The “Ink Spot” Strategy That Propels Wal-Mart And Counterinsurgency

I thought this was interesting. Here is Sam Walton, in his own words, detailing the Wal-Mart Strategy from the earliest days. What was novel at the time is now a somewhat common way for businesses to expand. It’s also used in the military as part of an “ink spot” strategy.

But before we get to that, here is Sam Walton writing in Made in America:

Now that we were out of debt, we could really do something with our key strategy, which was simply to put good-sized discount stores into little one-horse towns which everybody else was ignoring. In those days, Kmart wasn’t going to towns below 50,000, and even Gibson’s wouldn’t go to towns much smaller than 10,000 or 12,000. We knew our formula was working even in towns smaller than 5,000 people, and there were plenty of those towns out there for us to expand into. When people want to simplify the Wal-Mart story, that’s usually how they sum up the secret of our success: “Oh, they went into small towns when nobody else would.” And a long time ago, when we were first being noticed, a lot of folks in the industry wrote us off as a bunch of country hicks who had stumbled onto this idea by a big accident.

Maybe it was an accident, but that strategy wouldn’t have worked at all if we hadn’t come up with a method for implementing it. That method was to saturate a market area by spreading out, then filling in. In the early growth years of discounting, a lot of national companies with distribution systems already in place— Kmart, for example— were growing by sticking stores all over the country. Obviously, we couldn’t support anything like that.

But while the big guys were leapfrogging from large city to large city, they became so spread out and so involved in real estate and zoning laws and city politics that they left huge pockets of business out there for us. Our growth strategy was born out of necessity, but at least we recognized it as a strategy pretty early on. We figured we had to build our stores so that our distribution centers, or warehouses, could take care of them, but also so those stores could be controlled. We wanted them within reach of our district managers, and of ourselves here in Bentonville, so we could get out there and look after them. Each store had to be within a day’s drive of a distribution center.

We saturated northwest Arkansas. We saturated Oklahoma. We saturated Missouri. We went from Neosho to Joplin, to Monett and Aurora, to Nevada and Belton, to Harrisonville, and then on to Fort Scott and Olathe in Kansas —and so on. Sometimes we would jump over an area, like when we opened store number 23 in Ruston, Louisiana, and we didn’t have a thing in south Arkansas, which is between us and Ruston. So then we started back -filling south Arkansas. In those days we didn’t really plan for the future. We just felt like we could keep rolling these stores out this way, and they would keep working, in Tennessee, or Kansas, or Nebraska— wherever we decided to go. But we did try to think ahead some when it came to the cities. We never planned on actually going into the cities. What we did instead was build our stores in a ring around a city— pretty far out— and wait for the growth to come to us. That strategy worked practically everywhere. We started early with Tulsa, putting stores in Broken Arrow and Sand Springs. Around Kansas City, we built in Warrensburg, Belton, and Grandview on the Missouri side of town and in Bonner Springs and Leavenworth across the river in Kansas. We did the same thing in Dallas.

This saturation strategy had all sorts of benefits beyond control and distribution. From the very beginning, we never believed in spending much money on advertising, and saturation helped us to save a fortune in that department. When you move like we did from town to town in these mostly rural areas, word of mouth gets your message out to customers pretty quickly without much advertising. When we had seventy-five stores in Arkansas, seventy-five in Missouri, eighty in Oklahoma, whatever, people knew who we were, and everybody except the merchants who weren’t discounting looked forward to our coming to their town. By doing it this way, we usually could get by with distributing just one advertising circular a month instead of running a whole lot of newspaper advertising. We’ve never been big advertisers, and, relative to our size today, we still aren’t. Just like today, we became our own competitors. In the Springfield, Missouri, area, for example, we had forty stores within 100 miles. When Kmart finally came in there with three stores, they had a rough time going up against our kind of strength.

So for the most part, we just started repeating what worked, stamping out stores cookie-cutter style. The only decision we had to make was what size format to put in what market. We had five different store sizes—running from about 30,000 to 60,000 square feet— and we would hardly ever pass up any market because it was too small. I had traveled so much myself looking at competitors in the variety store business that I had a good feel for the kind of potential in these communities. Bud and I knew what we wanted in the way of locations. Like so many of the ideas that have made our company work from the beginning, we’re still more or less following this same strategy, although today we’ve moved into some cities outright. But I think our main real estate effort should be directed at getting out in front of expansion and letting the population build out to us.

A lot of companies are now trying to do similar things.

Interestingly, something similar came up in General Stanley McChrystal’s memoir My Share of the Task:

The strategy was neither new nor guaranteed to work. It was a version of the “ink spot” approach French General Lyautey made famous in Madagascar and Morocco and one often adopted in counterinsurgency campaigns of the nineteenth and twentieth centuries. The concept called for providing secure zones inside which the population could be protected, governed, and allowed to conduct economic activity free from insurgent pressure. The theory held that as people were free to live their lives, this would enhance the government’s legitimacy and strength. And as these domains of government control expanded— like inkblots seeping on a page— they would conjoin. The United States’ counterinsurgency doctrine, which outlined the steps of “clear, hold, and build,” was a manifestation of this approach. That summer, we added “sustain” as a fourth tenet. Success in counterinsurgency was less dependent upon the brilliance of the strategy— the concept is not that hard to understand— than it was on the execution. Counterinsurgency is easy to prescribe, difficult to perform.

The Default-Thinking Method of Problem Solving

You’ve been here before. It’s Monday morning and you walk into the office only to have your boss call an urgent meeting to “streamline processes.” You haven’t thought about this enough to have an opinion but you go anyway.

You know how to deal with this. You’ve done it before. You turn on your default brain and start solving the problem. You build a hypothesis to determine the problem, find some data to analyze, and presto out comes some efficiency.

Most of the time this works well enough, but not always. Sometimes—more often than we’d like to admit—things change: markets shift and consumers behave in unpredictable ways. Now we’re rudderless.

In the wonderful book The Moment of Clarity: Using the Human Sciences to Solve Your Toughest Business Problems, the authors write:

We are forever in the midst of change, but not all of it is seismic. It’s vital for a business to understand the difference between the uncertainties present on an average day and the uncertainties of a major cultural shift. … Business issues can be categorized along a problem scale within three levels of complexity . This framework is useful for distinguishing very complex problems from those that are actually manageable.

The Three Levels of Business Problems

1. A clear-enough future with a relatively predictable business environment. You know what the problem is, and you can apply a proven algorithm to fix it. “If I invest $ 1 in media spending for advertising, I know that I will get something like $ 1.5 back because of market stimulation.” “The industry has average admin costs of 8 percent of total revenue. Mine are 10 percent. We should cut that back.”

2. Alternative futures with a set of options available. You have a feel for the problem and might have seen something like it before. It makes sense to test your hunch as a hypothesis. For example, “Our sales numbers are down even when we invest in more salespeople, but we have seen the same pattern in the European Union and China. We might be hiring too many new salespeople too quickly and expecting them to deliver the same payback that the existing salespeople are delivering.”

3. High level of uncertainty, with no understanding of the problem. You simply don’t know what the problem is, let alone the solution. You can see that something is wrong, but have no clear idea about what to do. For example, “Our media division is losing business to internet start-ups,” “We are investing more in customer service, but our customers are becoming increasingly dissatisfied with us,” and “We are designing products that seem right for the marketplace, but the marketplace isn’t interested.”

Most of our problems tend to be in 1 or 2. Uncertainty, remember, happens when we fail to know the range of possible outcomes (and, correspondingly, their probabilities.) These are really messy problems.

Solving the problems of 1 and 2 are generally much easier. We use default thinking.

