Harvard Business Review: An Anthropologist Walks Into A Bar
By Christian Madsbjerg and Mikkel B. Rasmussen, March 2014
In 2006 a major European brewing company we’ll call BeerCo was faced with falling bar and pub sales and, despite muscular market research and competitive analysis, couldn’t figure out why. Customers liked its core product, a standard lager, and store sales were up. But something wasn’t clicking in bars, and aggressive promotions weren’t helping. What was wrong?
Having exhausted conventional research approaches, BeerCo commissioned a team of social anthropologists to visit a dozen bars in the UK and Finland to find out. The anthropologists approached the project as if they were studying an unfamiliar tribe in Borneo. They immersed themselves in the life of the bars, simply observing the owners, staff, and regulars without any hypothesis about what they might find. They returned with 150 hours of ethnographic video, several thousand still photographs, and hundreds of pages of field notes. Over the ensuing weeks a team of managers from BeerCo sifted through the raw data together with the anthropologists, searching for themes.
In time, patterns emerged. Although BeerCo had thought that bar owners valued its promotional materials—coasters, stickers, T-shirts, and so on—in fact those items were at best underused, at worst treated with derision (in one bar, a researcher found them crammed inside a cupboard and labeled “box of crap”). The team also discovered that female servers felt trapped in their jobs and resented having to be flirtatious, an experience they referred to as being “hot pantsed.” What’s more, they knew very little about BeerCo’s products and didn’t want to know any more—and yet they were a primary channel for sales.
These findings and others led to a sharp shift in how BeerCo approached pubs and bars. Instead of bombarding them with one-size-fits-all promotional materials, it began customizing items for different types of bars and bar owners. It trained its salespeople to understand each bar owner better and invented a tool to help owners organize sales campaigns. It created in-workplace “academies” to train waitstaff about its brands and won over female servers by providing taxi service for employees who worked late. After two years BeerCo’s pub and bar sales rebounded, and both sales and market share continue to grow.
Most people in business associate the human sciences—anthropology, sociology, political science, and philosophy—with academia, and for good reason. The work of scholars in these fields is notoriously difficult to understand, and the insights they offer often seem to have little practical relevance in business.
But that is changing rapidly. An emerging method is dramatically shaping how businesses can apply the human sciences. This new approach is finding its way into the labs of technology companies such as Intel, IBM, and Samsung; the marketing departments of large consumer-product companies such as Adidas, Lego, and Procter & Gamble; global health care companies such as Novo Nordisk and Pfizer; and the thinking and writing of business leaders and new breeds of consultancy that, like our own, merge hard and soft sciences.
According to a recent global study of 1,500 CEOs conducted by IBM, the biggest challenge those CEOs face is the so-called complexity gap. Eight out of 10 expect the business environment to grow in complexity, but fewer than half feel prepared for the change. The research also reveals that CEOs see a lack of customer insight as their biggest deficit in managing complexity. They prioritize gaining customer insight far above other decision-related tasks and rank “customer obsession” as the most critical leadership trait.
Accordingly, many companies are turning to customer research that is powered by big data and analytics. Although that approach can provide astonishingly detailed pictures of some aspects of their markets, the pictures are far from complete and are often misleading. It may be possible to predict a customer’s next mouse click or purchase, but no amount of quantitative data can tell you why she made that click or purchase. Without that insight, companies cannot close the complexity gap.
In the rush to reduce consumers to strings of ones and zeros, marketers and strategists are losing sight of the human element. Consumers are people, after all. They’re often irrational, and they’re sometimes driven by motives that are opaque even to themselves. Yet most marketers cling to assumptions about their customers’ behavior that have been shaped by their organizational culture, the biases of the firm’s managers, and, increasingly, the vast but imperfect data stream flowing in.
The human sciences approach is a radically different way to understand customers. It starts by examining the roots of their behaviors—the complex interplay between their interior lives and their social, cultural, and physical worlds. It digs deep for insights that elude more-traditional business tools. This nonlinear process, which we call sensemaking, reveals the often subtle and unconscious motivations informing consumer behavior and can lead to insights that enable transformations in product development, organizational culture, and even corporate strategy. As we will see, sensemaking and the tools of human science are at their most powerful when helping businesses address novel problems, or “big unknowns,” in unfamiliar social or cultural contexts, such as new geographical markets or new generations of consumers. They can also be highly revealing in cases where current markets or consumers have begun behaving in unexpected ways.
