Chapter One

Making Sense of the World

True genius resides in the capacity for evaluation of uncertain, hazardous, and conflicting information.

—Winston Churchill

The first thing a visitor to the headquarters of the Ford Motor Company will notice upon arrival is the flags. They surround the entrance to the imposing blue building in Dearborn, Michigan, each one from a country where Ford has operations. There are so many flags that the long walkway up to the main door of the building has the air of a United Nations assembly.

The lobby and lower floors of the headquarters maintain this atmosphere of diplomatic cheerfulness—people come and go with a friendly efficiency, dinging the countless elevators doing brisk business up and down. The very top floors of the headquarters, however, are oddly quiet. This is where Mark Fields, president and CEO since 2014, has his office. The main objective of almost everyone who spends any amount of their day up here is to protect his time and attention.

From his penthouse office, Fields looks out and sees the vast expanse of the Ford campus. There’s a reason visitors need a car to go to meetings at Ford; it’s impossible to cover the campus on foot. Through the windows, the company resembles a little country of engineers making power trains, brakes, and software. To the left is the headquarters of product development; and to the right, the marketing buildings tower over well-kept lawns.

From this singular vantage point, Mark Fields makes decisions that have lasting impact on hundreds of thousands of employees all over the world. But his perspective is fundamentally limited: like most CEOs, he is protected from the world by official and unofficial layers of people. Ford employees will spend months preparing for a one-hour meeting with him, rehearsing over and over again every aspect and responses to every possible question he might have. In ways both direct and indirect, the 199,000 people working for Ford are offering him a highly curated information stream. Some of them are glossing over issues because they don’t want to be the bearers of bad news. Others, however, are simply editing out descriptions and details in the name of efficiency. With every single edit in every single conversation, Fields is in danger of losing touch with potent human intelligence that will help him make strategic decisions. And yet, he can’t pay attention to everything. Somehow, within these limitations, Fields has to make daily decisions that will determine the future of more than 150 billion dollars in annual revenue.

In the past, he was able to use his intuition to guide him through many of these choices. He has decades of experience in the car industry, including serving as the CEO of Mazda. And, until recently, Ford’s model of selling cars—using research and engineering to develop new features to appeal to Ford’s mostly American drivers—was a good fit for its buyers. Drivers were eager to pay more money for technologically advanced features, and Ford could use the same marketing that had proved so successful for their very first Model T in 1908: “High Priced Quality in a Low Priced Car.” Ford consistently won over drivers with its solid expertise in car engineering—unlike General Motors, Ford has always been a car lover’s company. In short, Fields and many of the Ford engineers grew up in the same world as the people buying Ford’s cars.

But what happens when people who are living in other worlds start buying Ford’s cars? People living in Brazil or China possess strikingly different worldviews, sentiments, and aspirations than do Americans. To these people, Ford’s history of solid engineering and middle class values is meaningless. What’s more, its specific, high-quality features are often irrelevant or even detriments to the value of the car. Ford had been investing in technologies like Lane Assist—an automated system designed to keep vehicles inside the white lines—but what if their potential drivers live in a Chinese city without clearly demarcated lanes? Ford has explored the idea of driverless cars, but many of their new customers live in places like New Delhi, India, where employing a driver is the norm for car owners and an important way of signifying status.

Faced with a multitude of such problems, the carefully designed spaces and perspectives of an executive like Mark Fields suddenly do not seem so advantageous. He is no longer making decisions based on the knowledge of his own world. He needs to understand the worlds of people in cultures vastly different from his own. What matters to the engineers in Detroit is likely to overlap with what matters to, say, a Texan looking for a truck. But Fields and his engineers at Ford have begun to sense that they don’t know enough about what is relevant to a young creative in Shanghai eager to make career and artistic connections, for example, or an entrepreneur in Chennai who is seeking out more space for spiritual reflection in the midst of a grinding work schedule.

When I work with executives like Fields—helping them to discover other cultures and people in emerging markets—they almost always describe their experience in the same way. They can no longer trust their instincts alone as a guiding light for wise decisions. They say, I’ve lost my intuition. And they all want to get it back—quickly. But how?

