Market Power

Flex Your Market Power

IN 2016, HATCHIMALS WERE the hottest toy of the Christmas season. They are cute little electronic bird toys that you can take care of, kind of like a modern Furby. Supply was short, and people went to great lengths to get their hands on them. As RetailMeNot reported on December 6, 2016: While Hatchimals retailed for about $60 at the time, they were selling for as much as $1,200 on eBay. As you can see, people will pay very inflated prices when the supply available for a product is low relative to its demand. With that type of profit opportunity, enterprising individuals perennially buy Christmas-season toys from retail stores so that they can resell them at higher prices on secondary markets (like ticket scalpers do for desirable concert tickets). When you take advantage of price differences for the same product in two different settings, it’s called arbitrage . Back in the nineties, when eBay launched, it created numerous arbitrage opportunities by connecting newly minted salespersons to customers anywhere in the world. In college, Lauren found eBay to be a great source for making spare cash by pairing small-town anime lovers, who didn’t have anime shops in their own towns, with products she bought at a local anime shop near MIT. Sometimes she would even find arbitrage opportunities within eBay itself. She found she could make a profit by relisting items in a better category or by using better keywords so that more people would find the listing. For example, she once found a designer wedding gown on sale for fifty dollars in the dress-up and costume section but thought she could resell it for hundreds of dollars if she listed it in the pre-owned wedding dress section. She was right—it went for more than two hundred dollars! Price differences like these tend to not last very long, because others notice and pursue the same discrepancies until they no longer exist. It can certainly be profitable to take advantage of these short-term opportunities, but you need to keep finding new ones to continue turning a profit. In this chapter we explore the opposite of arbitrage: sustainable competitive advantage . This mental model describes a set of factors that give you an advantage over the competition that you can sustain over the long term. A working flywheel (see Chapter 4) can drive such advantage—think of what Amazon has on its competition with regard to shipping because of its size and investments in warehousing and delivery. The signature of sustainable competitive advantage is what economists call market power , the power to profitably raise prices in a market . For instance, when Amazon has raised its Prime price, it hasn’t lost many customers. An extreme showing of market power is a monopoly . Monopolies have vast market power because they have little competition. As an example, consider the EpiPen, a medical device needed by people with severe allergies to treat potentially fatal allergic reactions. In 2016, Mylan, the company behind this well-known brand, controlled more than 90 percent of the market for these types of devices. From 2007, when it bought the brand from Merck, through 2016, its market share hadn’t decreased despite having raised the price for the device by more than 500 percent. This price increase is an incredible showing of market power, aided by the recall of a competitor’s device and the U.S. Food and Drug Administration’s rejection of another one during this time frame. If a monopoly raises its prices, you can either pay the higher price or forgo its product, which in many cases (such as for needed life-saving devices) is not an attractive option. The other extreme is perfect competition , markets where many competitors provide the exact same product, perfect substitutes (also known as commodities ). A thirty-two-ounce bottle of isopropyl alcohol is thirty-two ounces of isopropyl alcohol no matter whom you buy it from. If a commodity supplier raises prices, you just buy from another supplier at the lower price. Consequently, these commodity providers have no market power. Market power also applies to you personally in the labor market. If you are just starting out in an industry and have only basic, undifferentiated skills, you can be a commodity. That means you have no advantage over other potential employees for the same job. From the employer’s perspective, you are interchangeable with other applicants for the position. In this situation, you have no ability to negotiate compensation and must accept the market rate for your services. However, this situation doesn’t necessarily mean you get paid minimum wage. As with the Hatchimals, market price, in this case compensation, is a function of supply and demand. Plenty of people right out of school can make good money because the demand is high for their services. For example, there are many newly minted nurses each year, but nurses are in high demand right now (at least in the U.S.), so new graduates can find work at attractive starting salaries. On the other hand, even though the number of new graduates with PhDs in history is relatively small, there are even fewer tenure-track teaching positions available for them, and consequently it is very difficult even to secure one of these jobs. When you are undifferentiated—with no sustainable competitive advantage and therefore no market power—you are completely subject to the supply-and-demand forces in the market, and the price they deliver to you. That speaks to picking an industry in high demand for the long term, such as nursing. It also speaks to the need to differentiate yourself from your peers by developing a unique set of skills that the market values. Then you have the opportunity to demand higher compensation by demonstrating the distinctive value you bring to your employers or clients. For example, in nursing, such differentiation could be achieved by a combination of experience and continuing education in a nursing specialty like critical care, anesthesiology, or pain management. Of course, if there is no demand for your special set of skills, then there is no opportunity for you to flex market power. For example, many Olympic athletes need day jobs because there just isn’t enough market demand for their sport. They cannot support themselves on their extraordinary skills alone. Having market power—individually or organizationally—is an attractive position because you can use your advantages to sustain profit for a long time. That’s why it is called sustainable competitive advantage. Nothing lasts forever, though. New technologies arise that disrupt the old. Monopolies fall. Patents expire. Regulations evolve. New job skills crop up, supplanting the way things were done before. In Chapter 4, we examined how to watch out for, anticipate, and even engender such change. In this chapter, we examine super models to help you find and hang on to market power. SECRET SAUCE Major life, career, and organizational choices can be thought of as bets on the future. You can be either right or wrong in those bets. If wrong, you won’t achieve the success you wanted; if right, you will. However, to achieve a really high degree of success, you need something extra: to be contrarian in your