How to Identify the Big Unknowns
Many business problems are technically complex, but managers fully understand them, know what data they need to address them, and have a well-defined process for moving forward. Big unknowns, in contrast, are highly unfamiliar business problems. The less familiar you are with a given type of problem, the market, and the customers, the less relevant the conventional research toolbox becomes and the more relevant human science and sensemaking become.
Sensemaking has particular value when you want to understand unfamiliar social or cultural contexts—new geographical markets, for example, or new generations of consumers—or when your assumptions about your current customers seem to be misguiding you.
The diagnostic below, which sorts business problems into three categories, can help you determine what type of problem you are facing—and, therefore, whether sensemaking might apply. Managers commonly mistake level-three problems (big unknowns) for level-two ones (hypotheticals) and consequently often fail to use sensemaking tools when they’re needed.
Level 1: Knowns
You have a high degree of familiarity with the customers and the market.
You have a clear view of the future.
You know exactly what the business problem is.
Conventional data and analytics can help you solve it.
Example: Holiday sales of our product are below target because of weather-related low customer volume in stores. If we boost TV advertising by X and discount by Y, sales will rebound.
Level 2: Hypotheticals
You are moderately familiar with the customers and the market.
You can envision a range of possible outcomes.
You have a feel for the problem and have seen something like it before.
You can frame a set of hypotheses to test.
You are familiar with the sources of data and the analytical model you need to find a solution.
Example: Our per-store sales are down even though we have invested in more salespeople. There are several possible explanations, and we can come up with ways to test them.
Level 3: Big Unknowns
You are highly unfamiliar with the customers and the market.
You have little sense of likely outcomes.
You have not seen this type of problem before.
You have no hypotheses to test.
Your usual sources of data and analytics will not clearly help you find a solution.
Example: Our innovation pipeline is full, but our launches are not creating growth.
Sensemaking in Action
At the core of sensemaking lies the practice of phenomenology: the study of how people experience life. Management science can tell Starbucks, for example, how many cups of coffee its customers will drink in a day; phenomenology reveals how those customers perceive the coffee experience. Starbucks has famously leveraged its understanding of the phenomenology of coffee, profiting from customers’ willingness to pay a premium for the often subtle and complex Starbucks experience—the hip baristas, the community of telecommuters, the crafted playlists—as distinct from the coffee itself.
Consider how the Lego Group used phenomenology to understand its customers’ deepest motivations. Eight years ago Lego had lost touch with its core customers and was bleeding cash; today it’s one of the largest and most respected toy makers in the world, the result of a remarkable turnaround driven in part by its commitment to sensemaking.
The company’s downward spiral was propelled by its determination to leverage the brand and move into new markets rather than to understand what its customers—young builders and their parents—really wanted from play with its products. Acting on mistaken assumptions, Lego branched into action figures and video games, believing that kids, increasingly scheduled and often distracted by faster-paced electronic games, no longer had the time or patience for its old-fashioned plastic bricks. So Lego products got a lot cooler and more aggressive looking, but they also required less time and creativity from the kids playing with them. Meanwhile, parents’ nostalgia for the old Legos began to dissipate, and with it their impulse to buy the bricks.
CEO Jørgen Vig Knudstorp understood that customers had lost their connection with the brand and that new product lines weren’t the solution. He realized that Lego needed to better understand the phenomenon of play. What is children’s experience when they play, what do they desire from it, and how could Lego serve that need?
To find out, the company embedded researchers with families in the United States and Germany. The researchers spent months collecting data, interviewing parents and children, creating photo and video diaries, shopping with families, and studying toy shops—in short, amassing a vast store of information. As the Lego team methodically sifted through the data, key insights began to emerge. Among them was that children play to escape their overly orchestrated lives and to hone a skill.This insight exposed the false assumption that kids were too busy to engage with Legos. In fact, it emerged, a subset of children have both the time and the desire to commit to the bricks and want to achieve mastery.
As Paal Smith-Meyer, then the head of Lego’s new-business group, explains, “Now we are making products that are proud of being Legos. If you look at a box, you know it’s Lego. You can’t force someone to play with the bricks. The research allowed us to make a decision about whom we wanted to reach. It was a decision that grew into a mantra: We’re going to start making Legos for people who like Legos for what Legos are.”
This was a game-changing insight that conventional strategy processes—market data analytics, conjoint analysis, surveys, focus groups, and so on—had missed and probably could never have provided.
