Storytelling, Presenting and Getting Past the Stick in Your Bum

The other day I was thinking about how to present findings to a client about what was, frankly, a seemingly dry subject. Numerous stakeholders would be involved and would range from the CMO down to brand managers, product engineers, etc. So, knowing I had a dry subject and a conservative audience, I decided to rethink the question a bit.  Was the goal to present findings or was it something more? The goal is ultimately to shake the client’s foundations of belief, to rattle his or her assumptions, to create a new state a awareness.  Any good  presentation serves to evoke a participatory feeling in the viewers and bring them into the moment of experience, compelling them to consider new ways of classifying and thinking about their world, as well as their processes. The report will come later, but the presentation is about changing minds.

That brings us back to storytelling. When we bring our research and strategic thinking to life, the story we weave is less a list of data points than an interpretation and distillation of a series of experiences, Details are selectively recounted including all the “odds and ends that are associated with remembered events”  (see VanMaanen  1988).  The audience is drawn into the story created both by the author/editor and participant(s) – in other words, a good story, and a good presentation, is a shared experience, co-created in the moment. Bore the audience and there is almost no chance of affecting change. Selective packaging to exemplify generalized constructs is a standard practice. What we present needs to illustrate, provocate and elucidate. This is doubly so when addressing the needs of business and design teams with distinct, targeted problems and limited time.  Our editorial choices make points clear in what might otherwise be murky waters – we make learning sexy.  And that means becoming marvelous storytellers.

So what do we need to do to make a good story? First, start thinking in terms of symbols and metaphor. Stories are conveyed through language, which is by definition a symbolic system. The key to successful engagement is to move from structural aspects of a story to the symbolic, uncovering systems of meaning that resonate with clients and compel them to action. These symbolic dimensions that emerge in the narrative add value to brands by fulfilling culturally constructed concepts (quality, status, age, belonging, etc.). A brand is a signal that triggers a field of meanings in the consumer’s mind. These meanings are conveyed directly and inferentially through stories. By harnessing the symbolic power behind these meanings, strong brands move beyond the codes governing a product category and enter the personal space of the consumer.  The same holds true for the client.  Through storytelling and presentation of symbolic codes, clients move from fixating on the product line and can rethink what the brand means in a wider context.

Second, strip the presentation of text. You’re hear to talk and the image on the wall behind you is there to produce a response. Text, then, becomes a distraction unless you intend to use it as a visual manifestation of an idea (imagine a giant “NO” in lieu of something like a stop sign). The media tool we use, be it PowerPoint or something similar, is the comforting factor for audience and presenter alike, not the content. That means we can use the program for displaying images, visual cues and video, but we cannot let it become the focal point – it is like a set on which an actor performs. Don’t let it overshadow the actor.

Third, just because you’re using PowerPoint, it doesn’t mean that you can’t alter the stage. A presentation is like a play – so why not do it “in the round”? Promote physicality, discussion and direct interaction between you and the audience members. Give people small tasks throughout the presentation so that they are not passive recipients of information but co-creators. The more interaction, the more likely they will be to internalize the story you present.

Finally, have fun. It seems self evident, but it is perhaps the hardest thing most people find to do – they may talk about it, but they can’t actually do it. Remember, your role is to produce change, not recite facts.

Objectifying Objectivity

“Science is a social phenomenon…It progresses by hunch, vision, and intuition. Much of its change through time is not a closer approach to absolute truth, but the alteration of cultural contexts that influence it. Facts are not pure information; culture also influences what we see and how we see it. Theories are not inexorable deductions from facts; most rely on imagination, which is cultural.” Gould, 1981

Business people often like to think of themselves as scientists of sorts – their science is practical and applied, but first and foremost it is grounded in objectivity and hypothesis testing, the hallmarks of scientific reasoning. Scientists seek concepts and principles, not subjective perspectives. They seek laws, truths and testable, verifiable data.  And we as a society, be the business person or the designer, simply accept objectivity as a fact of life. Thus, we cling to a myth of objectivity: that direct, objective knowledge of the world is obtainable, that our preconceived notions or expectations do not bias this knowledge, and that this knowledge is based on objective weighing of all relevant data on the balance of critical scientific evaluation. And here is where I will no doubt irritate some and flat out piss off others – objectivity is a myth. So from the outset, let’s be clear. I am not implying that objectivity is a fallacy in and of itself. That would be absolutist. Rather, like all myths, objectivity is an ideal for which we strive. The search for objectivity is an intrinsically worthwhile quest, but it should not get in the way of an insight, which frequently happens. If you can’t quantify it, an insight loses its worth. And that is a terrible, terrible thing.