The default problem-solving model has its roots in what can be called instrumental rationalism. At the heart of the model is the belief that business problems can be solved through objective and scientific analysis and that evidence and facts should prevail over opinions and preferences. To get to the right answer, so the thinking goes, you should adhere to the following principles of problem solving:

1. All business uncertainties are defined as problems. Something in the past caused the problem, and the facts should be analyzed to clarify what the problem is and how to solve it.

2. Problems are deconstructed into quantifiable and formal problem statements (issues). For example, “Why is our profitability falling?”

3. Each problem is atomized into the smallest possible bits that can be analyzed separately— for example, breaking down the causes of profitability into logical issues. This analysis would include “issue trees” for all the hundreds of potential levers for either decreasing costs or growing revenue (customer segments, markets, market share, price, sales channels, operations, new business development, etc.)

4. A list of hypotheses to explain the cause of the problem is generated. For example, “We can increase profitability by lowering the cost of our operations.”

5. Data is gathered and processed to test each hypothesis— all possible stones are turned and no data source is left untouched.

6. Induction and deduction are used to test hypotheses, clarify the problem, and find the areas of intervention with the highest impact, or what is commonly called “bang for the buck.”

7. A well-organized structure of the analysis is deployed to build a logical and fact-based argument of what should be done. The structure is built like a pyramid that develops the supporting facts, some subconclusions, and an overall conclusion and then ends with a prioritized list of interventions to which the company should adhere.

8. All proposed actions are described as manageable work streams or must-win battles for which a responsible committee, or person, is assigned.

9. Performance metrics and a proposed time frame with follow-up monitoring are put in place for each committee to complete the task.

10. When all work streams have been completed, the problem is solved.

When done correctly by competent people, this can be a thing of beauty. This is, in part, why we hire consultants like myself, McKinsey, or Bain. We believe they can solve any problem. The idea that management is a type of science with a repeatable formula in the face of any problem is not a new idea. “It can be traced back to the nineteenth century, when positivism, the prevalent philosophy of the day, argued that you could objectively measure reality.” The founding father of the idea of management science, if there was one, Frederick Winslow Taylor.

Taylor left a prestigious education at Harvard to work at steel companies throughout Pennsylvania. Whereas most manufacturing and factory plants had cobbled together their organization through rules of thumb and common sense, Taylor was the quintessential positivist, seeking scientifically validated measurements, or properties. He followed workers, clicking his stopwatch every time they started and stopped, measuring the time it took to complete each discrete action of hauling their large iron ore loads. Through his enormously successful tenure at steel companies, he extracted generalized principles of management that he used to create the world’s first business case study. It wasn’t long before a partnership between Harvard’s School of Applied Science and its brand-new business school came calling. Might Taylor bring together his experience into something the school could teach its young students about productivity? Taylorism, based on the following premise, was born:

To work according to scientific laws, the management must take over and perform much of the work which is now left to the men; almost every act of the workman should be preceded by one or more preparatory acts of the management which enable him to do his work better and quicker than he otherwise could.

Today’s problems seem infinitely more complex than counting iron ore hauls and yet we still attack them with the same general approach of Taylorism. This is what most MBAs, including mine, taught: people work harder with the right incentives, optimize and perfect workflow, analyze every movement looking for efficiencies, remove discretion when possible because that creates variance, etc. Of course we’ve evolved Taylorism, today we call it “lean” and “six sigma” and whatever else.

For most of us, default thinking is so familiar to us— the very air we breathe— that we are no longer able to explain it or even to see it. For that reason, if we really want to understand why we continue to get people wrong, we need to unpack the fundamental assumptions that make up the culture of most of our days.

Is this really how we approach problems? What are the assumptions we’re making when we take this approach?

Assumption 1: People Are Rational And Fully Informed

One of the unintentional consequences of solving problems by testing logical hypotheses is that you are forced to assume that people are rational decision makers: aware of their needs, fully informed of all their choices, and capable of making the best choice. The reason is simple: it is very difficult to test a hypothesis about things that you can’t measure objectively. It’s even harder to test something that is deeply personal, cannot be decoded into explicit descriptions, and requires a lot of interpretation. Think about the question “Are you a good parent?” or “Do you have good taste?”

A simple answer misses most of what matters about parenting and good taste. To deal with this problem, companies base their problem solving on what can objectively be described, quantified, and analyzed without too much interpretation.

So we default to measuring perceptions and desires, more specifically, we end up with people’s perceptions of reality. There is nothing wrong with this but it is limited and we should be aware of its limitations. These are not the only two aspects of humanity that matter. And even if they were, the way default thinking solves problems rarely offers us any understanding of how they work. We find some spurious relationship, and assume causation when, in reality, it’s merely a correlation. When it changes we have no idea why. We’re more complex than that.

Most recent studies evaluating how people buy reveal us to be far more chaotic creatures. We rarely know what we want. We almost never fully grasp the market and, most important, we almost always buy something at a different price than what we thought we would. Even studies of people with written shopping lists (milk, eggs, apples, etc.) reveal that they find themselves far astray from their original intentions once they reach the grocery store.

We do this because intentions are relatively easy to study. But as Dr. House says, “everybody lies.”

People think they cook a lot, but they really don’t. It’s not that they want to lie to other people; they are simply lying to themselves.

There is often a wealth of distance between what people say and what people do.

It’s not that people don’t care about anything. They just don’t care as much as most companies assume that they do. And most often, people couldn’t care less. When they buy one kind of chocolate bar rather than another, it is rarely because they have a strong brand preference. More often than not, it is because the chocolate was closer on the counter, it had a color that fit the mood, or it simply came packaged as a “two for one.” The good news for companies is that we buy a lot of stuff. The bad news is that we don’t always know why.

Assumption 2: Tomorrow Will Look Like Today

A good example of this attitude can be found in a 2006 article in the McKinsey Quarterly. In identifying trends that will shape the business environment, the article says that management itself will shift from an art to a science:

Long gone is the day of the “gut instinct” management style. Today’s business leaders are adopting algorithmic decision-making techniques and using highly sophisticated software to run their organizations. Scientific management is moving from a skill that creates competitive advantage to an ante that gives companies the right to play the game.

We’re bombarded with the word “science.”

When thought leaders use the word science to describe a business discipline like marketing, retail design, negotiation skill, or strategy, we are led to believe that these disciplines can be predicated on scientific truths. Does the science of shopping have the same universal laws as Darwin’s theory of natural selection?

This is part of the reason we trick ourselves.

Rarely do we have to ask, “Where does the hypothesis come from?” But by assuming that the hypothesis is based on some kind of universal law, we fool ourselves into believing that the assumptions of the current moment will also hold true in the future. In these situations, the idea that management is a kind of natural science blinds us rather than enlightens us.

Assumption 3: Hypotheses are Objective and Unbiased

Here is a great example:

In the toy industry, the dominating idea is that children have a short attention span and need toys that stimulate their desire for instant traction. A toy, it is assumed, must grab the attention of the child in the store, and he or she should not need any skills to play with it. Another assumption is that physical toys are losing ground to digital toys because the former are too tedious and not stimulating enough.

In reality, when you study children— and if you read the majority of academic literature about children—you will probably reach the opposite conclusion: children are highly motivated by play experiences that require skill and mastery and that can give them a sense of hierarchy and accomplishment. Digital play is gaining in popularity precisely because it requires a very sophisticated skill set; it can be played for thousands of hours and it gives the players clear feedback with levels and hierarchies.

Over time, companies and people create “commonsense” ideas about the world and how it works. We take things as given and rarely challenge them.

The French anthropologist Pierre Bourdieu coined the term habitus to describe the somehow hidden but always present dispositions that shape our perceptions, thoughts, and actions. In his view, many things that we regard as common sense are in fact shaped by the social context we are in. Over time we learn what is normal and taken as a given through our social interaction with the world— our family, our society, our friends, our work— and our perceptions become a kind of automatic understanding of the world. This understanding enables us to act normally without really thinking about it. Over time, companies similarly create commonsense ideas about the world. Certain things are simply taken as a given, no longer contested: for example, the idea that designers and engineers will never see eye-to-eye, or that open offices provide more opportunities for collaboration.

