Natural Selection

Becoming One with Nature

BEFORE THE INDUSTRIAL REVOLUTION, most peppered moths in Manchester, England, were light-colored, using trees covered with pale bark and lichens as camouflage to avoid becoming prey for birds. The first reporting of a live dark moth was in 1811, but definitive proof of this variation didn’t appear until the first was captured in 1848. A dark moth was extremely rare, estimated to represent only 0.01 percent of the peppered moth population around that time. But by 1895, the frequency of dark-colored peppered moths in Manchester had risen from 0.01 percent to 98 percent! What happened? During this period, pollution from the new coal factories left the trees covered with soot and killed the pale lichens, resulting in darker trees. The light-colored moths’ color became a liability rather than an asset. The dark-color genes, however, immediately became incredibly useful, as any moths that expressed them were now camouflaged against the dark trees. Birds picked off the light-colored moths in droves, leaving dark-colored moths to propagate and take over the gene pool. England’s Clean Air Act of 1956 cleaned up the pollution, making the trees light again, reversing the trend, and ultimately making the dark-colored moths rare once more.

This rise and fall of the dark-colored peppered moth is a showcase of natural selection, the process that drives biological evolution. It was independently formulated by both Alfred Wallace and Charles Darwin, and later made famous by Darwin’s 1859 book On the Origin of Species by Means of Natural Selection. Traits that provide reproductive advantages are naturally selected over generations, making them more prevalent as species evolve to fit their environment.

Natural Selection Beyond Biology

Beyond biological evolution, natural selection also drives societal evolution, the process by which society changes over time. In any part of society, you can trace the path of how ideas, practices, and products have adapted to ever-changing tastes, norms, and technology. If you magically transported successful companies, movies, and books from fifty years ago to the present day, and released them now for the first time, most would not be successful because society has evolved so much since their heyday. Fifty years is a long time relative to the current rate of societal change. Think of the massive changes that can take place over the course of one generation. When Lauren was the same age as our youngest (seven), she had access to just seven TV channels (cable wasn’t widespread at that time), but now our kids can watch essentially whatever they want whenever they want with Hulu, Netflix, Amazon, etc. No wonder they refer to the 1980s as the “olden days.” You will live through many more societal shifts: economic cycles, waves of innovation, evolving norms and standards. With more people than ever and everyone more connected through the internet and globalization, these shifts are happening faster than in the past.

You must adapt to these changing environmental pressures to be successful. Just as species develop biological adaptations over generations, you need to be open to new ideas and paradigms, adjusting your thinking and behavior as necessary. Similarly, when organizations face disruption, they must find new ways to operate if they want to thrive. Professor Leon Megginson, paraphrasing Darwin, put it like this in a 1963 speech to the Southwestern Social Science Association: “It is not the most intellectual of the species that survives; it is not the strongest that survives; but the species that survives is the one that is able best to adapt and adjust to the changing environment in which it finds itself.” That is, you need to change color like the peppered moth did.

As the CEO of a fast-growing company, Gabriel finds that his job and the jobs of his team look very different from how they looked just eighteen months ago. That’s because as the company grows, what is required of its executives changes, moving initially from building a product (design, creation, etc.) to building a company (managing people, defining structure, etc.), to building a sustainable business (financial models, managing managers, etc.). In such a rapidly changing environment, you need a method for adapting quickly. Luckily, science gives us such a mental model for making sure we stay among the “fittest”: the scientific method.

Formally, the scientific method is a rigorous cycle of making observations, formulating hypotheses, testing them, analyzing data, and developing new theories. But you can also apply it simply by embracing an experimental mindset. The most successful (and adaptive) people and organizations are constantly refining how they work and what they work on to be more effective. As an example, think about your own productivity tools and methods. You can’t expect to discover the setup that helps you do your best work right away. But if you keep experimenting (with different schedules, software, organization, processes, etc.), you will get closer and closer to the optimal setup, enabling you to go much further, faster. The same mindset can be applied to other areas of your life, such as the all-important one of diet and exercise. What type of exercise program can you really stick to? What can you change in your diet or daily routines to make you eat healthier? When a scientific mindset is applied continuously via experimentation, you will improve your chances of being the fittest (some pun intended).

Natural selection and the scientific method are just the start. There are a host of natural laws that can help you understand the changes unfolding around you as well as how to adapt to them and even shape them. This chapter highlights many of these natural super models that can help you be more adaptive and manage change.

DON’T FIGHT NATURE

At some point you have likely heard someone paraphrase Isaac Newton’s first law of motion, often referred to as the law of inertia: “An object at rest stays at rest and an object in motion stays in motion with the same speed and in the same direction unless acted upon by an unbalanced force.” Inertia is a physical object’s resistance to changing its current state of motion. The meme above illustrates this concept in practice. As a metaphor, inertia can describe any resistance to a change in direction. In Chapter 1, we explained how you tend to have significant inertia in your beliefs because of confirmation bias and related models. This adherence to your beliefs can hamper your adaptability. By questioning your assumptions, you can adapt to new ways of thinking and overcome this personal inertia.

Inertia can increase the longer you hold on to your beliefs. If you’re like most people, many of your core political, religious, and social beliefs can be traced to the family and geographic culture in which you were raised as a child. Have you reevaluated these views recently? If not, you are likely clinging to many beliefs that are in conflict with other beliefs you came to hold later, or that you never properly questioned. The more inertia you have, the more resistant you will be to changing these beliefs, and the less likely you will be to adapt your thinking when you need to.