In most business situations the fact of the matter is that we choose which events, numbers, etc. we want to place value on and those we want to dismiss. This is occasionally conscious, but more often is the product of our worldview, what we hope to personally gain from the data we employ (e.g. a promotion), or simply how tired we are when we sit in on our 300th interview at the end of a long day.  Our beliefs and expectations exert a profound control on perceptions. In other words, we see what we expect to see, and we remember what we want to remember. If we believe that moms are the primary decision makers when it comes to buying groceries, we overlook the roles of other family members in the process, roles that may in fact be more important. So, while people misrepresent themselves in most traditional research (itself another topic of discussion for a later date), we in fact twist reality one turn further. Out of all the occurrences going on in the environment, we select those that have some significance for us from our own egocentric position.

What all this means is that the first problem with obtaining objectivity is that perception strengthens opinions, and perception is biased in favor of expectations. The second is, that our involvement by definition alters the situation. In 1927, Werner Heisenberg, in examining the implications of quantum mechanics, developed the principle of indeterminacy, more commonly known as “the Heisenberg uncertainty principle.”  He showed that indeterminacy is unavoidable, because the process of observation invariably changes the observed object. Whether we run a focus group or ask someone to fill out 20 questions in a survey, we are altering “normal” behavior and therefore the how an idea, a product or a brand would play out in real life. What this means is that probability has replaced determinism, and that scientific certainty is an illusion.

So what are we to do? How can we reconcile the profound success of the scientific method with the conclusion that the perception and process make objectivity an unobtainable ideal? Well, we accept a few things and move on. Science depends less on complete objectivity than most of us imagine. Business even less so, especially as it pertains to things like advertising and branding.  Admitting that allows us to use a biased balance to weigh and evaluate data, experiences and good old-fashioned gut reactions. If we’re aware of the limitations by which we assess and measure our area of study, be it cereal shopping habits or car purchase decisions, we can use those biases effectively. To improve the accuracy of a balance, we must know its sources of error.

Pitfalls of subjectivity abound. Some can be avoided entirely; some can only be reduced. The trick is to know when and how to use them to get at a real insight. Some of the more common pitfalls are:

  • Ignoring relevant variables: We tend to ignore those variables that we consider irrelevant, even if others have suggested that these variables are significant. We ignore variables if we know of no way to remove them, because considering them forces us to admit that the experiment has ambiguities. If two variables may be responsible for an effect, we concentrate on the dominant one and ignore the other. The point is, we cherry pick and doing so leads to flaws.
  • Confirmation bias: During the time spent doing our initial research (that stuff we used to call a Lit Review), we may preferentially seek and find evidence that confirms our beliefs or preferred hypothesis. Thus, we select the experiment most likely to support our beliefs. This insidiously frequent pitfall allows us to maintain the illusion of objectivity (for us as well as for others) by carrying out a rigorous experiment, while nevertheless obtaining a result that is comfortably consistent with expectations and desires.
  • Biased sampling: Subjective sampling that unconsciously favors the desired outcome is easily avoided by randomization. Too often, we fail to consider the relevance of this problem during research design, leading to suspect insights.
  • Missing important background characteristics: Research can be affected by a bias of human senses, which are more sensitive to detecting change than to noticing constant detail. In the midst of collecting data, however you chose to think of it, it is easy to miss subtle changes in context. That, unfortunately, often leads to overlooking interrelationships between people, events, etc. In other words, it means you overlook important information because you can’t tear yourself away from what you perceive to be important.
  • Conformation bias in data interpretation: Data interpretation is subjective, and it can be dominated by prior belief. We should separate the interpretation of new data from the comparison of these data to prior results.

Ultimately, there is nothing wrong with embracing our subjective side, our interpretative side, our artistic side. This doesn’t necessarily mean rejecting the search for objectivity (although sometimes that is in fact the best course of action), but it does mean we should recognize that when a client starts freaking out about our research results and, more importantly, our insights, we should be prepared and address it head on rather than trying to defend ourselves as “objective observers”. After all, I’ll be the first to say that I love mythology. That said, I don’t believe life sprang from body of Ymir (look it up) but I do believe we can learn quite a bit from the story about our humanity. Similarly, if we embrace the realities of a subjective, or at least causal world, we produce better thinking, better insights and better results.