This is one reason consultants can be effective, they come in with a different understanding and offer opinions—intentionally or not – that challenge some of these commonsensical views.

In terms of default thinking:

A company might think that it has created an objective set of possible hypotheses to test. But in reality each hypothesis is always based on something . Very often, that thing is a product of culture, not of science. And once our assumptions are firmly rooted in our cultural understanding, they have a way of becoming ever more entrenched.

Then confirmation bias kicks in. We look for opinions, ideas, and facts that support our beliefs.

In the end our hypotheses are “almost never based on objective truth.” How could it be otherwise? But of course the point is to know the limitations of the tools we’re working with and hope that awareness allows us to make better decisions by using better tools.

In Leo Tolstoy’s nonfiction magnum opus The Kingdom of God Is Within You, he writes:

“The most difficult subjects can be explained to the most slow-witted man if he has not formed any idea of them already; but the simplest thing cannot be made clear to the most intelligent man if he is firmly persuaded that he knows already, without a shadow of doubt, what is laid before him.”

If you can’t question assumptions at your company, you probably can’t question anything.

Assumption 4: Numbers Are the Only Truth

“Not everything that can be counted counts, and not everything that counts can be counted.” — Albert Einstein

The heart of default problem solving is quantitative analysis.

It has become so dominant that companies tend to forget that the world consists not only of quantities but also of qualities. Roger Martin, the dean of Rothman School of Management, argues that companies will simply lack ability to find the full potential of growth opportunities if they only focus on quantitative models: “The greatest weakness of the quantitative approach is that it decontextualizes human behavior, removing an event from its real-world setting and ignoring the effects of variables not included in the model.”

Default thinking catalogs the world into properties: how big is the market, how many people will buy our products, how many people know our brand, which category is growing fastest, which geography is the most profitable, which customers have the highest loyalty and what technologies have the highest adoption.

Yes all of those have a numbers side but they also have a qualitative side that might also shed light on things. If you know that a certain percent of your customers are happy with their interactions with your company, that’s different than knowing what the experience of interacting with your company is like. Both of those things are needed to inform decisions.

Numbers are great for covering your ass so they tend to trump anything else. Numbers however, limit ideas and solutions to only one right answer.

For obvious reasons, the past does not include data on things that haven’t happened or ideas that have not yet been imagined. As a result, data analysis of the future tends to underestimate or even ignore past events or conditions that can’t be measured while overestimating those that can. Nowhere is this more visible than in business case studies.

“In our view,” the authors write,” the quantitative obsession leads to a sorely diminished approach to future planning. It tends to be conservative rather than creative because it implicitly favors what can be measured over what cannot.”

Assumption 5: Language Needs to be Dehumanizing

Business and management science has become a world in itself, and the language of business has become increasingly technical, introverted, and coded. You don’t fire people anymore; you “right-size the organization.” You don’t do the easiest things first; you “pick the low-hanging fruit.” You don’t look at where you sell your products; you “evaluate your channel mix.” You don’t promote people; you “leverage your human resources.” You don’t give people a bonus check; you “incentivize.” You don’t do stuff; you “execute.” You “synergize, optimize, leverage, simplify, utilize, transform, enhance, and reengineer.” You avoid “boiling the ocean, missing the paradigm shift, having tunnel vision, and increasing complexity.” You make sure that “resources are allocated to leverage synergies across organizational boundaries and with a customer-centric mind-set that can secure a premium position while targeting white spots in the blue ocean to ensure that there is bang for the buck.” It can become almost poetic.

Talk about jargon.

The German philosopher Jürgen Habermas has developed an extensive analysis of what happens when technical language outstrips the language of everyday life. He argues that the change from a normal, everyday language to a technical, specific language suggests a shift in power. When technical language conquers simple language of the every day, it is a sign that the system is gaining ground and everyday human reality, what he calls the lifeworld, is losing ground. He goes so far as to call this shift a colonization of the lifeworld; everyday life being colonized by a force of bureaucratization and rationalization that it cannot defend itself against. Such a shift leads to a far more systematic, rule-based, and technical idea of the world. It widens the gap between who we really are and the systems that we have become.

* * *

Of course, default thinking doesn’t always work. You know you’ve stepped out of default thinking space when leaders say “think outside the box.” Problems arise when you try to solve the third type of problem (where there is a high level of uncertainty) with the same thinking you use to fix problems in one and two.

If you enjoyed this post, you’d love the book The Moment of Clarity: Using the Human Sciences to Solve Your Toughest Business Problems.

The Art and Science of Doing Nothing

I have often wondered whether especially those days when we are forced to remain idle are not precisely the days spent in the most profound activity. Whether our actions themselves, even if they do not take place until later, are nothing more than the last reverberations of a vast movement that occurs within us during idle days.

In any case, it is very important to be idle with confidence, with devotion, possibly even with joy. The days when even our hands do not stir are so exceptionally quiet that it is hardly possible to raise them without hearing a whole lot.

Rainer Maria Rilke

Idleness is a lost art. That’s the message behind Andrew Smart’s book: Autopilot: The Art and Science of Doing Nothing. “Being idle,” he writes, “is one of the most important activities in life.”

But all over the world something else is happening. We’re asked to do more, work harder, and strive to make every moment efficient. The message behind this book is just the opposite. You should do less, not more.

Neuroscientific evidence argues that your brain needs to rest, right now. While our minds are exquisitely evolved for intense action, in order to function normally our brains also need to be idle— a lot of the time, it turns out.

Chronic busyness is not only bad for your brain but can have serious health consequences. “In the short term,” Smart writes, “busyness destroys creativity, self-knowledge, emotional well-being, your ability to be social— and it can damage your cardiovascular health.”

Our brain, much like an airplane, has an autopilot, which we enter when resting and “relinquishing manual control.”

The autopilot knows where you really want to go, and what you really want to do. But the only way to find out what your autopilot knows is to stop flying the plane, and let your autopilot guide you. Just as pilots become dangerously fatigued while flying airplanes manually, all of us need to take a break and let our autopilots fly our planes more of the time.

Yet we hate idleness don’t we? Isn’t that just a waste?

Our contradictory fear of being idle, together with our preference for sloth , may be a vestige from our evolutionary history. For most of our evolution, conserving energy was our number one priority because simply getting enough to eat was a monumental physical challenge. Today, survival does not require much (if any ) physical exertion, so we have invented all kinds of futile busyness. Given the slightest or even a specious reason to do something, people will become busy. People with too much time on their hands tend to become unhappy or bored.

Yet, Smart agues, boredom is the key to self-knowledge.

What comes into your consciousness when you are idle can often be reports from the depths of your unconscious self— and this information may not always be pleasant. Nonetheless, your brain is likely bringing it to your attention for a good reason . Through idleness, great ideas buried in your unconsciousness have the chance to enter your awareness.

A brief history of idleness.

At least since Homer we’ve been ambivalent on the subject. In the Odyssey, the Lotus-eaters lolled around all day “munching lotus” and were both hospitable and seemingly quite content. But they were a threat to Odysseus and his crew. When he arrived at the land of the Lotus-eaters, the workaholic captain sent a couple of his men to investigate the locals. The Lotus-eaters “did them no hurt” but instead offered Odysseus’s men some of their brew, which was so overpowering that the Greeks gave up all thought of returning home. Odysseus, the personification of the heroic CEO, forced the affected men back to the ship and then tied them to the ship’s benches. He recognized that if the rest of the crew got a taste of the drug, they would never leave the island, and ordered the ship to cast off. In Samuel Butler’s translation, “they took their places and smote the grey sea with their oars.”