bet. In “Demystifying Venture Capital Economics, Part 1,” venture capitalist Andy Rachleff summarized this concept, originally formulated by investor Howard Marks, with the consensus-contrarian matrix : Rachleff elaborates: Consider the analogy of horse racing. If everyone bets on the same winning horse, no one gets a big payout. If you make the same choice as everyone else, a consensus bet, then there isn’t much ability for you to individually stand out, and so you can at most get a modest success. Venture capitalist Bill Gurley put it this way: “Being ‘right’ doesn’t lead to superior performance if the consensus forecast is also right.” But if you like a horse at fifty-to-one and she wins, then you have achieved a remarkable success. It is the difference between coming up with the next hot idea and being the fifth self-serve frozen yogurt franchise in your town. As Charlie Munger said in Poor Charlie’s Almanack , “Mimicking the herd invites regression to the mean” (see Chapter 5). His investing partner Warren Buffett puts it this way in Warren Buffet Speaks : “Most people get interested in stocks when everyone else is. The time to get interested is when no one else is. You can’t buy what is popular and do well.” In horse betting, the crowdsourced odds (see Chapter 6) reflect how many people agree with your bet. As a result, you get the highest returns when you bet on a horse that hardly anyone else is betting on. However, there is likely a good reason that no one is betting on that horse. As Jeff Bezos said at Vanity Fair ’s New Establishment Summit on October 20, 2016, “You just have to remember that contrarians are usually wrong.” A contrarian bet is therefore most likely to be successful when you know something that almost everyone else doesn’t. In other words, you know that the chance of being right is much greater than the crowd realizes, such as when you know a particular bet has a 10 percent chance of success, but the crowd thinks it’s 1 percent. Jeff Bezos again, in a 1997 letter to shareholders: Knowing something that is important yet mostly unknown or not yet widely believed is what investor Peter Thiel calls a secret . This has the same meaning as its colloquial use, just applied to innovation. As Thiel wrote in his 2014 book, Zero to One : A secret can be an idea that no one else has thought of, but it can also be an idea about how to achieve something that everyone else currently thinks is too risky. It is possible that an idea is not as risky as it seems, and by taking a first-principles approach you can come to a more correct risk assessment (see Chapter 1). Many investors actually passed on Airbnb because both sides of an Airbnb transaction seemed so risky that they thought there wouldn’t be a market for it. After all, an Airbnb transaction on one side calls for letting a stranger sleep in your home, and on the other side involves sleeping in a stranger’s home. Of course, the investors who passed were wrong; plenty of people were happy to bear those risks once Airbnb set up a marketplace to do so. The opposite can be true as well, in that people can substantially underestimate risks, such as in the 2007/2008 U.S. housing crisis, which led to a global financial crisis. The few people who correctly assessed this risk and bet on their secret knowledge made a lot of money, as depicted in the 2015 film The Big Short , based on a 2010 book of the same name by author Michael Lewis . A secret can also be how to turn someone else’s good idea into a great idea. Thomas Edison didn’t invent the lightbulb, but his concerted efforts made it long-lasting and commercially viable. You could similarly have a chance for great success if you see a viable path for an idea that everyone else is missing. Most currently central ideas in academic fields started out as secrets. You can find examples throughout this book, from the paradigm shifts of continental drift and germ theory in Chapter 1, to the statistics in Chapter 5 that we now take for granted, to all the influence models from Chapter 7, such as reciprocity . Mental models themselves are somewhat secret. The central theme of this book is that certain models from different fields can be applied to help you solve problems in other areas. Common knowledge in one field can be a secret in another. In another book by Michael Lewis, Moneyball , he explains how the Oakland Athletics baseball team was one of the first to use statistics to identify undervalued players by focusing on previously underappreciated statistics like on-base and slugging percentage. As a result, they assembled a world-class team with much less money than their competition. Now most professional sports teams employ a squad of statisticians to look for such anomalies. As Thiel says, many secrets are similarly hidden in plain sight. You just need to know where to look. Science fiction writer William Gibson put it like this: “The future is already here—it’s just not very evenly distributed.” By studying future-facing pockets of people and knowledge across different fields, you can get closer to secrets. Technologies that people use every day started their growth among small groups of innovators many years before they became commonplace. For example, long before computers were everywhere, enthusiasts gathered into groups such as the Homebrew Computer Club in Silicon Valley, which included Steve Wozniak (cofounder of Apple) and Jerry Lawson (inventor of the video game cartridge) among its members. Academic advances and groundbreaking ideas in every area follow a similar pattern, starting with innovators and early adopters before moving into the mainstream (see the technology adoption life cycle in Chapter 4). Find the Homebrew Computer Club equivalent for whatever area you’re interested in and you’ll find active discussions of secrets. Seeking out groups like these puts you in the know. You are then in the position to jump on an innovation bandwagon early and be among the groundbreakers in a new field or industry. However, if you aren’t set on changing the world, secrets can also be used on a smaller scale. Knowing about new technologies can help you improve your day-to-day life, through such current innovations as virtual assistants, new delivery services, or telemedicine. For instance, knowing about new medical advances can help you make better medical decisions, and knowing about the latest car technologies can help you make a safer vehicle choice. Just discovering a secret is not enough; your timing must also be right. Pushing on an idea too soon can result in a lot of wasted time and money, possibly leading you to miss out on the opportunity altogether. Unfortunately, new ideas and ways of doing things can face a lot of challenges that make this timing difficult to get right. A contrarian idea will almost inevitably face a fight against the inertia from the consensus idea (see Chapter 4). This inertia can be a barrier against both the spreading of the idea and the ability to raise capital to fund it. New ideas also often face technological barriers to mass adoption. Uber’s widespread adoption was possible only once everyone had a smartphone. YouTube became a mainstream possibility only once broadband access was prevalent. In