Think about how scientific theories change over time, but how old “facts” still persist. When our parents were in school, they weren’t taught about how an asteroid led to the extinction of the dinosaurs, because that theory wasn’t put forth until 1980. And now, forty years later, this widely accepted asteroid theory has come under increased scrutiny in terms of how large a role it actually played in causing the mass extinction. Something different may very likely be in textbooks decades from now. Have you heard that the latest research indicates that Tyrannosaurus rex had a form of feathers over parts of its body? Or that the war on saturated fat and dietary cholesterol that loomed large when we were kids in the 1980s has been completely revised, and now whole milk and eggs are thought to be part of a healthy diet? It can be hard to change old habits and beliefs once they are so ingrained, even if you now know them to be flawed. We are of course aware of both of these revisions, but still the image that comes to mind when we hear about T. rex is not that of a feathered dinosaur, and we still take pause at the idea of eating eggs every day.

Organizations face a similar danger because of inertia. A long-term commitment to an organizational strategy creates a lot of inertia toward that strategy. This inertia can lead to suboptimal decisions, referred to as a strategy tax. For example, most people would like to reduce their online footprint and be tracked less by advertisers. As a result, web browsers have incorporated more privacy features. For example, in 2017, Apple’s Safari browser introduced a feature called Intelligent Tracking Prevention, which attempts to prevent ads from following you around the internet. However, we expect that Google will not add a feature like this to its Chrome browser, because Google itself is the company tracking you on most sites, since its long-term strategy is to dominate online advertising. Since Google tracks you, it can sell advertisers the ability to follow you around the internet with its ads. Google’s strategy of being the world’s biggest advertising company requires it to pay the tax of not adding significant anti-tracking features to its browser, since doing so would counteract that strategy. Apple does not have to pay this tax since it does not have such a strategy.

Politicians and political parties create strategy tax when locking themselves into a long-term position. For example, the U.S. Republican Party has staked out a position that opposes climate change mitigation, with many politicians denying that man-made climate change is even taking place. As the negative effects of man-made climate change are becoming clearer through increased catastrophic weather incidents, this strategy tax may start to cost politically. Reversing course once a strategy tax is established can be even more costly. In 1988, George H. W. Bush delivered this famous line at the Republican Party’s national convention: “Read my lips: no new taxes.” Later, this commitment caused significant problems for him when he faced a recession as president. Ultimately, Bush decided he had to break his pledge and raise taxes, and it cost him reelection. The lesson here is that you should, as much as possible, avoid locking yourself into rigid long-term strategies, as circumstances can rapidly change. What strategy taxes are you currently paying?

A model related to the strategy tax is the Shirky principle, named after economics writer Clay Shirky. The Shirky principle states, Institutions will try to preserve the problem to which they are the solution. An illustrative example is TurboTax, a U.S. company that makes filing taxes easier, but also lobbies against ideas that would make it easier to file taxes directly with the government. For example, “return-free filing,” a system in which the government would send you a pre-filled form based on information it already has available, would work well for most people. It is already a reality in some countries, saving time and money for millions. Yet TurboTax fights against the adoption of such a program because it wants tax filing to continue to be complex, since it is the solution to that problem. Sometimes a person or department will try to preserve an inefficient process, even when a new idea or technology comes around that can make things easier. Think of the stodgy person at your office or school who is always talking about the “way it’s always been done,” constantly anxious about change and new technology. That person embodies the Shirky principle. You do not want to be that person.

Inertia in beliefs and behaviors allows entrenched ideas and organizations to persist for long periods of time. The Lindy effect is the name of this phenomenon. It was popularized by Nassim Taleb in his book Antifragile, which we mentioned in Chapter 1. Taleb explains: The Lindy effect applies to technologies, ideas, organizations, and other nonperishable things. Assuming that the thing in question is not falling out of favor, the longer it endures, the longer you can expect it to further endure. The Lindy effect explains the continued relevance of Shakespeare and the Beatles. Since they show no signs of falling out of favor, the Lindy effect tells us we can expect Shakespeare plays to be performed for at least another four hundred years, and Beatles songs to be heard for at least another fifty.

Of course, things can and do eventually become unpopular, and there is another mental model to describe the point at which something’s relevance begins to decline. This model is peak, as in peak sexism, peak Facebook. This concept was actually popularized with oil, as peak oil is usually defined as the point in time when the maximum amount of oil is being extracted from Earth. After peak oil, the decline may be a slow one, but it will have begun, with oil production falling each year instead of rising. People have predicted peak oil many times. As far back as 1919, David White, the chief geologist of the U.S. Geological Survey, predicted in “The Unmined Supply of Petroleum in the United States” that the U.S. “peak of production will soon be passed, possibly within three years.” Many similar predictions have come and gone, and peak oil has still not occurred. What has happened instead is that increased demand has driven innovation in how to get more oil out of the ground, continually increasing yearly production. Now, though, a better argument for peak oil is starting to form as the oil market’s underlying structure is proving to be unhealthy. The effects of climate change are looming. Solar energy is quickly becoming cost-competitive with oil on a global scale. Increasing cost-competitiveness of electric cars and the advent of autonomous vehicles and ride-sharing services are threatening to collapse the car and truck markets as we know them. All of these have the potential to create lasting effects on the oil market. Whether you are a market observer or a market participant, these structural changes are worth considering when you’re thinking about a possible new reality for the oil market. Should your next car be electric? Should you buy another car at all?

