Lies are an important source of design insight. Design research ought to embrace lies as potential sources of creative inspiration. Lies are indicators of a gap between what we are and what we think we ought to be. Well-designed products soften and assuage the effects of this gap.

Photo courtesy of: www.flickr.com/photos/lwr/213108466

The other day, one interviewee asked me, near the end of the interview, what “is this all about.” At first I was confused, having explained the study we were conducting and what specifically we were interested in finding out. Yet she pressed me further, wanting to know the “mystery” behind the study.

I reflected and realized that she was expecting a great “reveal” of the “real” purpose behind the study. She was expecting me to pull back the curtain and tell her what I was actually interested in.

If you have ever participated in a university psychology study, this story will sound familiar to you. You had likely been recruited as an undergraduate, incented to participate with the promise of a few percentage points tacked onto your final grade.

Or perhaps you attended a focus group, which had a one-way mirror at one end of the room that you were directed to “try to ignore.” Or maybe you have answered a telephone survey that had a mysterious combination of questions the meaning of which you could not decipher.

Perhaps you, like my participant, have been conditioned to believe that “unbiased” or “scientific” social research involves trickery or outright deception. Proponents of this approach may argue that in order to get “the truth,” researchers must mask their true intentions, lest participants lie. This kind of research seeks to sanitize the results, to make them somehow untainted by “bias.”

What underlies this idea of deception and lying in social research? There is an assumption that The Truth is something that lives within the minds of your participants and your job as a social researcher is to pry that nugget out of their minds. Your job is to eliminate any “bias” that would filter this truth.

This is the same assumption ethnographers make when they believe a year’s fieldwork is essential. The classic anthropological model is a one-year field assignment. But ethnographers who hold this view are actually similar to market researchers who assume participants may “lie.” They are hoping to establish “rapport,” so that participants will eventually “drop their guard” and show the ethnographer their “true” or “authentic self.”

But if you assume that the truth is something we create, in tandem with our participants, authenticity or truthfulness become irrelevant concepts. Instead, a researcher can assume participants do indeed lie, but that lying is an interesting data point. The savvy, design ethnographer can ask, “Now why did she lie about cleaning her oven weekly, when she clearly hasn’t cleaned it in months?”

This is not a clean stove

These kinds of questions can lead to interpretive gold.

Perhaps oven cleaning is considered “proper,” and women are encouraged to act “properly” by cleaning their ovens regularly. Perhaps a better-designed stove looks “clean” on its exterior, whether it is actually clean inside or not. Perhaps a better-designed stove provides women with mechanical “excuses” of why it should NOT be cleaned regularly, thereby absolving its owner of any shame.

Both design solutions assuage the guilt and the shame of having not lived up to a perceived norm.

Indeed, the Swiffer provides exactly this kind of “cover.” Hardwood floors are supposedly “different” than regular floors and require a “different” kind of broom and mop. It just so happens that the Swiffer is faster, more ergonomic, and less messy than a regular broom. It requires less effort, yet Swiffer uses are told they are doing the “proper” thing by using this “special” kind of broom.

When you are hunting for design solutions, become a lie detector. Do not question the veracity of a participant’s statement, but go deeper. Why did he say that he “tries to not be the dad on the cell phone”? What ideal is not living up to?

Design interventions based on lies could promise to be the most user-accepted designs.

Yesterday, I attended Roger Martin’s presentation of his new book, The Design of Business, hosted at the Ontario College of Art and Design. Roger gave a brief overview of his book and then engaged in a dialogue with the host, Michael Dila, and members of the audience.

Roger explained that some organizations are better able to embrace “design thinking,” which he defines as the ability to think both analytically and intuitively. He pointed out in his presentation and in his book that 20^th century corporations have perfected the analytical frame of mind, but fail continuously to embrace the abductive leaps of logic that innovation requires.

Audience members repeatedly asked how to equip their organizations to embrace design thinking. Roger advised designers to “empathize” with their analytical peers, and business managers to “empathize” with their intuitive colleagues.

