Google’s business model creates and captures value through advertising. The beauty of Google’s advertising model (i.e., the reason it creates value) is that it based on information about our specific needs, tastes, and intentions. This means a dollar spent advertising with Google is likely to be more efficient than a dollar spent on ads in newspapers. But to make this business model work, Google needs a lot of information about us—what we like doing, what we might want to buy, where we are thinking of going on vacation, whether we have children, and so on. Information is a critical resource for Google’s business model—it could not create value without it. And we are critical resource providers to Google. Our participation in Google’s ecosystem is clearly worth a lot to Google’s shareholders. As of this writing, Google’s market capitalization is about $775.17 billion.18 Google does not pay us one cent for all this valuable information. And here is the crazy thing—we do not seem to mind. We give away this massively valuable resource for free.
How does this happen? Why are we willing to subsidize Google by just giving away our information? Is it just pure generosity? Not really. We give away our information to Google because we have no alternative means to monetize the value from it. There is no market in which we can sell information about what we ate for breakfast, what we might be planning to do this weekend, or what kind of car we like. Why not, you may ask? There seem to be markets for everything. Why is there no market for information? It goes back to what Nobel Prize winner and seminal economic theorist Ken Arrow called “the fundamental paradox of information.” Now known as Arrow’s paradox, it says that the only way to price a piece of information (say, what I ate for breakfast) is to reveal the information. But, once I reveal the information, no one really has to pay for it. Without a market for information through which we could monetize information about ourselves, that information has essentially zero value for us. Before Google, our personal information was like a massive oil reserve trapped underground that no one could access, and the value of anything that cannot be accessed is precisely zero.
The brilliance of Google’s business model is that it figured out a way to access this information by giving us tools that simultaneously performed functions we valued (like Internet search, sending e-mail, keeping calendars, finding videos, etc.) and that automatically collected information about us. Every time we use a Google application, we give the company information. But it’s a quid pro quo—we get to use the applications for free. So we get something we value in exchange for giving Google something that we as individuals are not able to extract value from in the first place.
Facebook follows a similar model, providing its members, for absolutely free, a means to interact virtually with a network of “friends.” But, in return, it gets something really valuable. It gets information about what we are doing, what we like to do, what pieces of news we find interesting, and so on. This is extremely valuable information to advertisers and others interested in influencing our behavior.
Crowdsourced review sites like TripAdvisor, Yelp, and even Amazon also utilize undervalued resources. Reviews are a critical feature of sites selling products and services. These reviews provide a vital source supporting their business models. And yet how much are we paid to provide such a valuable resource? Absolutely zero. The motives for people to contribute to crowdsourced ventures (including open-source software projects) have been widely studied by economists and sociologists. The general conclusion from this research is that people gain a certain degree of psychological satisfaction from sharing their opinions.19 The cost of contributing is the time required to actually write the review. But, remember, there is no additional opportunity cost because there never was a market into which you could sell your independent reviews.
You may have noticed a link between the principle of “exploit-free resources” and the earlier principle of “create value for the ecosystem.” They tend to go hand-in-hand. One of the ways you get access to resources for “free” is to provide something else in return that is valued by those resource contributors. Google and Facebook provide services of tremendous value to their users that they do not even charge for. In essence, this is good old-fashioned bartering. I give you something for free (like my information), and you give me something in return for free (like access to e-mail or a social network). If there is no market for a particular resource, then bartering might just be a good way to access that resource for “free” or at least for a relatively low cost.
Business Model Design Principle 4: Build upon Hard-to-Imitate Resources. Good business model innovations are just as vulnerable to imitation as are good technological innovations. McDonald’s may have pioneered the concept of the modern quick service restaurant chain, but there are now hundreds of rivals competing in the market. Uber and Lyft both offer ride-sharing services based on similar business models (albeit with different strategies). In the video on demand market, Netflix competes with literally dozens of other players who have adopted a similar subscription-based business model. Business model innovations can quickly commoditize if you cannot keep imitators at bay.
The question is how. For technological innovation, you can often (but not always) resort to patents or other legal devices. Patents get much trickier when it comes to business models. Technically, business methods can be patented (such as Amazon’s 1-click shopping). Generally, these patents are issued on the software that underpins a particular business method (e.g., an online auction).20 There was a surge in business method patenting after 1997, but subsequent court rulings have tightened the criteria.21 And, while individual methods might be patented, the possibility of patenting an entire model seems remote. It is probably best to proceed under the assumption that your business model innovation cannot be protected by patents. If it works, you are likely to have imitators, and you need a strategy to defend against that imitation.
