Clayton M. Christensen

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“The Real Test Of A Sweeping Business Hypothesis Is Whether Or Not It Has Predictive Power”

January 26, 2016 in Excerpts, Science/Tech, Urban Studies | Permalink

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The particular rules Clayton Christensen laid down for disruptive innovation probably don’t much matter because the world doesn’t exist within his constructs, but ginormous companies (even entire industries) being done in by much smaller ones has become an accepted part of life in the Digital Age.

In trying to explain this phenomenon, Christopher Mims of the Wall Street Journal explores the ideas in Anshu Sharma’s much-debated article about Stack Fallacy, which argues that companies moving up beyond their core businesses are likely to fail (Google+, anyone?), while those moving down into the guts of what they know have a far better chance. For an example of the latter, Mims writes of the ride-sharing sector. An excerpt:

To really understand the stack fallacy, it helps to recognize that companies move “down” the stack all the time, and it often strengthens their position. It is the same thing as vertical integration. For example, engineers of Apple’s iPhone know exactly what they want in a mobile chip, so Apple’s move to make its own chips has yielded enormous dividends in terms of how the iPhone performs. In the same way, Google’s move down its own stack—creating its own servers, designing its own data centers, etc.—allowed it to become dominant in search. Similarly, Tesla’s move to build its own batteries could—as long as it allows Tesla to differentiate its products in terms of price and/or performance—be a deciding factor in whether or not it succeeds.

Of course, the real test of a sweeping business hypothesis is whether or not it has predictive power. So here’s a prediction based on the stack fallacy: We’re more likely to see Uber succeed at making cars than to see General Motors succeed at creating a ride-sharing service like Uber. Both companies appear eager to invade each other’s territory. But, assuming that ride sharing becomes the dominant model for transportation, Uber has the advantage of knowing exactly what it needs in a vehicle for such a service.

It is also worth noting that the stack fallacy is just that: a fallacy and not a law of nature. There are ways around it. The key is figuring out how to have true, firsthand empathy for the needs of the customer for whatever product you’re trying to build next.•

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“The Prediction Of The Theory Would Be That Apple Won’t Succeed With The iPhone”

June 20, 2014 in Books, Excerpts, Science/Tech, Urban Studies | Permalink

My main objection to the 10,000-hour rule is that it cherry-picks particular pieces of research that provide a nice round number for a narrative attempting to make sharp an old saw (“Practice Makes Perfect”). It tells a macro story that doesn’t gibe with the micro, trying to pitch a camping tent over an entire city, stretching the fabric beyond its capacity for coverage.

The cult of Disruption is not dissimilar in how it goes about building its case. In the business world and beyond, radical innovation and its ability to replenish is revered, sometimes to a jaw-dropping extent. In one of my favorite non-fiction articles of the year, “The Disruption Machine,” Jill Lepore of the New Yorker takes apart the bible behind the idea, Clayton M. Christensen’s The Innovator’s Dilemma, which like the 10,000-hour rule, builds its case very selectively and not necessarily accurately. An excerpt:

“The theory of disruption is meant to be predictive. On March 10, 2000, Christensen launched a $3.8-million Disruptive Growth Fund, which he managed with Neil Eisner, a broker in St. Louis. Christensen drew on his theory to select stocks. Less than a year later, the fund was quietly liquidated: during a stretch of time when the Nasdaq lost fifty per cent of its value, the Disruptive Growth Fund lost sixty-four per cent. In 2007, Christensen told Business Week that ‘the prediction of the theory would be that Apple won’t succeed with the iPhone,’ adding, ‘History speaks pretty loudly on that.’ In its first five years, the iPhone generated a hundred and fifty billion dollars of revenue. In the preface to the 2011 edition of The Innovator’s Dilemma, Christensen reports that, since the book’s publication, in 1997, ‘the theory of disruption continues to yield predictions that are quite accurate.’ This is less because people have used his model to make accurate predictions about things that haven’t happened yet than because disruption has been sold as advice, and because much that happened between 1997 and 2011 looks, in retrospect, disruptive. Disruptive innovation can reliably be seen only after the fact. History speaks loudly, apparently, only when you can make it say what you want it to say. The popular incarnation of the theory tends to disavow history altogether. ‘Predicting the future based on the past is like betting on a football team simply because it won the Super Bowl a decade ago,’ Josh Linkner writes in The Road to Reinvention. His first principle: ‘Let go of the past.’ It has nothing to tell you. But, unless you already believe in disruption, many of the successes that have been labelled disruptive innovation look like something else, and many of the failures that are often seen to have resulted from failing to embrace disruptive innovation look like bad management.

Christensen has compared the theory of disruptive innovation to a theory of nature: the theory of evolution. But among the many differences between disruption and evolution is that the advocates of disruption have an affinity for circular arguments. If an established company doesn’t disrupt, it will fail, and if it fails it must be because it didn’t disrupt. When a startup fails, that’s a success, since epidemic failure is a hallmark of disruptive innovation.”

 

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