Strategy - Your Plan Is Wrong - How Google Works (2014)

How Google Works

Strategy—Your Plan Is Wrong

We have no idea what your venture is or even your industry, so we won’t presume to tell you how to create a business plan. But we can tell you with 100 percent certainty that if you have one, it is wrong. MBA-style business plans, no matter how well conceived and thought out, are alwaysflawed in some important way. Faithfully following that flawed plan will result in what entrepreneur Eric Ries calls “achieving failure.”55 This is why a venture capitalist will always follow the maxim of investing in the team, not the plan. Since the plan is wrong, the people have to be right. Successful teams spot the flaws in their plan and adjust.

So how can a new venture attract great people and other important things (like financing) without having a plan? In fact, it’s fine to have a plan, but understand that it will change as you progress and discover new things about the products and market. This rapid iteration is critical to success, but equally important is the foundation upon which the plan is built. The tectonic, technology-driven shifts that characterize the Internet Century have rendered some of the commonly accepted strategic fundamentals we learned in school and on the job incorrect.56 So although your plan might change, it needs to be based on a foundational set of principles that are grounded in how things work today and that guide your plan as it shape-shifts its way to success. The plan is fluid, the foundation stable.

Some prospective team members may be turned off by this flexibility; most people don’t like uncertainty. Smart creatives, on the other hand, relish the “we’ll figure it out” approach—they have, as Jonathan wrote in one person’s review, the “pliancy to roll with the punches in this vertiginous environment.”57 In fact, they won’t trust a plan that claims to have all the answers, but will jump at one that doesn’t, as long as it is built on the right foundation.

Jonathan’s team taught him this lesson not long after he joined the company in 2002. Back then the company had a very well thought-out strategic foundation. It just wasn’t very well written out. In fact, no one had taken the time to fully document the Google strategy since the company’s founding in 1998. Jonathan set out immediately to rectify this glaring oversight. He wanted to build the traditional, doomed-for-obsolescence-before-the-ink-dries type of business plan to which he was accustomed, but his team of deputies—Marissa Mayer, Salar Kamangar, and Susan Wojcicki—stopped him.58 The company didn’t need to document its plan (or even have one), they argued, but in order to hire new people and keep everyone moving in the same direction, it did need to document the foundation for that plan. Give Googlers those foundational elements, Salar, Marissa, and Susan said, and they would figure out the rest.

The result was a presentation entitled “Google Strategy: Past, Present, and Future.” We delivered it to the board in October 2002 (setting the stage for Mike Moritz’s request for a more comprehensive plan the following summer), and components of it continued to be used to describe Google’s approach for years thereafter. The principles that it describes were quite different from those of the normal late-’90s dot-com, and today they stand as a foundational blueprint for how to create an Internet Century success story: Bet on technical insights that help solve a big problem in a novel way, optimize for scale, not for revenue, and let great products grow the market for everyone.

Bet on technical insights, not market research

In the mid-’90s, when Larry and Sergey began to research the PhD thesis project that would become Google, the leading search engines ranked their results based on the content of a website. If you typed in a query such as “university,” you were just as likely to get a link to the website of a bookstore or a bike shop as you were to get one to an actual university. In fact, during a visit to one of those search companies, Larry complained about the poor results he got when he used the “university” query with their product. The fault was his, he was told. He should have been more precise with his query.

So Larry and Sergey discovered a better way. They figured out that they could determine the quality of a web page—how relevant its content would be in answering the user’s query—by figuring out which other pages linked to it. Find a page that a lot of other pages point to, and you have probably found a page with higher-quality content.59 There are a lot of other factors that made Google Search so much better than the competition when it launched—for example, it placed more faith in results found on academic websites—but the heart of the product’s advantage consisted of this single technical insight about using the web’s link structure as a roadmap to the best answer.

Since then, most of Google’s successful products have been based on strong technical insights, while most of the less successful ones lacked them. AdWords, the Google ads engine that generates most of the company’s revenue, was based on the insight that ads could be ranked and placed on a page based on their value as information to users, rather than just by who was willing to pay more.60 Google News, the site that aggregates news headlines from thousands of media outlets, was based on the insight that we could algorithmically group stories by topic, not source. Chrome, Google’s open-source browser, was founded on the insight that as websites grew more complex and powerful, browsers needed to be reengineered for speed. Pick an innovative, successful Google product, and you are likely to find at least one significant technical insight behind it, the sort of idea that could have appeared in a technical journal. Knowledge Graph in search is based on organizing the Internet’s vast amount of unstructured data about a particular person, place, or thing into structured data, and presenting it in an easy-to-consume format. YouTube Content ID creates a unique data representation for every audio and video clip and matches that fingerprint against a global rights database, thereby giving content rights owners the ability to find (and sometimes monetize) their content on YouTube. Translate gets help from a vast multilingual user base to continuously improve translation quality. Hangouts (live video chat with one or more people) transcodes various video formats in the cloud rather than at the device level, making it one-click easy to conduct a global video conference from any device.