More generally, the Lindy effect and peak concepts can help you assess any idea or market opportunity and better predict how it might unfold. Is the market healthy? Has it already reached its peak? How long has it been around? Remember, markets that have been around a long time have more inertia. And the healthier the market is, the more difficult it will be to change. In fact, something with a lot of inertia, even after its peak, can take an extremely long time to decline. Over the past decade, consumers have read fewer physical newspapers and have been “cutting the cord” with cable, yet plenty of newspapers and cable subscriptions are still sold and will continue to be sold for decades to come. Similarly, fax machines, video rental stores, and dial-up internet feel like relics of the nineties, but people still send plenty of faxes, and, as of the time of this writing, in late 2018, there still exists a Blockbuster video store in Bend, Oregon, and more than a million people still use AOL dial-up! As Samuel Clemens (aka Mark Twain) said, “The report of my death was an exaggeration.”

U.S. Newspaper Circulation

Momentum is a model that can help you understand how things change. Momentum and inertia are related concepts. In physics, momentum is the product (multiplication) of mass and velocity, whereas inertia is just a function of mass. That means a heavy object at rest has a lot of inertia since it is hard to move, but it has no momentum since its velocity is zero. However, a heavy object gets momentum quickly once it starts moving. The faster an object goes, the more momentum it has. However, its inertia remains the same (since its mass remains the same), and it is still similarly difficult to change its velocity. To relate the concept to a real-world example, sending faxes is continually losing momentum. However, the act still has a lot of inertia since the technology is entrenched in many business processes. As a result, the momentum behind sending faxes decreases very slowly.

In your life, you can take advantage of this concept by seeking out things that are rapidly gaining momentum. For example, you could join an organization that is just starting to take off or start a new organization that leverages an innovative technology or idea that is beginning to go mainstream. In Chapter 3, we discussed the benefits of focusing on high-leverage activities to make the most out of your time. Activities associated with organizations or ideas with high and increasing momentum are very often high-leverage, because your efforts get amplified by the momentum. Similarly, creating inertia by entrenching beliefs and processes in others is also a high-leverage activity. Once they are established, those beliefs or processes will be difficult to unwind, persisting for a long time. Think about those beliefs from childhood that we spoke about earlier and how hard they are to let go.

In an organizational context, establishing such beliefs and norms is the act of creating culture, which we will explore more fully in Chapter 8. Here, though, consider the relation of culture to inertia embodied in this saying: Culture eats strategy for breakfast. It is a warning that if you embark on a strategy that is in opposition to your organization’s culture, which has much more inertia than even its strategy, it is very unlikely to succeed. For example, in 2013 the U.S. government embarked on a strategy to create a website where citizens could directly apply for healthcare coverage. The website, HealthCare.gov, was to be made available on October 1, 2013, though unlike major technology firms, the U.S. government does not have a culture attuned to creating mainstream websites on a deadline. This culture/strategy mismatch was obvious when the government botched the launch of HealthCare.gov. In the first week of operations, only a small percentage of those interested were able to enroll. A strike team was assembled to fix the website, filled with top talent from major tech firms, a group steeped in a culture better matched to this strategy. Quite simply, to be successful you need your organization’s culture to align with its strategy. As an organizational leader, you must recognize if there is a mismatch and act accordingly. As the U.S. government eventually did, you could create a new team with a different culture more fit for the strategy. You could abandon the strategy or pursue a modified strategy more aligned with the existing culture. Or you could try to change the culture over time, steering it toward the desired long-term strategy, recognizing that it may be a slow and challenging process.

In new organizations, you have the opportunity to mold the culture toward long-term strategic directions. However, consider that the world can rapidly change around you. It follows, then, that you eventually may have to rapidly change your organization’s strategy as well. Consequently, the best organizational culture in many situations is one that is highly adaptable, just as it is recommended for people themselves to be highly adaptable. That is, you likely want to craft an organizational culture that can readily accept new strategies or processes. A culture like this is agile, willing to experiment with new ideas, not tied down to existing processes. The good news is that if you can establish inertia and momentum in an adaptable culture, or in any context really, it can have staying power. A mental model that captures this process well is the flywheel, a rotating physical disk that is used to store energy. Flywheels are still used in many industrial applications, though a more relatable example to get the concept is a children’s merry-go-round. It takes a lot of effort to get a merry-go-round to start spinning, but once it is spinning, it takes little effort to keep it spinning.

Flywheel

Nonprofit marketing expert Tom Peterson credits the flywheel model for the growth of the global anti-poverty nonprofit Heifer International from $3 million in revenue in 1992 to $90 million in 2008. In the 1970s, Heifer International created its gift catalog fundraising concept, encouraging people to give a gift like a goat or water buffalo to a family in need in order to make them more self-reliant. With Peterson’s help, Heifer improved the catalog each year, running dozens of experiments through changes to its look, contents, production, distribution, and publicity. This constant testing and experimentation helped the company’s revenue grow a little bit each year, never slowing down. It has continued to sustain higher and higher levels through today. In his book Good to Great, Jim Collins relates many similar examples, using the flywheel metaphor to summarize how companies systematically and incrementally go from good to great. An example of a flywheel in everyday life is how it takes a lot of time and practice to become an expert on a topic, but once you are an expert it takes only minimal effort to remain on top of new developments in the field. On a shorter time scale, any personal or professional project can be viewed from the perspective of a flywheel. It is slow when you get started on the project, but once you gain some momentum, it seems easier to make progress. And as we discussed in Chapter 3, when we multitask, we never get enough momentum on any one task for it to start to feel easier. Instead, we are constantly spending energy starting and restarting the wheel rather than taking advantage of its momentum once we get it to start spinning. The flywheel model tells you your efforts will have long-term benefits and will compound on top of previous efforts by yourself and others. It’s the tactical way to apply the concepts of momentum and inertia to your advantage.