Gaining the type of understanding that Mark Fields is after—an understanding of other worlds—is only possible with profound insights into culture. And we can’t have a meaningful insight into culture if we don’t embrace a rigorous and sustained engagement with it. When I use the words “rigorous” and “engagement,” I don’t mean market research numbers or data analytics. I mean a study of culture that involves the humanities: reading a culture’s seminal texts, understanding its languages, getting a firsthand feel for how its people live. Not “76 percent of 21-to 35-year-olds living in urban areas in Brazil buy premium coffee.” This kind of data tells us nothing about culture.

Take Starbucks. Yes, the success of the company relies on technology and quantitative analysis: they need the most advanced coffee machines and roasters; they need a streamlined supply chain, well-designed mobile apps, and up-to-date financial technology to drive the company’s growth. But the actual heart and soul of the company—its raison d’être—is based on a simple but profound cultural insight. Howard Schultz understood how to modify the Southern European coffee culture to the contours of American life. Today all this seems far too obvious, but it was only thirty-five years ago that coffee in North America meant a lukewarm cup of Folgers. Schultz’s insight required an understanding of Italian language and culture—he went to Italy and studied the famous Italian coffee bars before taking over at Starbucks—as well as an attunement to an unmet desire in the United States for more shared community spaces.

When we want to understand people—real people in the rich reality of their worlds—we need this type of cultural intelligence. We need to know how their cassoulet smells after an hour in the oven; we need to know that the sand and dirt blowing in their deserts hurts their eyes in the morning; we need to know that their poetry never uses the first-person singular, and that they have always considered their mountains a safe haven when under attack. Investigating a culture in this way—achieving a 360-degree understanding of it—calls on every part of our humanity: we must bring our intellects, our spirits, and all our senses to the task. Most important to remember: if we want to say something meaningful about another culture, we have to let go—just a little bit—of the biases and assumptions that form the scaffolding of our own culture. When we commit to losing a part of ourselves, we gain something profoundly new in exchange. We gain insight. I call the practice of cultivating these types of insights sensemaking.

What Is Sensemaking?

Sensemaking is a method of practical wisdom grounded in the humanities. We can think of sensemaking as the exact opposite of algorithmic thinking: it is entirely situated in the concrete, while algorithmic thinking exists in a no-man’s-land of information stripped of its specificity. Algorithmic thinking can go wide—processing trillions of terabytes of data per second—but only sensemaking can go deep.

We can trace sensemaking’s roots back to Aristotle, the Greek philosopher, who described practical wisdom as phronesis. When a highly skilled person exhibits phronesis, it’s not just that they possess knowledge of abstract principles and rules. Phronesis is an artful synthesis of both knowledge and experience.

In the business world, we see phronesis when skilled traders perform in concert with market conditions and when experienced corporate managers sense subtle changes in organizations involving tens of thousands of people. When a legislative reform is implemented, a politician exhibiting phronesis can envision the chain of events that will play out in every domain of his or her constituency all at once. Many masterful leaders—knowledgeable and experienced—describe systems, societies, and organizations as an extension of their body. It is a part of them and they are a part of it.

How do these people achieve such extraordinary results? Though there is no shortcut to this work—no five-step plan, “life hack,” or killer PowerPoint to automatically get us there—there are some basic principles that can help all of us stay open to the insights that matter most. These principles are based upon the wealth of theories and methodologies that make up the humanities. I have framed each one of them to sit in direct contradiction to the prevailing assumptions of our algorithmic age.

In the following chapters, I will address each principle in more depth and provide a richer intellectual context for them. We will meet the master practitioners who wrestle with their own interpretations of such a practice based on the following ideas:

The Five Principles of Sensemaking

1. Culture—not individuals

2. Thick data—not just thin data

3. The savannah—not the zoo

4. Creativity—not manufacturing

5. The North Star—not the GPS

1. Culture—Not Individuals

Alice Munro, the Nobel Prize–winning short story writer, once wrote, “It’s as if tendencies that seem most deeply rooted in our minds, most private and singular, have come in as spores on the prevailing wind, looking for any likely place to land, any welcome.” We like to conceive of ourselves as highly individual, with our own autonomous modes of behaving. Yet, despite the promise of independent thought in modern liberal democracies, our notions of what is appropriate and relevant come to us through social context. As the astute Munro noted, this context determines what shows up as appropriate and relevant—tendencies that travel “like spores.”