Product leaders create product plans, but those product plans often (usually!) lack the most important component: What is the technical insight upon which those new features, products, or platforms will be built? A technical insight is a new way of applying technology or design that either drives down the cost or increases the functions and usability of the product by a significant factor. The result is something that is better than the competition in a fundamental way. The improvement is often obvious; it doesn’t take a lot of marketing for customers to figure out that this product is different from everything else.

Sometimes developing technical insights is simple—OXO built a business by ergonomically redesigning kitchen tools—but more often it’s hard, which is perhaps why most companies don’t make it a foundation of their strategy. Rather, they follow the conventional MBA approach of figuring out what they are best at (their competitive advantage, per Michael Porter),61 and then leveraging that to expand into adjacent markets. This approach can be very effective if you are an incumbent that measures success in percentage points, but not if you are trying a new venture. You will never disrupt an industry or transform your business, and you’ll never get the best smart creatives on board, if your strategy is narrowly based on leveraging your competitive advantage to attack related markets.

Companies can also rely on smart tactics in pricing, marketing, distribution, and sales to squeeze out more market share and higher profits. Think of all the products in a grocery aisle slapped with a “new, improved” label, when in fact the only discernible improvement is in packaging and advertising. These tactics are often informed by market research, which involves a set of consultants slicing and dicing the company’s prospective customer base into narrowly defined segments—digital millennials here, Generation X there, tweens, bleens, spleens—leading the product designers to end up creating 31 flavors of mediocrity (no offense, Baskin-Robbins). The best thing about market research consultants? They are easy to blame and fire when they are wrong.

Excite@Home, where Jonathan ran the product team in the late ’90s, was a company founded on a set of technical insights that turned the coaxial cables carrying TV shows into people’s homes into broadband pipelines. The cable modem Excite@Home developed was a breakthrough product, but it ran headlong into an intractable enemy: market research. The cable operators had data showing that their customers mostly had personal computers (PCs) with Intel 80286 and 80386 processors, so Excite@Home’s modems needed to support those systems. But Excite@Home’s engineers knew that those older processors didn’t have the horsepower to do anything interesting with a broadband connection, and that customers with those computers who bought their service would have a bad experience. The cable operators pushed hard on this point, trying to force Excite@Home to offer a useless service for outmoded PCs because that is what their market research said to do. But the market research failed to see that PC performance was following Moore’s Law by doubling roughly every two years, and that pretty soon all those slow PCs would be gone.62

While Excite@Home ultimately prevailed in this particular argument, the company was not immune to making market research–driven mistakes. When it asked potential customers what they cared most about, the top answer was speed, so that’s what Excite@Home highlighted in its marketing. But even though cable broadband was indeed fast, the feature users really loved once they got the service was that it was “always on”; they didn’t have to wait for the dialing and hissing of modems and servers consummating their cyberspace connection to access the web. Jonathan and colleagues marketed to what users said they wanted, but market research can’t tell you about solving problems that customers can’t conceive are solvable. Giving the customer what he wants is less important than giving him what he doesn’t yet know he wants.

There’s nothing wrong with continuous improvement and smart business tactics, but the tail is wagging the dog when market research becomes more important than technical innovation. Most incumbents get their start through technical insights, but then they stray (as tail-wagged dogs often do). The suits become more important than the lab coats. This may or may not be a fashion mistake, but it’s certainly a mistake for the incumbent—and an opportunity for the attacker.

Basing products on technical insights has always been a core principle of Google, but its importance became even more clear to us in 2009, when we reviewed our product line and started to see a pattern emerging: The best products had achieved their success based on technical factors, not business ones, whereas the less stellar ones lacked technical distinction. Our brand had gotten strong enough that any product we launched would gain a certain amount of market momentum just by virtue of coming from Google. If we measured success by number of users, we could (and did) trick ourselves into believing that the products were successful. Sometimes they weren’t, though; momentum for many of these offerings flat-out stalled. And in virtually every case, the flat-lining products were the ones that lacked technical insights.

