Note: This is part of a series of posts explaining the individual parts of The Innovation Matrix. See this post for a description of the full model and what can be done with it.
I presented The Innovation Matrix at a conference last week. After the other three speakers in my session had given their talks (all excellent!), the first question we got threw me for a bit of a loop. The point that was raised was that the guy thought that everything that we had presented was very linear, and not very systems-oriented.
This made me realise that I didn’t make one of the key points that underpins The Innovation Matrix – it’s actually based on complex system thinking. And the key insight that I get from it is this: there is a (sometimes huge) disconnect between the effort you put into innovating, and the return that you realise. The relationship between the two is non-linear.
You can have an extremely high level of Innovation Commitment, and sink large amounts of time and resources into it, and still be lousy at innovating.
The whole point of the matrix is that this non-linearity exists, it surprises people, and we need to be aware of it.
What is the best way to address this?
The most important skill to deploy in complex systems is experimentation. When faced with high levels of uncertainty, and systems that respond non-linearly, we can’t predict in advance which ideas will succeed.
This is why building a culture of experimentation is an essential part of Innovation Competence. This is the approach that is outlined by Peter Sims in his excellent book Little Bets: How Breakthrough Ideas Emerge from Small Discoveries.
I just read another equally outstanding book that discusses a similar approach. It’s by Grant McCracken – Culturematic: How Reality TV, John Cheever, a Pie Lab, Julia Child, Fantasy Football . . . Will Help You Create and Execute Breakthrough Ideas.
In his last book, Chief Culture Officer: How to Create a Living, Breathing Corporation,
Nearly all of his examples come from popular culture (the Old Spice campaign, Andy Samberg on Saturday Night Live, etc.), but the approach that he outlines is actually a general one. Here is how he describes it:
Eventually, I found an idea that helps explain these oddities. I call it Culturematic. A Culturematic is a little machine for making culture. It is designed to do three things: test the world, discover meaning, and unleash value.
Why does Samberg’s standalone production studio work so well for SNL?
It was to give SNL a little spaceship that could go places and do things out of the range of the SNL players. At 30 Rock, no one invests so much as a second in something that might not work. Because the clock is ticking. But The Lonely Island can try stuff until something works. Here, failure is acceptable, because, as Michaels puts it, it’s the guys, not the cast, who “take the risk.”
…
Many Culturematics return nothing. This is not to say they fail. They tell us that this is a tree up which we no longer wish to bark.
That’s experimenting! And that’s how we innovate.
Here is how McCracken describes innovation at Unilever – think about where this would put them on The Innovation Matrix:
British researcher John Kearon recently looked at the innovation record of Unilever, a Dutch-British corporation. The results were surprising. Unilever has a great track record, creating not just new brands and products but entire categories in the U.K. consumer market: laundry powder, fabric softener, margarine, and moisturizing soap. Kearon noticed that none of these discoveries came from the innovation centers Unilever set up in the 1990s. Everything about the innovation centers looked right. They hired the best people. They spent real money. They centralized Unilever’s creative efforts. And as Kearon explains, by and large they failed: The innovation center model is good at creatively farming existing brands and has added significant value to the likes of Dove, Lynx and Flora. However, as a model of innovation it is too centralized, too evidence-based, too marketing-science orientated to have the freedom and contrariness to originate new categories that can create even greater value. Kearon recommends another approach. If you want to innovate as Google, Apple, and Red Bull have, he says, you should follow a couple of rules: Don’t look for big ideas. Seek small ideas that can grow. Fail fast. Fail often. Keep learning and never give up. Excellent, very Culturematic advice.
Very Culturematic, and very Little Bets.
The question at the conference threw me because I hate linear models – they almost never describe the real world. And The Innovation Matrix is not linear. It actually describes a non-linear problem: that we can’t predictably increase our innovation capability simply by increasing our commitment to innovation, or simply by throwing more resources at it.
There is always mystery about which ideas will actually work. This is part of what creates the disconnect.
In a non-linear world, the best strategy is to innovate through experimentation. As Saul Kaplan says: Think Big, Start Small, Scale Fast.
Figuring out how to do this is the best possible first step if you are trying to change your position on The Innovation Matrix, because it’s the best way to actually get better at executing ideas.
(And if you want some tips on how to proceed, I can’t recommend the books by Sims and McCracken strongly enough)
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