Why does this matter? If we want to understand the most profound insights of a culture, we must first understand why people in that culture act the way they do. That understanding is rarely—if ever—based upon what individual people say or even on what they claim to do. Instead, it is built around an understanding of worlds. Whether we are in the world of hedge fund managers, union employees, artists, mothers, or politicians, we, as humans, are sensitive to how others in our world do things, change things, and think about things.

Philosophy can help us understand this better. Although it is often considered esoteric, philosophy is our greatest intellectual tool for analyzing deeply held cultural assumptions. Martin Heidegger, considered by many to be the greatest philosopher of the twentieth century, overturned all of the presuppositions of Western philosophy when he argued, in 1927, that these unspoken assumptions—the oxygen of our everyday lives—should be called “Being.” He defined it as “That on the basis of which beings are understood.” This radical new way of conceiving of “us” stood in direct contradiction to the prevailing edicts of rival philospher René Descartes: I think, therefore I am. Heidegger’s “Being” had nothing to do with an individual thinking, analyzing, or standing at a distance—objectively—from a context.

Heidegger, and the generation of philosophers who followed in his footsteps, argued that there are very few situations—if any—in which the pure, self-contained individual subject has a significant role to play. For this new cadre of philosophers, social context, or “Being,” was not just the driver of our everyday behavior; it was the very filter through which reality showed up as intelligible and meaningful. If we were children in the European Middle Ages, for example, our sense of identity and aspiration would necessarily be in relationship to the Church. A young knight in the Middle Ages would experience all phenomena as a reflection of his place next to God. Today, of course, it would never occur to a young man to become a knight—unless as a choice of kitsch or costume. Our reality—everything that we perceive as meaningful—is highly contextual and historical. And most of the time we are incapable of thinking beyond that context. Humans are defined by the society in which they live, Heidegger argued. All of this means that when someone like Mark Fields at Ford wants to understand how to sell cars in places like China, India, and Brazil, he needs a much more nuanced understanding of the social context of these new drivers. And sensemaking is the fastest and most effective means of achieving this type of understanding. To be clear, sensemaking is not a superficial brush-up on the arts—throwing on an album as background music or cruising through a museum exhibit in thirty minutes before going out for a drink. Sensemaking is a demanding form of cultural engagement; its rigor is precisely what makes it so rewarding.

Let me give you a little thought experiment involving two different musicians to illustrate how this works: If you put on jazz great Charlie Parker’s Savoy and Dial recordings, you are transported back to Minton’s Playhouse club in 1940s Harlem, where the smoke was thick and racial tensions hung heavy in the air. You can hear how his technical proficiency breaks the space-time continuum and, as his playing gets faster and faster, you experience the emergence of an entirely new kind of music called bebop.

If, instead, you put on David Bowie’s album “Heroes” from 1977 and engage with that one single line “We can be heroes, just for one day,” you open yourself up to the desperation of a youth culture infected with cynicism—little in the way of employment or hope for a better future.

Both of these pieces of music offer a direct portal into other worlds. We start to see how reality is structured for a jazz musician in Harlem during World War II and for young people in the post-punk era on the streets of London and New York. Through the nuances of the music, we come to an understanding about the cultural hopes and fears in these specific times and places. We learn what is worth celebrating and what rules—aesthetic, social, or political—need to be broken.

I had a profound experience with this on a recent visit I made to LACMA, the Los Angeles County Museum of Art. I wandered into the room displaying Islamic art from the late Middle Ages and I saw an older man with a worn face sitting on a bench and looking up at a manuscript depicting “The Gathering of Lovers.” In the watercolor, brilliantly rendered gold angels surround a figure of Adam, sitting at peace in the center. I stood in the back of the room so as not to disturb the man, but he turned around to speak to me, his face filled with tears. He told me that he was an undocumented worker from Mexico and that he was grieving the death of his mother. He connected with the storytelling in the manuscript painting, he said, because it was clear to him that this artist, working hundreds of years ago in an area of the world utterly foreign to him, had similar wishes for his family. “He wanted them to be in a place of beauty and calm after they died,” he told me. And then he thought for a moment before saying, “He must have been just like me.”

Great art connects us across the ages. It invites us to empathize with worlds at the very edge of our imaginative horizons. “… just like me.” At the same time, it can reveal to us the specific assumptions that shape our own worlds, our own particular moments in history.

