Tricia Wang

Editor’s Note: Tricia provides an excellent segue between last month’s “Ethnomining” Special Edition and this month’s on “Talking to Companies about Ethnography.” She offers further thoughts building on our collective discussion (perhaps bordering on obsession?) with the big data trend. With nuance she tackles and reinvents some of the terminology circulating in the various industries that wish to make use of social research. In the wake of big data ethnographer’s, she suggests, can offer thick data. In the face of derisive mention of “anecdotes” we ought to stand up to defend the value of stories.

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image from Mark Smiciklas at Intersection Consulting

Big Data can have enormous appeal. Who wants to be thought of as a small thinker when there is an opportunity to go BIG?

The positivistic bias in favor of Big Data (a term often used to describe the quantitative data that is produced through analysis of enormous datasets) as an objective way to understand our world presents challenges for ethnographers. What are ethnographers to do when our research is seen as insignificant or invaluable? Can we simply ignore Big Data as too muddled in hype to be useful?

No. Ethnographers must engage with Big Data. Otherwise our work can be all too easily shoved into another department, minimized as a small line item on a budget, and relegated to the small data corner. But how can our kind of research be seen as an equally important to algorithmically processed data? What is the ethnographer’s 10 second elevator pitch to a room of data scientists?

…and GO!

Big Data produces so much information that it needs something more to bridge and/or reveal knowledge gaps. That’s why ethnographic work holds such enormous value in the era of Big Data.

Lacking the conceptual words to quickly position the value of ethnographic work in the context of Big Data, I have begun, over the last year, to employ the term Thick Data (with a nod to Clifford Geertz!) to advocate for integrative approaches to research. Thick Data uncovers the meaning behind Big Data visualization and analysis.

Thick Data: ethnographic approaches that uncover the meaning behind Big Data visualization and analysis.

Thick Data analysis primarily relies on human brain power to process a small “N” while big data analysis requires computational power (of course with humans writing the algorithms) to process a large “N”. Big Data reveals insights with a particular range of data points, while Thick Data reveals the social context of and connections between data points. Big Data delivers numbers; thick data delivers stories. Big data relies on machine learning; thick data relies on human learning.

CAUTION

As the concept of “Big Data” has become mainstream, many qualitative researchers from Genevieve Bell (Big Data as a person) to  Kate Crawford (algorithmic illusion, data fundamentalism), and danah boyd (privacy concerns) have written essays on the limitations of Big Data. Journalists have also added to the conversation. Caribou Honig defends small data, Gary Marcus cautions about the limitations of inferring correlations, Samuel Arbesman calls for us to move on to long data. Our very own Jenna Burrell has produced a guide for ethnographers to understand big data.

Inside organizations Big Data can be dangerous. Steven Maxwell points out that “People are getting caught up on the quantity side of the equation rather than the quality of the business insights that analytics can unearth.” More numbers do not necessarily produce more insights.

Another problem is that Big Data tends to place a huge value on quantitative results, while devaluing the importance of qualitative results. This leads to the dangerous idea that statistically normalized and standardized data is more useful and objective than qualitative data, reinforcing the notion that qualitative data is small data.

These two problems, in combination, reinforce and empower decades of corporate management decision-making based on quantitative data alone. Corporate management consultants have long been working with quantitative data to create more efficient and profitable companies.

With statistically sound analysis, consultants advise companies to downsize, hire, expand, merge, sell, acquire, shutdown, and outsource all based on numbers (e.g.Mckinsey, Bain & Company, BCG, and Deloitte).

The risk in a Big Data world is that organizations and individuals start making decisions and optimizing performance for metrics—metrics that are derived from algorithms..

Without a counterbalance the risk in a Big Data world is that organizations and individuals start making decisions and optimizing performance for metrics—metrics that are derived from algorithms. And in this whole optimization process, people, stories, actual experiences, are all but forgotten. The danger, writes Clive Thompson, is that “by taking human decision-making out of the equation, we’re slowly stripping away deliberation—moments where we reflect on the morality of our actions.”

INSPIRATION and EMOTION

Thick Data is the best method for mapping unknown territory. When organizations want to know what they do not already know, they need Thick Data because it gives something that Big Data explicitly does not—inspiration. The act of collecting and analyzing stories produces insights.

