Jill Lepore, a professor of history at Harvard and writer for the New Yorker, has written a critique of Clayton Christensen’s theory of disruptive innovation that is worth thinking through. Christensen’s The Innovator’s Dilemma (the dilemma is for firms to continue making the same decisions that made them successful, which will lead to their downfall) has been incredibly influential since its 1997 publication, and has moved the concept of disruptive innovation from its arcane Schumpeterian origins into modern business practice in a fast-changing technological environment. Disrupt or be disrupted, innovate or die, become corporate strategy maxims under the theory of disruptive innovation.
Lepore’s critique highlights the weaknesses of Christensen’s model (and it does have weaknesses, despite its success and prevalence in business culture). His historical analysis, the case study methodology, and the decisions he made regarding cutoff points in time all leave unsatisfyingly unsystematic support for his model, yet he argues that the theory of disruptive innovation is predictive and can be used with foresight to identify how firms can avoid failure. Lepore’s critique here is apt and worth considering.
Josh Gans weighs in on the Lepore article, and the theory of disruptive innovation more generally, by noting that at the core of the theory of disruptive innovation lies a new technology, and the appeal of that technology (or what it enables) to consumers:
But for every theory that reaches too far, there is a nugget of truth lurking at the centre. For Christensen, it was always clearer when we broke it down to its constituent parts as an economic theorist might (by the way, Christensen doesn’t like us economists but that is another matter). At the heart of the theory is a type of technology — a disruptive technology. In my mind, this is a technology that satisfies two criteria. First, it initially performs worse than existing technologies on precisely the dimensions that set the leading, for want of a better word, ‘metrics’ of the industry. So for disk drives, it might be capacity or performance even as new entrants promoted lower energy drives that were useful for laptops.
But that isn’t enough. You can’t actually ‘disrupt’ an industry with a technology that most consumers don’t like. There are many of those. To distinguish a disruptive technology from a mere bad idea or dead-end, you need a second criteria — the technology has a fast path of improvement on precisely those metrics the industry currently values. So your low powered drives get better performance and capacity. It is only then that the incumbents say ‘uh oh’ and are facing disruption that may be too late to deal with.
Herein lies the contradiction that Christensen has always faced. It is easy to tell if a technology is ‘potentially disruptive’ as it only has to satisfy criteria 1 — that it performs well on one thing but not on the ‘standard’ stuff. However, that is all you have to go on to make a prediction. Because the second criteria will only be determined in the future. And what is more, there has to be uncertainty over that prediction.
Josh has hit upon one of the most important dilemmas in innovation — if the new technology is likely to succeed against the old, it must offer satisfaction on the established value propositions of the incumbent technology as well as improving upon them either in speed, quality, or differentiation. And that’s inherently unknown; the incumbent can either innovate too soon and suffer losses, or innovate too late and suffer losses. At this level, the theory does not help us distinguish and identify the factors that associate innovation with continued success of the firm.
Both Lepore and Gans highlight Christensen’s desire for his theory to be predictive when it cannot be. Lepore summarizes the circularity that indicates this lack of a predictive hypothesis:
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. … When an established company succeeds, that’s only because it hasn’t yet failed. And, when any of these things happen, all of them are only further evidence of disruption.
What Lepore brings to the party, in addition to a sharp mind and good analytical writing, is her background and sensibilities as an historian. A historical perspective on innovation helps balance some of the breathless enthusiasm for novelty often found in technology or business strategy writing. Her essay includes a discussion of the concept of “innovation” and how it has changed over several centuries (having been largely negative pre-Schumpeter), as has the Enlightenment’s theory of history as being one of human progress, which has since morphed into different theories of history:
The eighteenth century embraced the idea of progress; the nineteenth century had evolution; the twentieth century had growth and then innovation. Our era has disruption, which, despite its futurism, is atavistic. It’s a theory of history founded on a profound anxiety about financial collapse, an apocalyptic fear of global devastation, and shaky evidence. …
The idea of innovation is the idea of progress stripped of the aspirations of the Enlightenment, scrubbed clean of the horrors of the twentieth century, and relieved of its critics. Disruptive innovation goes further, holding out the hope of salvation against the very damnation it describes: disrupt, and you will be saved.
I think there’s a lot to her interpretation (and I say that wearing both my historian hat and my technologist hat). But I think that both the Lepore and Gans critiques, and indeed Christensen’s theory of disruptive innovation itself, would benefit from (for lack of a catchier name) a Smithian-Austrian perspective on creativity, uncertainty, and innovation.
The Lepore and Gans critiques indicate, correctly, that supporting the disruptive innovation theory requires hindsight and historical analysis because we have to observe realized outcomes to identify the relationship between innovation and the success/failure of the firm. That concept of an unknown future rests mostly in the category of risk — if we identify that past relationship, we can generate a probability distribution or a Bayesian prior for the factors likely to lead to innovation yielding success.
But the genesis of innovation is in uncertainty, not risk; if truly disruptive, innovation may break those historical relationships (pace the Gans observation about having to satisfy the incumbent value propositions). And we won’t know if that’s the case until after the innovators have unleashed the process. Some aspects of what leads to success or failure will indeed be unknowable. My epistemic/knowledge problem take on the innovator’s dilemma is that both risk and uncertainty are at play in the dynamics of innovation, and they are hard to disentangle, both epistemologically and as a matter of strategy. Successful innovation will arise from combining awareness of profit opportunities and taking action along with the disruption (the Schumpeter-Knight-Kirzner synthesis).
The genesis of innovation is also in our innate human creativity, and our channeling of that creativity into this thing we call innovation. I’d go back to the 18th century (and that Enlightenment notion of progress) and invoke both Adam Smith and David Hume to argue that innovation as an expression of human creativity is a natural consequence of our individual striving to make ourselves better off. Good market institutions using the signals of prices, profits, and losses align that individual striving with an incentive for creators to create goods and services that will benefit others, as indicated by their willingness to buy them rather than do other things with their resources.
By this model, we are inherent innovators, and successful innovation involves the combination of awareness, action, and disruption in the face of epistemic reality. Identifying that combination ex ante may be impossible. This is not a strategy model of why firms fail, but it does suggest that such strategy models should consider more than just disruption when trying to understand (or dare I say predict) future success or failure.