Despite the Western cliché of China as a country where work, productivity, and industry are enshrined as the greatest of ideals, during Confucian times idleness wasn’t a sub-culture but an integral part of the culture. A Confucian gentleman grew long fingernails to prove that he did not have to work with his hands. Confucianism actually disdained hard work and instead idealized leisure and effortlessness. According to Lawrence E. Harrison, a senior research fellow at Tufts, “for the Chinese, Sisyphus is not a tragedy but a hilarious joke.” Harrison writes that the highest philosophical principle of Taoism is wu-wei, or non-effort, which means that a truly enlightened person either spiritually or intellectually goes about life with the minimum expenditure of energy. In military matters, the ancient Chinese held that a good general forces the enemy to exhaust himself and waits for the right opportunity to attack, using the circumstances to his advantage while doing as little as possible. This is in contrast to the Western idea of trying to achieve some predefined objective with overwhelming effort and force. It is thus paradoxical that in spite of China’s long history of embracing idleness, it’s currently thought of as the world’s factory. This might be because, as a Chinese physicist told me recently, China has only “overcome” Confucianism in the last half century or so.

With the coming of the Enlightenment in the West, as work became mechanized, bureaucratized, and de-humanized, philosophers fought back. At that point, as the capitalist world system started an unprecedented period of expansion, Western culture popularized the concept of the “the noble savage,” one of whose particular attributes was lounging around and eating the fruit that supposedly fell into his lap. The incomparable Samuel Johnson published a series of essays on the benefits of being idle in the periodical The Idler from 1758 to 1760. He wrote that, “Idleness … may be enjoyed without injury to others; and is therefore not watched like Fraud, which endangers property, or like Pride, which naturally seeks its gratifications in another’s inferiority. Idleness is a silent and peaceful quality, that neither raises envy by ostentation, nor hatred by opposition; and therefore no body is busy to censure or detect it.”

But the capitalists could not be stopped. The 19th century saw the advent of the global industrial economy. As human beings came to function like cogs in the complex machine called the factory, Frederick Taylor, godfather of the efficient American work ethic, introduced “scientific management” to capitalist overseers in The Principles of Scientific Management. His goal was to integrate the life of the worker with the life of business, by the means of what was then considered scientific understanding of humans. Taylor sought to increase production efficiency by minutely measuring the time and motion of tasks. Anticipating modern productivity fads like Six Sigma, Taylor looked to replace each tradesman’s knowledge and experience with a standardized and “scientific” technique for doing work. While Taylorism was and still is hugely popular among the business class, humanists of all stripes were unenthusiastic. In 1920, perhaps in reaction to increasing Taylorization, the concept of the robot— a fully mechanized, soulless worker, physically as well as spiritually dehumanized— was introduced by Czech playwright Karel Čapek. The very word “robot” means “worker” in Czech. The same year, American humorist Christopher Morley published his now-classic essay On Laziness. “The man who is really, thoroughly, and philosophically slothful,” he wrote, “is the only thoroughly happy man. It is the happy man who benefits the world. The conclusion is inescapable.”

With the advent of the 1980s and Ronald Reagan, the mantra that productivity was essential to self-esteem took hold. It was good for America, it was good for business. Laziness, on the other hand, was anti-American …

Autopilot: The Art and Science of Doing Nothing goes on to explore the benefits and history of idleness in more detail.

Antifragile: A Definition

"Complex systems are weakened, even killed, when deprived of stressors."

“Complex systems are weakened, even killed, when deprived of stressors.”

I was talking with someone the other day about Antifragility, and I realized that, while a lot of people use the word, not many people have read: Antifragile, where Nassim Taleb defines it.

Just as being clear on what constitutes a black swan allowed us to better discuss the subject, so too will defining antifragility.

The classic example of something antifragile is Hydra, the greek mythological creature that has numerous heads. When one is cut off, two grow back in its place.

From Antifragile: Things That Gain from Disorder:

Some things benefit from shocks; they thrive and grow when exposed to volatility, randomness, disorder, and stressors and love adventure , risk, and uncertainty. Yet, in spite of the ubiquity of the phenomenon, there is no word for the exact opposite of fragile. Let us call it antifragile. Antifragility is beyond resilience or robustness. The resilient resists shocks and stays the same; the antifragile gets better. This property is behind everything that has changed with time: evolution, culture, ideas, revolutions, political systems, technological innovation, cultural and economic success, corporate survival, good recipes (say, chicken soup or steak tartare with a drop of cognac), the rise of cities, cultures, legal systems, equatorial forests, bacterial resistance … even our own existence as a species on this planet. And antifragility determines the boundary between what is living and organic (or complex), say, the human body, and what is inert, say, a physical object like the stapler on your desk.

The antifragile loves randomness and uncertainty, which also means— crucially—a love of errors, a certain class of errors. Antifragility has a singular property of allowing us to deal with the unknown, to do things without understanding them— and do them well. Let me be more aggressive: we are largely better at doing than we are at thinking, thanks to antifragility. I’d rather be dumb and antifragile than extremely smart and fragile, any time.

It is easy to see things around us that like a measure of stressors and volatility: economic systems , your body, your nutrition (diabetes and many similar modern ailments seem to be associated with a lack of randomness in feeding and the absence of the stressor of occasional starvation), your psyche. There are even financial contracts that are antifragile: they are explicitly designed to benefit from market volatility.

Antifragility makes us understand fragility better. Just as we cannot improve health without reducing disease, or increase wealth without first decreasing losses, antifragility and fragility are degrees on a spectrum.

By grasping the mechanisms of antifragility we can build a systematic and broad guide to nonpredictive decision making under uncertainty in business, politics, medicine, and life in general— anywhere the unknown preponderates, any situation in which there is randomness, unpredictability, opacity, or incomplete understanding of things.

It is far easier to figure out if something is fragile than to predict the occurrence of an event that may harm it. Fragility can be measured; risk is not measurable (outside of casinos or the minds of people who call themselves “risk experts”). This provides a solution to what I’ve called the Black Swan problem— the impossibility of calculating the risks of consequential rare events and predicting their occurrence. Sensitivity to harm from volatility is tractable, more so than forecasting the event that would cause the harm. So we propose to stand our current approaches to prediction, prognostication, and risk management on their heads.

In every domain or area of application, we propose rules for moving from the fragile toward the antifragile, through reduction of fragility or harnessing antifragility. And we can almost always detect antifragility (and fragility) using a simple test of asymmetry : anything that has more upside than downside from random events (or certain shocks) is antifragile; the reverse is fragile.

Deprivation of Antifragility
Crucially, if antifragility is the property of all those natural (and complex) systems that have survived, depriving these systems of volatility, randomness, and stressors will harm them. They will weaken, die, or blow up. We have been fragilizing the economy, our health, political life, education, almost everything … by suppressing randomness and volatility. … stressors. Much of our modern, structured, world has been harming us with top-down policies and contraptions (dubbed “Soviet-Harvard delusions” in the book) which do precisely this: an insult to the antifragility of systems. This is the tragedy of modernity: as with neurotically overprotective parents, those trying to help are often hurting us the most (see iatrogenics)

Antifragile is the antidote to Black Swans. The modern world may increase technical knowledge but it will also make things more fragile.

… Black Swans hijack our brains, making us feel we “sort of” or “almost” predicted them, because they are retrospectively explainable. We don’t realize the role of these Swans in life because of this illusion of predictability. Life is more, a lot more, labyrinthine than shown in our memory— our minds are in the business of turning history into something smooth and linear, which makes us underestimate randomness. But when we see it, we fear it and overreact. Because of this fear and thirst for order, some human systems, by disrupting the invisible or not so visible logic of things, tend to be exposed to harm from Black Swans and almost never get any benefit. You get pseudo-order when you seek order; you only get a measure of order and control when you embrace randomness.