 

Metaphor and Design

“Metaphor is for most people device of the poetic imagination and the rhetorical flourish–a matter of extraordinary rather than ordinary language. Moreover, metaphor is typically viewed as characteristic of language alone, a matter of words rather than thought or action. For this reason, most people think they can get along perfectly well without metaphor. We have found, on the contrary, that metaphor is pervasive in everyday life, not just in language but in thought and action. Our ordinary conceptual system, in terms of which we both think and act, is fundamentally metaphorical in nature.” George Lakoff

As rational people who like to rationally talk about doing rational things, we like to think we choose products based on what we can see, hear, feel, taste and touch. Is this a good beer? We taste it. Is this a good car? We drive it. We like to believe that we make our judgments by distinguishing tangible distinctions. But is there’s a lot more to the equation than just our five senses. There is more to it than cataloging functional benefits. There are the subconscious elements, the deeper meanings, the other intangible benefits that products offer, which factor into the formula and influence our decisions.

The concepts that govern our thought are not just matters of the intellect. They have deeper meanings that intertwine the supposed rational with the symbolic. They govern our everyday functioning, from the expression of complex beliefs and concepts down to the most mundane details. These systems of meaning structure what we perceive, how we perceive it and how we act upon those perceptions.  They inform us how to get around in the world, how we relate to other people and even how to select objects of consumption. Our conceptual system thus plays the central role in defining our everyday realities. And we structure concepts in relation to each other.  Take the concept of argument as war: 

  • Your claims are indefensible.
  • He attacked every weak point in my argument.
  • I demolished his argument.
  • I’ve never won an argument with him.
  • You disagree? Okay, shoot!
  • If you use that strategy, he’ll wipe you out.
  • He shot down all of my arguments. 

We do this all the time – time is money, data is geology, clothing is theater.  Consequently, understanding associations between concepts is pivotal to turning insights into action, whether you are designing an object or a strategy.

Pure metaphor.

Sometimes, when luck is with you, you can just show us something that isn’t your product at all and tell us it is. This is the use of  pure metaphor: something that stands in for your product that helps clarify and convince. This is obviously a good idea when your product is intangible, but also when the product is, frankly, dull, complicated or has no contextual frame of reference.

I once saw a poster in a library. In it, a hiker was pausing on a beautiful vista overlooking the Grand Canyon, the awesome spectacle looming before him. The poster could have been advertising Timberland or Arizona tourism or even cigarettes, but headline instead read, “Knowledge is free. Visit your library.” Visually, the message was the perfect use of metaphor. A library visit is like an odyssey through immense, spectacular country; it goes beyond the things housed there speaks to the underlying sense of discovery, exploration and surprise.

Fused metaphor.

Unfortunately, pure metaphors are rare, the reason being that it’s simply easier to create a fused metaphor. With a fused metaphor, you take the product (or something associated with it, the way a toothbrush is associated with toothpaste) and attach, or fuse it, with something else.

Objects, at least from a design or advertising perspective, that are modified in some way are often more engaging to us. We are, after all, naturally curious creatures. Unmodified images are often just clichés or stale representations. Disrupting the symbolic structure and associated metaphor primes the viewer’s psyche, drawing them into product or message to make sense of what’s going on. For example, one of advertiser David Ogilvy’s famous ideas was “The Man in the Hathaway Shirt,” who wore an eye patch and was thereby more interesting than a man who didn’t. He wasn’t just the your typical handsome man, he was a wounded, brave, paragon of masculinity with a story to tell.

Unlike pure metaphor, fused images help contextualize the selling argument for us. we don’t have to leap quite as far when part of what we’re looking at is what’s for sale.

So what? At its most basic level, design is about people rather than the objects and spaces we construct.  Design facilitates interaction between people and brands, mediated by the products and spaces those brands construct. We think in terms of solving problems (addressing functional needs, increasing efficiencies, etc.), but problems aren’t unchanging.  They are fluid and influenced by a host of factors, from basic function to notions of status to whether or not they make sense in relation to our worldview.  Because genuinely innovative, new ideas are almost always the product of juxtaposition, they can be nearly impossible to quantify in terms of risk or acceptance. But that doesn’t mean there aren’t ways to reduce risks.  

Why? Because metaphors endow products and spaces with human-like characteristics, making them more approachable and usable. They couch them in concepts with which we are already familiar and make the process of acceptance easier. They also make conversion from insight to object, space or message easier in the same way, by grounding them in concepts people understand, they can more readily see differences and similarities.  They can more easily envision what materials, words, colors, etc. will resonate and can start to readily think in new directions.

Doing so simply requires using a different set of tools than those typically used to test peoples’ reactions.  This is when the use of metaphor in the design process becomes most important. Metaphor provides us with the means to understand complex spaces, things and relationships. Like the example of “argument is war,” imagine applying the same model to designing a product.  Food as spirituality, for example: 

  • This dish is heavenly.
  • This ice cream is divine.
  • Bacon is good for the soul

Ask yourself these questions:


1. What is this product? What does it do? The logotype for Exhale, a pulmonary disease therapy company, demonstrates visually what they do best: they help us breathe better. Each subsequent letter in the logo is less heavy and lighter in color than the previous. As we read the name, we realize and understand its meaning through this visual metaphor.

