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.

The New York Times reports that the American Medical Association is considering doing away with the venerable symbol of the physician: the lab coat. There’s a very good reason to get rid of lab coats: they’re dirty. But the symbol of the lab coat is far more important. The New York Times reports the empirical flaw in wearing lab coats:

The group�s Council on Science and Public Health is looking at the role clothing plays in transmitting bacteria and other microbes and is expected to announce its findings next year.

This empirical finding shouldn’t be surprsing. We also know, for example, that male physician’s ties are wearable petri dishes. The verdict ought to be clear, therefore that we should get rid of lab coats. Not so fast, say physicians.

Getting rid of the lab coat is getting rid of one of the most important symbols of a physician’s identity. Dr. Richard Cohen told the New York Times how important that lab coat is:

�When a patient shares intimacies with you and you examine them in a manner that no one else does, you�d better look like a physician � not a guy who works at Starbuck�s.�

Here is the lesson for designers: empirical “fact” is not the whole story. What role any particular symbol plays in social life is just as critical. What’s fascinating about this story is that physicians are now trained in “evidence-based medicine,” meaning they are trained to diagnose and treat based on more “rigourous” science (I have my doubts about that rigour, but that’s another blog post).

Yet here is a clearly “scientific” reality about the danger of treating patients while wearing a bacteria-infested lab coat and/or tie, and physicians continue to wear them. For all their protestations of “evidence,” physicians too are social beings, embedded in a social world. They too must convey an identity, even if the symbols used for doing so compromise their ability to complete their stated vocational mission.

The symbol is powerful. Designers who base their decisions on so-called “evidence” ought to pay attention to other kinds of evidence, such as the enduring patterns of social interactions. We should pay attention to any enduring patterns of social behaviour but *especially* those which fly in the face of supposed “logic.”

In an earlier post, I examined how text is transformed when it is created and shared in digital form. In this post, I argue that time itself is transformed when it is represented in digital format. To illustrate, consider my experiment with my Filofax.

Yes, I said Filofax. I still have one. I haven’t filled it with inserts in years, even though that was actually one of my favourite end-of-year rituals. I would make a special trip to the stationary store, just to buy the next year’s worth of calendar. In the process, I would review last year’s appointments, marvel at how much I had gotten done and how fast time had passed. I would linger over favourite appointments, which seemed, at the time, inconsequential, as recorded in my scribbled hand.

I bought a 2009 insert for my Filofax and inputted only two weeks’ worth of appointments. It took me 20 minutes.

Analogue time "reckoning"

The time it took me to enter in all these appointments was more than just scribbling. It was reviewing, remembering, considering. I could not physically enter overlapping appointments. There simply wasn’t room!

Now compare this to the same amount of time, as rendered by my iCal:

Digital Time "Reckoning"

There are overlapping appointments, my husband’s appointments easily inputted into mine, meetings from people I barely know, all dropped into my life automatically. Worse, I carry this around, automatically updating it, second by second, through my iPhone.

Sociologists use the term “time reckoning” to describe how we collectively understand time and make it intelligible to ourselves. There was a great hullabaloo about “clock time,” when clocks came to replace the seasons as our primary way of time reckoning. We forgot we didn’t know how long a minute actually was — we actually now think we can tell how long 23 minutes and 42 seconds is (spoiler: we can’t, especially when we’re enjoying ourselves!).

Now we have “digital” time reckoning, which bears almost no resemblance to how we actually experience time. If you have the misfortune of using time tracking software like TimeControl, then you will likely recognize this fantastical, farcical, FrankenTime:

Screenshot from Microsoft's TimeControl

According to this, a mythical interaction designer named Joseph Gardner spent 8 hours and 20 minutes on Sunday “design interface.” Ignoring the assault on proper grammar for a moment, let’s take a step back and understand what this means. First off, Poor Old Joe was working on Sunday. Notably, TimeControl allowed this kind of time use, despite the fact that it likely broke overtime laws. But secondly, how long is 8 hours and 20 minutes? Did Joe forgo the need for bathroom breaks? Was he glued to the chair for precisely 8 hours and 20 minutes? How long did he actually spend in that chair anyway?

Digital time allows to represent time in impossibly tiny fragments, and to work impossibly long hours. This kind of time would never be recorded in one’s Filofax — there simply isn’t room for all those hours. Moreover, the time it takes to record one’s time in a Filofax also requires one to contemplate the implications of 8 hours and 20 minutes of work on a Sunday.

In short, the difference between analogue and digital time is that digital time is even less like cognitively experienced time than “clock time.” Digital time can be schedule effortlessly, without any thought to the physical need for sleep, food, or relaxation. Digital time is a faster, manifold version of clock time, one that makes it possible for use have multiple, synchronous events.

Hugh Dubberly and Paul Pangaro had a great post on Interactions magazine about designing for conversations. They propose to use how a conversation actually works to make interactions better. They rely heavily on Claude Shannon’s conversation model to help guide the conceptual model of interaction designs.

In Shannon�s model an information source selects a message from a known set of possible messages, for example, a dot or a dash, a letter of the alphabet, or a word or phrase from a list. Human communication often relies on context to limit the expected set of messages.

I applaud Dubberly and Pangaro’s attempts to use rigourous theory to support interaction design. But I’d have to agree with Peter Jones as he wrote in the comment section, that other philosophically informed communication theories are more robust when it comes to designing for conversation. Peter specifically mentions Winograd and Flores’s “conversation for action model” which relies on Habermas’s contention that you are acting when you communicate.

I’ll add to Peter’s critique. Garfinkel’s ethnomethodological approach gave way to “conversation analysis,” which posits that speakers use “indexical expressions” (or phrases that are fraught with meaning but are meaningful to the participants through unspoken means). Where in Dubberly and Pangaro’s article is the discussion of such expressions?

Where also is the notion of turn taking? Turn taking is a very significant component of a conversation. Try to have a trans-atlantic mobile phone conversation and you’ll see how important smooth turn taking is to meaningful conversation.

I would exhort interaction designers to continue to read and integrate theory into their mental models. But I would also discourage them from taking the short route; theories are debated for a reason. Interaction design ought to be a robust digital representation of those debates, and include all aspects.