Change is the mantra of modern life. Gone are the days when every generation was much like the one that preceded it. Now, every decade seems to be transformational. The changes are driven by our own activities in pursuit of what we think we desire, but like the character of a folktale who is granted a wish, we often end up regretting what we wished for. Sometimes we don’t even realize that we are the agents of our own misfortune and remain permanently trapped in a maze of unforeseen consequences.
It is ironic that in the midst of all this change and the use of keywords such as “evolve” and “adapt” in the vernacular, so little effort has been made to consult evolutionary theory. In this chapter I will show that for a group to be adaptable to changing environments is different from being well adapted to a current environment. I will provide some examples of adaptable groups drawn from the literature on businesses. Between-group competition in the business world is so intense that it acts as a crucible for the cultural evolution of effective change methods, since adaptable firms will survive longer and replicate their social organizations more than firms that are incapable of change. This is what economists such as Joseph Schumpeter and Friedrich Hayek meant by phrases such as “creative destruction” and “spontaneous order.” They took a few steps toward an evolutionary worldview, perhaps as many steps as could be taken during their time, but modern evolutionary theory provides a much more powerful and diverse toolkit for understanding the cultural evolution of effective change methods in the business world and how they, in turn, can be adapted to effectively manage change in other walks of life.
Before I review change methods that work, let’s clear the deck of change methods that won’t work.
One thing that won’t work is laissez-faire—the idea that our societies will work best if we leave them alone. If there is anything that evolution teaches us, it is that the pursuit of lower-level self-interest does not automatically benefit the common good. As we have seen in previous chapters, evolution frequently results in behaviors that are good for me but not you, us but not them, or all of us today without regard for future generations. If we want to manage our societies for the common good, ultimately at the global scale, then it is up to us to navigate toward that goal. There is no natural order that will do it for us.
Yet another thing that won’t work is centralized planning, in which a group of experts decides what needs to be done and proceeds to execute their grand plan. The reason that centralized planning seldom works is because the world is too complex to be understood by anyone.1 No matter how smart the decision-makers or how well informed by theory, there is always the likelihood of unforeseen consequences. This is true not only at the scale of nations, where efforts at centralized planning have failed repeatedly, but also at the scale of business firms, where command-and-control change efforts have a very poor track record.2
There is something between centralized planning and laissez-faire that can work: a managed process of variation and selection. First there must be a target that we are aiming to hit. For a business, this might be profitability, social responsibility, or the development of a new product line. At the planetary scale, it might be a robust global economy or the reduction of greenhouse gases. These targets become the criteria for selection, similar to an animal breeder such as William Muir selecting for egg productivity in hens or the target of creating a smart city with a 311 system for reporting dysfunctions.
Then there must be variation, which exists in two forms: planned and unplanned. We can deliberately formulate alternative strategies for reaching the target goals, comparing them to each other and to current practices using rigorous statistical methods. This is how I evaluated the Regents Academy, Ron Prinz evaluated Triple P, and Steve Hayes evaluated his self-help book. Science itself can be regarded as a carefully managed variation-and-selection process of this sort, where the target of selection is the advancement of objective knowledge.3
In addition, unplanned variation exists all around us. Every firm has its own way of doing things, every state has its own health care plan, and nations vary widely on a scale of well-being, as we saw in the previous chapter. Calling this variation “unplanned” isn’t quite right because a lot of thought might have gone into the practices of each group. Nevertheless, the groups are likely to differ in so many ways that identifying the differences most relevant to the target of selection can be difficult. If your firm is more profitable than mine, what exactly should I copy? On the other hand, unplanned variation can include successful practices that are beyond the imagination of those making planned comparisons. It is therefore wisest to include both planned and unplanned variation in the variation-and-selection process.