Some cultures prioritize efficiency and order in their meetings, while other cultures use meetings as a way to secure alliances and establish power between players. Lunch is a two-hour feast in some cultures and a ten-minute sandwich in others. Ambition is admired and celebrated in certain circles, and denigrated and mocked in others. These unspoken rules are far away, but so close. They only come to the fore when we keenly observe them or when they break down. It is only when a new hire at work demands an executive title, for example, that company employees become aware of the culture’s disdain for hierarchy.

When we practice sensemaking, we stop seeing a room as a space filled with individual items and we start seeing the structures that form a cultural reality. In algorithmic thinking, a bottle of perfume is defined by how many milligrams of liquid exist within it; a pen is a piece of plastic with metal attached to it. In contrast, sensemaking perceives everything in relationship to everything else. The perfume becomes equipment—along with lipstick, high heels, and text messages—in the world of dating. The pen, along with a word processor and paper and books, is part of the world of writing. Pens, perfume, hammers, word processors: everything in our lives has some bearing on everything else. Nothing exists in an individual vacuum.

Philosophers give this concept many names. Pierre Bourdieu would call it “habitus”; Ernesto Laclau and Michel Foucault referred to it as “the discourse,” and still others dubbed it “our conversation” or “the conversation.” All of these various thinkers are indebted to Heidegger, who was the first to discover what he called “Being,” or background practices.

Although philosophers have been describing this concept for close to a century now, it is too often forgotten or disregarded in our modern world. In realms where quantitative analysis reigns supreme—corporations and financial firms come to mind, as do, increasingly, education and health institutions—these notions of shared worlds and background practices are radical. Just think about the way companies or political campaigns try to understand markets and voters: they ask people what they think. In a focus group or a survey, they take people out of the context of their regular lives and pepper them with questions about discrete ideas, products, or policy ideas. By decontextualizing experiences—pulling worlds apart in an attempt to create an assembly of facts—they miss almost everything that can shed light on human behavior. This is why their conclusions are wrong most of the time.

The concept of “culture—not individuals” serves as an essential corrective to the widely held belief that human behavior is based on individual choices, preferences, and logical structures. We will delve deeper into the structure and importance of shared worlds in Chapter Three.

2. Thick Data— Not Just Thin Data

If sensemaking is interested in cultures, not individuals, it follows, then, that sensemaking data has a completely different texture. A study of French culture, for example, would be dry and technical if it only included data from the Organization for Economic Cooperation and Development (OECD). What about the tactile and visceral pieces of data that communicate so much about French life—a loaf of fresh bread or a glass of Bordeaux? What about reading the poetry of Rimbaud or listening to a song by Serge Gainsbourg? Though these are certainly pursuits that bring us pleasure, they are also pieces of data that are essential to sensemaking.

In 1973, anthropologist Clifford Geertz developed the term thick description to characterize his ethnographic field notes. He was interested not just in human behavior but in how that behavior related to the greater cultural context. Geertz spent the lion’s share of his academic career writing about the nuances of culturally complex gestures, the thickness that adds depth to life. Take the wink as an example: the computer might classify it as a twitch of the eye lasting for a millisecond, but we all know that a wink can mean so much more. This tiny movement has the ability to communicate “I’m not serious,” “Let’s leave together,” “You’re an idiot,” and so many other, more ineffable messages.

Taking inspiration from Geertz’s phrase, I like to call sensemaking data “thick data” because it expresses what is meaningful about a culture. Thick data captures not just facts but the context of those facts. Eighty-six percent of households in America drink more than six quarts of milk per week, for example, but why do they drink milk? And what is it like? An apple weighing .09 pound and a gram of honey is thin data. A Rosh Hashanah meal with apples dipped in honey, by contrast, is thick data.

Think about it this way: if you are sitting in a chair right now, you know with quite some detail what the sound will be if you push the chair back. What if you drop a piece of paper from four feet and let it float down until it hits the floor? You know how it will feel when it leaves your hands; you know that its fall will be characterized by a gentle wafting back and forth; you know that it will land silently. Just think for a moment about all the stuff you know. You know when a cup of coffee is just a touch too cold; you know how it feels outside just before a thunderstorm; you know something is wrong when you look in your partner’s eyes. Philosophers have called this our familiarity with the world. It is the background upon which we deal with our lives and go through our days.