When organizations want to know what they do not already know, they need Thick Data because it gives something that Big Data explicitly does not—inspiration. The act of collecting and analyzing stories produces insights.

Stories can inspire organizations to figure out different ways to get to the destination—the insight. If you were going to drive, Thick Data is going to inspire you to teleport. Thick Data often reveals the unexpected. It will frustrate. It will surprise. But no matter what, it will inspire. Innovation needs to be in the company of imagination.

When organizations want to build stronger ties with stakeholders, they need stories. Stories contain emotions, something that no scrubbed and normalized dataset can ever deliver. Numbers alone do not respond to the emotions of everyday life: trust, vulnerability, fear, greed, lust, security, love, and intimacy. It’s hard to algorithmically represent the strength of an individual’s service/product affiliation and how the meaning of the affiliation changes over time. Thick Data approaches reach deep into people’s hearts. Ultimately, a relationship between a stakeholder and an organization/brand is emotional, not rational.

Some people are uncomfortable with the use of the term “stories” to describe ethnographic work. There’s a lot of confusion that stories are the equivalent to anecdotes. Market researchers question if it is a “fad.”  Even in academia, many sociologists shun the use of “stories” because it makes their qualitative work appear less scientific. I was often told to use “cases” instead of “stories.”

There’s a big difference between anecdotes and stories, however. Anecdotes are casually gathered stories that are casually shared. Within a research context, stories are intentionally gathered and systematically sampled, shared, debriefed, and analyzed, which produces insights (analysis in academia).  Great insights inspire design, strategy, and innovation.

NPR has a segment that illustrates the power of Thick Data, featuring Frans de Waal, a primatologist and biologist who just published “The Bonobo and the Atheist: In Search of Humanism Among the Primates”. Through his experiments, de Waal provides evidence to support his theory that a sense of fairness—the groundwork for morality—is not unique to humans. In the above video, de Waal shows two Capuchin monkeys receiving different rewards for performing the same action. The monkey that gets a cucumber becomes very upset when she sees the monkey next to her given a grape as a reward for performing a similar task. In the monkey world, grapes are crack and cucumbers are stale bread.

“If I show the data, which are graphs and stuff like that, people are not really convinced, if you show the emotional reaction, the amount of emotion that goes in there, then people are convinced.” Frans de Waal

In his research statement, de Waal makes a captivating case for the principles of Thick Data: “I show that video often, because if I show the data, which are graphs and stuff like that, people are not really convinced, if you show the emotional reaction, the amount of emotion that goes in there, then people are convinced.”

As de Waal makes clear, sometimes the quantitative data alone will not make a compelling argument. Even scientists need stories to make their point.

OPPORTUNITIES

Roger Margolis, who coined the term Big Data, emphasizes the need for stories: “stories tend to spread quickly, helping spread the lessons from the analysis throughout an organization.”

While using Big Data in isolation can be problematic, it is definitely critical to continue exploring how Big Data and Thick Data can complement each other. This is a great opportunity for qualitative researchers to position our work in the context of Big Data’s quantitative results. Companies like Claro Partners are even reframing the way we ask questions about Big Data. In their Personal Data Economy research, instead of asking what Big Data tells us about human behavior, they asked what human behavior tells us about the role of Big Data in everyday life. They created a toolkit for clients that helps them shift their “perspective from a data-centric one to a human-centred one.”

Here are some areas where I see opportunity for collaboration between the two methods within organizations (this is not meant to an exhaustive or comprehensive list):