I can’t help but be reminded of the world’s most ineffective coaching in John Cusak’s movie Better Off Dead. Cusak’s character is attempting to win a ski race to impress his love interest. His hapless friend Booger offers this useless advice, “Try to ski…faster.”

Roger’s advice fell short because he could not explain the social dynamics of organizational change. Just like Booger, he simply described; he failed to explain.

Explaining Organizational Change: Innovative Values

One woman in the audience asked specifically what cultural traits design-thinking organizations exhibit. Roger suggested vague ideas such as a concern for the future. The Value Orientation Model can specifically identify value systems that are, yes, future oriented, but have four other qualities that support innovation. Anthropologist Florence Kluckhohn argued that all cultures can be understood in terms of five major values. I have adapted this model to show the groupings of organizations. Innovative organizations, surprisingly, embrace “static” values, thus allowing the free floating of ideas.

Figure 1: The Value Orientation Model

Adapted from Kluckhohn, F. R. (1953). Dominant and variant value orientations. Personality in Nature, Society and Culture. . J. a. K. Murrayh, F.R. New York, Knopf: 346.

Being future oriented can be conducive to innovation, as Roger indicated. But if an organization obsesses over its future state, it may have difficulty focusing on tasks at hand. This future orientation is not enough, particularly if the organization prizes “doing” over “becoming.”

Take, for example, “the productivity myth,” which Tony Schwartz explores on Harvard Business Review’s blogs. He complains that writing and responding to ever more emails does not add value – yet it appears to be “productive.” Organizations that consider emails “productive” have a “doing” orientation, instead of a “becoming” orientation. An organization must prize both the future and the process of “becoming” in order to be innovative.

Moreover, this organization must trust its employees. If the organization’s culture implicity believes that “man is born bad,” then it will not provide employees with the freedom and autonomy they need to be innovative. Roger argued Taylorist management styles of command and control have outlived their usefulness. I would agree with him. However, I would argue that no company that believes its employees will “steal time” from the company can ever truly forsake Taylorist principles.

Take, for example, WalMart, which was recently named one of Businessweek’s top 50 innovative companies. Its innovation, according to Businessweek, is its razor thin supply chain and cost-conscious green practices. Does this mean WalMart is innovative? No, it means it is cost-conscious. WalMart will never get out of the business of selling cheap goods at the lowest prices because it does not trust its employees to be autonomous. Individual store managers cannot begin selling locally-targeted goods because they are not trusted to experiment. WalMart will never design an iPhone; it will only figure out how to sell it more cheaply than anyone else.

Roger’s book explains design thinking well, but he only describes how it plays out in real organizations. In order to understand how design thinking is adopted, one must have a sociological lens on organizational change – and that means understanding the nature of socially defined values.

Designing Design Thinkers

Organizational change is notoriously difficult to effect. Management consultants have tried it, now designers are trying it. Building on Roger’s description, and offering my explanation of the underlying value system, I now offer an application designing a design-thinking organization.

1. Map your values: understand what values your organization prizes by doing an audit of the “good worker.” What do people say a “good worker” is? Rosabeth Moss Kanter used the “good worker” rubric to explain how women faced subtle discrimination in her classic Men And Women of The Corporation. When you know how your organization thinks, you’ll know what it values.
2. Create value goals collectively: decide as a group what values you would like to embrace. This means more than crowdsourcing. This means hosting open dialogue meetings where the only expected outcome is a discussion. Voting will help, but only after you have face-to-face discussions.
3. Use art: community theatre, interactive installations, and performance art have transformative properties. Encourage members of the organization to describe their experiences through comedic skits at meetings, collaborative and humorous art projects that can displayed in main areas. Art speaks truth. Knowing your organization’s values requires truth telling — and it especially helps if you laugh a lot.
4. Embrace “Static Values” when you can: In her incredibly insightful article on innovation, Carol Steiner argues that innovators reject established ways of thinking, Unfortunately, deeply trained scientists, managers, and social scientists spend so much time learning established ways of thinking, they forget to be open to new ideas. Be open, she argues, but simply BEING.