On the other hand, trying to change something that has a lot of inertia is challenging because of the outsized effort required. That doesn’t mean it isn’t worth the effort, but you should go in with eyes wide open, knowing that it can be difficult and time-consuming. If you do decide to try enacting such a change, there are several useful models to aid you in your quest.

First, from biology, there is homeostasis, which describes a situation in which an organism constantly regulates itself around a specific target, such as body temperature. When you get too cold, you shiver to warm up; when it’s too hot, you sweat to cool off. In both cases, your body is trying to revert to its normal temperature. That’s helpful, but the same effect also prevents change from the status quo when you want it to occur. In general, societies, organizations, families, and individuals usually exhibit homeostasis around a set of core cultural values or metrics that relate to the status of the group. Doing so ensures their self-preservation (or so they think). For example, in the U.S., attempts at campaign finance reform have continually failed as lobbying groups have found new and innovative ways to react to regulations, and they continue to infuse their money into politics. On a more mundane scale, within organizations or communities, people often naturally resist change, regularly responding with the mantra “If it ain’t broke, don’t fix it,” “Don’t rock the boat,” or “That’s how we do things around here.” This reaction can be rationalized and justified because change can be disruptive, even if the proposed end state has attractive benefits. In our kids’ school district right now, there is a debate about changing the school start times based on solid research showing that teenagers do better with later start times. However, moving school times causes a decent amount of disruption to various pockets of the community, and would require many families and teachers to adjust their schedules and arrangements, such as for childcare. If the goal is to achieve the best educational outcome for the students, the data shows that start times should be moved, though the reaction to protect the status quo is nevertheless understandable. Unfortunately, as a result of these types of homeostatic reactions, we stay in suboptimal arrangements for too long, from toxic personal relationships to poor organizational processes, all the way up to ineffective government policies.

When you fight homeostasis—in yourself or in others—look out for the underlying mechanisms that are working against your efforts to make changes. A good example would be exercising more to lose weight only to have your increased exercise lead to an increased appetite. Anticipating this reaction, some people eat protein after working out to mitigate the homeostatic effect, because certain types of slow-digesting proteins help you feel full for longer. What is the “eating protein” equivalent in whatever situation you’re dealing with? Finding the answer can help you overcome the status quo. One common approach is to get data that support the desired change, and then use that data to counteract objections to it. In the school start-times example, some people claim that making the start time later will just cause teenagers to stay up later, negating the effect. But studies from actual school districts that have already made the change show that is not the case, and that teenagers do in fact sleep more on average with later school times.

This concept of trying hard not to deviate from the status quo reminds us of a toy that is generically called a roly-poly toy (in the U.S., Playskool had a branded version called a Weeble—“Weebles wobble, but they don’t fall down”), which rights itself when pushed over. These toys work using two useful concepts that are also metaphorical mental models that help you when enacting change: potential energy and center of gravity. Potential energy is the stored energy of an object, which has the potential to be released. Center of gravity is the center point in an object or system around which its mass is balanced.

Potential Energy

Any time a roly-poly is tilted, its potential energy increases, as it takes in the energy used to tilt the toy. When released, this energy gets translated into a wobble around its center of gravity. Potential energy like this comes in many physical forms: gravitational, such as any object lifted up; elastic, such as a taut bowstring or spring; chemical, such as the energy locked up in food or fuel; etc. Metaphorically, we talk about people and organizations having pent-up energy, energy waiting to be unlocked, released from its stored state, and unleashed on the world. Hidden potential energy is another thing you can look for when seeking change. Think of people in your organization who are motivated to make the change happen. They may be willing to help you. Talking to a diverse set of potential stakeholders can help you discover these hidden pockets of potential energy.

The term center of gravity is used notably in military strategy to describe the heart of an operation. Knowing an opponent’s center of gravity tells you where to attack to inflict the most damage or what pieces of their infrastructure they will defend more than others. The closer to their center of gravity, the more damage you will cause, and the more they will risk defending it. As applied tactically to enact change, if you can identify the center of gravity of an idea, market, or process—anything—then you might effect change faster by acting on that specific point. For example, you might convince a central influencer, someone other people or organizations look to for direction, that an idea is worthwhile. Businesses often take advantage of this concept by seeking endorsements from celebrities, influencers, press, or marquee clients. One endorsement can have a cascading effect, as your idea is able to spread because you convinced the right person. In this context, it’s a type of pressure point: press it, and you can move the whole system.

So far in this section we’ve discussed the power of inertia (strategy tax, Shirky principle), how to assess it (peak, Lindy effect), how to take advantage of it (flywheel), and how to think about reversing it through tactical models (homeostasis, potential energy, center of gravity). A couple other chemistry concepts will also be helpful to you tactically: activation energy and catalyst. Activation energy is the minimum amount of energy needed to activate a chemical reaction between two or more reactants. Consider striking a match to ignite it: the friction from striking the match supplies the activation energy needed for it to ignite. A catalyst decreases the activation energy needed to start a chemical reaction. Think of how it is easier for a wildfire to start on a hot and dry day, with increased temperature and decreased moisture serving as catalysts. More generally, activation energy can refer to the amount of effort it would take to start to change something, and catalyst to anything that would decrease this effort. When you are settled into the corner of the couch, it requires a lot of activation energy to get up. However, knowing there is ice cream in the freezer is a catalyst that lowers this activation energy. When attempting change, you want to understand the activation energy required and look for catalysts to make change easier.

