THREE

The Old Innovator’s Dilemma versus the New Innovator’s Dilemma

CHAPTER SUMMARY: This chapter provides an update to Clayton Christensen’s insightful model of how companies experience and deal with innovation in a world in which disruption no longer comes only from bottom-up attacks and instead can come from any direction. We create a model, which we call the New Innovator’s Dilemma, that explains this new reality, and then illustrate these omnidirectional disruptions in five sectors: media, retail, e-commerce and voice commerce, transportation and logistics, and finance. Then we dive into specific detail on some case studies: Amazon Go, Allbirds, and Tesla. Last, we study second-order disruptions in the context of the New Innovator’s Dilemma.

When the late highly respected Harvard Business School professor Clayton Christensen published his best-selling book The Innovator’s Dilemma in 1997,¹ the world was early in the digital explosion that accompanied the widespread adoption of the Internet. Christensen posited that good-enough technological innovation would allow startups to attack lower-end product categories in various market sectors. The innovations would initially be inferior to incumbent processes and technology, leading legacy companies to dismiss the potential of the upstart firms and their technology; but inevitably, Christensen argued, the upstart firms and their technology would swim upstream and disrupt the entire industry over time by making goods of comparable or superior quality available at considerable cost savings.

Christensen found in his research that legacy companies were poorly equipped to adapt to disruptive innovations, for a variety of reasons, including the need to keep producing large revenues from existing products that would be cumbersome and risky to continually improve. He recommended that firms facing this sort of disruption open up a second company or create a separate branch, independent of the parent company. The new organization’s task would be to create a competitor, grow the competitor, and ultimately cannibalize the parent company and allow the new subsidiary to continue capturing value for the original company and its shareholders.

This is surely an oversimplification of Christensen’s original theory, which has been updated since. But The Innovator’s Dilemma arose in a different technological epoch, and its prescriptions are themselves being disrupted by converging exponential technologies. Technology development and product adoption are occurring so much faster today than even a decade ago that the nature of the innovation game has changed radically. A host of compounding factors has created an entirely new innovator’s dilemma game, one far more complex and difficult to navigate than the older scenario in which a new competitor making cheaper steel rebar and bottom-feeding on the least lucrative part of the market will swim upstream. And understanding the rules of this new innovation game is essential to playing it well.

Here are some of the most important ways in which the game has changed:

•   The competition no longer comes from your industry alone; it may be, as Peter Diamandis once told me, two kids in a garage building an exponential technology.

•   Innovation in a business model triumphs over innovation in products, and platforms triumph over business models.

•   Companies that adopt technology sooner and more successfully gain an exponentially increasing advantage. Those that don’t lead the disruptions become their casualties.

•   The information now available has shifted power from seller to buyer; intellectual capital and brand no longer lock in the customer. You either build loyalty via value and innovation—or perish.

•   The very nature of trust has changed. It was formerly institutions whose trust mattered; now it is individuals. A company’s reputation rests on what an individual or community thinks of it, and ratings and reviews have become more important than brands and advertising.

•   When it comes to management, command no longer works; management occurs through communication and persuasion.

•   Innovation thrives in diversity, and it is your people who make it happen. These people, the “collective,” can solve problems—or create them.

•   Joining a startup rather than a large, established company is no longer regarded as risky; potential employees often perceive it as the fastest path to career advancement and the place for top performers.

The essential point of all these changes is that innovation is the key to business survival—innovation is a bottom-up process, not a top-down one. And underlying breakthrough innovation is the reality that everything that can be digitized is being digitized—and rapidly.

Improvements in computing have enabled first-order exponential infrastructure advancement in storage cost, network distribution and bandwidth, and sensor cost. With such improvements continuing, costs of all vectors are falling rapidly. For this reason, second-order disruptions are now being joined by third-order disruptions of the way systems fit together and of the way we interact with our technology.