I was recently invited to speak at Ottawa’s Social Media Breakfast. The organizers, Simon Chen, Rob Lane and Ryan Anderson, asked me specifically to bring a sociologist’s understanding to social media. Below is my presentation. For the full version, with the notes, visit the full slideshare version.

My essential argument for the presentation was that we don’t have enough deep understanding of “the social” in social media. Social media gurus abound these days, but too few of them actually understand social theory. Sociologists have been thinking about and researching social interactions for over a century. Just because we are now using the Web doesn’t mean those essential insights are no longer valid. Quite, the contrary, I argue. Social theory is even more relevant today because it coheres and synthesizes design and marketing research. We need social theory to provide some weight, some shape to what we learn about social media use.

As an aside, I notice “social business” is an emerging buzz word. All business is social. Those who argue “social business” is new are missing the point; we have only just begun to realize social interaction is fundamental to business, in part because we have begun to engage in empathetic research projects such as ethnography. When you do quantitative surveys, for example, it’s incredibly easy to dismiss the real impact of your business policies on your customers or employees. But when you hang out with your employees and hear candid feedback about how you’ve organized your business processes, it’s impossible to ignore the social impact (Undercover Boss is a great example of this phenomenon). “Social business,” then, is the effect of “taking on the role of the other” in your employee or customer research. It is not new.

But back to social media. I offer two social theories: social capital (Bourdieu) and dramaturgical theory (Goffman) to explain how we interact both on and off-line. Social networks are a source of wealth, says Bourdieu. Social interaction is a well-crafted play, says Goffman. I apply these theories to well executed, and not-so-well executed social media experiences.

Bourdieu understood our social networks to be a source of wealth. It’s what helps the rich get richer, he argued. Rich people know other people who can help them make more money or to keep the money they have. Sociologist Mark Granovetter found that in fact, it is the “weak ties” we have with our acquaintances that gets us jobs, for example. “Strong ties” with friends and family may enrich us spiritually but provide us fewer job opportunities.

Goffman had another framework for understanding social interaction: the theatre. Goffman believed social actors play roles when they interact. We have scripts, a wardrobe, a set, make-up, and a cast (or “team” as he called it). Embarrassment happens when the script slips. Imagine you must be both a manager, a father, a school buddy, and a cousin all at the same time. Embarrassing! This is what online social networks do to us everyday: they force us to play multiple roles at the same time. Good social media allows “audience segregation,” which lets us select which role to play when.

In the Q&A afterward, I mentioned a few pieces of social research that would help people understand social theory. The first is

McMillan, S. and M. Morrison (2006). “Coming of Age With The Internet: A Qualitative Exploration of How The Internet Has Become An Integral Part of Young People’s Lives.” New Media and Society 8(1): 73-95.

The second that is a wealth of information about social networking and online life:

Wellman, B. and C. Haythornwait, Eds. (2002). The Internet in Everyday Life. New York, Blackwell.

And finally, the original sources:

Bourdieu, P. (1986). The forms of capital. Handbook of Theory And Research for The Sociology of Education. J. G. Richardson. New York, Greenwood: 248.

Goffman, E. (1967). Interaction Ritual: Essays on Face-to-Face Behaviour. New York, Pantheon Books.

Few would disagree that fundamental economic change is upon us. Business models are crumbling daily. From the auto industry to the banking industry, it is clear that old ways of doing things are no longer working. The market research industry is just as vulnerable to this shift, yet, like the auto industry before it, it is hardly aware of how deeply its business model is threatened.

The Long Disruption

The market research industry is built for the 20^th Century mass production model, which is rapidly disappearing. The “mass audience” is gone and a fragmented diverse populace has taken its place. This new “audience” defies the easy aggregation of summary statistics on which market research so often relies.  Chris Anderson of Wired figured this out long ago with his book The Long Tail.

The Economic Disruption of The Long Tail -- Anderson, Wired Magazine

He argued that technology lowered the cost of providing services to ever-smaller niches of people, making it possible to sell profitably goods and services that were once too specialized.