both cases there were earlier attempts to accomplish similar things that failed because the timing wasn’t right. The rest of the world wasn’t yet sufficiently equipped with the necessary technology. Apple famously introduced the Apple Newton tablet device in 1993 and discontinued it in 1998 after lackluster sales. More than a decade later, Apple introduced a new tablet device—the iPad—which had the fastest initial adoption rate of any mainstream electronic device up to that point, even ahead of the iPhone and the DVD player. What changed? For one thing, the internet: you could do so much more with the iPad relative to the Newton, given the previous twenty years of internet advances. Similarly, in 1995, Newsweek published a now-infamous opinion piece by Cliff Stroll entitled “The Internet? Bah!” which basically said that the internet’s potential impact was wildly overstated. Cliff Stroll was neither a Luddite nor a noob in the tech world. As stated in his piece, he was an early adopter, having been on the internet already for two decades, even famously catching a hacker. He just couldn’t see that 1995 was the right time for mainstream internet adoption. While it wasn’t yet the right time for a mainstream tablet like the Newton, enough people were coming online to enable sites like Amazon (founded in 1994) and eBay (founded in 1995) to become viable. It is certainly fair and reasonable to question hype, especially because so many overhyped ideas fizzle out before they take off. Additionally, some of the ideas best primed for takeoff aren’t hyped much at all. Psychologist Robert Sternberg explained to Psychology Today : “Creative ideas usually get a weak reception, at least initially . . . but contrarians give their lives meaning by attempting to change the way things are to the way they think they should be.” William Brody, former president of Johns Hopkins University, told a story in a 2004 faculty newsletter about giving a presentation about digital radiography as a young faculty member in the late 1970s to a standing-room-only crowd at an international meeting. The promise of this new technology was the totally “filmless” radiology department, and he had some interesting results to share. Next door, a new imaging technology was presented to only a handful of people, most of whom were collaborators or family of the presenter. While decades later the medical community was still waiting for filmless radiology departments, the other presenter, Sir Peter Mansfield, went on to win a Nobel Prize in 2003 for his contributions to the invention of magnetic resonance imaging (MRI) technology. To address this timing question more systematically, ask yourself why now? This simple yet powerful mental model comes from venture capital firm Sequoia Capital, early investors in Apple, Oracle, PayPal, YouTube, Instagram, Yahoo!, WhatsApp, and many more business ideas that went on to become household names. For every rocket-ship startup, there is a good answer to this question underpinning it, usually based on some rapidly unfolding secret due to a confluence of recent advances and adoption of underlying technology. The same concept applies for almost any change you want to make, from trying out a new organizational process to pursuing a new career. Why now? Would it make a difference if you waited longer? What would you be waiting for in particular? Given the array of things you can work on, is there another change you should be making right now? You can also consider this question using inverse thinking (see Chapter 1). Instead of asking why now?, ask now what? When you see something change in the world around you, ask yourself what new opportunities might open up as a result. From the political sphere to the personal and organizational, many sweeping changes happen in the wake of a real or impending crisis. Politician Rahm Emanuel offers this perspective: “You never want to let a serious crisis go to waste. And what I mean by that [is] it’s an opportunity to do things you think you could not do before.” The why now model also explains why there are often concurrent academic discoveries across the world and similar startups independently emerging simultaneously. Wikipedia has a huge list of instances like these, and there is a name for the concept: simultaneous invention , or multiple discovery . Modern calculus was independently formulated around the same time in the seventeenth century by Isaac Newton and Gottfried Leibniz. And as we mentioned in Chapter 4, Charles Darwin and Alfred Wallace jointly published the theory of natural selection after independent discovery. The underlying conditions were ripe for these ideas, and often more than one person will act on the same secret once they have determined the time is right to pursue the opportunity. VISION WITHOUT EXECUTION IS JUST HALLUCINATION Unfortunately, even knowing a secret at the right time still isn’t enough to guarantee success. People with great, timely insights often fail to achieve great returns due to poor execution. In this section we will explore mental models that can improve your chances of successful execution. The title of this section is a modern take on an old Japanese proverb, “Vision without action is a daydream. Action without vision is a nightmare.” Successful, world-changing ideas almost always involve changing the behavior of a large group of people: how they live, work, entertain themselves, or even how they think. For example, as noted earlier, Airbnb has changed the way many people travel. Whether your idea is business-focused or not, you can think of the people whose behavior it seeks to change as your “customers.” In this context, your secret is the insight you have on how the behavior of your customers should be changed, e.g., people should be able to rent out rooms directly from one another. Your “product” is therefore how you specifically are using your secret to cause a behavioral change in your customers, e.g., creating a marketplace of rentable rooms over the internet. Even if you are the first to market with the idea, you will still lose out to the competition if your product cannot create the necessary behavioral change. The first person or organization to try to capitalize on a secret can indeed have a first-mover advantage , crafting a competitive advantage derived from being the first to move into a market with a product. However, they can also experience a first-mover disadvantage if they make a lot of mistakes. Fast-followers can copy the first mover, learn from their mistakes, and then quickly surpass them, leaving the first mover ultimately disadvantaged even though they were first. For a first mover, the difference between success and failure hinges on whether they can also be first to achieve product/market fit . That’s when a product is a such a great fit for its market that customers are actively demanding more. This model was also developed by Andy Rachleff, who explained in “Demystifying Venture Capital Economics, Part 3,” “First to market seldom matters. Rather, first to product/market fit is almost always the long-term winner. . . . Once a company has achieved product/market fit, it is extremely difficult to dislodge it, even with a better or less