Trust is a fine example. Public trust in systems such as Uber rests on our social recognition that online reputation systems can be effective; perhaps even more effective than legacy reputation systems. So we may feel in some ways more comfortable getting into a stranger’s car than into a Yellow Cab, even though Yellow Cab is a brand that has been around for many decades and is a well-known quantity. These trust systems, such as Yelp and eBay, couldn’t have evolved without the Internet, ubiquitous access, and social acclimatization to online trust.

All the changes that make second-order disruptions possible link directly or indirectly back to Moore’s law and our rapid improvements in digital systems—and to the continuing pace of those improvements. As we look at the smartest companies that have taken advantage of these disruptive exponential advances, we see novel ways of approaching business with an eye to the future—even, in the case of Netflix, when the company’s legacy business of renting DVDs appeared to be a lucrative standalone venture.

This brings us to what we’ll call the New Innovator’s Dilemma. Today, competition and disruption can come from anywhere: from below, from above, from adjacent fields, and from totally unrelated companies. Dollar Shave Club came literally out of nowhere, almost overnight; and Uber did not work from the bottom of the taxi market up, as Christensen’s model dictates, but began as a way to call expensive limousines with a smartphone, pivoting to the mass market only after the company had attained a clear product–market fit. And Tesla began with an expensive sports car on par with a Ferrari and accessible to just as small a portion of the population.

Because innovation can come from any direction, legacy companies have to keep watch in all directions for upstarts.

The new diversity of attack vectors dictates that companies must have new strategies for dealing with disruption. Christensen’s prescription was largely that, in order to counter a disruptive entrant coming from the bottom up, a legacy company should spin out a competing upstart free to compete from the bottom up. The New Innovator’s Dilemma stipulates that competition can arrive suddenly and wallop higher-end, high-margin products, causing a more existential threat. In the span of a few years, the Apple Watch has cast doubt over the future of the market for independent fitness trackers (which, in part, is why leading fitness tracker Fitbit sold to Google after taking a battering on the public markets). No longer the mythical frog in the pot unnoticing of the water’s rising temperature, legacy companies are the frog leaping about trying to understand how to respond to the boiling cupful of water from nowhere that has landed on its head.

One thing is clear: the pace of change and the breadth of innovation have pushed Innovators’ Dilemmas new and old into entirely new territory.

From Netflix to Hulu to Cheddar and BuzzFeed: Massive Media Disruptions

When Netflix CEO and founder Reed Hastings decided to tackle the DVD business, he planned to use streaming media over the burgeoning broadband Internet to create an over-the-top (OTT) media service: a one-to-one relationship with customers. This ploy sought to take custom not only from Blockbuster (Netflix’s rival) but also from large media organizations that controlled content production and the content-transmission pipes (cable and satellite television). Hastings knew, too, that the fate of his company depended on net neutrality, a legal principle that proscribes transmission companies’ discrimination against content providers. It was, in part, this distribution plan that enabled Netflix to build a business that accounts for more than 12 percent of global bandwidth consumption (which its subscribers pay for).²

Creating a streaming content behemoth was highly expensive. Netflix hired talented programmers by the dozen, many of them on seven-figure annual salary packages. The company became the largest consumer of cloud-computing capacity on Earth, paying tens and then hundreds of millions of dollars per annum. It had built the world’s largest content-distribution company, without owning infrastructure and with minimal capital expenditures.

Hastings had rightly gambled that costs of bandwidth and cloud computing would continue to fall and that Netflix would benefit from that. Netflix was also taking a large gamble on the power of algorithms—code and software—to wring more efficiency out of bandwidth. In the face of the legacy media empires that had been built by installing many billions of dollars’ worth of infrastructure—servers, data centers, and so on—Hastings’s approach took vision and daring.

Of course, someone had to pay for the infrastructure that Netflix rented—and that was largely Jeff Bezos and Amazon, who first cracked the nut of rented computing on a massive scale. Amazon, one of the companies that best understands Moore’s law, turned the business of selling partial chunks of computing into an incredible windfall of its own that has become the largest source of profits for the giant that Bezos built. Amazon used its negotiating power to obtain lower prices on ever-better technology even in areas less affected by the Moore’s law trends, including storage, databases, bandwidth, SMS, email services, and nearly every other computation-dependent infrastructure capability that modern organizations depend upon.

