativity, I called this perspective “socioculturalism”; it represents the most important new approach to understanding creativity in years.
And my new book Group Genius is inspired by these insights, too.

I’m now reading Richard Ogle’s new book, Smart World.  His title is a clever term that captures the key message of distributed cognition–that the world itself makes us smarter.  Ogle’s book is about what he calls “idea spaces,” a concept similar to what Thomas Kuhn long ago called a paradigm–a way of thinking about the world, a way of perceiving data, a way of asking questions.  Ogle’s line of argument is consistent with my new book Group Genius; in fact, both of our books were quoted in a recent U.S. News & World Report story about collaboration and creativity (June 18, 2007).  What I really enjoy about Ogle’s book is the detailed stories about the real historical processes behind innovation; in this, his book continues in a tradition that includes Basalla’s The Evolution of Technology and Andrew Hargadon’s How Breakthroughs Happen.  With this amount of detail, it takes some sustained effort to read this new book, but it will be worth the effort.

The Structure of Good Ideas

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.

Does competition kill creativity?

I’m a big fan of collaboration. All the research shows that significant innovations emerge from collaborative groups, not from solitary loners. And I emphasize this message when I give talks to corporate audiences. But more than once or twice now, someone in the audience will ask: “Do you think competition will kill creativity?”

You might be surprised to learn that my answer is “No”–as long as it’s the right kind of competition. And lots of research shows that too little friction can block creativity, too.

Yes, competition kills creativity if it’s a destructive, winner-takes-all form of competition; if ideas are hoarded so that their owner gets sole credit; if communication stops because others are viewed as “the enemy”. But the most innovative companies, in fact, foster a form of collaborative competition. A good example is BMW. Young designers from the Munich headquarters to its DesignWorks studio in Los Angeles are often asked to compete against each other. Apple’s Macintosh computer was only one of two parallel windows-and-mouse computer projects created by Steve Jobs; the other was the Lisa. These two teams each invented slightly different solutions to basic problems; for example, instead of a mouse cursor control, the Lisa used a touch pad, now found on just about every laptop computer. Multiple parallel projects, in competition with each other, can drive innovation forward because they generate more potential solutions.

Groups that have no friction in them–groups where everyone gets along and shares the same beliefs–all too frequently fall into group think, a downward spiral where bad ideas are never criticized, and doomed projects are never terminated, because to do so would damage the group’s wonderful feeling of togetherness. Group researchers refer to this as cohesiveness, and too much of it blocks creativity.

Like so much else with innovation, the right solution is the Goldilocks solution: not too much cohesion, not too much competitiveness, but somewhere in the middle will be “just right.”

The building that threw up on itself

Stata Center at MITBack in Boston for my 25th MIT reunion, I had my first chance to visit the Frank Gehry designed Stata Center. After exploring the building, I came to the conclusion that this controversial building is widely misunderstood. From the exterior, some people say it looks as if a crazy architect dropped a pile of kid’s blocks onto Amherst Avenue. Some locals call it “the building that threw up on itself”.

Many architects love it. In a rave review, Boston Globe columnist Robert Campbell wrote “Everything looks improvised, as if thrown up at the last moment. That’s the point.”

If you read my new book GROUP GENIUS, you’ll know that I believe improvisation is the key to innovation. But you have to go inside Stata to understand its genius: this is a building that’s designed to foster connections, networks, and collaboration. You can’t get very far inside the first floor before you suddenly realize that you can see everywhere. Stata center interiorOffices jut out into the four-story atrium at odd angles, and you can look up and see researchers working above you. Just about every office and hallway wall is floor-to-ceiling glass. Climbing up to the fourth floor and walking along the many stairs and crosswalks, when you look back down on those second story offices you discover that they don’t have ceilings; you’re looking down on creativity at work. You stand or sit just about anywhere on those first four floors, and see creative work going on all around you. You feel connected to the community in a way that I’ve never experienced before in a physical space.

On the first floor there are no “hallways” in the conventional sense. Wide thoroughfares cross at odd angles, bringing people into constant contact. There are seating areas in niches designed to encourage spontaneous meetings, and whiteboards are everywhere. You pass a cafeteria, where the tables are placed so that you almost have to walk through the seated diners. A branch of the library offers internet workstations, but not in cubicles: in a separate zone defined by two parallel walls. You get the feeling that you’re in a buzzing bazaar, surrounded by activity.

The glass office walls mean that you have to give up some privacy; but the potential benefit is an increase in collaborative work. The new waist-high cubicles being sold by Steelcase and Herman Miller allow everyone to see everyone else, too. But even the most innovative organization sometimes needs quieter, more private spaces, and the upper floors have meeting rooms and lecture spaces. But these are like pods off to the side of the main flow of activity. And at the Stata Center, the main flow is group genius at work.

High executive pay and the collaborative economy

Call it collective intelligence, Web 2.0, swarming, or crowdsourcing—we’re supposed to be a new kind of world where collaboration and loosely structured groups always win. So why are senior executives making so much more than everyone else? Last Friday the New York Times reported that Office Depot CEO Steve Odland made $12 million, which is more than four times what the second highest paid executive there makes. In 2004, the average CEO made, on average, 431 times more than the rank-and-file worker; in 1990, it was “only” 107 times more. If it’s all about collaboration, then why are a few superstars making all the money?

Most economists argue that superstar salaries make sense, and not only for CEOs. Take pop stars: Princeton economist Alan B. Krueger studied the money they made from their concert tours between 1982 and 2003, and found that in 1982, the top one percent made 26 percent of all the revenue, where in 2003 their share jumped to 56 percent. Take sports: Twenty years ago, the best paid baseball player was Gary Carter, who earned $2.4 million from the New York Mets—41 percent more than the 25th-ranked player. This season, the top-paid player, Yankees Roger Clemens, is making $28 million, more than twice as much as the 25th ranked player. Even American universities, long resistant to market forces, are embracing the superstar phenomenon. Hiring one big-name professor can raise a school’s reputation faster than hiring ten mid-level scholars—and that professor can easily make twice as much as his mid-level colleagues.

By way of explanation, economists note that organizations are more complex and more global than ever before, and that the competition for top talent is more severe. When it comes to pop music and sports, they point out that the globalization of American sports means that more money is coming in; and the psychology of the fans leads them to glorify specific players. You can only wear one player’s number on your jersey when you go to the game. So economists conclude that small differences in ability can translate into huge differences in pay.

But when the rank and file keep hearing about the benefits of collaboration and teamwork, you can’t blame them for being cynical. Is all this talk about collaboration really just a sham?

No, and the new science of collaborative networks resolves this apparent paradox. First, scientists have discovered that it’s common for networks to have positions of great power, even when the network depends on the collective actions of everyone to succeed. Second, it’s not often realized that CEOs today are, in fact, extremely effective at fostering collaborative networks, both in their organization and with other organizations. CEOs are paid more not only because their companies are larger, but also because their companies participate in extensive collaborative webs with other companies, other countries, and complex networks of customers. Third, the superstars of today get all of their earning power from the network that they represent. Pop singers and baseball players are paid more because their fan base is larger, with new media outlets overseas and with more effective marketing that leads to greater fan loyalty.

As collaborative networks become more powerful, the salaries of those who can create and manage them grows. The growth in executive pay is an outcome of the growth of collaborative networks. Superstars get all of their power from us.