expensive product.” A company without product/market fit finds it extremely hard to obtain customers; in contrast, a company with product/market fit finds it relatively easy to obtain customers. This concept can be widened to “fits” in a variety of situations: person/organization fit, member/group fit, culture/strategy fit, message/audience fit, etc. As we explored in Chapter 8, a person in just the right role can produce amazing results, and an organizational strategy attuned perfectly to its culture can be a quick and resounding success. Similarly, a message can strike just the right tone for a specific audience such that it will deeply resonate. You see this phenomenon repeatedly in politics when certain candidates hit a nerve with a segment of the population, as Bernie Sanders and Donald Trump did in the U.S. 2016 presidential election cycle. A model that captures these phenomena is resonant frequency . This model comes from physics and explains why glass can break if you play just the right note: Each object has a different frequency at which it naturally oscillates. When you play that frequency, such as the right tone for a wineglass, the energy of the wave causes the glass to vibrate more and more until it breaks. When you achieve product/market fit, the effect is similar. When this happens, results are not just a little better, they’re dramatically better. Product is flying off the shelves. That’s what you’re looking for with product/market fit or any other fit—signs of real resonance. In Chapter 8, we also discussed 10x teams . True resonance is like that: not one or two times better, but many, many times better. Resonance One way to increase your chances of getting to product/market fit is through customer development , a product development model established by entrepreneur Steve Blank that focuses you on taking a customer- centric view. Customer development’s goal is to help you find a sustainable business model by applying the scientific method (see Chapter 4) through rapid experimentation with your customers. You set up a quick feedback loop with them to learn as much as you can about their needs, resulting in a repeatable process to acquire and retain them. Way back in Chapter 1 we explained how you want to de-risk an idea by testing your assumptions as cheaply as possible. Customer development is one way to do that, by talking directly to customers or potential customers. As Blank says, “There are no facts inside the building so get the hell outside!” If you can ask the right questions, you can find out whether you have something people really want, signaling product/market fit. Of course, you probably won’t make something people really want on the first shot. That’s why you build an MVP (again, see Chapter 1) and run experiments with customers to see how it is actually used (if at all), continually refining your product as you incorporate real-world feedback via this rapid experimentation process. Customer development works in a wide variety of situations: Talk to residents before you move somewhere. Interview current employees before you take a job. Poll a community before enacting a new policy. For any idea you have, think about who the “customer” is and then go talk to them directly about your “product.” Think focus groups, surveys, interviews, etc. When you are trying to act on a secret by delivering a product or service, you are in a race against your competition for product/market fit. To give yourself the best chance of winning this race, you must engage in customer development the fastest. A model from the military can help: the OODA loop , which is a decision loop of four steps— observe , orient , decide , act ( OODA ). U.S. Air Force colonel John Boyd developed the OODA loop to assist fighter pilots in dogfights, where there isn’t time for analysis between actions. Each pilot is trying to quickly outmaneuver the other, reacting to the other’s moves and surrounding circumstances. Boyd showed repeatedly that the pilot who can adjust more quickly—who moves faster through the OODA loop—will usually win. They take an observing glance at the changing conditions, immediately re- orient their assessment of the situation, decide the next best course of action, act on it without hesitation, and then repeat this loop. OODA Loop The faster you can make your OODA loop, the faster you can incorporate external information, and the faster you’ll reach your destination, be that product/market fit or something else. The OODA loop applies best in situations where rapid learning will give you an advantage; not every situation is so uncertain and ever changing, though many are. One area that is always changing and evolving is technology, making it a great example of an area where OODA loops are particularly effective. Increasingly, all major businesses, not just traditional “tech” companies, are trying to utilize technology to gain an edge on their competition. As a result, creating fast OODA loops is becoming more important over time. The organization with the fastest OODA loop learns faster than its competitors, consistently makes better decisions, and adapts faster to the unfolding technology landscape. OODA loops may call natural selection to mind (see Chapter 4). Species that have faster life cycles evolve faster, so you might say they have a faster OODA loop. For example, some bacteria can create a new generation in fifteen minutes. This is a primary reason why it doesn’t take long for bacteria to become resistant to the drugs designed to fight them. Similarly, having a faster OODA loop helps you adapt faster to changing circumstances, including reaching product/market fit before your competitors. If, after extensive customer development, you still cannot find this promised land of product/market fit, then you must pivot to something different. A pivot is a change in course of strategic direction, and there are many famous examples. You may be surprised to know that Twitter started as a podcasting network or that Nintendo actually dates back to 1889, when it was founded as a playing-card manufacturer. Over the course of Nintendo’s history, it tried its hand at a variety of businesses with limited success (taxi service, motel chain, TV network, instant rice sales). After its stock price bottomed out in 1964 as playing-card sales dropped, it was saved by a pivot to the toy industry after a maintenance engineer, Gunpei Yokoi, invented the Ultra Hand toy. Yokoi thereafter took a leading role in transitioning Nintendo into a video game powerhouse. Some pivots are less extreme. For example, PayPal started out as a way to beam payments physically between handheld devices before finding product/market fit with online payments. Similarly, Starbucks started out selling roasted whole coffee beans and equipment. In fact, Starbucks didn’t sell its first latte until thirteen years after the company was founded. After a trip to Italy, employee and future CEO Howard Schultz persuaded the founders to test the coffeehouse concept after seeing the popularity of espresso bars in Milan. Schultz eventually bought the company from them and expanded Starbucks to what it is today. Pivoting is usually difficult because it cuts against organizational