Complex systems are full of interdependencies— hard to detect— and nonlinear responses. “Nonlinear” means that when you double the dose of, say, a medication, or when you double the number of employees in a factory, you don’t get twice the initial effect, but rather a lot more or a lot less. Two weekends in Philadelphia are not twice as pleasant as a single one— I’ve tried. When the response is plotted on a graph, it does not show as a straight line (“linear”), rather as a curve. In such environments, simple causal associations are misplaced; it is hard to see how things work by looking at single parts.

Man-made complex systems tend to develop cascades and runaway chains of reactions that decrease, even eliminate, predictability and cause outsized events. So the modern world may be increasing in technological knowledge, but, paradoxically, it is making things a lot more unpredictable.

An annoying aspect of the Black Swan problem— in fact the central, and largely missed , point —is that the odds of rare events are simply not computable.

Robustness is not enough.

Consider that Mother Nature is not just “safe.” It is aggressive in destroying and replacing, in selecting and reshuffling . When it comes to random events, “robust” is certainly not good enough. In the long run everything with the most minute vulnerability breaks, given the ruthlessness of time— yet our planet has been around for perhaps four billion years and, convincingly, robustness can’t just be it: you need perfect robustness for a crack not to end up crashing the system. Given the unattainability of perfect robustness, we need a mechanism by which the system regenerates itself continuously by using, rather than suffering from, random events, unpredictable shocks, stressors, and volatility.

Fragile and antifragile are relative — there is no absolute. You may be more antifragile than your neighbor but that doesn’t make you antifragile.


Here’s an example

All of this can lead to some pretty significant conclusions. Often it’s impossible to be antifragile, but falling short of that you should be robust, not fragile. How do you become robust? Make sure you’re not fragile. Eliminate things that make you fragile. In an interview, Taleb offers some ideas:

You have to avoid debt because debt makes the system more fragile. You have to increase redundancies in some spaces. You have to avoid optimization. That is quite critical for someone who is doing finance to understand because it goes counter to everything you learn in portfolio theory. … I have always been very skeptical of any form of optimization. In the black swan world, optimization isn’t possible. The best you can achieve is a reduction in fragility and greater robustness.

If you haven’t already, I highly encourage you to read Antifragile.

Image credit: velinov.

10 Books Bill and Melinda Gates Recommended to the TED Audience This Year

The organizers of TED asked Bill and Melinda Gates to suggest some books that attendees might enjoy. Bill picked 5 and Melinda picked five and their choices couldn’t be more different or interesting. Gates even picked one from his favourite living author.

This isn’t the first time I’ve cherry picked book ideas from Gates. I ordered a few of his 7 best books of 2013 and 2012. The diversity of what he reads is mind-boggling. And, largely because of Gates, I’ve started reading Vaclav Smil.

Bill Recommends

“Each of the books on my list,” Gates said, “had a big impact on my thinking and really informed my work. Four of them are quite optimistic about our ability to make the world a better place. The Vaclav Smil book makes clear that if we hope to address climate change, we’ll have to transform our energy infrastructure—and that will be harder than most of us might realize.”

The Better Angels of Our Nature by Steven Pinker

Steven Pinker’s carefully researched study stands out as one of the most important books I’ve ever read. Pinker paints a remarkable picture showing that the world has evolved over time to be a far less violent place than before. It offers a fresh perspective on how to achieve positive outcomes in the world. A thoroughly worthwhile read.

Getting Better by Charles Kenny

I know from personal experience that stepping into the public square to announce that foreign aid is important and effective can be lonely work. Charles Kenny’s elegant book on the impact of aid carefully documents how the quality of life—even in the world’s poorest countries—has improved dramatically over the past several decades. With reams of solid data to support his case, he argues that governments and aid agencies have played an important role in this progress.

Behind the Beautiful Forevers by Katherine Boo

Katherine Boo spent three years getting to know the people of Annawadi, a slum of about 3,000 people on the edge of a sewage-filled lake in India’s largest city. Her book is a poignant reminder of how much more work needs to be done to address the inequities in the world. But it’s also an uplifting story of people striving to make a life for themselves, sacrificing for their families, and in their own way, being innovative and entrepreneurial in creating a vibrant local economy.

The Man Who Fed the World by Leon Hesser

Norm Borlaug is one of my heroes—and Leon Hesser’s biography is a fascinating account of Borlaug’s life and accomplishments. This is a story of genius, self-sacrifice, and determination. Borlaug was a remarkable scientist and humanitarian whose work in agriculture is rightfully credited with saving the lives of over a billion people.

Energy Myths and Realities by Vaclav Smil

Vaclav Smil is probably my favorite living author. If you care about energy issues, I recommend this volume, though its unvarnished look at the realities of energy use and infrastructure may be disconcerting to anyone who thinks solving our energy problems will be easy. Smil provides a rational framework for evaluating energy promises and important lessons to keep in mind if we’re to avert the looming climate crisis.

Melinda Recommends

The note Melinda sent to TED along with her selections read: “Those of us interested in development spend a lot of time thinking about what it takes to translate a great idea into results on the ground. Each of these books has helped deepen my understanding of how the global development community can drive and sustain meaningful change, even in the face of difficult circumstances. Together, they paint a portrait of a world where progress is achievable if we work together and learn from each other.”

The Last Hunger Season by Roger Thurow

Roger Thurow movingly chronicles the lives of four Kenyan farmers as they struggle to support their families through the wanjala, Swahili for “hunger season.” This book is both about the importance of investing in Africa’s smallholder farmers and a compelling blueprint for doing it effectively. Thurow shows how, together, we can make this wanjala the last one.

However Long the Night by Aimee Molloy

This is the story of an extraordinary woman: Molly Melching. For more than 40 years, Molly has worked in Senegalese communities to help improve lives for some of the country’s poorest people. Her success is based on her insistence on working in close partnership with local communities. That way, change is always driven from the center out, not the top down. This book reinforced my own belief that developing communities already have the potential and desire to spark the change that will lead to better lives for themselves and their families.

In the Company of the Poor by Paul Farmer and Gustavo Gutierrez

Paul Farmer is longtime friend of mine, and through these pages, you can hear his voice and feel his deep personal connection to improving lives for people who are too often ignored. You also get a sense of his (and Father Gutierrez’s) intellectual commitment to changing the systems that lead to poverty, so that their work has a permanent impact.

Change by Design by Tim Brown

Design thinking is a model of problem solving that could have huge implications for global health and development. It’s an approach that recognizes that the people facing challenges have the best understanding of what solutions will really work for them—so we need to invite them to participate in the design process as well. So many of the women and families I meet already have the potential to lift themselves out of poverty. Design thinking reminds us that to unlock this opportunity, we have to first enlist their help.

Mighty Be Our Powers by Leymah Gbowee

In 2011, Leymah Gbowee became a global figure when she won a Nobel Prize for launching a grassroots women’s movement that led to peace in Liberia. This is an amazing tale of a group of women coming together to change the course of a country’s history—and it’s also the inspiring story of how Leymah overcame her own doubts and fears and found the courage to lead them.

Why We Miss Creative Ideas That Are Right Under Our Noses

Here is an interesting excerpt from an interview with Jennifer Mueller and Shankar Vedantam, author of The Hidden Brain: How Our Unconscious Minds Elect Presidents, Control Markets, Wage Wars, and Save Our Lives.

While this is an argument for distance, it’s also an argument for the incubation phase of innovation.

[T]he research seems to suggest that part of the reason we miss seeing creative ideas that are right under our nose is because the ideas are right under our nose. There’s this new research that looks at how people evaluate creativity. Jennifer Mueller at the University of San Diego and her colleagues … find that where the idea comes from appears to influence whether people think it’s creative.