In chapter 5, I introduced the important concept of an evolutionary process built by another evolutionary process.4 An evolutionary process such as the immune system, individual learning, and transgenerational cultural change is itself a product of genetic evolution. Actually, genetic evolution by itself illustrates the same concept, since the current mechanisms of genetic inheritance are far more sophisticated than their ancient precursors.5 The mechanisms of human cultural evolution have also changed over the centuries, especially with the advent of new technologies such as writing, the printing press, and computers, which enable vastly more information to be transmitted across generations than before.6 A detailed analysis of the archaeological, anthropological, and historical records will probably document the process of more adaptable societies replacing less adaptable societies over the last ten thousand years. Business firms are a type of society, so the same approach can potentially explain the cultural evolution of successful change methods in the business world. Here are three examples.
If you’re a businessperson, it’s no secret that Toyota is a shining example of a corporation that works well and adapts to the ever-changing environment of automobile manufacturing. Founded in 1937, it has become the second-largest automotive corporation in the world (following the German Volkswagen group) and is the world leader in hybrid electric vehicle sales. An entire genre of business books is devoted to analyzing its success. Yet emulating the success of Toyota is easier said than done. An automobile manufacturing plant rivals a multicellular organism or a social insect colony in the complexity of its design. Consider the queen of a termite colony, who is fed and protected by an army of workers and lays an egg from her hugely distended abdomen every few seconds. Now consider Toyota’s manufacturing plant in Georgetown, Kentucky, which also houses an army of workers and spits out an automobile at a rate of about one per minute. Each automobile is so well designed that it can be driven several hundred thousand miles, which is roughly the distance from the earth to the moon. Take a visitor’s tour of the plant and you will witness what is sometimes described as a symphony between people and machines, as the cars move along a conveyor belt in a system pioneered by Henry Ford in the early twentieth century.
How is efficiency and productivity monitored in such a complex system and how are improvements made? Although business leaders complain about centralized planning at the level of national governments, they often employ a “command-and-control” form of social organization in their own companies. The management runs the company in a top-down manner by gathering data on performance and issuing orders that staff are expected to execute. If performance doesn’t improve, then the unsuccessful managers are fired and new ones are hired. This is a form of cultural evolution that works to a degree, just as the failure of whole businesses and their replacement by other businesses works to a degree, but the success of command-and-control is limited for a single business in the same way that it is limited for government. Human social organizations are too complex for anyone to know how they work, and the kind of performance data that is usually collected is too aggregated to be very useful. Knowing that a given unit failed to meet its productivity quota or that a given part has an unacceptable proportion of defects doesn’t tell you what needs to be done to improve the situation.
Here’s an example of the kind of complexity that an automobile assembly plant is confronted with on a daily basis. Let’s say that at a particular point on the assembly line, the operators need to keep a number of parts within easy reach. This means that the parts need to be in relatively small bins and need to be replenished as they are used up. The parts are brought to the plant in large lots, so someone has to divide them into small lots and physically transport them to the assembly line at frequent time intervals. Less effort for the assembly line worker requires more effort for the receiving and distribution departments. What’s the best way to manage this trade-off to maximize overall productivity? Countless trade-offs like this must be managed, all interacting with each other, similar to trade-offs in the physiology of a multicellular organism or the social physiology of an insect colony.
Toyota has a way of continuously improving its operation that dates back to its origin as a company that made weaving looms. Here is how Sakichi Toyoda, founder of the Toyoda Automatic Loom Works, responded when the design plans for one of his looms was stolen.
Certainly the thieves may be able to follow the design plans and produce a loom. But we are modifying and improving our looms every day. So by the time the thieves have produced a loom from the plans they stole, we will have already advanced beyond that point. And because they do not have the expertise gained from the failures it took to produce the original, they will waste a great deal more time than us as they move to improve their loom. We need not be concerned about what happened. We need only to continue, as always, making our improvements.7
A key phrase in this passage is “experience gained from failures.” Most people think about failure as something to be avoided. In most businesses, people are promoted for their successes, which provides a strong incentive to avoid taking risks and to conceal failures when they occur. From an evolutionary perspective, however, failures are the current frontier of adaptation. Every failure provides an opportunity for a variation-and-selection process to go to work to improve the efficiency of the whole operation.