inertia, involves openly admitting failure, and requires finding a better direction, all at the same time. But it can also be necessary. Pivoting is appropriate when your current strategy is not going to bring you the results you are seeking. Consulting advisers, who can more easily see your situation objectively, can help you determine whether a pivot is a good move. More broadly, pivoting can apply across all areas of life: your career path, a difficult relationship, how you’re approaching meeting your child’s educational needs, and so forth. When considering a pivot, you can use a few mental models to help you decide what to do. Harvard Business School professor Clayton Christensen named and championed the model of jobs to be done , which asks you to figure out the real job that your product does , which can be different than what you might initially think. An oft-cited example by Christensen is a power drill: “Customers want to ‘hire’ a product to do a job, or, as legendary Harvard Business School marketing professor Theodore Levitt put it, ‘People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!’” Knowing the real job your product does helps you align both product development and marketing around that job. Apple does this exceptionally well. For instance, it introduced the iPod in 2001 amid a slew of MP3-player competitors but chose not to copy any of their marketing lingo, which was focused on technical jargon like gigabytes and codecs. Instead, Steve Jobs famously framed the iPod as “1,000 songs in your pocket,” recognizing that the real job the product was solving was letting you carry your music collection with you. In a December 8, 2016, podcast with Harvard Business Review , Christensen describes another illustrative example, this one about milkshakes served at a particular fast-food restaurant. You might assume that a milkshake’s job is to be a special treat to cap off a meal. While it is true that many parents order shakes as an after-dinner family treat, this restaurant learned that almost half of their shake customers were using them for a different job—to make their long morning commutes more interesting. People felt their trips were more enjoyable as they sipped milkshakes while moving through traffic. Doing two jobs at once sounds great, but that usually means at least one job isn’t being done particularly well. In this case, parents didn’t like how long it took their kids to drink the shakes. Yet that was one of the key features for the commuters. The restaurant chain realized they needed two different products to do the two different jobs well. They decided to further improve the shake for the commuters by making it even thicker, adding more chunks, and moving the shake machine to the front of the stores for the fast on-the-go service that commuters wanted. They then needed to market a wholly different dessert product to kids and their parents. When you truly understand what job people are really trying to get done by using your product, then you can focus your efforts on meeting that need. Asking customers what job they really want done can tell you the root of their problem and eliminate faulty assumptions on either side, ultimately resulting in a solution with a higher chance of success. In your analysis, you want to figure out what job your product is really currently doing and where it might be miscast, as in the milkshake example (see 5 Whys in Chapter 1 for a tactical technique). When you talk to customers, beware of their focus on a specific solution instead of on the problem they’re trying to solve. For example, as a statistician, Lauren has often been asked to perform statistical analyses using a specific computational technique. However, the particular techniques suggested are often the wrong ones. That’s because non-statisticians are usually unable to determine the best statistical plan on their own, and so instead they suggest a technique they know, regardless of whether it is appropriate (see Maslow’s hammer in Chapter 6). Telling a client or colleague that they are proposing to solve a problem in completely the wrong way can at times be difficult. Lauren recognizes, though, that using a particular technique is not really the job the client wants done. The client really wants a correct analysis, and will gladly accept that analysis from Lauren regardless of how she gets there. To approach these situations, Lauren tries to get the client to take a step back and define their ultimate objective, using layman’s terms. Outside of business, you can ask yourself the same questions in the context of any personal connection (“What does this person really want out of this relationship?”) or anywhere you are contributing (“What did they really hire me to do?”). From this perspective, you can determine whether you are really getting the job done with your current strategy. Is there a different approach that might do the job better? Understanding the answer to these questions will help you determine whether you need to make a pivot. Another clarifying model is what type of customer are you hunting? This model was created by venture capitalist Christoph Janz, in a November 4, 2016, post on his Angel VC blog, to illustrate that you can build large businesses by hunting different size customers , from the really small (flies) to the really big (elephants). What Type of Customer Are You Hunting? Janz notes that to get to $100 million in revenue, a business would need 10 million “flies” paying $10 per year, or 1,000 “elephants” paying $100,000 per year. Believe it or not, there are successful $100 million revenue businesses across the entire spectrum, from those seeking “amoebas” (at $1 per year) to those seeking “whales” (at $10 million per year). More commonly, with any project, and certainly with a business, you want to define what success looks like and whether it is achievable under reasonable assumptions and time frames. Janz’s framing steers you toward a particular quantitative evaluation: How many “customers” will it take to achieve success? And what exactly do you need them to “pay” (or do)? Once you answer these questions, you can then ask whether there are enough of these types of customers out there. If not, you might consider pivoting toward bigger or smaller types of customers. A key reason why this model matters is because how you interact with your customers depends on the type of customer you are hunting. If you need to reach ten million people, you can’t do that by talking individually to each one. Additionally, it is challenging to get ten million people to pay a high “price” for a product. In contrast, you can deal individually with one thousand customers and get each of them to “pay” you more. In the business context, hunting different customers means deciding to put out a free or minimally priced service to millions of people (like Spotify or Snap) versus selling a high-priced product to large enterprises (like Oracle or Salesforce). Or, within an industry, it’s deciding between customer segments that choose to pay much different amounts, such as Rolls-Royce and Lamborghini versus Kia and Hyundai in the automobile sector. In a political context, a candidate in a local election can try to meet