The Fight for Attention and the Massive Shift in Valuations of Media Companies

In the footsteps of Netflix followed Hulu. Owned by a group of major content producers—including the United States’ largest cable-television providers, Disney and Comcast—Hulu was designed to compete directly with Netflix, turning the tables on the upstart and enjoying all of the benefits in costs and distribution that Netflix did in order to grow so quickly. This was the revenge of the content studios (principally Disney and Comcast) and the owners of content-transmission pipes (including Comcast again), both of which Netflix had outwitted during its rapid rise. Hulu used a pure over-the-top media-service ploy, following Netflix’s tactics to the letter, building an infrastructure in the cloud and seeking to access customers via broadband data connections that customers paid for as part of their monthly telecommunications bills rather than in traditional cable-television slots for which the content networks, such as HBO or ESPN, had to pay high slotting fees to companies such as Comcast.

What made this business model possible was laws preventing telecoms and cable companies from discriminating against content providers, enabling customers to use their allocated broadband as they saw fit for any service, including Netflix. The knowledge of how to build and run an extensive streaming video network had spread as the crew that had created Major League Baseball’s excellent streaming capability in the United States began to outsource its expertise—and suddenly, in the late 2010s, every major content provider was striving to offer an OTT service of its own. The competition also included Google’s YouTube, with its application YouTube TV, a strong and clear attack from an adjacent precinct of the media industry.

But perhaps the purest iterations of this media disruption arose from the new content upstarts such as BuzzFeed. Founded by MIT Media Lab alumnus Jonah Peretti, BuzzFeed sought to use social content’s boundless replicability to attract participation and consumption. An unending stream of videos of the number of rubber bands required to burst a watermelon complemented listicles recycling trivia content, aiming to capture consumer attention and to keep it. BuzzFeed had taken brilliant advantage of its recognition that the modern Internet essentially was a vast marketplace for people’s attention and that the catchiest offerings won—and it recognized specifically that the Internet had severely undermined the value of old-style journalism. A story painstakingly reported for months by an investigative reporter at a major legacy publication had become no more valuable economically than a copy-cat summary with no real reporting posted hastily by BuzzFeed (although much of the credit for this strategy goes to a previously founded publication, The Huffington Post).

Legacy publications railed against the practice as a form of theft. But BuzzFeed continued to expropriate “eyeball” time, and legacy media brands struggled to hold their readerships. Even today BuzzFeed remains far more valuable than many established media properties, as evident in the fire sale of Time, Inc. and once-prized properties such as Fortune and Sports Illustrated. (Nonetheless, BuzzFeed itself hired a team of journalists for original reporting, but it had to reduce the unit due to its unprofitability.)

And this brings us, ironically, to Cheddar. A video-programming startup launched by Jon Steinberg, who had served as the C.O.O. of BuzzFeed for four years, Cheddar strove to meld the cheap but engaging content style of BuzzFeed with the OTT video-programming strategy of Netflix and Hulu. Steinberg used the lessons of Hastings (Netflix) and Peretti (BuzzFeed) to spin up a mini-television and video empire. Reading the unbundling of content perfectly, Steinberg secured distribution deals with legacy cable-connected providers hungry for millennial content, simultaneously mounting a strong OTT campaign to sell directly to consumers. And Steinberg and Cheddar hit paydirt. Having founded the company in early 2016, Steinberg sold it for $200 million to Altice Media in the summer of 2019,³ a whopping return after just three years for investors who had put just over $50 million into it, and a startling juxtaposition to long-established brands such as BusinessWeek, which sold for less than $5 million in cash.⁴

Retail Totally Disrupted: The Amazon Juggernaut (and Allbirds)

In October 2018, after more than 130 years in business, the iconic U.S. retailer Sears, Roebuck and Company filed for bankruptcy.⁵ From modest beginnings as a mail-order vendor of watches direct to consumers, Sears had become the largest retailer in the United States. At bankruptcy, Sears was a shadow of its original self. The flagging retailer had struggled to adjust to the digital age and had found itself tied to decrepit stores in increasingly undesirable locations. Served by a revolving door of managers, Sears struggled to create a culture that would allow it to evolve and innovate out of its troubles, and a number of rejuvenation initiatives ultimately failed. On top of its poor locations, spotty service, and questionable product mix, Sears had found itself saddled with dated software systems that it had failed to upgrade. Constantly on a back foot, it had also found itself unable to take advantage of new personalization, delivery, or A.I. technologies and keep up with its retail competitors.