The Sensemaking Process
To illustrate the stages of sensemaking, we’ll turn to a very different sort of company—a Danish medical technology firm. Coloplast was launched in 1954 when a nurse named Elise Sørensen watched her sister recover from an ostomy, a operation often performed on patients with cancer of the stomach or the colon. Although the procedure was a lifesaver, it left Sørensen’s sister ashamed of and socially isolated by the resulting stoma—a hole in the stomach for the discharge of waste. She dreaded leaving the house for fear that her homemade stoma bag—all that was available at the time—would leak. Sørensen devised an ostomy bag with an adhesive ring to hold it in place, and a business was born.
Five decades later Coloplast was a market leader in health care products in Europe and had been rated by patients as the world’s most patient-centric health care company. But by 2008 its biggest division, the ostomy division, was stagnating, even though the company was investing heavily in innovation and sales.
Coloplast was known for sophisticated R&D, and it had done everything fashionable in the innovation playbook: lead-user studies, user co-creation, design-thinking workshops, NPV calculations, and so on. The product pipeline was full, but product launches weren’t getting any traction. It was mysterious. Focus groups and large quantitative surveys had uncovered numerous annoyances encountered by ostomy patients, and scores of product ideas had been advanced to address them: better locking mechanisms for attaching bags, new adhesives, new filters, new materials. Yet none of this innovation was driving growth.
Coloplast’s leaders realized that something must be wrong with their fundamental assumptions about the ostomy market—beliefs that had guided them successfully for years. The company faced a big unknown: How could it find new sources of growth? The five-step sensemaking process provided the answer.
How to reframe a problem as a phenomenon
“Human scientists” base their research questions on phenomenology—the study of how people experience life. The goal is to understand the complex, subtle, often unconscious ways in which people interact with their surroundings.
Consider how a chef interacts with a kitchen, his fellow cooks, the waiters, the food, the guests, and myriad other aspects of his environment. Most of his interactions are below the level of consciousness. He opens the fridge with his right hand, yells in a certain tone to the waiters, and uses another tone with the cooks. He doesn’t measure the amount of pepper he puts on the meat, but he knows exactly how much is right. He tastes the sauce with his little finger and instantly knows just what it needs. He would be unable to accurately report on these moment-to-moment behaviors. To see patterns in them, you’d have to observe him closely.
If you’re in the restaurant equipment business and sales are inexplicably down, you probably won’t learn much by asking the chef if he likes this or that product. But if you frame the problem as a phenomenon—what is the chef’s experience of cooking?—you’ll have a better chance of uncovering his true needs.
Almost any business problem can be framed as a phenomenon. The trick is to shift your perspective from inside out (how the business perceives the problem) to outside in (how customers perceive it). For example:
Business Problem: How can our bank reduce churn?
Phenomenon: How do our customers experience banking, and why are they leaving?
Business Problem: How can we create a premium offering in coffee?
Phenomenon: What is a good coffee experience?
Business Problem: What should be our go-to-market approach for toys in China?
Phenomenon: What is the role of play in China?
1. Reframe the Problem
Sensemaking starts with learning to think of a problem as a phenomenon—that is, to see it in terms of human experience. This conceptual shift requires companies to stop looking at the market, the product, and the customer from their own perspective and examine the customer’s perspective instead. (See the sidebar “How to Reframe a Problem as a Phenomenon.”)
Thus, Coloplast recast the question “How do we capture new sources of growth?” as “What is the experience of living with ostomy?” Its managers knew a lot about customer metrics—who bought how much of which products when, and so forth. But they realized they knew less about their customers’ worlds. What was it like to be an ostomy patient? How did it affect your self-image? Your social life? What was a good day, or a bad day?
The company’s product development and marketing strategies had been driven by two assumptions about customers and their needs: that within two years of leaving the hospital, people had their ostomy care under control and were living essentially normal lives; and that product innovation should focus largely on improving the various features of an ostomy bag, one by one.
Clearly something was amiss with these assumptions. But what?
2. Collect the Data
Because data collection in the sensemaking process is explicitly designed to challenge assumptions, it differs fundamentally from conventional analytics and research approaches. Rather than administer a hypothesis-driven survey, run big numbers, or conduct carefully scripted focus groups, researchers engage in the lives of their subjects. Crucially, they approach the research without hypotheses, gathering large quantities of information in an open-ended way, with no preconceptions about what they will find. Only through such unprejudiced data gathering is it possible to divine the customer’s true experience.