The best way to prevent your business model from being imitated is to base it on some set of hard-to-replicate resources—like brand, unique operating know-how, proprietary technological capabilities, and reputation. This explains why successful business model innovators often invest very heavily in building brand equity early on. Increasing returns to scale, if properly exploited, can be a powerful barrier to imitation since either the value created for customers increases with the number of customers you have or the costs of serving those customers decreases with the number of customers. Facebook is a good example of the former since people like joining and using Facebook because a lot of friends are already using it. The more friends they have on Facebook, the more fun it is to use and so the more they are likely to use it. And the more they use it, the more fun it is for their friends to join and use. We have a virtuous circle. Amazon is a good example of a company that has exploited increasing returns to scale. As it attracted users (initially just those interested in buying books), it became attractive for more and more vendors to sell through its platform. As more vendors joined the Amazon marketplace and the variety of products increased, Amazon became a more convenient place to shop for us. As more people shopped online at Amazon, more companies wanted to sell their products there. Amazon’s size meant it had a great deal of bargaining power and so it could offer lower prices—which of course attracted more users. As volume increased, Amazon could afford to invest in more sophisticated and distributed warehousing and logistics infrastructure. This not only lowered costs, but it also shortened delivery lead times, which drove more demand to Amazon. Again, we have a virtuous circle.
Once that virtuous circle wheel is in motion, competitors can be hard pressed to imitate your model. They simply cannot imitate your volume or the cumulative size of your user base. But it is also important to “keep your foot on the gas.” Just being first is not enough: you need sustained investments. Social network sites like Friendster and MySpace failed to exploit their potential first mover advantages. It is hard to believe today, but in 2006 MySpace surpassed Google as the number one site visited on the web.22 MySpace should have
been unbeatable, but in just a few years Facebook crushed it. In 2011, MySpace sold for just $35 million.23 How did this happen? Part of the reason is that MySpace did not continue to evolve and improve its user experience (in other words, it started to create less user value). In addition, MySpace’s user base—while impressive at its peak—was still a relatively tiny fraction of the total market potential. Whereas both MySpace and Facebook started with focused user segments (high school students for MySpace and college students for Facebook), Facebook quickly expanded beyond that demographic boundary.
Another way to protect your business model from imitation is to build a specialized ecosystem around it. Almost all business models require the support of providers of complementary resources, such as software developers who write apps for the iPhone in Apple’s ecosystem. They make the iPhone platform more valuable for users. If your business model requires specialized complementary resources (like, say, software or accessories), then cultivating a network of complementary resources can not only enhance the value of your business model but can also become itself a powerful barrier to imitation. By the time Nokia realized that one of Apple’s key advantages was its deep ecosystem of app developers, it was too late to catch up. It was simply impossible for Nokia to convince independent software developers to write software for its proprietary platform (based on the Symbian operating system). Eventually, Nokia was forced to abandon its proprietary operating system and sold itself to Microsoft. But at less than 1 percent of the total smartphone market, Microsoft’s mobile operating system faces the same problem vis-à-vis the Apple and Android platform.24
Conclusion: Evolving Your Business Model
Technology can become obsolete, and so can your business model. Most companies are well aware of the risk of technological obsolescence and take steps like continued investment in R&D to defend themselves against it. Ironically, though, the forces making their business models obsolete are often missed. New competitors may introduce new business models to the market. New technologies may change which kind of resources can be monetized. Customer preferences may change in ways that cause your basis of value creation to decline. Competitive conditions may alter the economics of the way you capture value. An obsolete business model can be just as deadly to corporate health as obsolete technology. Just ask Blockbuster.
How do you keep your business model fresh? Part of the answer lies in the principles discussed in Chapter 2: an overall strategy that identifies business model innovation as a priority, allocating resources to business model innovation (just as you need to allocate resources to technological innovation). Second, business model innovation also requires the focused efforts of people within the company. That is often missing. For instance, at most companies when I ask who is in charge of technological innovation, I can generally get a pretty clear answer. People will point to the R&D organization or even name the chief scientific officer or senior vice president of R&D by name. If I ask the same question, though, about business model innovation, I usually get one of two responses: “it’s no one’s job” or “it’s everyone’s job” (which is the same as the former). Someone and some organization within the enterprise needs to be responsible for exploring, testing, and selecting ideas for business model innovation.
Finally, business model innovation like technological innovation requires experimentation and learning. No company would ever think about launching a significant innovation without building and testing prototypes. Experimentation is a natural and inherent part of every R&D organization’s repertoire. But, too often, companies do not apply the same logic to business model innovation. They either refuse to tamper with their model, or they try to introduce business model innovation without experimentation. The former dooms you to business model obsolescence, and the latter is highly risky. It is simply impossible to figure out all the details of business model innovation in advance, no matter how smart you are or how much analysis you do. Netflix’s business model evolved. Initially, the company’s pricing strategy was similar to Blockbuster’s: you paid per video. But, when that didn’t work, Netflix tried a subscription model. Amazon is a master at business model experimentation. Amazon Web Services—today the most successful cloud computing provider—grew out of an experiment to make the company’s application interfaces available to third-party developers.25 Business model innovation does not require having all the answers. It requires a capacity to experiment and to learn and a tolerance for risk. In essence, the organizational capabilities and culture required for business model innovation are no different from those required for technological innovation.