2. How does it differ from the competition? One of Herman Miller’s annual reports used transparent paper stock to suggest the serendipity of innovation: You look at one problem and sometimes see through it, the answer to another.

3. What’s the largest claim you can make for the product? That it’s a dog shampoo that dogs actually love? Then put the shampoo in packaging designed like something else they love: a fire hydrant.

4. What is this product’s central purpose? One annual report for the Calgary YWCA emphasized the organization’s work with battered women, so the report itself was torn and distressed. The headline on the beat-up cover: “Last year over 11,000 Calgary women were treated worse than this book.” This metaphor may even be stronger than if they had used actual photographs of battered women, since this approach is less expected. 

Once the metaphor is defined (and there will no doubt be more than one metaphor in the mix in many cases), other associations will start to emerge.  If associations are made between food and spirituality, for example, what does that mean for color palette choices, brand elements, package design, etc.?  That leads to defining not only the functional aspects of the design, but the story behind it.

And design, particularly when thinking about design of something that is new or takes an existing brand in a totally new direction, is akin to creating a story.  There are tensions, themes, characters, frames, etc.  Conflicts, tensions and interactions become connectors between ideas and actions. And like the elements or any story (or the type of story), metaphor allows you to categorize, structure and create boundaries with the information you work with.  The final result is a strategy for design that makes sense to the consumer.

Divorce

Package it, slap a label on it and sell it for $4.99 a pound. It’s as simple as that when you’re selling groceries, right? Hardly. Food, meat in particular, is tied to cultural sensibilities about production, cleanliness, family values and a host of other topics.
Meat, like Norman Rockwell images of the American farm, is myth. We’ve been conditioned to turn away from the origins of our food and respond to blood and death with repulsion. Or have we?
With wealth comes the desire to learn about where our food comes from, how it’s produced and what exactly is in it. The point is that shopping for food is an increasingly complex process as has less to do with securing calories than it does with symbols and meaning.

Defining Context

Planners, researchers and marketers increasingly think about consumer in complex ways. We understand that in a changing digital landscape, where people are dialed in 27/7, the context in which they learn and shop is incredibly important and influences what messages we deliver and how we deliver them.  So increasingly, we are thinking about what situations govern behavior and designing to fit that complexity. 

We spend a great deal of time talking about context, but rarely use models to define elements of it.  This particularly true when talking about mobile devices and accounts for the hit-and-miss quality of  most apps available on the market.  It is one thing to design a usable app that conforms to human factors and cognitive requirements, but it is quite another to design a stage in an environment, or an environment itself, when there are innumerable semi-autonomous devices mediating an swirl of information.  Consequently, it makes sense for us to think about how we structure context so that we can determine what exactly we can affect.

Physical Context

From the computational side of things, physical context refers to the notion of imbuing devices with a sense of “place.”  In other words, devices can distinguish the environments in which they “live” at any given moment and react to them. But this is much more difficult than it at first appears. Mapping out longitude and latitude is one thing, but reacting to socio-cultural features (political, natural, social, etc.) is much more problematic. Getting beyond demarcation of identifiable borders and structures, means coming to grips with place (as opposed to space).  That in turns having to be “aware” on some level. 

Think of a mall.  Within that mall are hundreds of stores, each with hundreds of devices and/or nodes of information. The device now has to decode what information is most relevant to itself, what information is most relevant to the user and how it will deliver that information.  Returning to the mall example, we have to think about a host of things in order to make any app relevant.  What competing retailer apps get precedence over others? When you receive an offer from one store, will the device “tell” other retailers in order to generate real-time counter offers?  When someone else is holding your device for you (say, while trying on clothing but needing to set the iPad aside or while your child plays Angry Birds on the couch in the evening), how will the device know what incoming content is private and what is public?  How will the device communicate with a location or with other devices as it moves throughout the mall? Is it even necessary? The point is simply this; we increasingly have access to the digital landscape at all points throughout the day and getting design right means understanding the systems in which people operate.

Device Context

Just as various kinds of sensory apparatus (GPS-receivers, proximity sensors, etc.) are the means by which mobile devices will become geographically aware, another class of sensors makes it possible for devices to become aware of each other. There is a fundamental difference between the ability to transmit data between devices and the ability (and desire) of devices to discover each other. And this presents a series of problems that are different in nature than those of physical context. Because this deals with choices of communication.

