Who killed Clayton Christensen?

Who killed Clayton Christensen? Jill Lepore did. With her mightier than a sword, pen that is.

Her article in the June issue of The New Yorker, “The Disruption Machine” is very long and very through in pointing out the flaws of Christensen’s thesis in his book The Innovator’s Dilemma (which is wildly popular and successful by almost any measure).

I once suggested to my editor, the recently wed Donna Carpenter LeBaron, that we do a piece pointing out the incompleteness of Jim Collins’ Good to Great, which isn’t hard to do, but she suggested that it’s better to offer a new solution than to highlight the flaws in the work of someone else.

So here goes.

First, the thumbnail idea of the innovator’s dilemma, I am told, is that organizations spend too much time keeping current customers happy and don’t focus on what the customers of tomorrow will want or need – which is a massive innovation on what they have today. So instead of a company focusing on how to make the best buggy whip, they should instead invest in innovating around the horseless carriage (my example, not Christensen’s).

Creative Destruction, credited to Joseph Schumpeter, became very popular in the middle of the 20th century, and Lepore suggests that Christensen’s thesis is not so different from his, and goes on with many examples of why Christensen’s algorithm for predicting the future of where innovation is needed and who is on the right track is flawed. One example she cites is that Christensen declared the iPhone could not possibly be successful (when it was first announced).

When I read Lepore’s piece, I instead wondered if the simple reason that the innovator’s dilemma is flawed in predicting the future, is because the model, or more precisely, the algorithm, went out of date sometime between Schumpeter and Christensen, and by that I mean that I suspect that something that was a valid assumption, or constant, in Schumpeter’s day is now a variable and Christensen’s model did not take that into account. That assumption / constant being human behavior.

These days when I work with clients, I talk a lot about behavior vectors. As a simple example, Uber wouldn’t have been possible had it not been for the sharp trajectory of the smart phone adoption vector. An even better example is Airbnb. David Brooks wrote in The New York Times how sure he was that Airbnb would fail because people would never trust strangers in their houses. I felt the same way, just as I thought no one would ever pay for a ringtone. In Schumpeter’s day, people were almost identical from one generation to the next – there were no radical shifts in values, notions of privacy (today teenagers will put anything on Facebook), or even the idea of what a phone is (my parents think of a phone completely differently than I do).

Today these changes happen all the time, so predicting which innovations will succeed, it no longer works to look in the rearview mirror, rather it’s likely that looking forward at various behavioral change vectors and what “innovation collisions” are likely, based on intersecting vector trajectories. Innovation collisions, then, are essentially opportunity tipping points.

An asterisk to this is probably behaviors of people in the baby boom era and older – as some or many of them are still in the “constant” category when it comes to behavior predictors using the rearview mirror approach (and Christensen was probably right about the failure of the iPhone with the older crowd). The innovator’s dilemma model might actually still hold up for innovations in the geriatric space because those people are so much more predictable than people in their teens, 20s, even 40s.

These adoption and behavior trajectories change very fast, so that makes it very hard to predict, but it is probably a better indicator than the rearview mirror approach.

-Ric

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