In 2017, the U.S. saw both a rapid takedown of statues commemorating Confederate leaders and the accelerating takedown of sexual predators via the #MeToo movement. In both cases it seems that once there was enough activation energy, the movements pushed forward very quickly. It turns out there was a lot of potential energy waiting to be unleashed once those first steps were taken. Furthermore, social media posts and reporting by journalists were catalysts, serving as both a blueprint and an outlet for others to publicize these causes.

In Chapter 3 we described how commitment can help you overcome present bias; it can also serve as a great catalyst, or forcing function, to reach the activation energy required for a personal or organizational change. It usually takes the form of a prescheduled event, or function, that facilitates, or forces, you to take a desired action. A common example of a forcing function is the standing meeting, such as one-on-one meetings with a manager or coach, or a regular team meeting. These are set times, built into the calendar, when you can repeatedly bring up topics that can lead to change. You can similarly build additional forcing functions directly into your personal or company culture. For instance, you can set the expectation of producing weekly project updates, which serve as catalysts to think critically about project status and communicate progress to stakeholders. A more personal forcing function would be a regular appointment with a trainer at a gym, or a weekly family meeting or budget review. These set blocks of time will grease the wheels for change.

The title of this section is Don’t Fight Nature. You should be wary of fighting high-inertia systems blindly. Instead, you want to look at things more deeply, understand their underlying dynamics, and try to craft a high-leverage path to change that is more likely to succeed in a timely manner.

HARNESSING A CHAIN REACTION

Now we will discuss what often creates the underlying momentum behind new ideas as they permeate society: critical mass. As we noted in the Introduction, in physics critical mass is the mass of nuclear material needed to create a nuclear chain reaction, where the by-products of one reaction are used as the inputs for the next, chaining them together in a self-perpetuating fashion.

Nuclear Chain Reaction

This piece of knowledge was essential for the creation of the atomic bomb. Below the critical mass, nuclear elements are relatively harmless; above, and you have enough material to drive an atomic explosion. In 1944 in Los Alamos, New Mexico, Austrian-British physicist Otto Frisch was tasked with determining how much enriched uranium was required to create the critical mass for the first atomic bomb. Believe it or not, Frisch figured out the critical mass in part by physically stacking three-centimeter uranium bars, continually measuring their radioactive output as the stack grew larger. One day he almost caused a runaway reaction, the first known criticality accident, by simply leaning over the stack with his body. Some of the radiation reflected off his body and back into the stack, already near the critical mass, causing the radiation-detecting red lamps in the vicinity to shine continuously instead of flickering intermittently as usual. Noticing the lamps, Frisch scattered some of the bars quickly with his hand, and later wrote in his memoir, What Little I Remember, that if he “had hesitated for another two seconds before removing the material . . . the dose would have been fatal.”

Critical mass as a super model applies to any system in which an accumulation can reach a threshold amount that causes a major change in the system. The point at which the system starts changing dramatically, rapidly gaining momentum, is often referred to as a tipping point. For example, a party needs to reach a critical mass of people before it feels like a party, and the arrival of the final person needed for the party to reach the critical number tips the party into high gear. Sometimes this point is also referred to as an inflection point, where the growth curve bends, or inflects. However, note that mathematically the inflection point actually refers to a different point on the curve, when it changes from concave to convex, or vice versa.

Most popular technologies and ideas have had tipping points that propelled them further into the mainstream. If you graph their adoption curves, as in the chart below, you can plainly see these points.

Technology Adoption Curves

When thinking about engaging with new ideas and technologies, you want to examine where they are along their adoption curves, paying special attention to tipping points. Did a tipping point just happen? Will one ever happen? What could be a catalyst? Being an expert in an area that is about to hit a tipping point is an advantageous position, since your expertise has increasing leverage as the idea or technology takes off. Conversely, specializing in an area that is a decade away from hitting a tipping point is a much lower-leverage situation.

The spreading, or diffusion, of an idea or technology is known as the technology adoption life cycle. In his 1962 book Diffusion of Innovation, sociologist Everett Rogers theorized that people belong to one of five groups based on how and when they adopt new things:

Technology Adoption Life Cycle

Consider the adoption of the cellphone, which, as you can see from the Technology Adoption figure, progressed in several stages. The initial users—the innovators and early adopters—were rich tinkerers or professionals (e.g., doctors) who were able and willing to pay the high expense because it helped them do their jobs better. Later, as the price came down and new use cases emerged (e.g., text messaging), the early and late majority adopted. And finally, when they felt left behind, the laggards bought cellphones. The smartphone has followed a similar pattern, albeit more quickly. Do you still know people who use flip phones? They are the laggards in the smartphone adoption lifecycle.

The curves that emerge from the technology adoption life cycle are known as S curves because they resemble an S shape. The bottom part of the S is the pace of initial slower adoption; then adoption kicks into high gear; and finally, adoption slows as the market saturates, creating the top part of the S.

S Curve

While developed as a theory about technological innovation, the concept of an adoption life cycle also applies to social innovations, including ideas of tolerance and social equality. In the past decades acceptance of same-sex marriage has swept through the early majority in the U.S., and even into the late majority among Independents and Democrats (see chart on next page). Reaching a critical mass is a common proximate cause (see Chapter 1) of a tipping point. But the root cause of why a tipping point has been reached is often found in network effects, where the value of a network grows with each addition to it (the effect). Think of a social network—each person who joins makes the service more enticing because there are then more people to reach.