This technological shift also means the end of “appointment television.” Digital video recorders allow individuals to time shift their programming to suite them, and not the program executives at television networks.

The Birth (And Death) of Market Research

What does this all have to do with market research? Full-service market research firms are built for the blockbuster era, not for the time of the long tail.

Market research was heavily influenced by the school of “applied sociology,” lead by Paul Lazarsfeld. While at Columbia, Lazarsfeld pioneered many statistical techniques we use today, including the cross tabulation (Babbie and Benaquisto 2002) and the Lazarsfeld-Stanton Analyzer, a machine that records audience reaction to programming in real time (Mattlerart 1996).

The Lazarsfeld-Stanton Analyzer summarizing "the public"

CNN used a variant of this machine for the recent State of The Union address, showing real-time reactions from Democrats in blue, Republicans in red, and Independents in yellow.

The Lazarsfeld brand of insight is based on a fundamental assumption: that the “average” means something. An entry-level statistics course will teach you that average is dragged up or down by extreme values, and the long tail is nothing if not a collection of many extreme values. There is nothing meaningful about knowing that the “average American” rented 30 digital movies a month if, in fact, there were many thousands of Americans who rented none and a many tiny segments that rented somewhere between zero and 40 movies. The “average” is meaningless in this example, yet this ham-fisted approach to summarizing “the public” is what the market research industry is built upon.

Design Research for The Long Tail

Market researchers may argue that with proper segmentation, you can understand every niche within the long tail. This may be true, but to truly understand the diversity between people, your task is not simply to “summarize” the audience, but to delve deeply into the dynamics of what makes them different.

This is why design research is a better fit for today’s long-tail economic model. Context matters. Design research is all about understanding the context because it is rooted in qualitative methodologies, and ethnography in particular. Designers solve contextual problems. The award-winning Braille watch, for example, allows its users to check the time surreptitiously and quickly, something that is both polite and useful. A Lazarsfeld approach would not uncover the social subtleties of checking one’s watch, and certainly could not uncover the specific needs of the blind.

The Braille Watch by David Chavez

Dan Formosa details this limitation of market research in his insightful article in Interactions magazine. He argues that market research should focus on consumer response — after a product is designed. Design research, on the other hand, is about evaluating a product as it is being developed. I would go further; design research is about knowing what to build as well as evaluating the prototype.

Design research uncovers how long-tail niches develop and what differentiates them. It is not the equivalent to “market segments” because it provides specific direction on how to apply research findings. What are the dynamics of renting a movie? What motivates the “heavy renter”? What is it about her television or home that supports heavy renting? You cannot know the answer to these questions by simply providing a laundry list of demographic characteristics and psychographic survey results. You must know the context in which the long tail emerges.

Some may say that good quality market research would not make these kinds of mistakes. And they are right. Highly skilled social scientists are method-agnostic; they choose the right method for the right research question. However, full-service market research firms have become the GM of the industry — they keep building Hummers instead of Priuses. Focus groups don’t uncover contextual nuances, but they’re cheap and profitable. Surveys don’t get to the heart of why a product doesn’t work. Design research, using an ethnographic approach, provides “thick description” of the entire phenomenon of renting movies.

This is where market research cannot go. And this is where market research will fail, unless it rejects the “build another Hummer” mentality.

References

Babbie, E. and L. Benaquisto (2002). Fundamentals of Social Research. Scarborough, Thomson Nelson.

Mattlerart, A. (1996). The Invention of Communication. Minneapolis, University of Minnesota Press.

Designing an innovative organization doesn’t necessarily mean a “flat” organization. We tend to believe that innovation and hierarchy are antithetical, but in truth, innovation often thrives in hierarchical organizations. Here are the key ingredients to an innovative organization, whether hierarchical or not.

The Internet: A Democratic Utopia We tend to believe that hierarchy kills innovation and creativity. This is particularly true for organizations that design and build technology. The cultural heritage of the Internet is one that implicitly values a utopian vision of anti-authority.