We found that when we told people the idea was generated far away, they rated the idea as significantly more creative than when the idea was generated nearby.

We’re talking about how a manager, a boss, would evaluate an idea that’s brought to them.

So it seems to happen … because our minds are prone to mixing these two things up. When things are nearby, they’re concrete and you can see the details of the things. On the other hand, when things are far away, they’re much more abstract. So thinking about things that are near and far puts us in different mental states. When you think about things nearby, you see the details, and so when a creative idea comes along, the first thing you ask is, can it work?

Now, most creative ideas are risky and the risks are obvious when you look at the details, so when you think about it with this detail-oriented mindset, you’re more likely to shoot the idea down. On the other hand, when you’re thinking about things that are far away, you’re in a more abstract frame of mind and so the first question you ask is not will this work; you’re more open to seeing the creative possibilities.

So it’s not just that as a manager, that the manager disrespects the employees. The manager is just familiar with the employees, he or she works with the employees every day, and they’re thinking about the details of it. Whereas somebody comes from the outside, they can think big.

So obviously it has to be said that some ideas are not creative and they deserve to be shot down, but the reason managers often are shooting down ideas that might be creative that come from subordinates is not because they’re necessarily bad managers, but they might be in this different mindset.

Creativity and innovation in organizations is inherently difficult. In part, because the people who make decisions tend to be the people with the most experience. That experience helps you spot big mistakes but it also makes it harder for you to “recognize out of the box possibilities” or do something that might go against how your organization makes money today. Also, in part because the skills generally associated with innovators overlap with ones organizations don’t like (such as, questioning and experimentation).

The key to building an innovative organization is developing a culture of open-mindedness: a sense of shared curiosity.

A Discussion on the Work of Daniel Kahneman asked the likes of Christopher Chabris, Nicholas Epley, Jason Zweig, William Poundstone, Cass Sunstein, Phil Rosenzweig, Richard Thaler & Sendhil Mullainathan, Nassim Nicholas Taleb, Steven Pinker, and Rory Sutherland among others: “How has Kahneman’s work influenced your own? What step did it make possible?”

Kahneman’s work is summarized in the international best-seller Thinking, Fast and Slow.

Here are some select excerpts that I found interesting.

Christopher Chabris (author of The Invisible Gorilla)

There’s an overarching lesson I have learned from the work of Danny Kahneman, Amos Tversky, and their colleagues who collectively pioneered the modern study of judgment and decision-making: Don’t trust your intuition.

Jennifer Jacquet

After what I see as years of hard work, experiments of admirable design, lucid writing, and quiet leadership, Kahneman, a man who spent the majority of his career in departments of psychology, earned the highest prize in economics. This was a reminder that some of the best insights into economic behavior could be (and had been) gleaned outside of the discipline

Jason Zweig (author of Your Money and Your Brain)

… nothing amazed me more about Danny than his ability to detonate what we had just done.

Anyone who has ever collaborated with him tells a version of this story: You go to sleep feeling that Danny and you had done important and incontestably good work that day. You wake up at a normal human hour, grab breakfast, and open your email. To your consternation, you see a string of emails from Danny, beginning around 2:30 a.m. The subject lines commence in worry, turn darker, and end around 5 a.m. expressing complete doubt about the previous day’s work.

You send an email asking when he can talk; you assume Danny must be asleep after staying up all night trashing the chapter. Your cellphone rings a few seconds later. “I think I figured out the problem,” says Danny, sounding remarkably chipper. “What do you think of this approach instead?”

The next thing you know, he sends a version so utterly transformed that it is unrecognizable: It begins differently, it ends differently, it incorporates anecdotes and evidence you never would have thought of, it draws on research that you’ve never heard of. If the earlier version was close to gold, this one is hewn out of something like diamond: The raw materials have all changed, but the same ideas are somehow illuminated with a sharper shift of brilliance.

The first time this happened, I was thunderstruck. How did he do that? How could anybody do that? When I asked Danny how he could start again as if we had never written an earlier draft, he said the words I’ve never forgotten: “I have no sunk costs.”

William Poundstone (author of Are Your Smart Enough To Work At Google?)

As a writer of nonfiction I’m often in the position of trying to connect the dots—to draw grand conclusions from small samples. Do three events make a trend? Do three quoted sources justify a conclusion? Both are maxims of journalism. I try to keep in mind Kahneman and Tversky’s Law of Small Numbers. It warns that small samples aren’t nearly so informative, in our uncertain world, as intuition counsels.

Cass R. Sunstein (Author, Why Nudge?)

These ideas are hardly Kahneman’s most well-known, but they are full of implications, and we have only started to understand them.

1. The outrage heuristic. People’s judgments about punishment are a product of outrage, which operates as a shorthand for more complex inquiries that judges and lawyers often think relevant. When people decide about appropriate punishment, they tend to ask a simple question: How outrageous was the underlying conduct? It follows that people are intuitive retributivists, and also that utilitarian thinking will often seem uncongenial and even outrageous.

2. Scaling without a modulus. Remarkably, it turns out that people often agree on how outrageous certain misconduct is (on a scale of 1 to 8), but also remarkably, their monetary judgments are all over the map. The reason is that people do not have a good sense of how to translate their judgments of outrage onto the monetary scale. As Kahneman shows, some work in psychophysics explains the problem: People are asked to “scale without a modulus,” and that is an exceedingly challenging task. The result is uncertainty and unpredictability. These claims have implications for numerous questions in law and policy, including the award of damages for pain and suffering, administrative penalties, and criminal sentences.

3. Rhetorical asymmetry. In our work on jury awards, we found that deliberating juries typically produce monetary awards against corporate defendants that are higher, and indeed much higher, than the median award of the individual jurors before deliberation began. Kahneman’s hypothesis is that in at least a certain category of cases, those who argue for higher awards have a rhetoric advantage over those who argue for lower awards, leading to a rhetorical asymmetry. The basic idea is that in light of social norms, one side, in certain debates, has an inherent advantage – and group judgments will shift accordingly. A similar rhetorical asymmetry can be found in groups of many kinds, in both private and public sectors, and it helps to explain why groups move.

4. Predictably incoherent judgments. We found that when people make moral or legal judgments in isolation, they produce a pattern of outcomes that they would themselves reject, if only they could see that pattern as a whole. A major reason is that human thinking is category-bound. When people see a case in isolation, they spontaneously compare it to other cases that are mainly drawn from the same category of harms. When people are required to compare cases that involve different kinds of harms, judgments that appear sensible when the problems are considered separately often appear incoherent and arbitrary in the broader context. In my view, Kahneman’s idea of predictable coherence has yet to be adequately appreciated; it bears on both fiscal policy and on regulation.

Phil Rosenzweig

For years, there were (as the old saying has it) two kinds of people: those relatively few of us who were aware of the work of Danny Kahneman and Amos Tversky, and the much more numerous who were not. Happily, the balance is now shifting, and more of the general public has been able to hear directly a voice that is in equal measures wise and modest.

Sendhil Mullainathan (Author of Scarcity: Why Having Too Little Means So Much)

… Kahneman and Tversky’s early work opened this door exactly because it was not what most people think it was. Many think of this work as an attack on rationality (often defined in some narrow technical sense). That misconception still exists among many, and it misses the entire point of their exercise. Attacks on rationality had been around well before Kahneman and Tversky—many people recognized that the simplifying assumptions of economics were grossly over-simplifying. Of course humans do not have infinite cognitive abilities. We are also not as strong as gorillas, as fast as cheetahs, and cannot swim like sea lions. But we do not therefore say that there is something wrong with humans. That we have limited cognitive abilities is both true and no more helpful to doing good social science that to acknowledge our weakness as swimmers. Pointing it out did it open any new doors.