In the past, Toyota assembly plants had cords called “andons” hanging down from the ceiling that operators were instructed to pull whenever an inefficiency occurred at their station. These cords, which have been replaced by more sophisticated monitoring equipment in modern Toyota plants, functioned like the pain receptors of a multicellular organism or the alarm signaling systems of social insect colonies. Just as poking a hole in a termite mound results in a swarm of activity to repair the damage, pulling the andon resulted in a swarm of activity to solve the problem. Plant managers had their offices located on the shop floor, rather than in a separate location, so that they could be directly involved in working with the lower-level employees who encountered the problem. Since the assembly line workers are closest to the problem, their knowledge is often essential for coming up with a solution, so that decision-making becomes both a bottom-up and a top-down process focused on solving problems at a very fine level of detail, rather than managers issuing directives on the basis of aggregated data such as quarterly reports.
When a tiny change is made in a complex system, the consequences can be magnified by the interactions among elements of the system. This is why the weather is so unpredictable, which gave rise to the term “butterfly effect”—a butterfly flapping its wings in Africa can result in a hurricane in Honduras.8 In an automobile assembly plant, a small improvement in one part of the system can easily disrupt other parts of the system. No one is smart enough to anticipate all of the indirect effects, so it is necessary to experiment. Toyota has learned from experience to implement only one change at a time and to monitor the effect on the whole system before adopting the change. Even making a few changes at the same time would result in interactions that are too difficult to track.
With a monitoring and improvement system in place, Toyota sets its production quotas so that failures will occur. Here is how the complex systems analyst Mike Rother describes this distinctively positive attitude toward failure in his book Toyota Kata:9
“No Problem” = A Problem
At a Toyota assembly plant, I was once told that the normal number of andon pulls is typically around 1,000 per shift. Each pull is an operator calling for assistance from their team leader because the operator is experiencing a problem; a cross-threaded bolt here, a task that took a little too long there. Naturally the number of andon pulls per shift varies, and I once heard of it dropping to only 700 pulls/shift. When I ask non-Toyota managers what they would do in this situation, I often get the answer, “We would celebrate the improvement.”
According to my source, what actually happened when the number of andon pulls dropped from 1,000 to 700 per shift is that the Toyota plant’s president called an all-employee meeting and said, “The drop in andon pulls can only mean two things. One is that we are having problems but you are not calling for help. I want to remind you of your responsibility to pull the andon cord for every problem. The other possibility is that we are actually experiencing fewer problems. But there is still waste in our system and we are staffed to handle 1,000 pulls per shift. So I am asking group leaders to monitor the situation and reduce inventory buffers where necessary so we can get back to 1,000 andon pulls per shift.
Inventory buffers are stocks of parts that workers can draw upon when the parts are not coming down the assembly line. They increase productivity over the short term but disguise inefficiencies in the process. Reducing the inventory buffers causes the workers to stand idle when the parts aren’t coming down the assembly line. This decreases productivity in the short term but increases it over the long term by revealing and eliminating inefficiencies in the whole system.
Toyota’s systemic approach to failure as the frontier of improvement is reflected in its policies toward both workers and managers. In companies governed by command-and-control, success and failure is attributed to individuals. If goals aren’t being reached, then the response is to fire and hire until they are. Toyota’s default assumption is that its employees are talented and hardworking. When problems occur, it is the system that needs improving and workers and managers need to work together to improve the system. Firing an individual for a systemic problem does not solve the problem. Toyota therefore retains its employees and recruits leaders from its own ranks more than other automobile manufacturers. It also has a system for perpetuating its culture that involves every employee having a mentor.
So far I have described how Toyota responds to failures in the same way that a multicellular organism responds to pain or a social insect colony responds to threat. In addition, Toyota has an impressive ability to move toward positive long-term goals in the same way that an individual person aspires to do more than merely react to pain. This requires first having a long-term aspirational goal (the target of selection) and then formulating concrete ways to move toward it in a step-by-step fashion. If the target goal had been to maximize quarterly earnings, it would have led to a different set of practices. Toyota’s change method bears an intriguing similarity to Acceptance and Commitment Therapy (ACT), which empowers individuals to mindfully work toward their valued long-term goals.