Yet even the demise of the country’s formerly largest and most powerful retailer fits a common pattern. The 2010s have been a decade of turmoil in the retail industry, worldwide, with dozens of publicly traded retailers having failed. Other major retailers that have been struggling to grow, such as Gap stores, have closed hundreds of underperforming locations; and around the developed world, malls have closed, leaving behind empty hulks.

The pall at the mall has suited one giant player just fine. Amazon, the retail juggernaut, has precipitated the decimation of retail perhaps more than any other business. The increasing trend toward shopping online has rendered most physical locations (which function as distributed warehouses) expensive albatrosses, and traditional retailers have found themselves forced to compete in technology-intensive e-commerce. Amazon’s meteoric rise is worth examining closely.

The tale of Amazon’s rapid transformation from a bookstore into a technology giant and subsequently into an “everything” store offering hundreds of millions of items is well known. Beneath the surface, the layers of disruption it has engendered are staggering. Amazon has disrupted or is in the process of disrupting every important facet of retail commerce. Because it is so willing to invest large amounts of money in anticipation of longer-term returns, Amazon can take gambles that few others will. And it is doing so by making effective use of the radical technology breakthroughs now available to the world of business.

Online Commerce and Voice Commerce

In the United States, anywhere between 25 percent and 50 percent of all searches for products online begin either on Amazon.com or on Amazon’s mobile app.⁶ Despite Google’s dominance in the field of search engines, Amazon has come to dominate product search. It does this with maniacal focus on making product search work well for customers. This shift is in its relatively early stages: growth of e-commerce continues to accelerate, at the cost of physical retail sales. Within Amazon’s online product search, every element of the customer experience is analyzed in minute detail and tuned so finely that most product designers in the e-commerce realm hew closely to the Amazon method of building an online store.

Not only has Amazon built a dominant platform in the fastest-growing retail-sales medium, it has also become a major player in the realm of voice commerce—and Amazon has traditionally struggled with consumer electronics. The voice-assistance market has become the fastest-growing market in technology, and Amazon is in the lead with products powered by its Alexa voice assistant. Early research indicates too that Amazon skews voice-search results in favor of its own products (as it does in product searches on Amazon.com).⁷

Transportation and Logistics

By convincing hundreds of millions of customers to expect every purchase to arrive in two days or less, Amazon set a new norm in retail. Today, this norm is about to give way to an even more radical one: same-day delivery of most purchases. In the process, Amazon has disrupted the transportation and logistics segment that has become vital to retail. Its fleets of jets and trucks deliver from its dozens of distribution centers, and it offers logistics and distribution services to millions of other companies. In other words, Amazon is the largest logistics and transportation company most people don’t know about. If we include its extended fleet of third-party delivery partners, it may even have become one of the largest five logistics and delivery companies in the world.

Amazon is also leading transformation in transportation: actively experimenting with drone delivery, an increasingly promising final-hop mode as battery energy density continues to improve and drone costs continue to fall.⁸ In the United Kingdom, Australia, and the United States, drone delivery is likely to become legal and common within the next five years. This would potentially allow Amazon to completely own its supply chain, dispensing with the third-party final-hop delivery partners that are both a major expense and the source of its greatest uncertainty in the journey from warehouse to customer doorstep.