We are on the verge of existing in a world with zero-infrastructure networks that can spring up anywhere, anytime. That means that devices are in a potentially constant state of discovery.  Returning to the mall for a moment, imagine that you are with a friend whose device is communicating with yours.  In there mall are a couple of thousand devices, all of which are discovering each other.  What happens now?  Assuming we’ve dealt with the problem of my mobile phone communicating with my friend’s phone while blocking out the other 2000 devices, we still have several thousand potentially “identities” that may have useful information for us.  How do we select how to manage that without devoting a ridiculous amount of time to setting up the hundreds of variables that shape what we do and don’t want at any given time? Perhaps more importantly, how do we develop a process to manage it that mimics, or at least compliments, the human brain and cultural patterns of behavior? All this is couched in a neat little world defined within a single, bounded  geographical unit.  So understanding device context is as important as understanding physical context.

Information Context

This is the realm of information architecture, plain and simple.  But with the advent of pervasive mobile, this topic is becoming even more complex.  Specifically, data no longer resides, literally or figuratively, “in” our computers.  Our devices are extensions of the cloud and exist as something akin to perceptual prostheses.  They exist to manipulate data in the same way a joy stick allows us to handle the arms of robot in a factory.  And this is important because it reflects a shift in how we think about and use information because all information (and the aps that carry that information) is transitory and by and large, public. 

 This changes the nature of what the device has to actually be. Storage issues are essentially removed from the equation.  Content can leap from place to place and device to device in an instant. All content will be customizable and reflect the human-application interaction rather than shaping it. This leads to the point that devices, and the people who use them, will find themselves in the 4th kind of context of social interaction, with all its peculiarities and contingencies. Just as our behavior and worldview shapes and is shaped by the moment in which we find ourselves, so too will our apps and information need to adapt to the moment.  In other words, devices will need to be more human.

Socio-Cultural Context

The whole humankind is riven with contrasting practices, cultures, tongues, traditions and world views. A cultural context may exist on levels as diverse as a workplace, a family, a building, a city, a county, a state, a nation, a continent, a hemisphere etc. A cultural context provides a shared understanding of meaning provides a framework for what “works” in the world. It is what helps you recognize “your kind” in all senses of the word.

And it is at the point of socio-cultural understanding where we gain a better perspective on what will and will not be accepted in the mobile universe.  We need to understand the essence behind the veil of design and usage to uncover meaning.  Take the beer pouring app as an example.  Here we have a simple app that mimics the pouring of a beer when you tilt your device.  On the surface it has little relevance to our daily lives.  It serves no direct function and yet it has been tremendously successful because of the cultural needs it to which it speaks – workplace breaks from the mundane, the ability to show off the newest thing, male-to-male bonding, etc.  Its absurdity is precisely what makes it relevant.  But in another context, say Saudi Arabia, the context shifts and meaning must change to fit that particular milieu.

The nature of our successes lies in understanding the reasons behind our beliefs and actions, in the symbolic exchanges we are part of and our abilities to code and decode those symbolic exchanges.  The nature of our mistakes essentially lies in a lack of comprehension. It leads to UI and app development that speak to a minority of the population even as they try to sell to the masses. Without understand the underlying epistemological constructs of a group (or more accurately, a mix of often associated groups at different points of interaction and interpretation) then we miss opportunities.

So What?

So why does any of this matter?  It matters because good design and messaging are increasingly difficult to master.  Our great technological leaps forward have also produced more complexity, which in turn leads to a greater need to make sense of what is “going on” in the broadest sense of the term when it comes to gathering insights and translating them into design and business applications. Without a means by which to categorize context, we can’t isolate those things that matter most and we miss enormous opportunities. So how do we get at underlying contexts? To be perfectly blunt, there is no perfect system because contexts change if we’ve done our jobs well (cause and effect), but there are ways to come close. Depending on the project, questions may be very tactical and specific or very strategic and broad. In either case, the first step is to clearly articulate what the overarching goal is.

First, rethink the problem. Frequently, what we see as the problem is in fact a facet of something else. For example, when researching something like an eBook the problem to be solved isn’t technology, it may be understanding why people read different material in different contexts. It may be about displaying books for colleagues and friends as a means of gaining status. The point is that the problem we see may not be the problem at all and we need to think about possibilities before we enter the field.

Second, begin defining the contexts.
Where does an activity or practice take place? Defining the contexts we want to examine helps articulate the range of possibilities for observation. For example, if we’re studying beer drinking, we need to articulate all the possible contexts in which beer is purchased and consumed.

Third, think through the complexity of the sample.
Who are the people we want to talk with? What are the social and cultural circles that will shape the event? It isn’t enough to define a demographic sample, you need to think in terms of cultural, social, professional and environmental systems, determining not only who will be the primary participants, but also the actors that shape the context.