U.S. Same-Sex Marriage Support

The concept of a network is wider, however, encompassing any system where things (often referred to as nodes) can interact. For example, you need enough uranium atoms (“nodes”) in the “network” of a nuclear bomb such that when one decays, it can rapidly interact with another, instead of dissipating harmlessly. To use another example from everyday life, the telephone isn’t a useful device if there is no one else to call. But as each person gets a phone, the number of possible connections grows proportionally to the square of the number of phones (nodes). Two phones can make only one connection, five can make ten, and twelve can make sixty-six.

Network Effects

2 phones = 1 connection 5 phones = 10 connections 12 phones = 66 connections

This relationship, known as Metcalfe’s law, is named after Robert Metcalfe, the co-inventor of the networking technology Ethernet. It describes the nonlinear growth in network value when nodes are connected to one another. His law oversimplifies reality since it assumes that every node (or telephone in this case) has the same value to the network and that every node may want to contact every other, but nevertheless it serves as a decent model. Having a million telephones on the phone network is much more than twice as valuable as having five hundred thousand. And knowing that everyone is connected is extremely valuable, which explains why Facebook has such a strong network effect.

Critical mass occurs when there are enough nodes present to make a network useful. Amazingly, the fax machine was invented in the 1840s, but people didn’t regularly use it until the 1970s, when there were enough fax machines to reach critical mass. The modern equivalent is internet messaging services: they need to reach critical mass within a community to be useful. Once they pass this tipping point, they can rapidly make their way into the mainstream.

Network effects have value beyond communication, however. Many modern systems gain network effects by simply being able to process more data. For example, speech recognition improves when more voices are added. Other systems gain advantages by being able to provide more liquidity or selection based on the volume or breadth of participants. Think of how more goods are available on Etsy and eBay when more people are participating on those sites. Network effects apply to person-to-person connections within a community as well. Being part of the right alumni network can help you find the right job or get you answers quickly to esoteric questions. Any time you have nodes in a system participating in some kind of exchange, such as for information or currency, you have the potential for network effects.

Once an idea or technology reaches critical mass, whether through network effects or otherwise, it has gained a lot of inertia, and often has a lot of momentum as well. In the fax example, after a hundred years of struggling for adoption, once fax technology passed the critical mass point, it became embedded in society for the long term. The lesson here is, when you know that the concept of critical mass applies to your endeavor, you want to pay special attention to it. Just as we suggested questions to ask about tipping points, there are similar questions you can ask about critical mass and network effects: What is the critical mass point for this idea or technology? What needs to happen for it to reach critical mass? Are there network effects or other catalysts that can make reaching critical mass happen sooner? Can I reorganize the system so that critical mass can be reached in a sub-community sooner?

It’s important to note that these critical mass models apply in both positive and negative scenarios. Harmful ideas and technologies can also reach critical mass and spread quickly through societies. Historical examples abound, from fascism to institutional racism and other forms of discrimination. For negative or positive, modern communication systems have made it much easier for ideas to reach critical mass. In Chapter 1 we explored how people are in echo chambers online, which make it easier for insular points of view to persist. In addition, ad targeting can find the individuals most susceptible to a message, both by targeting the people who are most inclined to believe it and by experimenting with different ad variations until the most manipulative method is discovered. In this manner, conspiracy theories and scams can thrive.

When discovering the atomic critical mass, Otto Frisch narrowly avoided a catastrophic chain reaction, known more generally as a cascading failure, where a failure in one piece of a system can trigger a chain reaction of failure that cascades through the entire system. Major blackouts on our electric grid are usually the result of cascading failure: overload in one area triggers overload in adjacent areas, triggering further overload in more adjacent areas, and so on. The 2007/2008 financial crisis is another example of a cascading failure, where a failure in subprime mortgages ultimately led to failures in major financial institutions. In biological systems, the decimation of one species can lead to the decimation of others, as their absence cascades through the food chain. This occurs often when one species almost exclusively feeds on another, such as pandas and bamboo or koalas and eucalyptus leaves. Or think about how many species depend on coral reefs for their survival: when the reef disappears, so do most of the organisms that rely on it.

It’s not all bad, though; these are natural laws that can be used for good or bad. The nuclear critical mass can be used for relatively safe, essentially unlimited nuclear energy, or the nuclear critical mass could be the delivery mechanism of a catastrophic nuclear winter. In any case, these mental models are playing an increasing role in society as we get more and more connected. As technologies and ideas spread, you will be better prepared for them if you can spot and analyze these models—how S curves unfold, where tipping points occur, how network effects are utilized. And if you are trying to gain mainstream adoption and long-term inertia for a new idea or technology, you will want to understand how these models directly relate to your strategy.

ORDER OUT OF CHAOS

Many global systems, including the economy and weather, are known as chaotic systems. That means that while you can guess which way they are trending, it’s impossible to precisely predict their overall long-term state. You can’t know how a particular company or person in the economy will fare over time or exactly when and where an extreme weather event will occur. You can only say that it seems like the unemployment rate is moving down or that hurricane season is coming up. Mathematician Edward Lorenz is famous for studying such chaotic systems, pioneering a branch of mathematics called chaos theory. He introduced a metaphor known as the butterfly effect to explain the concept that chaotic systems are extremely sensitive to small perturbations or changes in initial conditions. He illustrated this concept by saying that the path of a tornado could be affected by a butterfly flapping its wings weeks before, sending air particles on a slightly different path than they would have otherwise traveled, which then gets amplified over time and ultimately results in a different path for the tornado.