Kahneman and Tversky’s work did not just attack rationality, it offered a constructive alternative: a better description of how humans think. People, they argued, often use simple rules of thumb to make judgments, which incidentally is a pretty smart thing to do. But this is not the insight that left us one step from doing behavioral economics. The breakthrough idea was that these rules of thumb could be catalogued. And once understood they can be used to predict where people will make systematic errors. Those two words are what made behavioral economics possible.

Nassim Taleb (Author of Antifragile)

Here is an insight Danny K. triggered and changed the course of my work. I figured out a nontrivial problem in randomness and its underestimation a decade ago while reading the following sentence in a paper by Kahneman and Miller of 1986:

A spectator at a weight lifting event, for example, will find it easier to imagine the same athlete lifting a different weight than to keep the achievement constant and vary the athlete’s physique.

This idea of varying one side, not the other also applies to mental simulations of future (random) events, when people engage in projections of different counterfactuals. Authors and managers have a tendency to take one variable for fixed, sort-of a numeraire, and perturbate the other, as a default in mental simulations. One side is going to be random, not the other.

It hit me that the mathematical consequence is vastly more severe than it appears. Kahneman and colleagues focused on the bias that variable of choice is not random. But the paper set off in my mind the following realization: now what if we were to go one step beyond and perturbate both? The response would be nonlinear. I had never considered the effect of such nonlinearity earlier nor seen it explicitly made in the literature on risk and counterfactuals. And you never encounter one single random variable in real life; there are many things moving together.

Increasing the number of random variables compounds the number of counterfactuals and causes more extremes—particularly in fat-tailed environments (i.e., Extremistan): imagine perturbating by producing a lot of scenarios and, in one of the scenarios, increasing the weights of the barbell and decreasing the bodyweight of the weightlifter. This compounding would produce an extreme event of sorts. Extreme, or tail events (Black Swans) are therefore more likely to be produced when both variables are random, that is real life. Simple.

Now, in the real world we never face one variable without something else with it. In academic experiments, we do. This sets the serious difference between laboratory (or the casino’s “ludic” setup), and the difference between academia and real life. And such difference is, sort of, tractable.

… Say you are the manager of a fertilizer plant. You try to issue various projections of the sales of your product—like the weights in the weightlifter’s story. But you also need to keep in mind that there is a second variable to perturbate: what happens to the competition—you do not want them to be lucky, invent better products, or cheaper technologies. So not only you need to predict your fate (with errors) but also that of the competition (also with errors). And the variance from these errors add arithmetically when one focuses on differences.

Rory Sutherland

When I met Danny in London in 2009 he diffidently said that the only hope he had for his work was that “it might lead to a better kind of gossip”—where people discuss each other’s motivations and behaviour in slightly more intelligent terms. To someone from an industry where a new flavour-variant of toothpaste is presented as being an earth-changing event, this seemed an incredibly modest aspiration for such important work.

However, if this was his aim, he has surely succeeded. When I meet people, I now use what I call “the Kahneman heuristic”. You simply ask people “Have you read Danny Kahneman’s book?” If the answer is yes, you know (p>0.95) that the conversation will be more interesting, wide-ranging and open-minded than otherwise.

And it then occurred to me that his aim—for better conversations—was perhaps not modest at all. Multiplied a millionfold it may very important indeed. In the social sciences, I think it is fair to say, the good ideas are not always influential and the influential ideas are not always good. Kahneman’s work is now both good and influential.

Daniel Pink: The New ABCs of Selling

"To sell well is to convince someone else to part with resources—not to deprive that person, but to leave him better off in the end. That is also what, say, a good algebra teacher does."

“To sell well is to convince someone else to part with resources—not to deprive that person, but to leave him better off in the end. That is also what, say, a good algebra teacher does.”

“The only thing you got in this world is what you can sell. And the funny thing is, you’re a salesman, and you don’t know that.” — Arthur Miller, Death of a Salesman

No matter what you do for a living you’re in sales. That’s the conclusion Daniel Pink draws in his book To Sell Is Human: The Surprising Truth About Moving Others, a thought provoking book on “sales” that debunks some of the assumptions behind what we traditionally understand about sales. It’s about how to move people with passion and authenticity.

I’m convinced we’ve gotten it wrong. This is a book about sales. But it is unlike any book about sales you have read (or ignored) before. That’s because selling in all its dimensions—whether pushing Buicks on a car lot or pitching ideas in a meeting—has changed more in the last ten years than it did over the previous hundred. Most of what we think we understand about selling is constructed atop a foundation of assumptions that has crumbled.

It might be an idea, it might be yourself, it might be a product but you spend more of your time selling than you think.

Some of you, no doubt, are selling in the literal sense— convincing existing customers and fresh prospects to buy casualty insurance or consulting services or homemade pies at a farmers’ market. But all of you are likely spending more time than you realize selling in a broader sense—pitching colleagues, persuading funders, cajoling kids. Like it or not, we’re all in sales now.

Selling doesn’t have a good reputation. These clips from the 1992 movie Glengarry Glen Ross, based on David Mamet’s Pulitzer Prize winning play by the same name, play to what most of us think.

Pink takes one of the old adages of sales ABC — “Always Be Closing” and proposes a new ABC — “Attunement, Buoyancy, and Clarity.”

To sell well is to convince someone else to part with resources—not to deprive that person, but to leave him better off in the end. That is also what, say, a good algebra teacher does.

Most of selling used to take place in a world where the salesperson knew more than you did. Asymmetrical information created all sorts of problems for consumers. The person you needed to trust was also the one most able to deceive you. The seller knew more about the product than the buyer. This made buyers suspicious. And largely we remain as such. Thanks to the internet this is no longer the case but some of the problems still exist.

In a sort of Gresham’s Law, George Akerlof wrote (In The Market for “Lemons”) “Dishonest dealings tend to drive honest dealings out of the market … The presence of people who wish to pawn bad wares as good wares tends to drive out the legitimate business.”

In To Sell is Human, Pink picks up on this.

… prospective purchasers are on notice. When sellers know more than buyers, buyers must beware. It’s no accident that people in the Americas, Europe, and Asia today often know only two words of Latin. In a world of information asymmetry, the guiding principle is caveat emptor—buyer beware.

Imagine a world not of information asymmetry, but of something closer to information parity, where buyers and sellers have roughly equal access to relevant information. What would happen then? Actually, stop imagining that world. You’re living in it.

Buyers today aren’t “fully informed” in the idealized way that many economic models assume. But neither are they the hapless victims of asymmetrical information they once were. … The belief that sales is slimy, slick, and sleazy has less to do with the nature of the activity itself than with the long-reigning but fast-fading conditions in which selling has often taken place.

The balance has shifted. If you’re a buyer and you’ve got just as much information as the seller, along with the means to talk back, you’re no longer the only one who needs to be on notice. In a world of information parity, the new guiding principle is caveat venditor—seller beware.

Many of the common sales-practices of yesteryear don’t adapt well to information parity. In the new world, we need to re-cast the ABCs, Pink argues, to Attunement, Buoyancy, and Clarity.


Attunement “is the ability to bring one’s actions and outlook into harmony with other people and with the context you’re in,” Pink explains. It hinges on three principles.

1. Increase your power by reducing it.

… “power leads individuals to anchor too heavily on their own vantage point, insufficiently adjusting to others’ perspectives.” … The ability to take another’s perspective mattered less when sellers—whether a commissioned salesperson in an electronics store or a physician in her diploma—studded office—held all the cards. Their edge in information … gave them the ability to command through authority and sometimes even to coerce and manipulate. But as that information advantage has withered, so has the power it once conferred. As a result, the ability to move people now depends on power’s inverse: understanding another person’s perspective, getting inside his head and seeing the world through his eyes.