For example, at that time Google was experimenting in applying some of our expertise from online advertising to other advertising markets, including print, radio, and TV. These were clever efforts, supported by smart people, but they lacked that fundamental technical insight that would shift the cost-performance curve nonincrementally and provide significant differentiation. All three ultimately failed. And when we look back at other Google products that didn’t make it (iGoogle, Desktop, Notebook, Sidewiki, Knol, Health, even the popular Reader), they all either lacked underlying technical insights from the outset, or the insights upon which they were based became dated as the Internet evolved.

A period of combinatorial innovation

So where do you find these magical insights? In the Internet Century, all companies have the opportunity to apply technology to solve big problems in new ways. We are entering what lead Google economist Hal Varian calls a new period of “combinatorial innovation.” This occurs when there is a great availability of different component parts that can be combined or recombined to create new inventions. For example, in the 1800s, the standardization of design of mechanical devices such as gears, pulleys, chains, and cams led to a manufacturing boom. In the 1900s, the gasoline engine led to innovations in automobiles, motorcycles, and airplanes. By the 1950s, it was the integrated circuit proliferating in numerous applications. In each of these cases, the development of complementary components led to a wave of inventions.

Today the components are all about information, connectivity, and computing. Would-be inventors have all the world’s information, global reach, and practically infinite computing power. They have open-source software and abundant APIs63 that allow them to build easily on each other’s work. They can use standard protocols and languages. They can access information platforms with data about things ranging from traffic to weather to economic transactions to human genetics to who is socially connected with whom, either on an aggregate or (with permission) individual basis. So one way of developing technical insights is to use some of these accessible technologies and data and apply them in an industry to solve an existing problem in a new way.

Besides these common technologies, each industry also has its own unique technical and design expertise. We have always been involved in computing companies, where the underlying technical expertise is computer science. But in other industries the underlying expertise may be medicine, mathematics, biology, chemistry, aeronautics, geology, robotics, psychology, logistics, and so on. Entertainment businesses are built on a different form of technical expertise—storytelling, performing, composing, and creating—while consumer product companies combine technology and design to develop breakthrough products. Financial services companies use technical insights to create new securities and trading platforms (and get seriously rich, until the bubble bursts or the indictments hit). So regardless of your business, there is a robust corpus of technical knowledge upon which the industry is based. Who are the geeks in your company? The guys in the labs and studios working on new, interesting stuff? Whatever that stuff is, that’s your technology. Find the geeks, find the stuff, and that’s where you’ll find the technical insights you need to drive success.

Another potential source of technical insights is to start with a solution to a narrow problem and look for ways to broaden its scope. This is in keeping with a long and fine tradition in the world of innovation. New technologies tend to come into the world in a very primitive condition, often designed for very specific problems. The steam engine was used as a nifty way to pump water out of mines long before it found its calling powering locomotives.64 Marconi sold radio as a means of ship-to-shore communications, not as a place to hear phrases like “Baba Booey!” and “all the children are above average.” Bell Labs was so underwhelmed by the commercial potential of the laser when it was invented in the ’60s that it initially put off patenting it. Even the Internet was initially conceived as a way for scientists and academics to share research. As smart as its creators were, they could never have imagined its future functionality as a place to share pictures and videos, stay in touch with friends, learn anything about anything, or do the other amazing things we use it for today.

Our favorite example of building upon a solution developed for a narrow problem has to do with those clever early adopters of technology, the adult entertainment industry. When Google search started to ramp up, some of our most popular queries were related to adult-oriented topics. Porn filters at the time were notoriously ineffective, so we put a small team of engineers on the problem of algorithmically capturing Supreme Court Justice Potter Stewart’s definition of porn, “I know it when I see Google it.” They were successful by combining a couple of technical insights: They got very good at understanding the content of an image (aka skin), and could judge its context by seeing how users interacted with it. (When someone searches for a pornography-related term and the image is from a medical textbook, they are unlikely to click on it, and if they do, they won’t stay on that site for long.) Soon we had a filter called SafeSearch that was far more effective in blocking inappropriate images than anything else on the web—a solution (SafeSearch) to a narrow problem (filtering adult content).