In its own warehouses, Amazon is among the leaders (which include its Chinese competitor Alibaba) in deploying robots to raise productivity, and has purchased several leading robotics startups, such as Kiva Systems, to cement its position. These robots are rapidly replacing human labor. For example, Amazon is using giant robotic arms to stack bins of goods and using low-set 300-pound wheeled robots to ferry stacks of bins around warehouse floors, in a dance choreographed for efficiency. Humans used to stack the bins and push the stacks; now they watch the robots and troubleshoot. Amazon’s Staten Island facility, in New York City, is nearly 80,000 square meters in area; other Amazon facilities are larger still. No other major retailer outside China (with the exception of Walmart) has achieved a similar degree of automation on such a scale. In the one instance in which a competitor was bettering Amazon in warehousing, logistics, and automation—Diapers.com—Amazon bought the competitor.

Finance

Retail margins are traditionally thin, stretched by supply chains that demand advance payment for goods that consumers may not purchase for a full year. Amazon now offers loans and other financing to tens of thousands of merchants who do business on the site, often undercutting other financing options. What helps it do this well is its access to the sales performance of these vendors, which provides detailed insights into likely profit margins. It, too, has massive reams of data and insights into the detail, at every point in the supply chain, of how companies operate. And, because Amazon also manufactures its products for rebranding (and, in profitable categories, does so aggressively), it also knows how much each item should cost to make, enriching its insights into which vendors will warrant loans of what size and on what terms.

Amazon is not alone in the quest to break into the finance industry. Newer point-of-sale systems too, such as Square, offer credit on the basis of observable cash flow. A new generation of online-only, mobile-first banks, such as Monzo in the United Kingdom, has shown that providing a vastly superior customer experience at an unbeatable price can win wide adoption even in the most trust-sensitive industries—and even without physical branches.

A large clutch of insurance startups now seek to streamline a cumbersome legacy style of underwriting, using algorithms that can quickly access credit history, look at a phone image or a Google Earth photo, and study an applicant’s online behavior in order to issue a policy in a matter of seconds. Western Union, the legacy provider of money-transfer services, is being challenged not only by now-entrenched new arrivals such as PayPal but also by even cheaper over-the-top companies such as TransferWise, which are forcing banks to drop some of their most lucrative and exorbitant legacy fees: their levies on wire transfers.

Amazon Go and Physical Stores

Any of the dozens of Amazon Go stores now springing up in chic districts of leading cities around the globe feel initially like an upscale convenience store or small market. A small number of staff members walk around offering help. One thing you won’t need their help with is paying for your purchases. To enter the store, you need to launch your Amazon Go phone app; once it is running on your smartphone, you can walk out with any purchases you want to make, without even stopping at a register or a counter.

Of course, retail has been heading toward cashier-less stores and markets for many years, but Amazon Go’s robotic functions pervade every aspect of its interactions with shoppers. Ubiquitous cameras capture every shopper activity, track eye motions, and guide restocking decisions, and Amazon will probably deploy its advanced facial-recognition capabilities in the future to eliminate even the need for a phone app; its key to your wallet, bank account, and credit card will be your face. Even now, each Amazon Go store is akin to a human-powered A.I. laboratory, connected back to Amazon’s massive hive mind. Amazon Go, along with its Whole Foods grocery store chain, allows the company to finally close the loop between physical and online behaviors, giving it the most complete picture of buyer behavior that any company in history has enjoyed. Online and offline interaction inform each other for increasingly effective decisions.

Amazon Is Remaking All of Retail

Considering the areas in which Amazon is heavily investing in technology and innovation makes clear that the company is remaking the entire retail industry. This is causing all manner of disruption, as traditional retail struggles to adapt and to keep pace. None of this is to say that the smartest existing retailers can’t compete and innovate, but competition with large, established firms is coming not only from the likes of Amazon but also from skyrocketing new startups. We touched on this with the story of Dollar Shave Club, which used a marketing innovation and a slightly tweaked business model—razors as a subscription service—to capture market share before legacy companies were able to react.

