The Anomalies of Disruption

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Illustration Credit:  Paolo Beghini/Ikon Images

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Innovative examples from Apple, Uber, and Tesla show the importance of expanding views, getting granular, and using multiple models.

On his office door, Clayton Christensen — who at one point I called my teacher, mentor, boss, colleague, coauthor, and, most importantly, friend — had a handcrafted sign saying, “Anomalies Wanted.” Like a good scientist, Christensen believed that the things you didn’t expect provided the richest sources of learning. And indeed, many big changes after 2000 that just feel disruptive don’t quite fit Christensen’s theory of disruptive innovation model.

Lessons from these anomalies — the iPhone, Uber, and Tesla — strengthen our ability to predict the impact of in-process innovations like additive manufacturing and artificial intelligence by showing the importance of expanding our view, getting granular in our analysis, and using multiple models to analyze complex change.

Recall the basic idea of disruption, summarized in Christensen’s 1997 blockbuster book The Innovator’s Dilemma: Incumbents generally win when the game is about sustaining innovations that improve along known performance dimensions and lose to upstarts when the game is about disruptive innovations that intentionally trade off performance along traditional dimensions in the name of simplicity, convenience, or affordability.

The driver of disruption is the resource allocation process inside companies. That diffuse, difficult-to-manage process naturally prioritizes innovations that appeal to a company’s best customers. Those customers initially dismiss disruptions because of their limitations, so disruptive innovators take root with customers at the fringes of the market who relish their simplicity and affordability. Since companies innovate faster than people’s lives change, that which is initially not good enough for mainstream customers gets better and better until the disrupter combines good-enough performance with better simplicity and affordability. The market leader, which did everything you are supposed to do, fails in the face of disruptive change.

Anomaly 1: The iPhone

Here’s what Christensen had to say about the iPhone when it launched: “The iPhone is a sustaining technology relative to Nokia. In other words, Apple is leaping ahead on the sustaining curve [by building a better phone]. But the prediction of the theory would be that Apple won’t succeed with the iPhone. They’ve launched an innovation that the existing players in the industry are heavily motivated to beat: It’s not [truly] disruptive. History speaks pretty loudly on that, that the probability of success is going to be limited.”


Christensen would later recant. Why? He said he compared the iPhone to other phones, where he really should have been comparing it to laptop computers. And when you make that comparison, the disruptive nature of the iPhone comes into focus.

The early iPhone certainly had its limitations. Its battery didn’t last long. Typing wasn’t easy. There were only a handful of applications. It had new advantages, such as a cutting-edge internet browser and the kind of radical simplicity that had been Apple’s hallmark for decades. In classic disruptive fashion, the iPhone brought computing to new contexts, where people were delighted with a somewhat limited product.

Also, the iPhone wasn’t just a product play by Apple, it was an ecosystem play. Ron Adner from the Tuck School of Business at Dartmouth College has deeply studied ecosystems in his books The Wide Lens and Winning the Right Game. His research shows how innovation success requires smartly thinking about how to work with suppliers, channels to market, complementary industries, and more. That’s one reason, he argues, that Amazon’s e-reading platform Kindle crushed Sony’s e-reader. Even though Sony’s reader was technologically more sophisticated, Amazon made it incredibly easy to obtain content, making its device significantly more usable.

In classic disruptive fashion, the iPhone brought computing to new contexts, where people were delighted with a somewhat limited product.

Similarly, the full power of Apple’s disruption only became apparent about a year after the iPhone launched. While the elegance of its design captivated reviewers and early adopters, early sales weren’t that great. The browser was cool, but slow networks limited its functionality, and Apple did not allow third-party developers to create applications for the iPhone. Why would it need to? “What’s the killer app?” Steve Jobs said at the iPhone’s launch in January 2007. “The killer app is making calls. It’s amazing how hard it is to make calls on most phones.”

If you were Nokia, Research in Motion, Motorola, Palm, Handspring, or Ericsson, maybe you took solace in the iPhone’s slow start. By the end of 2007, however, Jobs changed course, and it shouldn’t have really been a surprise. When Apple’s iPod music player first came out, it was limited because it seamlessly worked only with Apple’s Mac computers. Then, when Apple ported iTunes to Windows-based computers, the product took off. Jobs had demonstrated that he was willing to be … flexibly controlling.

This time, Jobs announced that Apple would have a software development kit for third-party apps within four months. And the rest is history. In 2023, the App Store generated close to $100 billion in revenues for Apple. By way of comparison, The Coca-Cola Co. earns approximately $50 billion a year in revenue. Think about that the next time you start playing a silly game on your phone.

The anomaly of the iPhone teaches us to expand our view in three ways. First, think carefully about the comparison set. What job does a customer hire an innovation to get done? What else could it hire to get that job done? Second, zoom out to look at the broader ecosystem. Does the innovation change industry dynamics in a broader way? Finally, don’t just look at the snapshot of an innovation at a given time; watch the full movie and be flexible as a company’s full strategy comes into full focus.

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Here is a direct link to the complete article.

Scott D. Anthony (@scottdanthony) is a clinical professor at the Tuck School of Business at Dartmouth College and a senior adviser and managing partner emeritus at growth strategy consultancy Innosight. He is a coauthor of Eat, Sleep, Innovate (Harvard Business Review Press, 2020).

1. R.M. Henderson and K.B. Clark, “Architectural Innovation: The Reconfiguration of Existing Product Technologies and the Failure of Established Firms,” Administrative Science Quarterly, 35, no. (1) (1990): 9-30.

2. G. Petriglieri and J.L. Petriglieri, “The Return of the Oppressed: A Systems Psychodynamic Approach to Organization Studies,” Academy of Management Annals 14, no. (1) (2020): 411-449.



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