The initial plans for ARPANET explicitly included a commitment to the open architecture concept, with “no global controls at the operations level” (Leiner, 1998). In other words, those that designed the Internet designed it explicitly to have no central authority.

Stickin' it to The Man

This decentralized structure connoted a sense of democratic administration. The hacker ethic has reinforced this implicit belief in democracy. In his 1984 book Hackers, Steven Levy (Levy, 1984) traced how the “laid back” culture of universities, such as Stanford’s Artificial Intelligence lab, spread to other technology start-ups. Technological innovation came to be culturally synonymous with an explicit rejection of hierarchy.

The Innovation World Is Not Flat But this is cultural myth of “democratic” innovation is merely a representation of innovation, and not a necessary ingredient for it. Take, for example, Apple Inc. Apple’s legendary innovative reputation is not contingent on democracy – far from it. Indeed, it appears that Steve Jobs and his senior leadership team have a iron-grip of control over innovation projects. This hierarchical order is ironically represented as democratic, a fact that The Onion happily lampoons in “Apple Employee Fired For Thinking Different.”

The reality is that large organizations in today’s global economy require some form of hierarchical control. This is a requirement of both capitalism and the sheer scope of modern corporate life. Alfred Chandler (1977) showed how the growth of the railroads required detailed project management, making 20th century management both rational and hierarchical. 21st century management must grapple with the same issues of synchronizing the schedules of employees across multiple time zones, and grappling with constant changes in the competitive landscape and the economy. “Democratic” innovation is messy, time consuming, and difficult to manage. For this reason, many companies like Apple have created controlled environments in which innovation can occur.

Innovation Within A Hierarchy If your organization is hierarchical (and in most cases, that will be true), there are features of innovation that can be embedded within this hierarchical system.

Creating Flow Through Non-Time Measurement:

Clocking in at Creativity Inc.

Innovative teams are those that are insulated from time-based metrics of productivity. Working for one hour on a rote task is not equal to working for one hour on a groundbreaking project, yet oftentimes organizations treat these hours as exactly the same.

My research on time in interactive agencies found that time-based metrics frequently interrupt “flow,” making it difficult for designers to work creatively. Organizations that want to optimize creativity must abandon time-based metrics of performance.

Stop Lying About Democracy: rare is it today that an individual truly doubts the need for some form of hierarchy in a profit-seeking company. But pretending that hierarchy doesn’t exist is corrosive. Organizations that continually fail to live up to their democratic ideal must continually tell lies to mask this gap. Over time, this gap renders real democracy meaningless (after all, the Bullshitter cares nothing for the truth).

Ruthlessly Commit To Project Resources and Timelines: many people are familiar with the agile development notion of the “sprint.” A group of people are dedicated exclusively to a software project for a specific, discrete period of time. Their attention is devoted completely to this project and they are enormously productive as a result. Why do innovation project often fail? Simply because individuals are pulled in too many directions or senior leadership changes priorities, seemingly on a whim. If you mean to combat the negative aspects of hierarchy, then you must commit to a project and let nothing get in the way. Individuals must be dedicated. The project length must not be shrunk. And collectively, the organization must stake its reputation on this commitment.

Be Democratic When It Matters: creative people can take direction, even when it infringes on their work. But they must have a say in what infringements are negotiable. The biggest mistake managers can make is assuming that the bounds of hierarchy is understood equally by everyone; they are not. Accept that democratic rule can and should happen, even when it affects timelines. Be unfraid to collectively identify what is negotiable and what is not. Most people do not question the legitimacy of authority, but they do question the legitimacy of lack of debate. In the end, innovation can occur in hierarchical organizations. The democratic ideal provides an aspirational model but don’t be afraid to accept that it is an ideal, at times.

References

Chandler, A. D. (1977). The visible hand : the managerial revolution in American business. Cambridge, Mass.: Belknap Press.

Leiner, B. e. a. (1998, Februrary 20, 1998). A Brief History of the Internet.   Retrieved April 10, 2000, 2000, from http://www.isoc.org/internet/history/brief.html

Levy, S. (1984). Hackers: Heroes of the Computer Revolution. New York: Penguin Group.