The resulting data set is raw, personal, and firsthand—not the distorted version of reality that most market research tools produce. This eye-opening feed can be tremendously inspiring for business leaders used to thinking about their customers as abstractions—as segments, need states, or consumption occasions.
The sensemaking approach can be inspiring for business leaders used to thinking of customers as abstractions—as segments, need states, or consumption occasions.
Under the direction of Kristian Villumsen, Coloplast’s senior vice president of marketing at the time, social science researchers were dispatched all over the world to spend two days with ostomy patients, observing them with their friends and families, on the street, and, perhaps most important, when trapped at home because of anxiety or embarrassment about their condition. In addition, the researchers spent a day with stoma-care nurses in order to understand the way they choose products for their patients, how they prepare patients for discharge, and their concerns about patients’ ability to manage at home. The raw data were delivered to Coloplast in the form of carefully organized videos, diaries, photographs, field notes, and artifacts such as brochures and packaging.
Although this open-ended data collection casts a very wide net, it is a disciplined and structured process that needs to be overseen by human scientists skilled in research design. Essentially, it requires identifying key themes underlying the phenomenon (that is, the experience being examined) and dividing each one into a series of questions.
The phenomenon of how people experience living with ostomy can be broken down into themes including:
How does a stoma impact everyday life?
How do patients plan their everyday lives?
How do patients, nurses, and doctors variously perceive quality care?
What are patients’ and caregivers’ aspirations for care?
What are patients’ care routines?
What are patients’ crucial needs and challenges?
What are the key decision processes when choosing products and accessories?
With a set of guiding questions established, it’s fairly straightforward to determine the most effective methods of gathering relevant data: direct observation, participation in subjects’ activities, in-depth interviews, group interviews, video recording, and so on. As with any analytical process, data gathering and structuring must aim at making the information in each stream easy to compare. Data also must be organized and stored to facilitate simple searching and sharing—for instance, by coding information according to media types, geographies, and even individual study subjects.
3. Look for Patterns
At the end of the collection phase, the Coloplast team had a database consisting of 2,000 photos, hundreds of pages of field notes and interview transcripts, and two gigabytes of video. But without analysis, of course, data collection is just plain reporting.
The team therefore structured the data so that it could do deep dives into the life of every subject and also resurface to consider broader themes and the “families” within them (such as strategies to avoid accidents, or hygiene at home, at work, and during recreation). This allowed it to connect dots and reveal patterns.
The key to uncovering patterns is to find root causes—in this case, the fundamental explanations for patients’ and nurses’ behavior. The process is like peeling an onion. The outer layer contains directly observable facts, such as how often patients change their bags and what inconveniences they experience while doing so. The next layer contains the habits and practices informing patients’ behavior and choices. And finally there is the center—the underlying causes of those habits and practices.
Insights embedded in the inner layers are not directly obtainable; they emerge as patterns are discerned in the observations. To get to this deeper level of analysis, the Coloplast team applied a range of social science theories about how a chronic disability affects identity, how social stigma builds up, and the roles of hygiene, sexuality, and trust. This helped it see the data from various angles: Could social stigma explain why patients avoid going out? Do patients have different standards of hygiene at home and elsewhere? How are patients’ sex lives affected? What happens to a person’s identity when she comes home from the hospital as a chronic patient?
Along with trained researchers, Villumsen and his colleagues steeped themselves in the data sets and in their subjects’ lives. They saw that some patients were frustrated, whereas others spoke of shame or embarrassment or of awkwardness with a romantic partner. Many mentioned that horrifying moment—at a wedding, at a business meeting, in class—when they realized they had a leak.
As it repeatedly returned to the phenomenon—what is the experience of living with a stoma?—Coloplast started to understand the effects of differences between care in a clinical setting and care at home. It had known that when patients were in the hospital, they were often lying down, they were surrounded by experts, they might be below their normal weight because of their cancer, and they were focused almost entirely on stoma care. But the company had never realized the implications. When patients went home, they were usually without expert assistance. They had to contend with challenges related to how their bodies had changed: Some had scars, some had sagging skin from lost weight, some had regained weight so rapidly that they were now obese, and many had hernias developed after coming home. The solutions and routines established in a hospital setting made less and less sense as time went on. The products chosen with the nurse in the hospital fit less well, the treatment regimen was more complicated, and issues around leaks started to crop up.