Another example of this, which is actually more Amazon-like, is the eyeglass maker Warby Parker. Selling a product that requires the human touch and a prescription and that is highly dependent on taste was considered, at the dawn of the broadband age, a nearly impossible feat. eBay brokered the sale, but primarily as a peer-to-peer marketplace for used and otherwise non-retail clothing, collectibles, and other items. Then the shoe company Zappos (which, unsurprisingly, Amazon later acquired) was one of the early companies to break into high-touch online retail. Warby not only conquered high touch but also rolled out physical stores, financed by its online presence. Those stores log some of the highest sales turnover per square foot of any physical operation.⁹ (The lead among non-luxury retailers is generally held by Apple.) More impressive still, the pace of development of these upstart retailers is accelerating, via the same trends in technology, business, and consumption that we mentioned in the previous section.

Allbirds: From Zero to $1 Billion in Two Years

The idea seems almost too silly to be true: a comfortable pair of wool sneakers made with advanced fabric technologies and eco-friendly sugarcane foam and favored by elitist venture capitalists and startup founders becomes a billion-dollar company in a few short years. Yet that precisely describes the trajectory of Allbirds, a San Francisco apparel startup that, like Dollar Shave Club, grew rapidly by marketing expertly and directly to customers. Allbirds had something more: a technologically differentiated shoe that resisted odor and was insanely comfortable. The company wove its woolen uppers onto a unique type of foam made from sugarcane residue, creating a near-zero-carbon footprint. And, altruistically, Allbirds published its foam recipe.

First a darling of the tech set, Allbirds went mainstream quickly, selling the vast majority of its product via its own website. As Warby Parker did, Allbirds eventually set up a select group of physical outlets in high-traffic parts of luxury city neighborhoods. Ironically, Allbirds grew so popular that it attracted the attention of none other than Amazon, which pushed out a copycat product in September 2019.

Allbirds combines many elements of earlier successful startups in high-touch products, such as Zappos (with free shoe delivery and return), Warby, Bonobos, and others. Allbirds wove together an innovative product with rapid and effective marketing, using legacy distribution methods to crack massive but staid markets.

The significant difference between the results of the two is most obvious in the pace of disruption: managing to create an entirely new niche, Allbirds disrupted the footwear market in a mere two years.

Because creating vertically integrated retail companies without massive capital outlays is now much easier than ever before, an Allbirds, unlike legacy shoe companies, has a much faster cash-conversion cycle, spending far less time waiting for cash to roll in. Consequently, it does not need to create seasonal collections but can move at its own (faster) pace.

In retail, the “fast fashion” category has been one of comparative growth for a long time; Gap’s Old Navy brand is so much more successful than its sister brands that the company has considered carving out the subsidiary as a separate entity and taking it public. But Allbirds exemplifies how quickly startups from anywhere can capture market share.

Tesla Cars as Software and the Art of the Impossible

After no more than a decade in production, Teslas are the best-selling electric vehicles on the planet. In 2018, Tesla outstripped not only all other automotive brands but also all automotive groups, with delivery of 245,240 units and a 12 percent market share in the plug-in all-electric segment. Tesla’s U.S. unit sales had skyrocketed from 48,000 in 2017 to 182,400 in 2018. Reviewers had lavished praise on Teslas, and the new vehicles had garnered glowing safety ratings. Tesla is a prime case of what happens when a car company chooses to behave like a customer-focused software company such as Apple, which has legendarily charged high fees for a combination of beautiful hardware and slick software. Part of Tesla’s legend is the special acceleration mode, in one of its models, that endows the vehicle with a time from zero to 60 mph of less than 2.3 seconds, the fastest ever recorded by a production vehicle.¹⁰ CEO Elon Musk hilariously named it Ludicrous Mode. And who wouldn’t want to buy a car capable of a Ludicrous Mode?

In fact, Musk has shaken up the car world by thinking very, very differently and betting on a host of exponential trends that he believes will make Tesla better able to undertake second-order innovation. For starters, Tesla behaves as if a car were a software product that happened to have a skin and seats, rather than vice versa. To be sure, all of today’s cars are software intensive: the average vehicle contains millions of lines of computer code, controlling a host of key systems and onboard computers. But Tesla has, at Musk’s urging, fully embraced the software ethos. It ships frequent software updates to its cars, improving performance and safety constantly. Ludicrous Mode, too, was a software update—and a delightful surprise that led many commentators to compare the speedy software upgrade to “Easter eggs” (surprise gifts or revelations) in video games.