all their constituents, but this type of outreach becomes impossible in larger elections. And in those larger elections, fundraising becomes increasingly important because of the need to turn to TV and the internet to reach everyone, which is relatively expensive. This political reality has the consequence that statewide and national politicians need to focus considerable attention on courting (hunting) deep-pocketed individuals (whales/dinosaurs/elephants) to foot the bill for this advertising. A quantitative evaluation like this one is an example of a back-of-the-envelope calculation , a quick numerical assessment that you can calculate literally on the back of an envelope . A simple spreadsheet is the modern-day equivalent. This type of exercise forces you to quantify your assumptions and can quickly result in clarifying insights. With jobs to be done , you are asking what stakeholders are “hiring” you for. With what type of customer are you hunting? you are asking how many “customers” you need to be hired by and what you want them to give you in exchange for your doing the job. Like customer development, both of these models ask you to think from the customer perspective. Thinking this way can also help you develop personas , fictional characters that personify your ideal customers, which will help you better reason through a realistic assessment of your idea. What kind of people are your customers exactly—what are their demographics, likes versus dislikes, and hobbies? If you did customer development right, your personas should be modeled on characteristics of real people you’ve already met. Once constructed (say Bob and Sally are your personas), you can ask yourself: Would Bob and/or Sally do X? Thinking in terms of actual people, fictional or otherwise, can really ground you in the customer perspective and help you apply these assessment models more effectively. However, be careful not to allow availability bias (see Chapter 1) to limit the factors you consider for creating these personas. The most easily collected or available data might not lead to the most useful personas. Looking at the totality of these models, you should now know what success looks like (how many customers you need and what you need them to do) and whether you see a realistic path toward that goal. So, should you pivot? If the answer is still unclear, one litmus test is this: Do you have any bright spots , positive signs in a sea of negative ones? In a business context, this would be a small subset of customers who really like what you’re doing and are highly engaged with your product. Outside of business, you might look to the bright spots in your current job when considering the prospect of pivoting your career: What are the things you really like about your job? Are there enough of them to make you stay? What aspects would you like to retain if you do choose to pivot? If you have no bright spots after some time, it is likely you do need to pivot. It’s like the old phrase “You don’t have to go home, but you can’t stay here.” If you do have some bright spots, you can try to figure out why things are working there and focus on growing out from that base. This is actually a useful strategy for advancing any idea, struggling or otherwise, drawing on the military concept of the beachhead . That’s where a military offense takes and defends a beach so that more of their force can move through the beachhead onto the greater landmass. In other words, a beachhead is getting a foothold and using it as a launching point. Amazon’s beachhead was books. Tesla’s was its Roadster. These were positions they could stake out in the market, and then use to expand into adjacent markets. For your career, your beachhead might be your current skills and position, which you could use to launch toward a better position or more fulfilling career. A beachhead strategy is only one way to navigate the process of taking your secret and turning it into a product that achieves product/market fit. More broadly, this process can be compared to navigating a maze, what investor Balaji Srinivasan calls the idea maze . Imagine a physical maze, as in a corn maze at a fall festival or a hedge maze in a formal garden. The entrance is you starting out on your idea, and the exit is your idea’s ultimate success. Within the maze are lots of dead ends, and it is your job to navigate the maze and successfully get to the other side. As he said in a lecture: Josh Kopelman, another investor, equates founders who can successfully navigate the perils of finding product/market fit with heat-seeking missiles . As he wrote on his Redeye VC blog on August 2, 2010: These metaphors can apply to navigating any path in life. Successfully navigating the idea maze means understanding how best to interact with the people in your life through understanding what you want and need from them and what they want and need from you. It’s recognizing when you are on the wrong path in the maze, deciding when and how to pivot, and having the resilience to find a way to navigate obstacles put in your path. ACTIVATE YOUR FORCE FIELD Once you achieve product/market fit or whatever type of fit you are trying to achieve, it is time to protect your position. Warren Buffett popularized the term moat , making an analogy to the deep ditch of water surrounding a castle to describe how to shield yourself from the competition, thereby creating a sustainable competitive advantage. Moats are situationally dependent. The following are some cases in which they are used (not mutually exclusive): Elon Musk notably sparred with Warren Buffett on the concept of moats. In Musk’s words from a May 2, 2018, Tesla earnings call: “Moats are lame,” and “If your only defense against invading armies is a moat, you will not last long.” He was pointing out that, in his opinion, the most important sustainable competitive advantage is creating a culture that supports a higher pace of innovation, because that higher pace of innovation can overcome traditional moats. In our opinion, though, a higher pace of innovation is really just another type of moat, and the metaphor of the moat shouldn’t be taken too literally. Instead of a static moat, consider the sci-fi equivalent of a force field or a deflector shield, which allows you to move at warp speeds while still offering protection. You can both continue innovating (at warp speed) and also employ other types of moats (for increased defenses). The Eastman Kodak Company is a great case study on how to build a moat. Founded in 1888, Kodak dominated the camera market for a hundred years. It arguably had significant moat protection in all the categories mentioned above, successfully fending off competitors and reaping outsized profits for a century: When assessing your possible sustainable competitive advantages, be explicit. A list like the one above can be a big help. What are you doing that competitors can’t copy? What will keep the competition at bay and allow you to exercise your market power for the long term? Any single advantage could serve as the basis for your moat, but, as you can see from the Kodak example, several advantages can also work together, amplify one another, and produce an even bigger moat (force