This type of knowledge is not a banal fact; it is the very way we deal with the world. It is how we choose things in the supermarket, how we cook, read each other, and chop down a tree. We make sense of the world and get around in it using this knowledge. It is what AI researchers continually attempt to copy and inevitably get wrong. This is the knowledge that makes up thick data.

Because it is not universally applicable like thin data, thick data is often dismissed as insufficient or lacking rigor. But the reality is that our lives are dominated by thick data. When we leave it out of our decisions—or attempt to ignore it—we are working with a faulty model of humanity. In a business context, this misunderstanding of people can have disastrous consequences. After all, business is almost always about making bets on human behavior: which product is most likely to sell, which employee is most likely to succeed, what price is a customer willing to pay. Companies that excel at making these bets tend to thrive in the marketplace. And the only way to make these types of killer bets is to understand people better.

Thick data stands in direct contrast with thin data—the sort of data you get when you look at the traces of our actions and behaviors: we travel this much every day; we search for that on the Internet; we sleep this many hours; we have this many social connections; we listen to this type of music, and so forth. It’s the data gathered by the cookies in your browser, the Fitbit on your wrist, or the GPS in your phone. These properties of human behavior are undoubtedly important, but they are not the whole story.

If thin data seeks to understand us based on what we do, thick data seeks to understand us in terms of how we relate to the many different worlds we inhabit. This is precisely why moods are one of our most salient forms of thick data. For example, we can agree, between us, that the mood in the office is dull or the party is just getting started. We can know what it is like to be caught up in the excitement of a sports game or the fervor of a political demonstration. We can all feel the sadness of a cultural moment—“Where were you on 9/11?”—as well as the infectious joy that takes hold when we hear about a courageous act on the news. If our colleague tells us that she feels the organization isn’t ready for change right now—There’s too much stress around here—we nod our heads and agree. When we are attuned to this kind of data, we can sense the subtle but constantly evolving changes of the worlds all around us.

Why is this attunement such an imperative? After all, isn’t this what market research and technical reports are for? Despite what people in power assume, leaders and key strategic thinkers are almost always surrounded by layers and layers of abstraction. I have watched the faces of many top executives in the corporate world—faces trained to project composure and competence—turn white with shock when confronted with the raw reality of their business, its customers, and the world. Executives who run companies that make shoes often get their own shoes for free—many wouldn’t dream of entering a Foot Locker or a DSW. They don’t have real data on the reality of going to the shoe store—the problems of price, of presentation, of missing sizes. Many car executives haven’t bought their own vehicle since entering the industry. What do they know about the world of their customers? Without this texture of experience, the data shoved before these executives’ eyes loses any truth. Context and color are absent; all that remains are abstract representations of the world rather than the world itself.

Simply put, the imaginations and intuitions of top leaders are starving. They have been living on a diet of desiccated facts and figures—thin data stripped of all its organic life. This diet may sustain them through periods of relative stability, but they will likely be headed off course when markets shift. In the midst of changing circumstances, it is vital to reconnect with the emotional—even the visceral—context of humanity. This is where thick data comes in.

3. The Savannah— Not the Zoo

Where do we go to get more thick data? We must start by studying humanity in the full complexity and beauty of the lived world. This is the basis of a philosophical method we will discover called “phenomenology,” or the study of human experiences. With phenomenology, we are observing human behavior as it exists in social contexts, not in abstract numbers. It’s the difference between watching a pack of lions hunt on the actual savannah and seeing them get fed from a bowl in the zoo. The lions are technically eating in both scenarios. Which one do you think holds more truth?

Take the question of love as an example. In 2012, “what is love” was the most searched query on Google. Helen Fisher, a biological anthropologist, offered an answer that received a significant number of hits. Based on fMRI results, Fisher and her colleagues concluded that “romantic love” is not an emotion, but a motivation system—an involuntary chemical reaction. We love because it incentivizes us to engage in relationships with potential mates.

That is what love looks like in the laboratory or the zoo, but Fisher’s explanation tells us nothing about how we experience love. Historians tell us that romantic love is really only a recent phenomenon. In ancient India, love was seen as dangerously disruptive to social structures, and during the Middle Ages, love was considered akin to insanity. What is love today? Thousands of divorce lawyers would argue against Fischer’s explanation of a motivation system. Insights about how love works are only possible by observing what people do and experience in the real world.