• Health Care – As individuals have become more empowered to monitor their own health, Quantified Self values are going mainstream. Health providers will have increased access to collectively sourced, anonymized data. Projects such as Asthma Files provide a glimpse into the future of Thick and Big Data partnerships to solve global health problems.
• Repurposed anonymized data from mobile operators – Mobile companies around the world are starting to repackage and sell their customer data. Marketers are not the only buyers. City planners who want better location-based data to understand transportation are using Air Sage’s cellular network data.  To protect user privacy, the data is either anonymized or deliberately scrubbed of personal communication. And yet in the absence of key personal details, the data loses key contextual information. Without Thick Data, it will be difficult for organizations to understand the personal and social context of data that has been scrubbed of personal information.
• Social network analysis - Social media produces droves of data that can enrich social network analysis. Research scientists such as Hilary Mason, Gilad Lotan, Duncan Watts, and Ethan Zuckerman (and his lab at MIT Media Lab) are exploring how information spreads on social networks and, at the same time, are creating more questions that can only be answered by using Thick Data methods. As more companies make use of social media metrics, organizations have to be careful not to mistakenly believe that data alone will reveal “influencers.” A prominent example of misinterpreting a signal from Big Data network analysis is Cesar Hildalgo’s work that suggested Wikipedia could serve as a proxy for culture. Read Heather Ford’s correction.
• Brand Strategy and Generating Insight – Companies have long relied on market analysis to dictate corporate strategy and insight generation. They are now turning to a more user-centered approach that relies on Thick Data. Fast Company’s recent feature of Jcrew makes clear that where Big Data driven management consultants failed, the heroes that led a brand’s turnaround were employees who understood what consumers wanted. One employee, Jenna Lyons was given the opportunity to implement iterative, experimental, and real-time testing of products with consumers. Her approach resonated with consumers, transforming Jcrew into a cult brand and tripling its revenues.
• Product/Service Design – Algorithms alone do not solve problems, and yet many organizations rely on them for product and service design. Xerox uses Big Data to solve problems for the government, but they also use ethnographic methods alongside analytics. Ellen Issacs, a Xerox PARC ethnographer speaks to the importance of Thick Data in design: “[e]ven when you have a clear concept for a technology, you still need to design it so that it’s consistent with the way people think about their activities . . . you have to watch them doing what they do.”
• Implementing organizational stratgy – Thick Data can be used as a counterbalance to Big Data to mitigate the disruptiveness of planned organizational change. Quantitative data may suggest that a change is needed, but disruption inside organizations can be costly. When organizational charts are rearranged, job descriptions are rewritten, job functions shift, and measures of success are reframed—the changes can cause a costly disruption that may not show up in the Big Data plan. Organizations need Thick Data experts to work alongside business leaders to understand the impact and context of changes to from a cultural perspective to determine which changes are advisable and how to navigate the process. Grant McCracken calls this the Chief Cultural Officer, the “corporation’s eyes and ears, allowing it to detect coming changes, even when they exist only as the weakest of signals.” The CCO is the go to Thick Data person, responsible for collecting,  telling, and circulating stories to keep an organization inspired and agile. Roger Margolis, who coined the term Big Data, emphasizes the need for stories: “stories tend to spread quickly, helping spread the lessons from the analysis throughout an organization.”

FUTURE

We still have a lot of questions to answer for Thick Data inside organizations:

1. How do we report Thick Data up? Stories are effective, but stories require time, resource, and communication skills.
2. What are the indicators for successful Thick Data research?
3. How do we train teams in integrative Big Data and Thick Data approaches? There is greater demand for ethnographers as suppliers/providers than as employees inside organizations. There are not enough ethnographers working inside companies to internalize ethnographic research and to explore different ways to extend the insights of Big and Thick Data.

This is the time for ethnographic work to really shine. We’re in a great position to show the value-add we bring to a mixed-method project. Producing “thick descriptions” (a term used by Clifford Geertz to describe ethnographic methodology) of a social context compliments Big Data findings. People and organizations pioneering Big Data and Thick Data projects, such as Fabien Giradin from the Near Future Laboratory or Wendy Hsu, are giving us glimpses into this world.

So the next time someone talks to you about Big Data, try out your elevator pitch for Thick Data.  I’d love to hear what your experience is–does this term resonate? Do you have a more effective or alternative pitch to share?

In the upcoming months, I will be curating a follow up edition to Nicolas Nova’s Ethnomining theme on how ethnographers are positioning ethnographic work in the context of Big Data. I’m looking for guest contributors, please reach out if you’d like to participate.

In our interview with Steve Portigal this month I asked him about the hierarchy of formality he describes in his new book. For delivering the late-breaking or unprocessed findings (to communicate their informality) he uses e-mail, then Word documents, and finally polished results are delivered in PowerPoint. The ascendence of PowerPoint (not as an accompaniment to a project report, but as the report itself) in corporate settings and consultancy work I find really fascinating. Maybe because of the way it seems to prioritize communicating with as few words as possible, the pressure to edit down to the essentials, to consider what to omit just as much as what to include, how daunting! It seems obvious that this is reflection of the particularly intensive pressures of productivity, of delivering on the short project cycles of the private sector.