field). As we will see in a bit, though, even the biggest moats don’t last forever. These same moat types can apply to your personal place in an organization or field as well. For example: You can have the biggest personal network (exclusive access to relationships). You can build a personal following (strong, trusted brand). You can become the expert in an in-demand area (unique qualifications). You can create a popular blog (substantial control of a distribution channel). Each of these and more can create a moat that protects your place in a competitive landscape. Organizations and individuals that control working moats create lock-in when customers are locked in to their services because perceived switching costs are so high. There are many ways to create switching costs, such as cancellation fees, trusted relationships, new equipment costs, learning curves, network effects (see Chapter 4), brand affinity, etc. Many people feel locked into Facebook because this is how many of their friends and family choose to share photos and updates of what is going on in their lives. Employers can feel locked into certain key employees, which gives these employees leverage to ask for raises or other benefits. Some employees are so critical to a business’s operations that there is a whole class of insurance products called key person insurance, which pays out if these key people become incapacitated. These concepts also apply well beyond business situations. Many people feel locked into personal relationships, since the perceived costs (including emotional and psychological costs) of these changes are so high. Or you may feel locked into your housing situation, given the costs of physically moving and the opportunity cost (see Chapter 3) of spending your time on picking a new place, packing your things, making new friends, etc. Even countries get locked into diplomatic arrangements with high switching costs, as in the case of Brexit. A related pair of concepts resulting from moats are barriers to entry and barriers to exit , which prevent people or companies from either entering or exiting a situation or market. A new mobile operating system wanting to compete with Apple’s iOS or Google’s Android would need to re-create an app store populated with thousands of useful apps, a large barrier to entry. Some careers have high barriers to entry, such as expensive years of schooling required. Similarly, some personal contracts, such as noncompetes, partnership agreements, or even marriage, create significant barriers to exit. As with switching costs, barriers to entry and exit can come in many forms, such as trade secrets, like the Coca-Cola formula; high capital investment, like the cost of a huge factory; and government regulations that protect incumbents. A specific model centered on barriers to entry due to regulation is called regulatory capture , in which regulatory agencies or lawmakers get captured by the special interest groups they are supposed to be regulating, ultimately protecting these entities from competition. In 2012, Jeff Donn reported on a year-long Associated Press investigation of the U.S. Nuclear Regulatory Commission [NRC], resulting in a lengthy four-part series that noted: The disheartening part about this example is that nuclear power done right can be a safe and essentially unlimited source of low-carbon energy. Not regulating it effectively foments fears of nuclear energy and sets back the entire industry. Nobel Prize–winning economist Joseph Stiglitz pioneered the model of regulatory capture. One reason for its common occurrence is that special interest groups often collectively lobby regulators via lobbyists, whereas the individuals affected do not tend to put together strong lobbying efforts due to their lack of organization. Another reason is that the regulators themselves often operate in a revolving-door pattern in which, after their time as regulators, they take highly compensated jobs in the industry they were just regulating. Regulatory capture can happen outside the government as well, such as in occupational licensing, where certain occupations restrict the supply of professionals through control of their licensing boards and processes. For example, according to a Brookings report, in the U.S. about one-quarter of current jobs require a license, up from just 5 percent in the 1950s. These licenses cover occupations that you might think they should, such as medicine, and also those you might not think of, such as cosmetology. Critics contend that while some licensing can make sense, the trend is to require too much money and time to acquire these licenses, which protects people who already have them at the expense of competition. For example, they found the “number of days to obtain a cosmetology license varies from 232 in New York to 490 in Iowa.” Another common example is nonprofit or community boards that get overrun by the personal interests and motivations of friends or family. In its worst form, regulatory capture is just plain corruption, though it often also occurs naturally with good-faith intentions through regulators not seeking broad enough input from their constituents or not conducting comprehensive impact assessments (see availability bias and confirmation bias in Chapter 1). There are ways to diminish regulatory capture. As U.S. Supreme Court justice Louis Brandeis famously wrote in Other People’s Money , “Sunlight is said to be the best of disinfectants,” meaning that allowing people to see and understand regulation and its effects—increasing transparency—can lead to less regulatory capture by special interests. When people are held accountable and made to explain their actions, change can more easily occur. Strong moats, including those built upon regulatory capture and especially those built on network effects, can also lead to winner-take-most markets . This is where one company, once it reaches critical mass (see Chapter 4) through its network or dominant position based on another sustainable competitive advantage, effectively wins the market by taking most of the customers within it. For example, with more than two billion people on Facebook, a competitor won’t find it easy to re-create that network and compete with Facebook’s core offerings. Just because you won the market, however, doesn’t mean you will win in perpetuity. Andy Grove, former CEO of Intel, famously wrote in his 1999 book of the same name, “ Only the paranoid survive .” Intel’s early dominance was in memory chips; however, by the mid-1980s, Japanese manufacturers had effectively erased much of its competitive advantages in this market. But at the height of its dominance, Intel foresaw this existential competitive threat. As a result, it pivoted the focus of the company into microprocessors and reestablished a long-lasting moat (“Intel Inside”). Grove’s words serve as a reminder that even if you establish a working moat, you must be constantly evaluating the strength of it, and even when you have a strong product/market fit, your moat may give way and you may need to eventually pivot. And Intel’s new moat did in fact eventually give out with the rise of the chips that power the smartphone and other smaller devices. Remember Kodak? Its