The methodology of studying human experience is not interested in what is extraordinary, but what is ordinary and common for all (or most) of us. It isn’t about the “r2,” or the significant sample size. In fact, a relatively small number of people and their situations will suffice. These experiences should be collected and understood in order to fully see the patterns of behavior we all share. It is a method that brings leadership in actual touch with the people they purport to serve.

Of course, I often hear executives in my world say that they want to help their customers, clients, or employees by finding their “pain points” or “unmet needs.” To me, these phrases still communicate an unfortunate distance. They are looking down at people and abstracting their experience from on high. If you want to truly understand the people in your world, you must engage with them at eye level. You must do what they do and see what they see. But even that is not enough. If you really want to understand something about a culture, the trick is to see its ghosts—its artistic heritage, its history, its customs. There is no better training ground for such a perspective than the study of human experience.

4. Creativity— Not Manufacturing

After spending time in the field and engaging with the humanities to better understand the world, how do we achieve actual insights through sensemaking? In which situations is it okay to use a hypothesis and test it out? When is it better not to have any preconceived notions at all? These are different ways of reasoning through a problem: a concern at the center of a centuries-old debate about the scientific method. In the late 1800s, American philosopher and logician Charles Sanders Peirce became famous for defining the three kinds of reasoning we use to solve problems—deduction, induction, and abduction—each one appropriate for different levels of certainty.

Deduction is often called top-down reasoning because it starts with a more general law or theory—a hypothesis—and then attempts to apply it in specific instances. “All women are mortal. Sally is a woman.” Therefore we can deduce: “Sally is mortal.” Deductive reasoning is useful for constrained problems with set boundaries, but it is unable to incorporate new information.

Inductive reasoning, on the other hand, is the exact opposite of deductive reasoning. It is bottom-up, so it starts with specific observations and then moves up into a theory. “Sally is a doctor.” From our observation of Sally, we can then add: “Sally just finished school.” And from there, we can infer an explanation or a theory: “Sally graduated from medical school.” But when you reason inductively, you have limited yourself to one set of beliefs—all well and good for certain types of problems with set knowns and unknowns—but no longer useful for problems involving culture and behavior. We can observe that Sally is a doctor and then infer that Sally went to medical school, but this framing might not be relevant or meaningful for the problem we are trying to solve. What if we are trying to understand Sally in a completely different cultural context: her world as a mother to small children, or her world as an active member of the local political scene in her town? In these instances, inductive reasoning will shut out possible insights before we even know the context of our investigation.

Peirce contended that only abductive reasoning—or nonlinear problem solving—was capable of generating new ideas. He defined this type of reasoning as a kind of educated guess, appropriate after observing phenomena with no set or logical explanation. Here is a simple example from a series of observations: A window is broken in the house; the jewelry box is missing; the furniture has been overturned, and there are clothes scattered everywhere. Through abductive reasoning, we make a leap into the most reasonable conclusion: The house has been robbed.

For Peirce, abduction was about looking for answers. While the previous few hundred years had been about the development of science and the belief that the industrial age could conquer anything, Peirce, in his First Rule of Logic (1899), questioned what we thought we knew. “Do not block the way of inquiry,” he said, and he outlined these following four offenses that we commit when we reason:

1. We make an absolute assertion that we’re right.

2. We believe something isn’t knowable because we don’t have the techniques or technologies to figure it out.

3. We insist that some element of science is utterly inexplicable and unknowable.

4. We believe that some law or truth is in its final and perfect state.

Peirce rejected the notion that any theory was “true,” while maintaining that it could be “near true.” In other words, he believed there was always room for improvement, and endless potential for new truths to emerge.

It’s easy to see why scientists would dismiss the idea that you cannot come to the end of something—that facts are not necessarily conclusive. We all want our work to contain some measure of certainty, and living in the constant shadow of doubt is unpleasant. Peirce speaks to this discomfort in his 1877 essay “The Fixation of Belief”:

Doubt is an uneasy and dissatisfied state from which we struggle to free ourselves and pass into the state of belief; while the latter is a calm and satisfactory state which we do not wish to avoid, or to change to a belief in anything else.