The Office suite of applications does not, by any means, encompass the full range of formats that are our options for communicating about ethnographic research. For example, my first job title when I worked in industry (at Intel Corp) was “Application Concept Developer.” My task was to translate research findings from our team of social scientists (who used interviews, observation, diary studies, copious photographs, etc) into interactive design concepts. These were not prototypes, but rather interactive demonstrations showing how insights from fieldwork fed into novel designs for computing systems. This was an attempt to communicate between social scientists and engineers…using the language of building and by engaging through interactivity.

[Editor's Update: since posting this entry, I've been pointed in the direction of this excellent article (another one from EPIC), by Nina Wakeford, "PowerPoint and the Crafting of Social Data" which specifically considers PowerPoint as a format for outputting ethnographic analysis.

Broader consideration of PowerPoint includes:
- this article (stuck behind a paywall) on "PowerPoint in Public: Digital Technologies and the New Morphology of Demonstration" by David Stark and Verena Paravel in the journal Theory, Culture and Society.
- this intriguing looking book titled PowerPoint, Communication, and the Knowledge Society, by Hubert Knoblauch, published by Cambridge U. Press.]

Performing the fieldwork experience for audiences – raw data, transparency, and visuals

Prevailing formats are directly considered and questioned in an article from EPIC 2006 on “Rhetorics of Knowing in Corporate Ethnographic Research” by Dawn Nafus and ken anderson. They describe their own use of direct quotations and photographs from the field to deliver on their research mission to, “uncover new uses for computing power, identify important activities that are not well supported by technology, and understand barriers to technology adoption by studying real people in their natural live environments.” Quotations and photographs were employed to provide a kind of direct and transparent view of research informants who were shown photo-realistically and ‘speaking’ in their own words. Nafus and anderson considered, in retrospect, how their efforts to make ‘real’ and vivid these current and potential users (who were previously invisible non-entities that appeared nowhere in market segments, etc.) inadvertently oversimplified the work they were doing as researchers. These representations of “real” people also seemed to communicate the notion that such people could be straight-forwardly and transparently understood. From the perspective of the audiences they delivered their research findings to (often engineers, generally people not trained in the social sciences) the work they did amounted to (as one of the engineers described it), having “done drilldowns and got verbatims.”

This brings us to another challenge of work of presentations and the use of formats, especially visuals. Their purpose may not just be to make visible the populations being studied, but also to make visible the work of the researcher’s themselves; to establish their authority. The “confessional tale” is well-established in ethnographic writing (see Van Maanen, Tales of the Field). These are often set apart from whatever constitutes the ‘findings’ of the research, but show incidents of struggle or rapport building that demonstrate the difficulty of the work and why the author should be trusted on the matter. The photo of the researcher-in-the-field (often used as a marker of professional identity on websites and visual presentations) is a similar convention. The ethnographer appears somewhere exotic, somewhere distant from everyday life. Though, depending on the image, there’s the risk of making one’s work look too “fun.” Best for such a self-portrait to look studious, holding some sort of tool of data capture (a camera or notebook) or perhaps on an uncomfortable looking mode of transport (maybe something like a camel?).

an ethnographer in the field, but having too much fun?

Of course a format alone doesn’t do any of this automatically. As much as images might lend themselves to easily to misguided assumptions of transparency  and the performance of “I was there” that establishes researcher authority, a photo can, when carefully chosen, also confound in productive ways. I love to find excuses to use this image from Ghana (see below) as a way of explaining and talking about the concept of culture and challenging notions that people and the intent of their practices can be deduced either without interpretation (thus ‘objectively’) or that interpretations can be arrived at easily from a comfy distance.

what could it possibly mean?

Formats in Academic Ethnographic Work

The greatest conformity around format seems to be found in Academic work where text, text, and more text seems to prevail. One’s career and legitimacy as a scholar rests on a series of 8000 word articles or the occasional 100,000 word book with a few images, charts, or tables thrown in for good measure. That said there is an incredible power and flexibility in text, in what you can do with writing. But there also seems to be a kind of ‘path dependency’ at work here. The problem of scarcity in publishing budgets (especially academic publishing) may have made the copious use of visuals or videos too expensive or hard to distribute in the past, but this is no longer the same kind of constraint given possibilities for doing this kind of work on the Internet. There are recent efforts to break beyond this – one small step, is the photo essay series launched by the journal of Cultural Anthropology to offer “alternative forms of critical ethnographic expression.”