moat was also disrupted, though it didn’t pivot in time as Intel did from memory chips. In the 1990s, Kodak was rapidly disrupted by digital photography, and it ultimately declared bankruptcy in 2012 after a century of market dominance. You might think that it got caught off guard, but that isn’t true, just as it usually isn’t true in similar cases. As mentioned, Kodak’s investment in research and development was part of its moat. Kodak actually developed the very first digital camera, way back in 1975! But the timing wasn’t right for digital photography to prosper then, due to lack of a supporting ecosystem—graphics cards were not fully developed, physical hard drive size was too big, etc. Meanwhile, Kodak had been making most of its money from selling film. Digital photography of course has no film, and once it prospered, it fundamentally disrupted Kodak’s profitable analog model. When disruptive technologies like this first emerge, they are usually inferior to the current technologies in the ways that most buyers care about. For decades, digital photography was comparatively expensive and produced lower-quality photographs than film; however, its convenience (in not having to develop pictures) appealed to some buyers and allowed the market to progress. Slowly but surely, the price and performance gap between digital and film closed. Once it crossed the tipping point (see Chapter 4) of being attractive to most consumers, the digital camera market exploded. Consumer Camera Sales Analog vs. Digital, 1995-2012 Kodak wasn’t blind to these developments either. Initially it was even the market leader in digital cameras too, with a 27 percent share in 1999. However, it didn’t invest heavily enough in the technology relative to its competitors, the way Intel did when pivoting to microprocessors. Kodak simply wasn’t paranoid enough. The overall market for photography quickly and fundamentally shifted from the high-margin film business to a highly commoditized digital camera business, and Kodak simply wasn’t fast enough to adapt. It didn’t use its flywheel from the film business to fuel its path to domination in digital, and its share of the exploding digital photography market fell as a result. In 2007 Kodak was number four in digital photography and by 2010 they fell to seventh, at 7 percent market share, behind Canon, Sony, Nikon, and others. Just as this happened, these same digital camera manufacturers were similarly disrupted by Apple, Samsung, and others producing smartphone cameras. Same story: First, these new “cameras” were relatively expensive and produced lower-quality photographs, but they were more convenient. Over time, however, the quality kept increasing and there were more and more reasons to have a smartphone, leaving not enough reasons to have a separate digital camera. It is an interesting question in counterfactual thinking (see Chapter 6) to ask what would have happened if Kodak had tried to develop the digital photography market earlier. Would it have been able to dominate that market? Would we all have had digital cameras years earlier? Could it have eventually pivoted into a role powering the cameras in most smartphones or pivoted even more drastically and created a product like Instagram? We’ll never know. Consumer Camera Sales Digital vs. Smartphone, 2002-2016 In Clayton Christensen’s seminal work The Innovator’s Dilemma , he lays out the framework for how such disruptive innovations ripple through industries, ushering new industry entrants into power while leaving dead incumbents in their wake. The incumbent’s dilemma is whether to embrace the disruptive technology, usually at the great cost of the existing business. That’s what Intel did but Kodak didn’t do. If Kodak had more readily embraced digital camera technology, it would have directly cannibalized its outsized profits in analog film technology. Similarly, many companies are right now facing difficult decisions about whether to embrace new disruptive innovations like artificial intelligence, solar power, streaming video, driverless vehicles, and electric cars. Individual workers face comparable issues. Over the past decades, globalization has dramatically changed the job responsibilities and prospects for many across a wide swath of industries. Employees who were essential at one time saw their moats destroyed. Similarly, automation and artificial intelligence are poised to disrupt many more jobs over the coming decades. If you see disruption on the horizon in your field, you ought to prepare to respond sooner rather than later. Maybe that means investing in a new set of skills; maybe it means switching responsibilities; maybe it means pivoting to another field altogether. Unfortunately, truly embracing a disruptive innovation usually means major upheaval to the company or person itself: major losses of revenue in the short term, retraining from the ground up—a major pivot. There have been many instances where pivots have been advisable at the height of market dominance or earning potential. Unfortunately, market dominance can correspond with complacency. That’s why only the paranoid survive—you have to be paranoid to perceive the threat of something so small or far off in the future when you are in such good shape. When you embrace this model, you must therefore pay attention to a lot of small threats, most of which will turn out to be harmless. How do you distinguish the signal from the noise ? One approach is to closely monitor the progression of new threats as they progress from being used just by early adopters to being taken up by the mainstream, along the curve of the technology adoption life cycle as described in Chapter 4. Many technologies or ideas often capture some interest by innovators or early adopters, but very few actually make the jump to the early majority of the mainstream. Business strategist Geoffrey Moore named this jump crossing the chasm in a book by the same name. The chasm here refers to the fact that many ideas, companies, and technologies fail to make it from one side to the other. That’s because there is a huge gulf in expectations between early adopters and the early majority, which most things fail to meet. Early adopters like to tinker with things or are a small subset of people who really need something, but to cross the chasm into the early majority, a product has to solve a real ongoing need for a lot more people. And most products just aren’t compelling enough to cross this gulf and truly spread into the mainstream. Crossing the Chasm But if you think a competitive threat does have a decent chance of crossing the chasm, you should pay close attention. That’s because if they do cross the chasm, it will mark a tipping point of significant and much more rapid adoption. You need to be prepared when that happens, not caught off guard like Kodak. This process of maintaining your market power is never ending. You are constantly assessing new threats, bolstering the strength of your moats, and pivoting as needed over time. If you let your guard down, you will surely be disrupted. On the other hand, if you focus on maintaining your market power, which may involve some major pivots, you may be able to reap its benefits indefinitely.