For those of you who caught my Ignite TO presentation, here are the slides. For those of you who missed it, below is a text summary that goes with the slides.

I’d like to give thanks to my teacher and friend, Dr. Karen Anderson, whose scholarly work underpins many of the ideas in this presentation.

Slide 1:

This presentation about is the self, that it is a social phenomenon not a biological one.�Most theories of the self don�t give us a social angle but only a biological one.�This has an impact for technology design.

Slide 2:The self is an uniquely human phenomenon.�It is the internal private reality of the consciousness.�It is not anatomical or physiological.�It is not a body.It is only meaningful in social situations.

Slide 3:�So we have this internal, private reality, this consciousness.�Biological paradigms to explain it are inadequate.�Bodies are the containers of selves, not the actual self.�Containers matter.�But they are not the only thing that matters.

Slide 4:�Victor, was a �feral child� found in France.�He would not wear clothes.�Or Use a bed.�He farted.�He did not have a social self, but a biological one.His body functioned; his self did not.

Slide 5:�HAL 9000 has a self.�He is socially competent.�Aware of his inner reality.�He imagined that Dave and Frank were plotting against him.�Victor had no inner reality but HAL did. �HAL understood the social.

Slide 6:�All too often we think of the self as a piece of hardware, or an emotion chip.�Unfortunately, most of our ideas about the self are really about our hardware.

Slide 7:�For example, Sigmund Freud.�Freud thought biological experiences created the self.�In the form of ego and the superego.�We learn about our anus and develop a self, but this doesn�t explain Victor or HAL�s development.

Slide 8:�Even psychologist Piaget put biology first.�Piaget�s theory of child development relies on sensory experiences.�Not social experiences.�For Piaget, learning starts with a bodily interaction, not social interaction.

Slide 9:�Yet socially successful human beings must master the meaning of symbols.�Symbols have fine nuances, depending on the context.�Hand gestures are anatomically similar but mean different things at different times, in different places.

Slide 10:�Social interaction is built upon symbols, not biological impulses.�We are aware of our internal realities by interpreting social symbols.�The degree of force in a gesture matters. Who gives it matters.

Slide 11:�We interpret symbols, not react to them.�We are not Pavlovian dogs who salivate at the sound of a bell.�We are not somatically driven beings, but socially driven beings.�Our bodies have influence over us but they are not the self.

Slide 12:�George Herbert Mead offers us a theory of a social self.�The �I� is what Victor has: a purely instinctual consciousness.�The �me� is created through social interaction.��I should sit on a chair; it�s more socially appropriate.�

Slide 13:�The �generalized other� is when we realize there is a whole world out there.�That we then internalize into our own private reality.�We begin to imagine what �others� might say about our actions.�Our self imagines what other selves think of it.

Slide 14:�Often we design technology to be USABLE, not to be SOCIAL. We don�t enable social selves to use technology without an awkwardness, or embarrassment.

Slide 15: �Google Street View.�This technology has created a few embarrassing moments.�Google�s face blurring does not solve our embarrassment of interpreting this image.�Street View is functional, not social.

Slide 16:�Facebook continually fails to sense what selves need.�This self posted a picture of himself smoking.�Unfortunately, his mom recognized the room.�This is embarrassing.

Slide 17:�If we design for selves, not bodies, we think of everyone�s internal private realities.�Bodies need ergonomics, usability, accessibility.�Selves need to be shielded from embarrassment, awkward situations, and social breaches.

Slide 18:�Technology designed for bodies is like an awkward dinner party.�The technology we design should provide a consistent, social lubricant.�We must design technology like we design great parties.�Where the right people sit in the right seats.

Slide 19:�Socially meaningful symbols must be present.�This can be discovered through contextual inquiry,�Selves also require the ability to control their presentation to others.�And finally, the social �place� of technology must be clearly demarcated.