Specialization, the division between disciplines, and elitism also do seem to bear some responsibility, I think, for the minimal concern in the Academy with effective communication and consequently the lack of creative consideration around formats of presentation. Without rigid standards of output that scholars are judged on (i.e. the daunting hoop of producing a book-length ethnographic monograph) how will the elites of a discipline ensure that pretenders are kept out? To embrace experimentation is to perhaps let go of or gradually reestablish new criteria for evaluation. This very blog is also a foray into this experimentation, an expression of our desire to try alternate modes and combinations of formats with a goal of communicating more effectively and with a different audience then the ones reached through modes of presentation we normally work in. It works, maybe, because it isn’t rigidly peer reviewed and contributions are generally short and without heavy costs or consequences.

My intention in talking about formats was not to get bogged down (as I seem to have anyways!) in a discussion about text vs. images which implies that there is less to this conversation than I think there really is. Certainly last months ‘ethnomining’ edition is an excellent place to break out of a notion of ‘formats’ as just a matter of one media or another. I’m struck by the data visualizations in the blog posts for that edition and especially their intruiguing ambiguity. Beyond texts (short or long), images of all sorts, a PowerPoint slideset presented by a charismatic speaker, a compelling interactive application concept, a complex and aesthetically rich data visualization, there are surely possibilities waiting to be discovered.

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Editor’s Note: This post for May’s Special Edition on ‘Talking to Companies about ethnography’ comes from Steve Portigal who has a new book out this month titled Interviewing Users. As someone who’s been in the trenches for decades now running his own successful consultancy, Steve has done a great deal of both ‘interviewing users’ and ‘talking to companies about ethnography.’ Below we take the opportunity to interview him! We at Ethnography Matters are also big fans of the ‘War Stories‘ series on his blog where interviewers report on the unexpected things that happen to them in the field.

Steve Portigal is the founder of Portigal Consulting, a bite-sized firm that helps clients to discover and act on new insights about themselves and their customers. Over the course of his career, he has interviewed hundreds of people, including families eating breakfast, hotel maintenance staff, architects, rock musicians, home-automation enthusiasts, credit-default swap traders, and radiologists. His work has informed the development of mobile devices, medical information systems, music gear, wine packaging, financial services, corporate intranets, videoconferencing systems, and iPod accessories. He blogs at portigal.com/blog and tweets at @steveportigal.

Image courtesy of Rosenfeld Media

Ethnography Matters: First all Steve, congrats! We are so excited to have a copy of your book. Before diving into the specific questions, we want to know what motivated you to write this book?

Steve Portigal: Thanks! I’ve wanted to write a book from the time I was a little kid. I didn’t imagine it would be non-fiction, though! A lot of folks in the user experience and design worlds were feeling the need for a good book about this and my name came up as the author they’d want to see something from. I had been talking with Rosenfeld Media for a while about writing something, but it seemed like a daunting commitment. But when your peers are asking for it, it’s pretty compelling!

EM: So which part of the book was the most fun to write? Which part was the hardest?

SP: There were creative and intellectual challenges and rewards all the way along. A lot of the writing process was taking topics I had been speaking about for years and crafting the kind of text that is appropriate for a practitioner book. It was fun to revisit familiar points and find a better way to convey them. And then once in a while I’d hit on something that I maybe would typically gloss over in a presentation and realize I’d better dig a little deeper into myself and find away to explain something. The details of some of those moments are lost to memory, but the part of the process where I was discovering something by articulating it was pretty wonderful.

EM: Nice title, short, sweet and clear. How did you decide to narrow the focus down just to ‘interviewing’ as a method and without also writing in much detail about some of the other methods that so often go along with it in user research oriented towards design innovation – especially observation?

SP: Well, a lot of that is just figuring out what is the right way to talk about “this thing of ours.” For example by naming this blog “Ethnography Matters” you’ve put a stake in the ground not only about the scope of your topic but also the perspective you’re bringing to it. I felt that “going out and talking to users” was the piece of the work that could really benefit from what I had to share. I struggled with “design research” and “user research” and even “ethnography” but they all led in a different direction. I didn’t want to write a book about analysis and synthesis (or theory!); I wanted to write about what happens in the field. I cover a lot of other methods that go with interviewing (e.g., showing off artifacts, diary studies, etc.) but I think the biggest opportunity for readers may be to get better at talking to people.

