Everything is going faster! Change is accelerating! At least that’s what we hear all the time. What if this platitude reflected a misunderstanding of the nature of disruptions and how they develop? And what if, therefore, it led to the wrong answers by incumbents and startups? Let’s analyze the nature of disruptions and our relationship to time.
It is often thought that a disruption is a sudden phenomenon that takes market incumbents by surprise as they who could not see anything coming, like deers caught in the headlights. But that’s not correct. Consider the example of the low-cost airlines which disrupt the traditional airlines. When did they start? In the 70s! It is in 1975 that Southwest Airlines (SWA) invented the low-cost model (partly by chance, it should be noted) in the United States. For years its customers were mainly students and tourists who, for the first time, could fly within a US state, and then across the whole country when air transport was deregulated in the 80s. The impact on traditional airlines? Nil! Indeed, students and tourists were so-called non-consumers, ie before SWA, they simply could not travel by plane, as it was much too expensive. So at the beginning, SWA did not take any customers from traditional airlines. It grew the overall air travel market, but without pain for them. This largely explains their lack of response because conventional strategy teaches us to respond to competitive attacks in our market, not to somebody who creates a complementary market.
Then as SWA and copycats developed, low-cost air travel became mainstream; the students who used it first had grown up and become professional adults and found it perfectly normal to continue to “travel smart”. That is when, in the years 2000, low-cost really took off. This is also the time when it began to take customers from traditional airlines. Panic set in.
This explains the impression of speed: the disruption develops first almost invisibly (as far as our our performance measurement tools are concerned) for years, then it starts to take customers and there, we “see” it all at once. Hence a disruption develops in a non-linear way: During the first period, incumbents’ reaction is “Why worry?”, during the second period, it is “Oh my god! It is so sudden”. But it is not, it only suddenly accelerates.
In the case of air travel, the reason of the non-linear nature of a disruption is of a social nature: it takes time for a new practice to be socially accepted (here that low cost does not mean ‘dangerous’ and that it is not reserved for the poor). These social changes are typically non-linear: slow at first with some pioneers, and massive when the network effect plays out, when the so-called tipping point is reached. The tipping point is what incumbents see; its slow maturation for years is what we they do not see (or refuse to consider).
The non-linear nature is also sometimes explained by technological constraints. This is the case of artificial intelligence (AI). AI is everywhere these days, at the top of the hype curve and one could have again the impression that this is quite sudden. But again, AI is not recent, far from it: the first works date … from the 50s! As soon as the first computers were invented, researchers thought that it would only take a few years before we would have intelligent machines. It was wildly unrealistic. By the late 90s, after several false starts, a dire conclusion was drawn: we had been much too optimistic about the possibilities of intelligent machines. In 2004, two MIT labor specialists, Frank Levy and Richard Murnane, even wrote that “[…] computers cannot easily substitute humans for tasks such as driving.”
And yet less than 5 years later, the Google car traveled hundreds of thousands of kilometers by driving alone! Again, it seemed to come out of nowhere, but it did not. It relied on more than 50 years of patient work on computers, sensors, storage systems, artificial intelligence, etc. So why this sudden appearance after such a long work? Simply because the technologies on which it relies were not ready. You cannot have a self-driving car until its computer reaches a certain power, until the hard drive reaches a certain speed, and until the size of the necessary sensors reaches a certain minimum, among others things. Not until every single technology you rely on is ready (in terms of speed, size, poser, etc.) can you move on to the next stage. It is intrinsically non-linear.
A disruption is therefore a process, not an event. It emerges and develops, sometimes for years, without any noticeable impact, at least from the point of view of the incumbents, who thus tend to dismiss it. As time passes without visible impact, the dismissal seems more and more justified when, after sometimes a long while, it goes into accelerated mode. And then it generates shock and surprise, but this shock and this surprise are entirely self-inflicted. They result from the inability from incumbents to appreciate the true non-linear nature of the disruption.
Hence, we should not be fooled by naive statements such as “everything goes faster today” because these can cause decision-makers to over-react. Dealing with a disruption requires above all a good understanding of its mechanisms; it is more a matter of patience than reactivity. Nothing shows it more clearly than Nespresso, Nestlé’s flagship product, a project born by chance which took 21 years to reach its break-even point and become the success we know, or the Adobe PDF product, which took ten years to be profitable.
In conclusion, understanding the dynamics of a disruption matters, both for incumbents and for new entrants and startups, and managers’ relationship to time could well be the key to success in the face of disruptions.
More on the Nespresso development saga here Nespresso: when the simplicity of the product hides the complexity of the innovation process. Read more on the topic: How We Underestimate the Disruptive Potential of a New Technology. Also on disruption: Disruption Is Not a Question of Technology, but of Business Model