4
IS THE PARTY REALLY OVER?
Why You Should Not Always Eat Your Own Lunch
It is hard to think of a business today that does not face some kind of potential threat from transformative innovation. If you run an automobile company, you have to think about how radical technological innovations in electric engines and autonomous vehicles and business model innovations like ride sharing could upend your business. A leader of a grocery chain has to be concerned about the threat of Internet-based home-delivery business models—especially now that Amazon owns a major grocery chain. If you run Marriott, peer-to-peer networks like Airbnb have certainly attracted your attention by now. One of the perennial questions of innovation strategy is how you should deal with these threats.
You have heard the advice on this question many times. Perhaps you were at a conference on innovation. Perhaps it was in a conference room at your company. Perhaps a consultant told you. The topic turned to future innovation trends and the potential threat to your business, and then someone said it: eat your own lunch before someone else does. It is one of the most ubiquitous pieces of advice in the management of innovation. According to this logic, you should make your existing technology or business model obsolete before someone else does. Embrace the future—let go of the past. Like all clichés, it’s tiresome for its lack of originality. But “eat your own lunch” offends for a more important reason: it can be downright misleading. While the logic might seem impeccably obvious (better to be alive than dead), it is founded upon assumptions that do not always hold up. Dealing with the potential threats of disruptive innovation is a game requiring deep consideration of the nuanced interplay of technological and economic forces. It requires a strategy, not a slogan. In this chapter, we will explore how to develop such a strategy.
When Old Does Not Mean Obsolete: The Case of the Mainframe Computer
The mainframe computer has been commercially available since the late 1950s, and IBM’s dominance of this business over several decades propelled it to become one of the largest, most profitable, and most admired corporations in history. As we all know by now, the picture changed dramatically in the late 1970s with the emergence of the personal computer. Computer power was now on our desktop (and a bit later, on our laps), and we were unshackled from the tyranny of time-share computing. As personal computers became more and more powerful with each generation of microprocessors (Moore’s Law in action), businesses had less and less use for bulky mainframes. This was not good news for IBM, of course, which not only enjoyed a dominant market share in mainframes but also garnered juicy profit margins on them.
The PC looked exactly like the type of disruptive innovation that could sweep away a giant like IBM. But to its credit, IBM was not asleep at the wheel. By 1981, still relatively early in the PC revolution, IBM entered the market. And, in fact, one might argue that IBM’s entry into PCs played a key role in propelling the revolution forward into the corporate computing market. IBM leadership understood that PCs would eat into the company’s mainframe business—it was exactly for this reason it set up its PC organization in a separate stand-alone unit (in Florida, safely away from corporate headquarters in Armonk, New York). IBM was eating its own lunch.
For a while, this strategy seemed to be working. IBM’s PC sales skyrocketed and quickly grabbed a significant share of the market. IBM was widely heralded for its bold
move into PCs—it looked like the perfect business school case study to demonstrate how a large, highly successful organization could in fact be nimble enough to duck the forces of creative destruction. As mainframe sales declined, the strategy looked quite prescient. Predictions that the mainframe’s days were numbered were not hard to find.
There was only one problem with this strategy—the PC market was never that profitable and was never going to be. Partly thanks to decisions made by IBM to outsource the operating system (to a then little-known software company called Microsoft) and the microprocessor to Intel, the structure of the personal computer industry made it very hard for personal computer manufacturers and marketers to be profitable. Because Microsoft and Intel controlled key components of the system architecture, they were in a position to extract all the economic rents from the industry. Sure, IBM and others could sell a lot of personal computers, but the profits flowed back to Microsoft and Intel. Personal computers became a brutally competitive business because it was hard for IBM to really differentiate itself from others like Dell, Compaq, and Hewlett Packard based on the performance of its machines because everyone (except Apple) was using the same basic “Wintel” architecture. Facing declining margins and eroding market share, IBM decided enough was enough and sold its PC division to Lenovo in December 2004.1
In the meantime, the old dinosaur known as the mainframe has been resurrected by the emergence of cloud computing and more recently big data. What few anticipated in the early days of the PC revolution was that the Internet would usher in a whole new era of networked computing. Applications and data would gravitate back to remote locations, eventually giving rise to what we now call “cloud computing.” Some applications of cloud computing, like transaction processing, require massive amount of data storage and computational capacity, not to mention security and reliability—exactly the kind of thing mainframes are good at. Fortunately for IBM, it never listened to all of those who told the company to get out of mainframes. IBM’s System Z mainframe utterly dominates the mainframe market. In 2017, almost 90 percent of all credit card transactions globally were processed by an IBM mainframe.2 For IBM, mainframes are still a multibillion-dollar business with healthy margins. Mainframes will probably never be the gourmet lunch they were back in the 1960s and 1970s, but they turned out to be commercially far more durable than anyone predicted. Old? Yes. Obsolete? Not really.
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