Fourth, make a game plan that involves direct experiential information gathering, don’t just dig into statistics. Put together a guide to help navigate the data collection and a method for managing the data (remember, everything is data and it is easy to become overwhelmed without a plan). Having a series of key questions and observational points to explore is the first component. But don’t just think about the questions you will ask, but also include opportunities for observation, mapping, and participation.

Fifth, head into the field.
This is the heart of the process. Meaningful insights and moments of “truth” are slow to get at. Low-hanging fruit will be easy to spot, but the goal should be to find those deeper practices and meanings. Because everything is data, from attitudes to mannerisms to artifacts, it is important to capture as much as possible. Take notes, draw maps and sketches, take photographs, shoot video, and collect audio – the smallest piece of information may have the greatest impact

Sixth, do the analysis. Hands down, analysis is the most difficult, but also the most rewarding part of research. A trained ethnographer, for example, will do more than report anecdotes. A trained ethnographer will bring a deep understanding of cultural understanding and social theory to the analysis process. This goes beyond casual observation and starts to pull together the web of significances and practices that get to the underlying structures of why people do what they do. Analysis should always work within a framework grounded in the social sciences. Analysis takes time, but the results will include modes of behavior, models of practice, experience frameworks, design principles, and cultural patterns. Once the data has been analyzed and crafted into something meaningful, the research team should be able to provide a rich story with a clear set of “aha” findings.

Finally, it isn’t enough to simply hand off results. As compelling as we may find our insights, that doesn’t always translate into someone seeing immediately how to apply them. Once insights and findings are shared, you need to work with others to craft those findings into action plans, product ideas, etc.

The end result is that you create greater value for the client and for yourself. The process is, admittedly, more time consuming than traditional approaches, but it ultimately yields greater insight and reduces time and costs on the back end. It also yields better work that will impact the customer or end user more significantly. 

Context and the Changing Mobile Landscape

Marketers increasingly think about consumers in complex ways. It is understood that in a changing digital landscape, the context in which they learn and shop influences what messages we deliver and how we deliver them.  But we rarely define “context”. It is one thing to design a usable app that conforms to human factors and cognitive requirements, but it is quite another to design a stage in an environment when there are innumerable semi-autonomous devices mediating in a swirl of information.

Physical Context

Physical context refers to the notion of infusing devices with a sense of “place.”  In other words, devices can distinguish the environments in which they “live” and react to them. But this is difficult. Mapping out longitude and latitude is one thing, but reacting to features (political, natural, social, etc.) is much more problematic. Getting beyond the boundaries of identifiable borders and structures, means coming to grips with “place”.

Think of a mall.  There are hundreds of stores, each with hundreds of devices. The device now has to decode what information is relevant and how it will deliver information. What competing retailer apps get precedence over others? When you receive an offer, will the device “tell” other retailers in order to generate real-time counter offers? The digital landscape is continuous at all points throughout the day and getting design right means understanding the systems in which people operate.

Device Context

Just as various kinds of sensory apparatus (GPS-receivers, proximity sensors, etc.) are the means by which mobile devices will become geographically aware, another class of sensors makes it possible for devices to become aware of each other. This presents a series of problems that are different than those of physical context.

Technology is on the verge of existing in a world with zero-infrastructure networks that can spring up anywhere, anytime. Devices will exist in a constant state of discovery.  Returning to the mall, imagine that you are with a friend whose device is communicating with yours.  In the mall are a couple of thousand devices, all of which are discovering each other.  What happens now?  Assuming we’ve dealt with the problem of one friend’s device communicating with the other friend’s device while blocking out the other 2000 devices, you still have several thousand potential “identities” that may have useful information.  How is it decided what to manage without devoting significant time to setting up the hundreds of variables?

Information Context

This is the realm of information architecture. Data no longer resides “in” our computers.  Devices are extensions of the cloud and exist as something akin to perceptual prostheses.  They exist to manipulate data in the same way a joy stick allows us to handle the arms of robot in a factory.  This reflects a shift in how we use information because all information is transitory.

Storage issues are essentially removed from the equation.  Content can leap from place to place and device to device in an instant. Content will be customizable and reflect the human-application interaction rather than shaping it. Devices will find themselves in the fourth kind of context of social interaction, with all its contingencies. Just as behavior is shaped by the moment, so too will the apps and information needed to adapt.

Socio-Cultural Context

Each person is unique to contrasting cultures, tongues, traditions and world views. A cultural context may exist on levels as diverse as a workplace, a family, a building, a county, a continent, a hemisphere. Cultural context provides a framework for what “works” for each consumer in the world.