Basing automobile systems squarely in software capable of updates has many benefits: speed, flexibility, and the ability to add new features far more swiftly and easily. Then there is safety, which brings us to Tesla’s unique way of taking advantage of A.I. As noted previously, Tesla treats its cars as an intelligent network. The company constantly collects data from cars on the road, using them both to improve vehicle performance and, more famously, to power the machine-learning systems that will be necessary for driverless cars, and it has the largest library of vehicle road data from which to build autonomous vehicle systems. This is not to say that other car makers are not gathering data; but Tesla built its technology infrastructure to be always on and always in touch with its vehicles, with A.I. central to the company’s strategy.

A third Tesla innovation concerns batteries. This is nearer a linear than an exponential innovation, but it is illustrative of Musk’s thinking. To ensure an ample supply of batteries (one of the elements required for batteries, lithium, being in short supply) at good prices, Tesla decided to build the Gigafactory—one of the world’s largest battery factories. Tesla calculated that mainstream acceptance of its cars would necessitate pricing them at or below comparable internal-combustion vehicles, and that—batteries being the costliest item in driverless cars—battery prices would have to fall. Relying on its own battery factory also gives Tesla much more control over its own fate; nearly all other car makers are ordering batteries from third parties.

Tesla’s ultimate vision is far from realized. Musk has been open about viewing Tesla as a Trojan Horse to remake the world’s energy supply and radically shift our energy sources to renewable ones. Tesla’s home-battery business, which dovetails nicely with the Gigafactory, and Tesla’s solar-panel business (which has been flagging of late)¹¹ hitch Tesla’s fortunes to a runaway exponential freight train: the plummeting costs of solar power panels. In a way, too, Tesla’s trajectory illustrates how innovation and competition can arise from adjacent fields. Tesla is, at heart, less an automobile manufacturer than an interloper from the software ecosystem, with very little car DNA in its workforce.

To say Tesla is already successful may be premature. The company remains heavily in debt, with many short-selling investors betting that it will have to raise more money and pay a hefty price for it—though so far it is these investors who have paid the price for betting against Musk. But Tesla has single-handedly brightened global perceptions of electric cars, doing what dozens of companies have tried but failed to do—and has thereby induced the world’s automotive giants to accelerate their plans for electrics and to invest in autonomous vehicles, in the same way that SpaceX forced the large satellite-launch providers to rethink their legacy approaches to building rockets and boosting satellites into orbit.

The Second-Order Innovator’s Dilemma

A close look at the examples we’ve provided of industry disruptors—Netflix, Amazon, Tesla—reveals that none of them actually meet the criteria for a classic Christensen Innovator’s Dilemma analysis. Tesla entered the market with a very high-end product: its first Roadster is now a collector’s item. The Roadster sold for about $100,000 when it was first released; Tesla has swum downstream since then, and is only now entering the lower end of the vehicle market. Nor did Amazon work from the bottom up: it took a systems-thinking approach and applied it broadly to one industry after another to improve all aspects of that industry. In a sense, what Amazon employed was more an innovative way of thinking about business than an innovative business.

Netflix and the OTT content providers have certainly undercut the costs of legacy cable and pay TV providers; and, of the three, Netflix bears the most resemblance to a classic Innovator’s Dilemma case study. In reality, a technology company masquerading as a content company, Netflix invested heavily in content-delivery technologies using its video-delivery expertise, and in using A.I. to automatically recommend further viewing at the end of every viewing program. This is not bottom up; it is a revolutionary way of engaging with users on a variety of devices, of building an enormous infrastructure on a subscription basis alone. To compare Netflix’s strategy to those of startup manufacturers of steel rebar does the innovative company no justice. In other words, very clearly, the rules of the innovation game have changed. In the next chapter, we will study why legacy companies fail and what company innovation now hinges on.