“Observation” is another one of those popular words when people talk about this work and I never understand exactly what is meant. How many teams are actually going out to simply observe shoppers, pedestrians, farmers or x-ray technicians, without asking questions? That doesn’t seem like a primary approach that the teams I talk to are interested in. Of course, if you are going out to someone’s home or office to interview them, by all means you should be observing what’s going on – that’s the context of contextual research!

EM: This month’s “special edition” of Ethnography Matters is on “how to talk to companies about ethnography.” This is something you obviously have deep and diverse experience with. I was very interested by your proposed hierarchy of formality: e-mail vs. word documents vs. PowerPoint for delivering research reports. How/why do you think PowerPoint has ascended to this position and what it means for the way research is understood and consumed?

SP: Chris Conley has described how modern corporate life is dominated by PowerPoint (along with email and meetings). I can’t speak to the history of adoption that has led to this but it’s certainly the context in which we’re engaging with people in corporations. I was bummed the other day to hear a presentation from a junior researcher inside a major technology company who was creating research decks that weren’t even to be presented, just emailed to the team who commissioned the research. I think the context here is an evolving belief (aka “lean” and its friends) that while we should be talking to customers, we shouldn’t be making a big deal out of it. There’s no time for aligning on objectives, framing the problem and ensuring we have the right people to talk to. There’s certainly no time to deeply analyze the kind of data that comes from research and so it’s not too surprising that the default tools in those types of organizations are the ones that generate the least creative friction. Ultimately, I care less about the formats we use than whether or not we are connecting with people in the organization around what they can do with what we’ve learned.

EM: How much heterogeneity is there between companies / clients? Are there any broad typological characterizations of companies and their attitude towards user research? Does this inform different ways of delivering research results, different ways of “talking to” these companies?

SP: There are no doubt dozens of frameworks (see for example, Jess McMullin’s Design Maturity Model on page 142) for characterizing the organization. But let me throw out a new one: in the Passover Haggadah there is the example of the four sons. One wise, one wicked, one simple and one who does not know how to ask a question. The wise son asks to have all of the history, insight and other findings explained to him. We’re encouraged to explain everything to him. The wicked son separates himself from the issue by asking why it’s important to you. We’re told to tell him why it’s important to us (and not persuade him that it should be important to him). The simple son doesn’t even focus in on the issue and just asks “What is this?” so we’re to give him the headline. We’re told to approach the son who doesn’t even know how to ask a question and take the initiative to explain things to him. And one scholar writes about a fifth son who isn’t even in the room and it’s up to us to seek him out and give him the lowdown.

Sure, it may be a bit forced but it’s not hard to see those sons as archetypes of individuals, departments or entire workplace cultures. Whatever your framework is, you obviously need to understand the specifics of who you are dealing with and have a range of approaches for responding. All of this stuff with people (be they clients or research subjects) is messy and I’m not so comfortable with pre-emptive categorization and its resultant tactical choices.

EM: What’s cool about this book is that a lot of the methods you suggest are used at the company you founded, Portigal Consulting. So what are some of your favorite techniques in the book that you use to train non-ethnographers in ethnographic methods?

SP: I’m not sure if we’re learning ethnographic methods per se, but here’s something simple that always bears fruit. After I share best practices with teams, I ask them to get into groups of three and take turns interviewing, being interviewed, and observing the dynamic between the interviewee and interviewer. Then we debrief. People will talk about what was easy, what was hard, what recommendations they ignored, what tactics they tried, and so on. And of course everyone’s experience will be different so that prompts a great discussion.

EM: In your book you write that “Poor interviews produce inaccurate information that can take your business in the wrong direction…” Can you tell us an example of where you have seen this happen? What were the consequences of that bad interview?