It is at this point where a better perspective is gained on what will and will not be accepted in the mobile universe. Take a beer pouring app that mimics the pouring of a beer when the device is tilted.  It serves no direct function and yet it has been successful because of the cultural needs it to which it speaks – workplace breaks, male-to-male bonding, etc. But in another context, say Saudi Arabia, the context shifts. Success lies in understanding the reasons behind the consumers beliefs and actions in the symbolic exchanges, and the ability to code and decode those exchanges.  Marketing mishaps come from a lack of comprehension.

So What?

Our great technological leaps forward have also produced more complexity, leading to a greater need to make sense of insights. Without a means to categorize context, marketers will miss identifying trends that matter most. What to do?

  • Rethink the problem. Frequently, “the problem” is a facet of something else. For example, when researching an eBook the problem to be solved isn’t technology, it is understanding why people read different material in different contexts. It may be about displaying books as a means of gaining status. The point is the problem seen may not be the problem at all.
  • Define the contexts. Defining the contexts helps articulate the range of possibilities for observation. For example, if the consumer behavior is drinking beer, all contexts in which beer is purchased and consumed need to be articulated.
  • Think through the sample. Who is the marketing targeting? What are the social circles that will shape the event? It isn’t enough to define a demographic sample, you need to think in terms of cultural systems.
  • Make a plan that involves experiential information gathering, not just statistics. Develop a guide to navigate the data collection and a method for managing the data (everything is data). Don’t  just think about the questions to ask, but also include opportunities for observation and participation.
  • Head into the field. This is the heart of the process. Meaningful insights and moments of “truth” are slow to get at. Low-hanging fruit will be easy to spot, but the goal should be to find those deeper meanings. Because everything is data, from attitudes to artifacts, it is important to capture as much as possible.
  • Do the analysis. Analysis is the most difficult, but also the most rewarding. The goal is to bring a deep understanding of cultural behavior to the analysis process. This goes beyond casual observation and gets to the underlying structures of why people do what they do.

The process is more time consuming than traditional approaches, but it ultimately yields greater insight and reduces time and costs on the back end. The end result is that you create greater value for the client and for the company.

Anthropology and Usability: Getting Dirty

There are significant methodological and philosophical differences between ethnographic processes and laboratory-based processes in the product development cycle.  All too frequently, proponents of these data collection methods are set at odds, with members on both sides pointing fingers and declaring the shortcomings of  the methods in question.  Methodological purity, ownership and expertise are debated, with both ends of the spectrum becoming so engrossed in justifying themselves that the fundamental issues of product development are compromised.  Namely, will the product work in the broadest sense of term. One side throws out accusations of a lack of measures and scientific rigor.  The other side levels accusations about the irrelevance of a sterile, contextually detached laboratory environment.  At the end of the day, the both sides make valid points and the truth, such as it is, lies somewhere between the two extremes in the debate.  As such, we suggest that rather than treating usability and exploratory work as separate projects, that a mixed approach be used.

So why bridge methodological boundaries? Too frequently final interface design and product planning begin after testing in a laboratory setting has yielded reliable, measurable data.  The results often prove or disprove the functionality of a product and any errors that may take place during task execution.  Error and success rates are tabulated and tweaks are made to the system in the hopes of increasing performance and/or rooting out major problems that may delay product or site release and user satisfaction.  The problem is that while copious amounts of data are produced and legitimate design changes ensue, they do not necessarily yield data that are valid in a real-life context.  The data are reliable in a controlled situation, but may not necessarily be valid when seen in context. It is perfectly possible to obtain perfect reliability with no validity when testing. But perfect validity would assure perfect reliability because every test observation would yield the complete and exact truth.  Unfortunately, neither perfection nor quantifiable truth does exist in the real world, at least as it relates to human performance.  Reliable data must be supported with valid data which can best be found through field research.

Increasingly, people have turned to field observations as an effective way of checking validity.  Often, an anthropologist or someone using the moniker of “ethnographer” enters the field and spends enough time with potential users to understand how environment and culture shape what they do.  Ideally, these observations lead to product innovation and improved design.  At this point, unfortunately, the field expert is dropped from the equation and the product or website moves forward with little cross-functional interaction. The experts in UI take over and the “scientists” take charge of ensuring the product meets measures that are, often, somewhat arbitrary.  The “scientists” and the “humanists” do not work hand in hand to ensure the product works as it should in the hands of users going about their daily lives.