Indeed, Coloplast realized that the problem it believed it had largely solved—leakage—in fact remained a formidable, life-altering challenge. The company had misinterpreted the findings of its conventional research, concluding that because patients generally stopped complaining about leakage after a while, the problem no longer existed. The pattern-recognition process revealed that the complaints had dropped off not because the problem was solved but because people had radically adapted their lifestyles to avoid the risk of accidents, accepting that their new lives were, in the words of one patient, “probably as good as it gets.”
In reality, the sad, recurring pattern looked like this: After the initial shock of surgery, returning to everyday life was hard, but patients tried to resume their social lives—going out for dinner, going to the movies, seeing friends. After the first leak in public, however, they started to map their environments for private places where they could address accidents. Soon they stopped exploring, limiting themselves to environments they knew well. After a few more leaks, they limited their lives even further: no more restaurants or other high-risk places. Within two years many stopped going out altogether. So although patients had, in this way, achieved some measure of control over the issue—and hence no longer complained about it—they had lost the richness of their lives in the process.
4. Create the Key Insights
Only when Coloplast’s managers discovered that leakage persisted and had such profound effects on quality of life did they begin to seriously question their core business assumption—that the company’s innovation focus on polymer and adhesive technology had largely solved the customers’ main problem.
Returning to the data with a new lens, the team asked, “What are we missing?” It looked for gaps between the industry’s assumptions and patients’ experiences. This time, too, as it sifted through the data, a theme began to emerge. In interviews and videos, many nurses observed, “There is no perfect product, because there is no perfect patient” and “It’s a good product, but it’s not right for everyone.” In parallel were comments from patients about the struggles they sometimes experienced securing their bags. No matter how high-tech the polymers and adhesives, many patients just couldn’t get a reliable fit. They tried all sorts of homemade solutions, experimenting with accessories such as rings, paste, special glues, and creams to protect the skin from leakage.
As the team went back through the data, a game-changing insight emerged: Stoma patients’ bodies are all so different that no single solution exists. The main challenge wasn’t the type of stoma a patient had—it was the type of body a patient had. That might seem an obvious point, but Coloplast’s innovation process had blinded management and R&D engineers alike to the possibility. Just as individuals can suffer from confirmation bias (a reflexive seeking of only information that supports an existing position), so can entire organizations.
Just as individuals can suffer from confirmation bias (a reflexive seeking of only information that supports an existing position), so can organizations.
Coloplast’s adhesive worked perfectly well on a perfectly fit and uniform body. But the manifold changes in patients’ bodies—whether scars and bumps from surgery or weight shifts from cancer—badly compromised fit.
This was a major problem—and, incredibly, no one in the billion-dollar industry had addressed it. It immediately became clear that Coloplast needed to categorize body types and create products designed specifically for each one. Nothing in its pipeline—nothing in anyone’s pipeline—came even close to accomplishing this. The business potential was huge.
5. Build the Business Impact
Insights, of course, must be translated into initiatives. While steps one through four introduce executives to the sensemaking process and therefore are typically new, the final step calls for business leaders to do something familiar: build innovation strategies.
Coloplast invited thousands of customers to submit photos of their bodies in various positions and used the photos to identify four basic body types. The “Fit to Real Bodies” study had direct implications for all the company’s business divisions. R&D needed to invent new technologies; manufacturing had to develop new tools; marketing needed to create a compelling story; sales had to sell a new type of product; and customer service had to build a patient-support system.
The BodyFit product line, introduced in 2010, has been a resounding success, both as a solution for patients and as a business. The two product families within it to date have met their commercial targets, and further innovations are being launched in 2014. Coloplast’s ostomy business is now growing faster than the overall market for ostomy products.
The BodyFit project, along with similar initiatives in other divisions, has also energized the company culture. Employees from R&D to sales have a renewed sense of purpose and a more innovative spirit, animated by the shift from a technology- to a customer-driven focus and the demonstrable impact of the new product lines on customers’ lives and the company’s fortunes. Companies have long used ethnographic tools in market research. The innovation in sensemaking is less about the research technique than about the human-sciences-based analysis. A growing number of organizations globally have begun to apply sensemaking, having recognized that it can help solve some of the toughest business problems, such as finding new growth, winning in new markets, and capitalizing on cultural change. Sensemaking reveals answers that conventional tools can’t, and it enables business leaders to think creatively about what business they are really in.
This article originally appeared in the Harvard Business Review.