Toyota is exceptionally good at improving its operations and adapting to its ever-changing environment—not by adopting a laissez-faire policy, not by centralized planning, but by a sophisticated process of variation and selection. Its adaptability is largely responsible for its dominance in the automotive sector. Companies that are less adaptable either go under or remain in the marketplace by copying success. This is the process of creative destruction imagined by economists such as Joseph Schumpeter, but a modern evolutionary perspective paints a more complicated picture.
Let’s think about the Toyoda Automatic Loom Works as a mutant firm. However its founder came by the method of continuous improvement, it made his firm more adaptable than competing firms. The Toyoda firm captured the loom market, an example of firm-level selection. Then the same method spread to other business sectors, such as automobile manufacturing.
Competing firms were quick to notice the success of Toyota and eager to emulate its methods. Cultural evolution often takes the form of groups copying the best practices of other groups, rather than going under and being replaced by them. But here we encounter a major complication. Firms that attempt to copy Toyota often end up copying its current practices, like the thieves who stole the design plan for one of the looms, without copying the evolutionary process that gave rise to the current practices. This is why efforts to emulate Toyota so often fail.
Years were required for complex systems analysts such as Mike Rother to figure out the processes that make Toyota work, in part because even Toyota executives couldn’t articulate them. Cultural evolution often results in practices that work without anyone knowing why they work. Rother and his associates succeeded in part because they were scientifically oriented (a rarity in the field of business and management), had a deep appreciation of complex systems, and had a workable knowledge of other fields such as evolution and psychology. Thanks to their efforts, other business firms can do a better job emulating Toyota because they can copy the evolutionary process rather than merely imitating current practices. Finally, Rother is fully aware that the variation-and-selection process built by Toyota can be applied to many other business sectors and in non-business contexts, including individuals adapting to their everyday lives.10
That’s the good news. The bad news is that roughly a century has elapsed since this cultural mutation first arose in Japan early in the twentieth century. While it has spread, it has not spread fast or far enough. I’m betting that less than 5 percent of the readers of this book are familiar with the material about Toyota that I have presented. In the meantime, elements of Toyota’s “social physiology” are becoming outdated. In the past, Toyota has perpetuated its culture by having every employee mentored by a more experienced employee (what Rother calls the Coaching Kata). That system won’t work when a new factory has to be built in a foreign country and only a small fraction of the workforce is experienced. Whether Toyota can adapt to a new transnational and multicultural environment remains to be determined.
Clearly, something more is required for evolutionary processes exemplified by Toyota to become widespread in all walks of life. Another cultural mutation that took place in the business world can add to the insights that we have gleaned from Toyota.
The biological world is full of examples of convergent evolution—species that resemble each other, not because they are historically related, but because they have experienced the same selection pressures. Convergent adaptations resemble each other functionally (for example, the hard shells of turtles and armadillos or the eye of the octopus compared to the vertebrate eye) but usually differ in their mechanisms and development by virtue of their different historical origins, illustrating the need to ask all four of Tinbergen’s questions in conjunction with each other.
Examples of convergent cultural evolution can also be found in the business world, including a change method called “rapid results” that converges upon Toyota’s adaptability in functional terms, without any historical connection, using different procedures and maintaining cultural continuity in different ways.11 The rapid results method was the brainchild of Robert H. Schaffer, a business consultant who observed how hard and well people work together in emergency situations. Not only do they pull off miracles, but they experience intense pleasure doing it, despite the emergency situation being dysphoric in other respects. This by itself can be understood from an evolutionary perspective, since life-and-death situations requiring group solidarity occurred regularly throughout our evolutionary history. Our minds are prepared for them.12
The specific event that inspired these thoughts was a wildcat strike that took place at a New Jersey oil refinery. About 450 supervisors, managers, and engineers were forced to run an operation that normally employed a workforce of 3,000, not just for a few days, but for four months—and they did it well.