But why stop there? Over the next couple of years we took the technology that had been developed to address the porn problem and used it to serve broader purposes. We improved our ability to rate the relevance of images (any images, not just porn) to search queries by using the millions of content-based models (the models of how users react to different images) that we had developed for SafeSearch. Then we added features that let users search for images similar to the ones they find in their search results (“I like that shot of Yosemite—go find me more that look just like that”). Finally, we developed the ability to start a search not with a written query (“half dome, yosemite”), but a photograph (that snapshot you took of Half Dome when you visited Yosemite). All of these features evolved from technology that had initially been developed for the SafeSearch porn filter. So when you are looking at screen upon screen of Yosemite photos that are nearly identical to the ones you took, you can thank the adult entertainment industry for helping launch the technology that is bringing them to you.

Don’t look for faster horses

When you base your product strategy on technical insights, you avoid me-too products that simply deliver what customers are asking for. (Henry Ford: “If I had listened to customers, I would have gone out looking for faster horses.”)65 That sort of incremental innovation can work very well for incumbents who are concerned with maintaining the status quo and quibbling over percentage points of market share. But if you are starting a new venture or trying to transform an existing enterprise, it’s not enough.

Basing products on technical insights seems like a fairly obvious approach, but it is a lot more difficult to practice than to preach. Back in 2009, after we conducted the product review that demonstrated just how important it was to follow this strategy, we asked the product managers for all of our major products in the pipeline to describe in a few sentences the technical insight upon which they were building their plan. Some of them could, but many of them couldn’t. “What is your technical insight?” turns out to be an easy question to ask and a hard one to answer. So for your products, ask the question. If you can’t articulate a good answer, rethink the product.

Optimize for growth

It used to be that companies got big slowly and methodically. Create a product, achieve success locally or regionally, then grow a step at a time by building sales, distribution, and service channels, and ramping up manufacturing capability to match your progress. Everything took its time. The acorn, after long, slow decades, grew into the oak.

We called this “growth,” and there may still be industries where it is good enough. As in “top-line growth this quarter was 8 percent”—and that’s good enough for a bonus or promotion. Well, enjoy those days, because they are short-lived. If you are trying to do something big, it’s not enough to just grow, you need to scale. Not scale as in that thing you step on in the morning to see how the diet’s going, or the verb that means to climb something (although scaling things is good exercise, which leads to a better outcome when you scale the scale). No, this is a new type of scale; it means to grow something very quickly and globally.

In the Internet Century, this sort of global growth is within anyone’s reach. We have the democratization of just about everything—information, connectivity, computing, manufacturing, distribution, talent—so it no longer takes a phalanx of people and a widespread network of offices to create a company with global reach and impact. That doesn’t mean that your strategy can ignore the question of how to scale, just the opposite. Scaling needs to be a core part of your foundation. Competition is much more intense and competitive advantages don’t last long, so you have to have a “grow big fast” strategy.

The ecosystem matters a lot. The most successful leaders in the Internet Century will be the ones who understand how to create and quickly grow platforms. A platform is, fundamentally, a set of products and services that bring together groups of users and providers to form multisided markets.66 Platforms are increasingly (if not exclusively) technology based. For example, YouTube is a platform that lets anyone create videos and distribute them to a global audience (or, in most cases, just a familial one). Or a classic example is the telephone, whose platform (the network of wires and switches that connects devices and lets people talk to each other) was pretty worthless when the first phone was connected to it, as there was no one to call. But as each additional phone was added, the network became more useful to everyone who used it (since there were more people they could call).

Talking about landline phones seems downright quaint now. Back then, scaling meant reaching millions: It took the global phone network eighty-nine years to reach 150 million phones.67 Today, platforms can grow to support billions, and in a much shorter time. Facebook, which broke out from a host of social networking sites when it turned itself into an application platform, hit a billion users not long after its eighth birthday.68 Android, the leading mobile operating system, activated its billionth device in its fifth year.69 While financial analysts anguish over its profitability, Amazon always focuses on growth. Now it is one of the most disruptive forces in at least three different industries: retail, media, and computing.

When Jonathan first met Larry Page one day in 1999, they were walking across the Google parking lot to Jonathan’s car when Larry mentioned, almost in passing, that he knew there had to be a way, eventually, to monetize search. After all, Larry reasoned, when someone did a search they were telling Google exactly what they were interested in. At the time, Google’s search traffic was ramping up but the company wasn’t making much money. Larry and Jonathan were discussing a potential partnership between Google and Excite@Home, which was a well-funded company formed by the merger of @Home, a pioneer in the cable modem business, and Excite, one of the web’s early search engines. But while Excite@Home was trying to monetize its traffic in every way possible, Google patiently focused on growth. There were plenty of opportunities to cash in; as traffic to grew rapidly, the company could have followed the lead of every other commercial website and put ads on the home page. But it didn’t. Instead it invested in improving the search engine.