Often the divide stems from the argument that the lack of a controlled environment destroys the “scientific value” of research (a similar argument is made over the often small sample size), but by its very nature qualitative research always has a degree of subjectivity.  But to be fair, small performance changes are given statistical relevance when they should not.  In fact, any and all research, involves degrees of subjectivity and personal bias.  We’re not usually taught this epistemological reality by our professors when we learn our respective trades, but it is true nonetheless.  Indeed, if examining the history of science, there countless examples of hypothesis testing and discovery that would, if we apply the rules of scientific method used by most people, be considered less than scientifically ideal James Lind’s discovery of the cure for scurvy or Henri Becquerel discovery the existence of radioactivity serve as two such examples.  Bad science from the standpoint of sample size and environmental control, brilliant science if you’re one of  the millions of to people to have benefited from these discoveries.  The underlying problem is that testing can exist in a pure state and that testing should be pristine.  Unfortunately, if we miss the context we usually overlook the real problem. A product may conform to every aspect of anthropometrics, ergonomics, and established principles of interface design.  It may meet every requirement and have every feature potential consumers asked for or commented on during the various testing phases. You may get an improvement of a second in reaction time in a lab, but what if someone using an interface is chest deep in mud while bullets fly overhead.  Suddenly something that was well designed in a lab becomes useless because no one accounted for shaking hands, decrease in computational skills under physical and psychological stress, or the fact that someone is laying on their belly as they work with the interface.  Context, and how it impacts performance with a web application, software application, or any kind of UI now becomes of supreme importance, and knowing the right question to ask and the right action to measure become central to usability.

So what do we do?  We combine elements of ethnography and means-based testing, of course, documenting performance and the independent variables as part of the evaluation process.  This means detaching ourselves from a fixation with controlled environments and the subconscious (sometimes conscious) belief that our job is to yield the same sorts of material that would be used in designing, say, the structural integrity of the Space Shuttle.  The reality is that most of what we design is more dependent on context and environment than it is on being able to increase performance speed by 1%.  Consequently, for field usability to work, the first step is being honest with what we can do. A willingness to adapt to new or unfamiliar methodologies is one of the principal requirements for testing in the field, and is one of the primary considerations that should be taken into account when determining whether a team member should be directly involved.

The process begins with identifying the various contexts in which a product or UI will be put to use.  This may involve taking the product into their home and having them use it with all the external stresses going on around them.  It may mean performing tasks as bullets fly overhead and sleep deprivation sets in.  The point is to define the settings where use will take place, catalog stresses and distractions, then learn how these stresses impact performance, cognition, memory, etc.  For example, if you’re testing an electronic reading device, such as the Kindle, it would make sense to test it on the subway or when people are laying in bed (and thus at an odd angle), because those are the situations in which most people read — external variables are included in the final analysis and recommendations.  Does the position in bed influence necessary lumens or button size? Do people physically shrink in on themselves when using public transportation and how does this impact use?  The idea is simply to test the product under the lived conditions in which it will find use.  Years ago I did testing on an interface to be used in combat.  It worked well in the lab, but under combat conditions the interface was essentially useless.  What are seemingly minor issues dramatically changed the look, feel, and logic of the site. Is it possible to document every variable and context in which a product or application will see use?  No. However, the bulk of these situations will be uncovered.  And those which remain unaddressed frequently produce the same physiological and cognitive responses as the ones that were uncovered.  Of course, we do not suggest foregoing measurement of success and failure, time of task, click path or anything else.  These are still fundamental to usability.  We are simply advocating understanding how the situation shapes usability and designing with those variables in mind.

Once the initial test is done, we usually leave the product with the participant for about two weeks, then come back and run a different series of tests.  This allows the testing team to measure learnability as well as providing test participants time to catalog their experience with the product or application.  During this time, participants are asked to document everything they can about not only their interaction with the product, but also what is going on in the environment.  Once the research team returns, participants walk us through behavioral changes that have been the result of the product or interface.  There are times when a client gets everything right in terms of usability, but the user still rejects the product because it is too disruptive to their normal activities (or simply isn’t relevant to their condition).  In that case, you have to rethink what the product does and why.

Finally, there is the issue of delivery of the data.  Nine times out of ten the reader is looking for information that is quite literal and instructional.  Ambiguity and/or involved anecdotal descriptions are usually rejected in favor of what is more concrete. The struggle is how to provide this experience-near information.  It means doing more than providing numbers.  Information should be broken down into a structure such that each “theme” is easily identifiable within the first sentence.  More often than not, specific recommendations are preferred to implications and must be presented to the audience in concrete, usable ways.  Contextual data and its impact on use need the same approach.

A product or UI design’s usability is only relevant when taken outside the lab.  Rather than separating exploratory and testing processes into two activities that have minimal influence on each other, a mixed field method should be used in most testing.  In the final analysis, innovation and great design do not stem from one methodological process, but a combination of the two.