Slide 20:�In the end, we design our world for selves.�Technology designed for bodies just gets in the way.�If technology is designed for bodies, selves change to meet the needs of technology.

I would prefer that have technology adapt to selves.

Thank you

I am a big fan of MUJI, the simple Japanese housewares company. So I was quite interested to read a post by their art director Kenya Hara on the New York Times’s “Room for Debate.” Hara argues that Japanese people have

…a special ability to focus fully on what’s right in front of our eyes. We tend to ignore what is not an integral part of our personal perspective. We ignore that our cities are a chaotic mess, filled with ugly architecture and nasty signage.

Hara believes that Japanese simplicity is a function partly of this narrow focus. Beautiful designs are better appreciated because of this focus, in Hara’s opinion. (Well known design guru John Maeda also weighs in and argues that the dearness of Japanese food is the primary issue).

A Beautiful Japanese Lunch: New York Times

Philosopher Dennis Dutton argues, interestingly, the American lunch box is of the same instinct: Americans have attempted to make their lunch beautiful but in distinctly different ways. Dutton leaves the symbolic interpretation of these competing “lunch beautifying” methods up to the reader’s imagination.

This reader thinks that by using exterior packaging instead of the food itself, Americans are not beautifying lunch as much as they are obscuring it. Indeed, they even commodifying it by making each lunch, regardless of content, look similar. The content of the lunch itself is irrelevant; whether it is fresh, healthy food or rotting, cheap, fast food, every lunch looks the same in a lunch box.

Perhaps this is indicative of the American spirit if industrialization. Mass production in the Fordist tradition (“You can have whatever colour car you like, as long as it’s black”) is an American value that has been spread around the world. Forget about the content of the thing, instead focus on its packaging, its marketing or its uniformity. This is what Ritzer means by the “McDonaldization of Society.” When the content of a thing matters less than how much of it is sold or how efficient it is to sell it, this is the height of capitalism — and perhaps of American culture.

This is perhaps the essence of why Americans can accept truly horrible food, while the Japanese and the French famously reject it. But it doesn’t explain why Hara thinks Japanese aesthetics are ruled in part by the ability to “focus” on one thing.

Is the Japanese form of capitalism less in need of obscuring and masking than the American? Is ugliness more tolerated by Japanese society and therefore, less of a threat to its form of capitalism?

“But how many people did you talk to?” If you’ve ever done qualitative research, you’ve heard that question at least once. And the first time? You were flummoxed. In 3 short minutes, you can be assured that will never happen again.

Folks, qualitative research does not worry about numbers of people; it worries about deep understanding. Weber called this “verstehen.” (Come to think of it, most German people call it that too. Coincidence?). Geertz called it “thick description.” It’s about knowing — really knowing — the phenomenon you’re researching. You’ve lived, breathed, and slept this thing, this social occurrence, this…this…part of everyday life. You know it inside and out.

Courtesy of daniel_blue on Flickr

You know when it’s typical, when it’s unusual, what kinds of people� do this thing, and how. You know why someone would never do this thing, and when they would but just lie about it. In short, you’ve transcended merely noticing this phenomenon. Now, you’re ready to give a 1-hour lecture on it, complete with illustrative examples.

Now if that thing is, say, kitchen use, then stand back! You’re not an Iron Chef, you are a Platinum Chef! You have spent hours inside kitchens of all shapes and sizes. You know how people love them, how they hate them, when they’re ashamed of them and when (very rarely) they destroy them. You can tell casual observers it is “simplistic” to think of how many people have gas stoves. No, you tell them, it’s not about how many people, it’s about WHY they have gas stoves! It’s about what happens when you finally buy a gas stove! It’s about….so much more than how many.

Welcome to the world of verstehen. When you have verstehen, you can perhaps count how many people have gas stoves. Sure, you could determine that more men than women have them. Maybe you could find out that more of them were built between 1970 and 80 than 1990 and 2000. But what good is that number? What does it even mean?

When you’re designing, you must know what the gas stove means. You must know what it means to transform your kitchen into one that can and should host a gas stove. You must know why a person would be “ashamed” to have a gas stove (are they ashamed of their new wealth? do they come from a long line of safety-conscious firefighters?). You must know more than “how many.”