We took a similar approach with our AdWords ads platform. We cut deals with publishing partners such as America Online (AOL) and Ask Jeeves, who used Google’s ad system to place ads on their sites. With these partnership deals, one concern was always around the revenue split. Let’s say we placed an ad on AOL’s or Ask Jeeves’s website, and the user clicked on it. The advertiser would then pay Google a certain amount of money, which we would share with the publishing partner. But how much to share? Our approach was usually to try to share as much as possible—remember, the priority was to grow, not to make more money. This kept the partners very happy. They all had ambitious revenue objectives, which were getting harder to meet as Google search gained momentum. So to close the gap and generate more revenue at quarter’s end, they always opted to show more ads.

Jonathan went so far as to visit his counterparts at AOL to counsel them against increasing their ads volume. You are hurting your user experience, he told them, and that will eventually impact your traffic. It didn’t matter. They prioritized revenue over growth; we did just the opposite.

At the risk of stating the obvious, though, a successful foundation must provide a good basis for revenue generation. The old dot-com mantra of “We have no idea how we’re going to make money (but look at our sock puppet!)” didn’t cut it then and still doesn’t. The Google founders knew that they would make money from advertising. Initially they didn’t know exactly how, and they were biding their time while scaling their platform, but they were very clear about the general revenue model.

There’s another important benefit of platforms: As they grow and get more valuable, they attract more investment, which helps to improve the products and services the platform supports. This is why, in the technology industry, companies always think “platforms, not products.”

Coase and the nature of the firm

One very compelling—and underappreciated—aspect of the Internet is how it has greatly expanded the potential to build platforms not just in the technology business, but in any industry.

Companies have always built networks, but historically those networks were internal and designed to reduce costs. In this way, they followed the tenets of University of Chicago economist and Nobel laureate Ronald Coase, who argued that it often makes sense for firms to do things internally rather than externally, because the transaction costs of finding vendors, negotiating contracts, and making sure the work gets done right are high. As Coase put it, “a firm will tend to expand until the costs of organizing an extra transaction within the firm become equal to the costs of carrying out the same transaction by means of an exchange on the open market or the costs of organizing in another firm.”70 Many smart twentieth-century companies ran the numbers and found that for much of what they wanted to get done, Coase was right: The internal management costs were lower than the transaction costs of outsourcing. This led them to do as much as they could within the organization, and, when they did go outside their four walls, they worked with a small group of tightly controlled partners. So the twentieth century was dominated by corporations that were large hierarchies—or, at their most expansive, closed networks.

Today, Coase’s framework still holds true—but it leads to radically different outcomes than it did in much of the twentieth century. Rather than growing the biggest possible closed networks, companies are outsourcing more functions and working with a bigger and more diverse network of partners. Why? Don Tapscott put it well in Wikinomics, when he wrote that “the Internet has caused transaction costs to plunge so steeply that it has become much more useful to read Coase’s law, in effect, backward: Nowadays firms should shrink until the cost of performing a transaction internally no longer exceeds the cost of performing it externally.”71 Most companies have taken this approach purely for operational and cost-cutting reasons: They save money by outsourcing jobs to lower-wage markets.

But they miss an important point. In the Internet Century, the objective of creating networks is not just to lower costs and make operations more efficient, but to create fundamentally better products. Lots of companies build networks to lower their costs, but fewer do so to transform their products or business model. This is a massive missed opportunity for incumbents in numerous industries, creating a giant opening for new competitors.

Twitter is not a technology company, it is a publishing company. Airbnb is a platform for the lodging industry, while Uber is one for personal transportation services. 23andMe is a platform play as well as a consumer service company. For a fee, it will map a customer’s personal genetic code; if it aggregates all of that data it could create a powerful data platform. Pharmaceutical companies, for example, could potentially use 23andMe’s data to identify participants in new studies, and when they do, contribute any additional data they create back into the platform.

The list goes on: Square for small-business payments, Nike FuelBand for physical fitness, Kickstarter for financing, MyFitnessPal for weight loss, Netflix for video entertainment, Spotify for music. These companies assembled existing technology components in new ways to reimagine existing businesses. They set up platforms for customers and partners to interact, and use those platforms to create highly differentiated products and services. This model can apply just about anywhere: travel, automobiles, apparel, restaurants, food, retail—there are ways to make products in virtually every industry better as more people use them.72

This is the difference between twenty-first- and twentieth-century economies. Whereas the twentieth century was dominated by monolithic, closed networks, the twenty-first will be driven by global, open ones. There are platform opportunities all around us. The successful leaders are the ones who discover them.