He ultimately argued that we hold fast to outdated and sometimes downright foolish ideas just to avoid staying in this “uneasy and dissatisfied state.” In other words, we often make really poor decisions just because it is so uncomfortable to do the hard work of thinking. And I don’t mean thinking in the deductive or inductive sense of the word—reasoning through a problem with a logical and linear set of steps. I mean the type of thinking that leads to all creative insights: filled with twists and turns, dead ends, and unexpected breakthroughs. Abductive reasoning is messy. It is extremely difficult for most of us to remain in this state of doubt for an indeterminate amount of time. But doubt is the only state of being that will open us up to new understanding. This is the real story of creativity.

5. The North Star— Not the GPS

We seem to live in an era of unprecedented complexity. Our world tells us that the pace of the seismic change occurring around us has rendered us incapable of seeing the big picture. Whether we are in the TV industry, attempting to navigate the emergence of streaming content providers like Amazon, Hulu, and Netflix, or medical practitioners barraged by an unending stream of often contradictory health studies, it is easy to accept these claims of overwhelming complexity. We want to throw up our hands and turn to the machines all around us: surely big data and algorithmic programming can make some sense of all of this. We, as humans, no longer can.

Allow me to surprise you: I believe that our world is actually no more complex than it has ever been, nor is it more incomprehensible. Yes, we have the Internet and the proliferation of wearable computing, but my grandmother experienced the destruction of two world wars, the discovery of penicillin, and the inventions of mass production, investment banking, and space travel. She lived through the agricultural revolution, witnessing mass starvation followed by a food system that now produces more than enough for everyone (when distributed intelligently). These are only a few of the innovations that utterly transformed her world during her time. Yes, we are living through change. Is it seismic? My grandmother would say, “Not really.”

Today’s world feels overwhelmingly complex because we are obsessed with organizing it as an assembly of facts. Big data makes us feel as though we can and should know everything there is to know on earth. But this is a fool’s quest, and it leaves everyone involved feeling depleted and lost. We are so fixated on staring at the oracle of the GPS that we have lost all sensitivity to the stars shining right above our heads. The tools of navigation have always been available to all of us. But we must take responsibility for interpreting them. This means executives need to be prepared to understand new and unfamiliar contexts—political, technological, cultural—and to interpret their place in our increasingly interdependent world.

Therein lies sensemaking’s greatest offering: it teaches us two essential things about leadership in an era of big data. To begin with, sensemaking can guide us in selecting an appropriate context for data collection. After all, the mere task of collecting data is meaningless in the abstract. What data do we collect? What for? How? It is impossible to study the world without some sort of paradigm for thinking about what you want to study.

Secondly, sensemaking shows us how to cultivate a perspective on how data fits together as an expressive portrait. Leaders must find a team who can use data to piece together a richly textured view of the world, in which resulting interpretations can add up to something greater than the data collected.

In this way, sensemaking teaches us where to put our attention. We don’t try to know everything; we work to make sense of something. In the midst of complexity, a sensemaking practice allows us to determine what actually matters.

The business of food products, for example, is not just about market entry plans, capital investment, and product positioning. It is about understanding how we, as a culture, sit in relationship to food. How we consume it; how we share it; what it means to us. Strategy is about finance but also about culture, people, emotions, behavior, and needs.

Instead of attempting to reduce the complexity of all of these layers of humanity—like a journey determined by the reductions of a GPS—the sensemaking practice follows the North Star. We learn to navigate through the rich reality of our world, developing a finely honed perspective on where we are and where we are headed. If algorithmic thinking offers us the illusion of objectivity—or a view from nowhere—then sensemaking allows us determine where we are. And, most important, sensemaking puts us in touch with where we are headed.

Before we can begin the journey, however, it is important to situate ourselves more specifically in the culture that vehemently advances the tenets of an algorithmic understanding of the world. Nowhere is this belief more widely held than in “Silicon Valley.” I write the name in quotes because I am not just referring to the strip of land in the southern San Francisco Bay Area. Silicon Valley is now an ideology, a mindset that values knowledge from the hard sciences above all other forms of knowing. Its cultural prerogatives have now seeped into every aspect of our modern life, including business, education, health care, media, and government. We cannot talk about the urgency of sensemaking without first making a stop to more fully dismantle the assumptions upheld in a Silicon Valley state of mind.