So the next time someone asks you, “how many people did you talk to?”, you can answer them with an hour-long treatise about why that doesn’t matter. You can tell them you are going to blow them away with the thick description of what this thing means to people. You are going to tell them you know more about this thing than anyone who ever lived, and then, dammit, you’re gonna design something so fantastic, so amazing that they too will be screaming in German. You have verstehen!

See my discussion about sampling methods in qual and quant research for more insight into the reasons why “how many” is irrelevant in qualitative research.

DT has a great post over at Design Sojourn that discusses Six Sigma methodology and how it relates to design. He cites Tim Brown at IDEO who argues that Six Sigma is essentially Newtonian, while design thinking is quantum. In his own design work, DT expressed doubts about using Six Sigma:

After studying the Six Sigma process, I point blank said: �There was no way any of my designers are going to be judged on the quality and success of a design based on how many sketches or iterations we did before we deliver it.�

Both Brown and DT cite Sara Beckman, who recently discussed the topic in the New York Times. Beckman reviews how Six Sigma focuses on incremental improvements, while design and design thinking focuses on big changes. For those of you who aren’t familiar with Six Sigma, it’s a method pioneered by Motorola, which aims to reduce the number of errors to 3 in one million. The “six sigma” refers to six standard deviations. The number of errors should be at the extreme end of the normal curve, or between + or – 3 standard deviations, represented by the Greek symbol sigma.

I argue that design is more complementary to the “interpretivist” paradigm of qualitative research while Six Sigma is positivist. Interpretivists don’t believe the world is a static place. They see reality as being continuously created by you, me and other social actors. There is no such thing as “The Truth” in interpretivist approaches, just different versions of the truth. Typical methods of interpretivists are ethnography, in-depth interviewing and discourse analysis. Positivist research, on the other hand, assumes that reality is static. Positivists believe that “The Truth,” is out there to be discovered. Typical methods would include quantitative surveys.

Designers should focus on interpretivist methods, therefore. They should uncover different versions of the truth using observation and interviewing, as well as deep reflection on symbols and their meanings. Surveys and other quantitative methods are more Six Sigma in that they can measure improvement over time. Designers ought to consider measuring improvement, but starting with qualitative approaches is best.

The technology consulting firm Gartner is predicting that social scientists will be very much in demand by businesses. Eweek summarizes Gartner’s outline of four types of roles for social scientists:

Web User Experience roles that include UI designers, virtual-assistant designers and interaction directors.
Behavior Analysis roles that include Web psychologists, community designers, and Web/social network miners.
Information Specialist roles that include information anthropologists who are expected to play historical Web fact finding and assisting in legal analysis, intellectual property management and where the quality of information is at risk.
Digital Lifestyle Experts roles that include helping senior management understand whats going on and stay aware, and building personal brands and managing online personas for desired online effect

Gartner’s Vice President Kathy Harris appears to have faith in social scientists’ ability to be creative:

Creative, artistic and clever people will develop the early iterations of these new jobs. This will enable businesses and government to take early advantage of new capabilities and develop them into mainstream skills.

I’m in full agreement that social science trains people in the right kinds of skills for the digital age. I was disappointed however to find that sociology had failed to capture Ms. Harris’s specific attention.Interestingly, the report mentions anthropologists and psychologists specifically, but not sociologists.

Sociologists have recently complained that they have not been given a place at Obama’s table. I argue that it’s because they’ve done a poor job of publicizing the great skills they have. Just last night I sat down with two other sociologists, one is a specialist in the sociology of science and the other in the socio-legal implications of changing family forms. Aren’t these the very people we need to help us understand the effects of genetic engineering? Or the potential outcomes of changing same-sex marriage laws?

I personally will continue to proclaim my training as a sociologist, and will convince business people that the “soft stuff” is a differentiator. I will also try to nudge my colleagues into the world of design, where their training in empathy and critical thought is welcome.