Another approach is to find ways to specialize; sometimes the best way to grow a platform is to find a specialty that has the potential to expand.73 To grow its search platform in the late ’90s, Google focused on one thing: being great at search, which we measured along five axes—speed (fast is always better than slow), accuracy (how relevant are the results to the user’s query?), ease of use (can everyone’s grandparents use Google?), comprehensiveness (are we searching the entire Internet?), and freshness (how fresh are the results?). The company was so intent on getting users the right answers, that Google search results often included links to Yahoo, AltaVista, and Ask Jeeves at the bottom of the page so users could easily try those sites if they didn’t like Google’s results.

At the time, most competitive sites were intent on becoming “portals,” multifunctional media sites that catered to a wide variety of interests and needs. Some of these companies—Netscape, Yahoo, America Online (AOL)—weren’t that interested in search, and were happy to cut partnerships with Google to let us handle that task.74 While Google certainly believed that search was one of the most important applications in the burgeoning Internet business, we didn’t choose to specialize in that area because our crystal ball told us it would ultimately be more lucrative and impactful than the alternate, more popular portal business model. Rather, we focused on search because it was something we felt we were better at than anyone else.75 So in those early days of the Internet, while these leaders of the industry were busy tending to their business of building Internet portals, Google search got better and better at providing great answers for users.

(Improving Google search also had the beneficial effect of increasing traffic to publishers’ sites, since it made it easier for users to find the news, information, and entertainment offered on those sites. This helped spur the migration of more content online.)

Default to open, not closed

Platforms generally scale more quickly when they are open. Look at the biggest platform of them all, the Internet. In the early ’70s, when Vint Cerf and Robert Kahn76 developed TCP/IP (Transmission Control Protocol / Internet Protocol), which enabled disparate computer networks (such as the Internet’s forefather, ARPANET) to be connected and communicate, they weren’t quite sure of the size of the networks they were connecting, or how many there were. So they didn’t set an upper limit on the number of networks that could be connected, and in fact decided to let any network connect to any other using their protocol. This singular decision to keep the Internet open (which was not a foregone conclusion at the time), directly led to the remarkable web we use every day. (Hal Varian calls the Internet “a lab experiment that got loose.”)

Or look again at the classic example of the landline telephone. Conceived as a single-application platform—voice communications—growth of the AT&T network in the United States eventually tapered off. There was practically no innovation, and the only growth came from population increases and baby-boom teenagers ordering second lines. But then, under government mandate, AT&T opened up its network to new devices and other carriers, and innovation took off. New types of phones, fax machines, data modems, cheap long-distance calling—Remember “long-distance call”? That was a thing, once—all innovations that became possible only after the platform went from closed to open.77

Another example is the IBM PC, which launched in 1981 with an architecture that allowed software developers and manufacturers to build applications and add-on components, and even their own “clone” PCs, without paying IBM licensing fees. This decision helped establish the IBM PC as the definitive standard in the emerging “microcomputer” market, giving a huge boost to a couple of small companies called Microsoft and Intel.78 It also drew flocks of applications, accessories, and competitive manufacturers into the ecosystem, and ultimately created the dominant computing platform for the next twenty-five years. None of this would have happened if the PC had been a closed platform.79

“Open” can be a rather Rashomon-like term—different companies will define it in different ways to meet their own objectives. But generally it means sharing more intellectual property such as software code or research results, adhering to open standards rather than creating your own, and giving customers the freedom to easily exit your platform. This can seem heretical to traditional, MBA-style thinking, which dictates that you build up a sustainable competitive advantage over rivals and then close the fortress and defend it with boiling oil and flaming arrows. Like most things heretical, open is terrifying to the establishment mindset. It’s a lot easier to compete by locking customers into your nice, closed world than it is by venturing out into the open wild and competing on innovation and merit. With open, you trade control for scale and innovation.80 And trust that your smart creatives will figure it out.

