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 p
oint 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:
Innovators (about 2.5 percent of the population) have the desire and financial wherewithal to take risks and are closely connected to the emerging field, usually because they are specifically interested in trying new things within it.
Early adopters (13.5 percent) are willing to try out new things once they are a bit more fleshed out. Early adopters do not require social proof to use a product or idea. They are often the influencers that help push an idea past a tipping point, thus making it more broadly known.
The early majority (34 percent) are willing to adopt new things once the value proposition has been clearly established by the early adopters. This group is not interested in wasting their time or money.
The late majority (34 percent) are generally skeptical of new things. They will wait until something has permeated through the majority of people before adopting it. When they get on board, it is often at a lower cost.
Laggards (16 percent) are the very last group to adopt something new, and they do so only because they feel it is necessity.
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 examp
les 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.
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