2. Use your head as much as your heart.
… Perspective-taking is a cognitive capacity; it’s mostly about thinking. Empathy is about emotional response; it’s mostly about feeling. Both are crucial. … (but) one is more effective when it comes to moving others. (Perspective-takers).

Pushing too hard is counterproductive, especially in a world of caveat venditor. But feeling too deeply isn’t necessarily the answer either – because you might submerge your own interests. Perspective-taking seems to enable the proper calibration between the two poles, allowing us to adjust and attune ourselves in ways that leave both sides better off.

This second principle of attunement also means recognizing that individuals don’t exist as atomistic units, disconnected from groups, situations, and contexts. And that requires training one’s perspective-taking powers not only on people themselves but also on their relationships and connections to others.

“I do this in every sales situation,” says Dan Shimmerman, founder of Varicent Software, a blazingly successful Toronto company recently acquired by IBM. “For me it’s very important to not just have a good understanding of the key players involved in making a decision, but to understand what each of their biases and preferences are. The mental map gives a complete picture , and allows you to properly allocate time, energy and effort to the right relationships.”

3. Mimic Strategically

Human beings are natural mimickers . Without realizing it, we often do what others do— mirroring back their “accents and speech patterns, facial expressions , overt behaviors, and affective responses.” The person we’re talking to crosses her arms; we do the same. Our colleague takes a sip of water; so do we. When we notice such imitation , we often take a dim view of it. “Monkey see, monkey do,” we sniff. We smirk about those who “ape” others’ behavior or “parrot” back their words as if such actions somehow lie beneath human dignity. But scientists view mimicry differently. To them, this tendency is deeply human, a natural act that serves as a social glue and a sign of trust . Yet they, too, assign it a nonhuman label. They call it the “chameleon effect.”


How to stay afloat amid that ocean of rejection is the second essential quality in moving others. I call this quality “buoyancy.” Hall exemplifies it. Recent social science explains it. And if you understand buoyancy’s three components— which apply before, during, and after any effort to move others— you can use it effectively in your own life.

Like attunement, Pink boils buoyancy down to three components—”which apply before, during and after any effort to move others.”

1. Before: Interrogative Self-Talk

We human beings talk to ourselves all the time— so much, in fact, that it’s possible to categorize our self-talk. Some of it is positive , as in “I’m strong,” “I’ve got this,” or “I will be the world’s greatest salesman.” Some of it— for a few of us, much of it— is negative. “I’m too weak to finish this race” or “I’ve never been good at math” or “There’s no way I can sell these encyclopedias.” But whether the talk is chest-thumping or ego-bashing, it tends to be declarative. It states what is or what will be.

However, the person whose example you should be following takes a different tack. His name is Bob the Builder. And if you haven’t been around preschool children in the last fifteen years, let me offer a quick dossier. Bob is an overall-clad, hard-hat-sporting, stop-motion-animated guy who runs a construction company. His TV program, which began in England in 1999, now entertains kids in forty-five countries. Bob is always finding himself in sticky situations that seem inevitably to call for traditional sales or non-sales selling. Like all of us, Bob talks to himself. But Bob’s self-talk is neither positive nor declarative. Instead, to move himself and his team, he asks a question: Can we fix it?

… Those who approached a task with Bob-the-Builder-style questioning self-talk outperformed those who employed the more conventional juice-myself-up declarative self-talk.

The reasons are twofold . First, the interrogative, by its very form, elicits answers— and within those answers are strategies for actually carrying out the task. … The second reason is related. Interrogative self-talk, the researchers say, “may inspire thoughts about autonomous or intrinsically motivated reasons to pursue a goal.”

2. During: Positivity Ratios

The broadening effect of positive emotions has important consequences for moving others. Consider both sides of a typical transaction. For the seller, positive emotions can widen her view of her counterpart and his situation. Where negative emotions help us see trees, positive ones reveal forests. And that, in turn, can aid in devising unexpected solutions to the buyer’s problem.

Positivity has one other important dimension when it comes to moving others. “You have to believe in the product you’re selling— and that has to show,” Hall says. Nearly every salesperson I talked to disputed the idea that some people “could sell anything”— whether they believed in it or not. That may have been true in the past, when sellers held a distinct information advantage and buyers had limited choices . But today, these salespeople told me, believing leads to a deeper understanding of your offering, which allows sellers to better match what they have with what others need. And genuine conviction can also produce emotional contagion of its own.

(Negative emotions, however, are valuable.)

(They) offer us feedback on our performance, information on what’s working and what’s not, and hints about how to do better.

3. After: Explanatory Style
In human beings, Seligman observed, learned helplessness was usually a function of people’s “explanatory style”— their habit of explaining negative events to themselves. Think of explanatory style as a form of self-talk that occurs after (rather than before) an experience. People who give up easily, who become helpless even in situations where they actually can do something, explain bad events as permanent, pervasive, and personal. They believe that negative conditions will endure a long time, that the causes are universal rather than specific to the circumstances, and that they’re the ones to blame. So if their boss yells at them, they interpret it as “My boss is always mean” or “All bosses are jerks” or “I’m incompetent at my job” rather than “My boss is having an awful day and I just happened to be in the line of fire when he lost it.” A pessimistic explanatory style— the habit of believing that “it’s my fault, it’s going to last forever, and it’s going to undermine everything I do” —is debilitating, Seligman found. It can diminish performance, trigger depression, and “turn setbacks into disasters.”

In other words, the salespeople with an optimistic explanatory style— who saw rejections as temporary rather than permanent, specific rather than universal, and external rather than personal— sold more insurance and survived in their jobs much longer. What’s more, explanatory style predicted performance with about the same accuracy as the most widely used insurance industry assessment for hiring agents. Optimism, it turns out, isn’t a hollow sentiment. It’s a catalyst that can stir persistence, steady us during challenges, and stoke the confidence that we can influence our surroundings.

Finally, we reach Clarity.

The problem we have saving for retirement, these studies showed, isn’t only our meager ability to weigh present rewards against future ones. It is also the connection— or rather, the disconnection— between our present and future selves. Other research has shown that “thinking about the future self elicits neural activation patterns that are similar to neural activation patterns elicited by thinking about a stranger.” Envisioning ourselves far into the future is extremely difficult— so difficult, in fact, that we often think of that future self as an entirely different person. “To people estranged from their future selves, saving is like a choice between spending money today and giving it to a stranger years from now.”

trying to solve an existing problem— getting people to better balance short-term and long-term rewards— was insufficient because it wasn’t the problem that most needed solving. The researchers’ breakthrough was to identify a new, and previously unknown, problem: that we think of ourselves today and ourselves in the future as different people. Once they identified that alternative problem, they were able to fashion a solution: Show people an image of themselves getting old. And that, in turn, addressed the broader concern—namely, encouraging people to save more money for retirement.

This conceptual shift demonstrates the third quality necessary in moving others today: clarity—the capacity to help others see their situations in fresh and more revealing ways and to identify problems they didn’t realize they had.

Good salespeople, we’ve long been told, are skilled problem solvers. They can assess prospects’ needs, analyze their predicaments, and deliver the optimal solutions. This ability to solve problems still matters. But today, when information is abundant and democratic rather than limited and privileged, it matters relatively less. After all, if I know precisely what my problem is— whether I’m hoping to buy a particular camera or I want to take a three-day beach vacation— I can often find the information I need to make my decision without any assistance. The services of others are far more valuable when I’m mistaken, confused, or completely clueless about my true problem. In those situations, the ability to move others hinges less on problem solving than on problem finding.

One final note on clarity, it’s important to give people clarity on how to think about a problem but to maximize potential you should give them clarity on action as well.

To Sell Is Human: The Surprising Truth About Moving Others reminds you that you’re always selling. You just might not be aware of it.