If you are attacking an entrenched incumbent, you can use its very entrenchedness to your advantage. Your porcine competitor is probably feasting at a closed trough, and you can take it on by matching your disruptive product with a disruptive business model. Open can play that part very effectively. It drives innovation into the ecosystem (new features for the platform, new applications from partners) and drives down the cost of complementary components. All of this leads to more value for users and more growth for the new ecosystem, usually at the expense of the incumbent’s (presumably) closed platform. Look, for example, at how organizations like Khan Academy, Coursera, and Udacity are trying to gain a foothold in the education market.81 They combine Internet Century technologies (online video, interactive and social tools) with an open business model (anyone can take any classes for free) that is radically different from how the entrenched incumbents operate (high tuitions to cover a high cost basis). No one can predict which, if any, of these disrupters will grow and thrive, or if some of the more nimble incumbents will fend them off. But what does seem certain is that this combination of technology + open will lead to a better learning ecosystem that provides, as Khan’s mission states, “a free world-class education for anyone anywhere.”

Open also allows you to harness the talents of thousands of people, because, as Sun cofounder Bill Joy noted, “no matter who you are, most of the smartest people work for someone else.”82 It spurs greater innovation, since people don’t have to reinvent work that’s already been done and can instead focus on pushing the entire system forward with new inventions. Netflix is a case in point: In 2006, the movie-rental company wanted to improve its recommendation algorithm, but internal efforts had plateaued. So they took a previously proprietary data set of a hundred million anonymized user movie ratings and published it, while announcing that the first person or team who could use that data to beat the current algorithm’s accuracy by at least 10 percent would win a $1-million prize. Even the contest was open: Netflix reported top teams’ progress on a public leaderboard, and within three years a winning solution emerged.83

There is another, less obvious but equally important benefit to open source. Putting all your information online shows that there are no hidden agendas. In software, when we open source code, everyone can see whether or not that code delivers any particular benefit to one company, and if it does, take action to rectify that advantage. Open-sourcing something says, in effect, that we are committed to growing a platform, an industry, and an ecosystem as a whole. It lets everyone see that the playing field is level, with no unfair advantages conferred upon any particular player. Removing this suspicion of unfair advantages helps growth.84

A final thought on defaulting to open is the concept of user freedom, a practice that is the opposite of customer lock-in: Make it easy for customers to leave. At Google we have a team whose job it is to make it as easy as possible for users to leave us. We want to compete on a level playing field and win users’ loyalty based on merit. When customers have low barriers to exit, you have to work to keep them.

Default to open, except when…

Open is not a moral argument. Defaulting to open is usually the best way to drive innovation and lower costs in an ecosystem, so view it as another strategic tactic at your disposal: Will going open help you achieve scale and profitability? Open’s virtuous halo can help attract smart creatives, mostly because, as the poet once sang, nothing can change the world like a global platform. (Well, the poet should have sung that, anyway.)

With a few exceptions, Google defaults to open, and for these exceptions we are often criticized as being hypocritical, since we preach open in some areas but then sometimes ignore our own advice. This isn’t hypocritical, merely pragmatic. While we generally believe that open is the best strategy, there are certain circumstances where staying closed works as well. When you have a product that is demonstrably better (usually because it is based on strong technical insights) and you are competing in a new, rapidly growing market, you can grow quickly without opening up the platform. This was the case with Google’s search and ads engines in our early days, but it is a fairly rare circumstance.

Plus, there are situations when open platforms do not work on behalf of users and innovation. Most incumbents who keep their platforms closed employ the argument that opening up their systems will hurt quality, so by keeping their closed platform closed they are just being good corporate citizens, looking out for the interests of their customers. In some cases, like ours, this argument is actually true. Opening up our search and ads algorithms would severely compromise quality, since there are many parties in the search world who profit from a worse user experience. They don’t want users to view and click on the most relevant results and ads, they want users to see and view their results and ads, even if it is a crummier experience for the user. So the search ecosystem is best served, we believe, by keeping secret the algorithms by which we match results to user queries.

In 2005, when we bought what was then a small mobile operating system called Android, there was some debate among our management team about whether or not we should keep it open. Andy Rubin and the Android team initially thought it should be closed, but Sergey suggested the opposite: Why not make it open? Keeping Android open would help us scale quickly in the highly fragmented mobile operating system space. So that’s what we did. Meanwhile, Apple launched the iPhone, built on a closed iOS, opting for control over scalability. Android stayed open, grew extraordinarily, and helped Google smoothly navigate the platform shift from PC to mobile by giving us a platform that was highly complementary to search (more people online with smartphones means more people searching more often). iOS stayed closed and achieved both massive scale and profitability. From the perspective of a new venture, either path is a win, but keep in mind that Apple’s success with the iPhone, just like Google’s with search, was based on an unusual set of technical insights that yielded an obviously superior product in a rapidly growing space. If you can achieve that sort of extreme impact with a closed system, then give it a shot. Otherwise, default to open.