This metaphor has been popularized in many forms of entertainment, including by Jeff Goldblum’s character in the 1993 movie Jurassic Park and in the 2004 movie The Butterfly Effect, starring Ashton Kutcher.

THE BUTTERFLY EFFECT

The fact that you are surrounded by chaotic systems is a key reason why adaptability is so important to your success. While it is a good idea to plan ahead, you cannot accurately predict the circumstances you will face. No one plans to lose their spouse at a young age, or to graduate from college during an economic downturn. You must continuously adapt to what life throws at you. Unlike an air particle, though, you have free will and can actively navigate the world. This means you have the potential to increase the probability of a successful outcome for yourself. You can at least attempt to turn lemons into lemonade by using these chaotic systems to your advantage. For example, some studies show that businesses started during a recession actually do better over time, and research by the Kauffman Foundation, summarized in “The Economic Future Just Happened” in 2009, found that the majority of Fortune 500 companies were started during tough economic times.

We’re sure you can point to times in your history when a small change led to a big effect in your life. It’s the “what if” game. What if you hadn’t gone to that event that led to meeting your spouse? What if you had moved into that other apartment? What if you had struck up a relationship with a different teacher or mentor? That’s the butterfly effect at the most personal level.

One way to more systematically take advantage of the butterfly effect is using the super model of luck surface area, coined by entrepreneur Jason Roberts. You may recall from geometry that the surface area of an object is how much area the surface of an object covers. In the same way that it is a lot easier to catch a fish if you cast a wide net, your personal luck surface area will increase as you interact with more people in more diverse situations. If you want greater luck surface area, you need to relax your rules for how you engage with the world. For example, you might put yourself in more unfamiliar situations: instead of spending the bulk of your time in your house or office, you might socialize more or take a class. As a result, you will make your own luck by meeting more people and finding more opportunities. Thinking of the butterfly effect, you are increasing your chances of influencing a tornado, such as forming a new partnership that ultimately blossoms into a large, positive outcome. You obviously have to be judicious about which events to attend, or you will constantly be running to different places without getting any focused work done. However, saying no to everything also has a negative consequence—it reduces your luck surface area too much. A happy medium has you attending occasional events that expose you to people who can help you advance your goals. Say no often so you can say yes when you might make some new meaningful connections.

Your luck surface area relates to the natural concept of entropy, which measures the amount of disorder in a system. In a clean room where there is a rule for where everything goes—socks in the sock drawer, shirts on hangers, etc.—there are not many possible configurations for everything in the room because of these strict rules. The maximum amount of entropy in this arrangement is small. If you relax those rules, for example by allowing clothes to go on the floor, there are suddenly many more possible configurations for everything in the room. The amount of possible disorderliness, the maximum entropy level possible for the room, has gone up significantly. In this context, increasing your luck surface area means increasing your personal maximum entropy, by increasing the possible number of situations you put yourself in. Your life will be a bit less orderly, but disorder in moderation can be a good thing. Of course, as we have seen so far, too much of a good thing can also be a bad thing. Too much entropy is just chaos. We refer to our kids as entropy machines because they create disorder very quickly. They don’t follow rules for where their belongings go in their rooms, so the maximum possible entropy for their rooms is very high. Almost anything can go almost anywhere and ultimately their rooms can get pretty close to this maximum, resulting in a big mess. As entropy increases, things become more randomly arranged. If left to continue forever, this eventually leads to an evenly distributed system, a completely randomly arranged system—clothes and toys anywhere and everywhere! In a closed system, like our kids’ rooms, entropy doesn’t just decrease on its own. Russian playwright Anton Chekhov put it like this: “Only entropy comes easy.” If our kids don’t make an effort to clean up, the room just gets messier and messier. The natural increase of entropy over time in a closed system is known as the second law of thermodynamics. Thermodynamics is the study of heat. If you consider our universe as the biggest closed system, this law leads to a plausible end state of our universe as a homogenous gas, evenly distributed everywhere, commonly known as the heat death of the universe. On a more practical level, the second law serves as a reminder that orderliness needs to be maintained, lest it be slowly chipped away by disorder.

This natural progression is based on the reality that most orderliness doesn’t happen naturally. Broken eggs don’t spontaneously mend themselves. In boiling water, an ice cube melts and never re-forms as ice. If you take a puzzle apart and shake up the pieces, it isn’t going to miraculously put itself back together again. You must continually put energy back into systems to maintain their desired orderly states. If you never put energy into straightening up your workspace, it will get ever messier. The same is true for relationships. To keep the same level of trust with people, you need to keep building on it. In Chapter 3, we discussed ways to proactively organize your time in order to spend this limited resource wisely, such as by using the Eisenhower Decision Matrix. Seen through the lens of entropy, your time, if left unmanaged, will start to go to random, largely reactionary activities. You will get pulled into the chaotic systems that surround you. Instead, you need to manage your time so that it is in a state of lower entropy. When you are able to make time for important activities, you are more easily able to adapt to your changing environment because you have the ability to allocate time to a particular important activity when needed.