Schaffer wondered if this kind of peak performance could be elicited under normal working conditions. He experimented with creating “emergency” situations by challenging small teams within a company to accomplish daunting goals in a short amount of time, such as doubling the number of customers for a new product line in 100 days. He discovered that the teams indeed leapt into action and displayed the same kind of zest as in an emergency situation. Hence, the concept of a “rapid results cycle” was born.
The rapid results method produced additional benefits. It turned out that when lower-ranking employees most closely associated with a given challenge (such as increasing sales or customer satisfaction) were tasked with solving the problem, they came up with better solutions than what top managers or outside consultants might suggest. This was because they were in a better position to understand the nature of the problem and devise workable solutions (note the convergence with Toyota’s practices). The “emergency” atmosphere also allowed bureaucratic rules to be relaxed. And group members were able to bask in their success rather than watch all the credit going to their bosses. Upper-level managers sometimes had difficulty relinquishing control and trusting the bottom-up process, but the results spoke for themselves.
Another benefit of the rapid results method was more subtle. As we have seen with Toyota, large companies are highly complex systems with many parts that must work in a coordinated fashion to function as a whole. The whole system cannot be optimized by trying to separately optimize each part, and nobody is smart enough to anticipate all of the interactions among the parts. Accomplishing positive change in a large company is therefore a formidable task, and top-down efforts are more likely to fail than succeed. The changes produced by rapid results cycles were small enough to be integrated with the larger business operation, like the small changes that Toyota makes in its assembly line operations. Far from nibbling at the edges of fundamental change, rapid results cycles could become an engine of fundamental change in an incremental fashion, producing short-term benefits along the way and without requiring expensive outside consultants. This combination of benefits might seem too good to be true, but it has been documented repeatedly and some major corporations have adopted rapid results cycles as their main change engine. It is important to stress that this requires both a bottom-up process (the rapid results teams) and a top-down process (a strategy for employing the teams in a way that results in a long-term systemic goal). Either process by itself would be inadequate.
Just as Toyota’s adaptable social organization spread from one business manufacturing sector (looms) to another (cars), the rapid results method spread from the business world to the seemingly very different world of international aid through the creation of a nonprofit organization called the Rapid Results Institute.13 As one example, previous efforts to persuade women to visit family planning clinics in Madagascar resulted in gains of only a few percentage points over a fifteen-year period. Rapid results teams composed of local women committed to the seemingly impossible goal of increasing the percentage by 30 percent in 100 days. Not only did the groups meet their goals, but some achieved gains as high as 500 percent. One can well imagine the women springing into action in a way that they would not have done before. The rapid results method is currently being employed in over a dozen developing countries on problems as diverse as child malnutrition, HIV/AIDS, and corruption.
Like Toyota, the rapid results method provides an example of cultural evolution in action. Its origin was serendipitous and idiosyncratic, much like a biological mutation. Nevertheless, it spread on the basis of its success. In functional terms, it converges on roughly the same solutions as Toyota (for instance, having the benefit of the whole system in mind, the formation of small teams, a combination of bottom-up and top-down processes, making changes in small increments). Many of the details are different from Toyota’s, as expected from their separate historical origins, but they both succeed admirably as variation-and-selection processes that enable rapid adaptation to change.
That’s the good news. The bad news is that decades have elapsed since the origin of the method. Despite a consulting agency (for business applications) and a nonprofit (for international aid applications), despite a book and articles in prestigious journals such as the Harvard Business Review and Stanford Social Innovation Review, despite material support from organizations such as the World Bank, the proportion of groups that know about rapid results in either the business world or the international aid world is still small. How many decades would be required for awareness, not to speak of practice, to reach even 5 percent?