Don’t follow competition

We are constantly amazed by how much business leaders obsess about their competition. When you get in a room with a bunch of senior execs from large companies, their attention can often wander as they check smartphones and think about the rest of their day, but bring up the topic of their competition and suddenly you’ll have everyone’s full attention. It’s as if, once you get to a particular level in an organization, you worry as much about what your competition is doing as how your own organization is performing. At the highest echelons of business, the default mentality is, too often, siege.

This fixation leads to a never-ending spiral into mediocrity. Business leaders spend much of their time watching and copying the competition, and when they do finally break away and try something new, they are careful risk-takers, developing only incremental, low-impact changes. Being close to your competition offers comfort; it’s like covering tactics in match race sailing, when the lead boat tacks whenever the follower does, to ensure that the follower doesn’t go off in a different direction and find stronger wind. Incumbents clump together so that no one finds a fresher breeze elsewhere. But as Larry Page says, how exciting is it to come to work if the best you can do is trounce some other company that does roughly the same thing?85

If you focus on your competition, you will never deliver anything truly innovative. While you and your competitors are busy fighting over fractions of a market-share point, someone else who doesn’t care will come in and build a new platform that completely changes the game. Larry again: “Obviously we think about competition to some extent. But I feel my job is mostly getting people not to think about our competition. In general I think there’s a tendency for people to think about the things that exist. Our job is to think of the thing you haven’t thought of yet that you really need. And by definition, if our competitors knew that thing, they wouldn’t tell it to us or anybody else.”86

This isn’t to say you should ignore competition. Competition makes you better. It keeps you sharp. We are all human and subject to complacency, no matter how often we tell ourselves to stay on our toes. Nothing lights a fire like a competitor. When Microsoft launched the Bing search engine in 2009, we were concerned enough to kick off an all-hands-on-deck process to intensify our efforts on search. This planted seeds that led to new features such as Google Instant (search results as you type) and Image Search (drag an image into the search box and Google figures out what it is and uses it as the query). You can draw a line from the launch of Bing to these great new features.

As Nietzsche wrote in Thus Spake Zarathustra: “You must be proud of your enemy; then your enemy’s successes are also your successes.”87 Be proud of your competitors. Just don’t follow them.

Eric’s Notes for a Strategy Meeting

We have spent countless hours working on strategy with our teams. This is an experience you will get to enjoy at some point, once you have gathered a coterie of smart creatives and are ready to write down the fundamentals of your new venture. So when you are on your way to that first strategy jam session, consider these pearls of (we hope) wisdom that we have collected from our own strategy sessions over the years, culled from conference-room whiteboards, Post-its stuck on walls, scribbled notes, and emails to ourselves.

The right strategy has a beauty to it, a sense of many people and ideas working in concert to succeed.

Start by asking what will be true in five years and work backward. Examine carefully the things you can assert will change quickly, especially factors of production where technology is exponentially driving down cost curves, or platforms that could emerge.

In a five-year timeline there are disrupters—and opportunities—in many markets. What will be the disrupters affecting you?

There is now almost perfect market information and broad availability of capital, so you need to win on product and platform. Spend the vast majority of your time thinking about product and platform.

When there is disruption in a market, there are two possible scenarios. If you are the incumbent, you can acquire, build, or ignore a disruptive challenger. Ignoring the challenger will work for only a short while. If you opt to acquire or build, you must viscerally understand the technical insights and options the challenger will use to attack.

If you are the challenger, you need to invent a new product and build a business around it, and understand the tools (business relationships, regulations, and lawsuits) and obstacles incumbents will use to stop you.

Consider the role of other players whose incentives can be aligned to help you. Your strategy should include a way you can have people outside the existing business framework (division, company, team) thinking about innovation along with the people inside.

Growth matters most. All big successes in the Internet Century will embody large platforms that get better and stronger as they grow.

Articulate a rough time frame and the end point you want to achieve.

Don’t use market research and competitive analyses. Slides kill discussion. Get input from everyone in the room.

Iteration is the most important part of the strategy. It needs to be very, very fast and always based on learning.

Many large, successful companies started with the following:

1. They solved a problem in a novel way.

2. They used that solution to grow and spread quickly.

3. That success was based largely on their products.

And the coterie you gather to work on this strategy? Choose it wisely. It shouldn’t just comprise the people who have been around the longest or those with the biggest titles, rather it should include the best smart creatives and the ones who will have a good perspective on the changes to come.

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