To apply the Eisenhower Decision Matrix usefully, though, you need to assess properly what is an important activity and what is not. Given the butterfly effect and the fact that you must interact with chaotic systems like the economy, making these determinations can be challenging. This is especially true when deciding how and when to pursue new ideas, where an unexpected encounter can reveal new and important information. To make these determinations, you must therefore seek to understand and simplify chaotic systems like the economy so that you can successfully navigate them. All the mental models in this book are in service of that general goal. You can also develop your own models, such as by making your own 2×2 matrices like the Eisenhower Decision Matrix. Below is one we made up relating specifically to helping you determine what events you might want to attend. You can use this 2×2 matrix to help you categorize events as either high or low impact and high or low cost (time, money, etc.). You want to attend high-impact, low-cost events, and ignore low-impact, high-cost events. The other two quadrants are more nuanced. If there is a high-impact, high-cost event, such as a conference far from where you live, it may be worth going to depending on the specifics of the event and your particular situation: do you have the time and money to go? Similarly, if there is a low-impact event down the hall that will take only an hour of your time, it might be worth attending because the cost is so low.

These 2×2 matrices draw on a concept from physics called polarity, which describes a feature that has only two possible values. A magnet has a north and south pole. An electric charge can be positive or negative. Polarity is useful because it helps you categorize things into one of two states: good or bad, useful or not useful, high-leverage or low-leverage, etc. When you mix two groupings together, you get the 2×2 matrix. These visualizations are powerful because you can distill complicated ideas into a simple diagram and gain insights in the process.

While 2×2 matrices can be illuminating, they can also be misleading because most things don’t fall squarely into binary or even discrete states. Instead they fall along a continuum. For example, if you’re considering ways to make extra money across a set of possible activities, you don’t just want to know if you will make any money with each; you want to know how much, and how difficult it will be to generate new income from each activity. Winning the lottery will be significantly different from finding money on the ground or getting a part-time job. One simple way visually to introduce this type of complexity is through a scatter plot on top of a 2×2 matrix, which visualizes the relative values of what you are analyzing.

While polarity can be useful, when making comparisons you must be careful to avoid the black-and-white fallacy—thinking that things fall neatly into two groups when they do not. When making decisions, you usually have more than two options. It’s not all black and white. Practically, whenever you are presented with a decision with two options, try to think of more. People are susceptible to the black-and-white fallacy because of the natural tendency to create us versus them framings, thinking that the only two options are ones that either benefit themselves at the expense of “others,” or vice versa. This tendency arises because you often associate identity and self-esteem with group membership, thereafter creating in-group favoritism and, conversely, out-group bias. Social psychologists Henri Tajfel and John Turner established research in this area, published as “The Social Identity Theory of Intergroup Behavior” in Political Psychology in 2013, that has since been corroborated many times. It showed that with the tiniest of associations, even completely arbitrary ones (like defining groups based on coin tosses), people will favor their “group.” Outside the lab, this tendency toward in-group favoritism often fosters false beliefs that transactions are zero-sum, meaning that if your group gains, then the other group must lose, so that the sum of gains and losses is zero. However, most situations, including most negotiations, are not zero-sum. Instead, most have the potential to be win-win situations, where both parties can actually end up better off, or win. How is this possible? It’s because most negotiations don’t include just one term, such as price, but instead involve many terms, such as quality, respect, timing, control, risk, and on and on. In other words, there are usually several dimensions underlying a negotiation, and each party will value these dimensions differently. This opens up the possibility for a give-and-take where you give things you value less and take things you value more. As a result, both parties can end up better than they were before, getting things they wanted more and giving things they wanted less. In fact, this give-and-take is the basis for most economic transactions! Otherwise, without misinformation, misunderstanding, or duress, people wouldn’t make all these transactions. Zero-sum is the exception, not the rule.

Black-and-white and zero-sum thinking simply do not provide enough possible options, just having two. Recognizing that there are more options and dimensions can be desirable in many situations, such as business deals. The more terms of the deal you consider, the more possible arrangements of deal terms there are. If managed properly, this increases the likelihood of a successful deal for both sides, of finding that win-win state. You can go too far, though. For example, in a complex business negotiation, you cannot discuss every word in the contract or else discussions will take forever, and you’ll never get a deal done. You must instead choose thoughtfully which words are worth discussing and which are not.

More generally, you must continually try to strike the right balance between order and chaos as you interact with your environment. If you let the chaos subsume you, then you will not make progress in any particular direction. But if you are too ordered, then you will not be able to adapt to changing circumstances and will not have enough luck surface area to improve your chances of success. You want to be somewhere in the middle of order and chaos, where you are intentionally raising your personal entropy enough to expose yourself to interesting opportunities and you are flexible and resilient enough to react to new conditions and paradigms that emerge.

If you study the biographies of successful people, you will notice a pattern: luck plays a significant role in success. However, if you look deeper, you will notice that most also had a broad luck surface area. Yes, they were in the right place at the right time, but they made the effort to be in a right place. If it wasn’t that particular place and time, there might have been another. Maybe it wouldn’t have resulted in the same degree of success, but they probably would have still been successful. Another pattern: many of the most influential figures (Bill Gates, Martin Luther King Jr., etc.) were at the center of major adoptions of ideas or technologies that swept through society via the critical mass models described earlier. In some cases, they created the new idea or technology, but more often they were the ones who brought the ideas or technologies into the mainstream. They created momentum and ultimately inertia by guiding the ideas and technologies through the technology adoption life cycle.

With deeper understanding of these models, you should be able to more easily adapt to the major changes that will come in your lifetime. You should also be able to spot them coming from afar and participate in them, as if you were catching a wave and having it glide you safely to shore. Being adaptable like this helps you in good times and bad. On the positive side, you can make better decisions with your life and career; on the negative side, you can be more resilient when setbacks and unfortunate events occur, and even help limit their negative effects.