Both of my examples, Toyota and rapid results, illustrate that cultural evolution is more complex than economists like Schumpeter imagined with his phrase “creative destruction.” Best practices do spread, but they seldom result in a “selective sweep,” which is the term that biologists use when a gene rapidly evolves from mutation to fixation in a population. Instead, they spread slowly and are often opposed by other selective forces, especially disruptive forms of within-group selection when the core design principles discussed in chapter 6 are not strongly implemented. Spreading by being copied is more difficult than it seems because it is difficult to infer from the products the processes that need to be copied.
As a result of these complications, cultural adaptations end up having something similar to the geographical distribution of a biological species. They are practiced only by some groups but not by others, in some walks of life but not others, and they remain invisible outside their borders. The same is true when we examine cultural evolution at larger scales.
So far, I have provided examples of single corporations that are adaptable by employing variation-and-selection processes. How about entire geographical regions? If we could create a map of the world that shows where technological innovations come from, it would be extremely uneven. Some regions, such as Silicon Valley, are oases of innovation, whereas most other regions are parched deserts. Silicon Valley is rare but it is not unique. Other oases exist; for example, the nation of Israel, as described by Dan Senor and Saul Singer in their book Start-Up Nation.14 Like mutations and species, innovation oases have separate historical origins and spread on their own merits until they come up against boundaries, like the geographical distribution of biological species.
The absence of innovation oases in most parts of the world is not for lack of trying. On the contrary, they are the envy of the world, and countless efforts to create them have been attempted by governments, universities, and corporations. Yet these efforts almost invariably fall short of expectations. Like many products of cultural evolution, an innovation oasis works without having been designed by anyone. The active ingredients need to be discovered, even by the people who carry them out on a daily basis. They are sufficiently mysterious, at least when viewed through the lens of current theories, that they have resisted the efforts of the best and brightest who try and fail to duplicate them.
Fortunately, there is a book that begins to explain the active ingredients of innovation oases in the same way that Mike Rother explains the active ingredients of Toyota: The Rainforest: The Secret to Building the Next Silicon Valley, by Victor W. Hwang and Greg Horowitt.15 Both authors have served as consultants for the creation of innovation oases (or “rainforests,” as they put it) around the world, and Hwang is currently vice president of entrepreneurship at the Ewing Marion Kauffman Foundation, which has been a leader in promoting entrepreneurship for over fifty years. There is something else that distinguishes Hwang and Horowitt. In addition to their extensive professional experience, both have drunk deeply from the well of Darwinian knowledge. They employ Tinbergen’s fully rounded four-question approach, which enables them to see what so many other experts are missing.
They are not blinded by the absurd conception of human nature known as Homo economicus, which pretends that individuals are rational actors who can be motivated entirely by money. Instead, they understand that humans are a product of genetic multilevel selection operating primarily at the scale of small groups, which has both positive and negative implications for creating a modern innovative society. On the positive side, we are innately prosocial and inclined to join in cooperative enterprises, which includes policing those who don’t cooperate. On the negative side, we typically confine our prosociality to small homogeneous groups, regarding outsiders with distrust. Also, most of us are inherently risk-averse. Gambling everything on long-shot possibilities doesn’t come naturally to us.
Hwang and Horowitt are also not blinded by the pervasive assumption that an innovative culture can be explained in terms of innovative individuals. Instead, they understand that innovation is a social process requiring many different types of people cooperating with each other. The challenge is to create a society that is both highly cooperative and highly diverse. This is such an unusual combination that the ingredients fail to come together in most geographical regions, resulting in innovation deserts.
The factors that enable diverse people to cooperate in regions such as Silicon Valley and Israel are serendipitous and historically contingent. Each innovation oasis has its own story, but they typically involve situations that force people from different nationalities and walks of life to cooperate with each other. In America it was the westward expansion. In Israel it was military service. In both cases, the circle of cooperation still excludes others—Native Americans and to a large extent African Americans in the case of the American westward expansion, and Palestinians in the case of Israel—but the circle of cooperation is still sufficiently diverse to include the elements needed to create new enterprises.
In an innovation oasis, there is a high diversity of relevant skills, a high degree of social connectedness, a high degree of generosity and trust, and a high degree of dreaming about creating something that does not currently exist—which is the target of selection for an innovator. The high degree of connectedness allows bad actors to be detected and punished by more upstanding members of the community, usually without needing recourse to legal action. Someone who steals an idea or cuts an unfair deal gets a bad reputation and is excluded from future cooperative interactions. One Silicon Valley lawyer is even quoted as saying “Good businessmen don’t need lawyers!” This kind of social organization is similar to hunter-gatherer tribes, where bullies are either punished or avoided and end up fending for themselves. In the case of innovation oases, however, tribal membership is open to anyone who can contribute to a current venture.
These projects might be temporary, but they are also complex. An apt comparison is with the movie industry—also a California specialty—where every movie requires the army of people listed in the credits to come together in a symphony of cooperation. It is a different symphony from the one that takes place in an automobile assembly plant, but a symphony all the same.
Hwang and Horowitt are practical change agents, not scientists and scholars, although they have drawn from the scholarly and scientific literature to a remarkable degree. They provide seven “Rules of the Rainforest” for those who want to create a rainforest of their own, which can readily be understood as a managed process, or policy, of cultural evolution.
RULE #1: THOU SHALT BREAK RULES AND DREAM. Achieving something new is the target of selection for groups of innovators.
RULE #2: THOU SHALT OPEN DOORS AND LISTEN. Innovation is a social process that requires cooperation.
RULE #3: TRUST AND BE TRUSTED. Trust is required to lower transaction costs. It is possible because of informal policing mechanisms.
RULE #4: EXPERIMENT AND ITERATE TOGETHER. No one is smart enough to understand a complex system and even the best theory can only narrow the field of plausible alternatives. The only way to evolve a complex system is by variation-and-selection processes.
RULE #5: SEEK FAIRNESS, NOT ADVANTAGE. Gaining advantage over other members of your group poisons collective efforts.
RULE #6: ERR, FAIL, AND PERSIST. Failure is the frontier of adaptation, for a start-up company no less than an automobile assembly plant.
RULE #7: PAY IT FORWARD. The overarching ethos of an innovation oasis is generosity, a willingness to help others without narrow expectation of gain, which is the very opposite of the conception of human nature imagined by orthodox economic theory.
In this chapter I have provided three examples of adaptable societies. All of them are drawn from the business world, where between-group selection is especially intense, acting as a crucible for the cultural evolution of groups that work well in the present and adapt well in the face of environmental change.
Yet each story is more complex than the standard notion of firm selection in economics. Firms that are both adaptive in their current environments and adaptable to changing environments do arise as “cultural mutations.” They do spread in competition with other firms. And they do diversify to occupy different niches in a multiple-niche economy. But decades are required and each cultural lineage comes against barriers that limit its distribution, similar to the geographical distribution of a biological species. As a result, even an example as fabled as Toyota is largely unknown outside the automotive industry, and the secrets of its success are inscrutable to many who earnestly want to copy it.
Clearly, more is needed for human groups of all sorts to adapt to change at the speed and scale that is required to solve the myriad problems of our age. The first step is to adopt the right theory. When our view of human nature is Homo economicus or when we think that creating an adaptive group is merely a matter of finding the most talented individuals, then we become incapable of seeing the ingredients that are actually required to create an adaptable society. We are like an engineer who is trying to build something using the wrong blueprint. It will never work, no matter how smart we are or how hard we try.
The right theory is based on the cultural evolution of complex systems. It notes that complex systems cannot be optimized by separately optimizing their parts. We must have in mind the performance of whole systems, which is the target of selection, and improve performance with a process of variation and selection of best practices. This is likely to work much better than laissez-faire or centralized planning. Making our societies more adaptable won’t be easy, especially at larger scales, but it will be possible with the right blueprint provided here by evolutionary theory, multilevel selection, and a solid four-question approach.