SP: Well, most of the time when I’m involved I like to think we’re not doing poor interviews! A long time ago we had done some work with a client and the results had really changed how they were thinking and talking about their customers, their product category and indeed the overall opportunity. And they called us up a few months later clearly in a bind: they had purchased video cameras and gone out and talked to a bunch of customers and they were hoping we could do some of that there magic stuff we do by taking their videotapes and telling them what the results were! Their inability to draw any conclusions from their presumably poor research was maybe the only thing that kept them from taking their business somewhere they shouldn’t! Another client started off our project by showing me the evolution of their product with the specific changes they had made because customers had asked for them. They had no design process and were just bolting on features and functionality, all as close as possible to directly implementing the requests anywhere they could fit them. They had been “listening” to customers but they had no process in place for either understanding the real need behind the request nor for synthesizing those needs across different customer types. They had no design strategy. They had really tied themselves up pretty badly and didn’t have any idea where to go from there.

EM: In Grant McCracken’s introduction to your book, he says that “Ethnography has suffered terribly in the last few years. Lots of people claim to know it, but in fact the art and science of the method have been badly damaged by charlatans and snake oil salesmen.” You’re definitely not a snake oil salemen so that’s a good reason to buy your book. So why has ethnography suffered so much in the past few years? What have you seen happen?

SP: As I mentioned before, I am seeing a lot of teams under unrealistic time pressure that prevents them from doing the kind of team communication, reflection and creative processing it takes to do this well. But I don’t think that’s the suffering Grant is talking about. I suspect he’s referring to the embracing of ethnography (although please substitute “innovation” or “design thinking” or whatever you like) by the business press and by business. The media has been regaling us with examples of big brands, sexy companies, and breakthrough products. Some aggressive folks will always pick up the scent of opportunity and do what it takes to cash in on it. It always seems to be about decomposing human behavior into an easy-to-understand rule system (with phrases like “cracking the code” or “why we buy” or “how we decide”). While there is some compelling research that’s part of this trend, there’s also a lot of horsefeathers (can I say “horsefeathers” on this blog?). In both cases (the folks who won’t give this work the time it requires and the folks that are selling magic beans) the commonality is the denial that gaining a new understanding of customers and designing a breakthrough solution is very hard.

EM: Our contributing editor, Rachelle Annechino wrote up a great post of interviewing tips for people who are introverted. So what are some tips that you have for introverts?

SP: That is definitely a great post! I know they come from Rachelle thinking about herself as an introvert, but I think what she’s written is simply good technique. She’s highlighted how defaults for an introvert are actually advantages and that’s important for reassuring introverts. But she’s also illustrating some things that extroverts don’t do as naturally that they should be doing.

I can certainly relate to the challenge of interviewing as an introvert. I have a clear memory from a couple of years ago where I hadn’t been in the field for a long time and just about having a panic attack as we went up to the door! Anyway, here’s some things that might help introverts

• Go with someone else. This is also good technique, but I think for introverts it has the advantage of reducing some of the stranger-stress
• Keep in mind that it’s just 2 hours out of your life. It will be over in 2 hours and one minute. So keep it in perspective
• Use the classic introvert coping tactic of playing a role. Interviewing is such a great fit because indeed you are playing a role. We don’t interview people the way we talk to them in real life, so the person you are presenting yourself as is you-as-interviewer. All your props (release forms, video camera, etc.) all support that role

EM: On page 8 in your book, you have a really good paragraph about the limitations of interviewing,
“Interviewing isn’t the right approach for every problem. Because it favors depth over sample size, it’s not a source for statistically significant data. Being semi-structured, each interview will be unique, making it hard to objectively tally data points across the sample. Although we are typically interviewing in context, it’s not fully naturalistic. A tool that intercepts and observes users who visit a website is capturing their actual behavior, but sitting with users and having them show you how they use a website is an artifice. Interviews are not good at predicting future behavior, especially future purchase intent or uncovering price expectations. Asking those questions in an interview will reveal mental models that exist today, which can be insightful, but won’t necessarily be accurate.”
Do clients have unrealistic expectations about interviews? How do you see this play out?

SP: I met a CEO at a pitch meeting who demanded examples of when I had provided a new insight to a company and they had turned around and created an iPhone-scale game-changer of an innovation. Umm, how often have there been innovations like that? While we can agree that ethnographic research (or similar) could be an essential ingredient in that type of business success, there’s a huge burden on the organization that has to innovate based on those insights. Why would you hold your insights vendor accountable for that outcome?

At any rate, all projects start off by uncovering objectives and exploring the best way to address those objectives. I wouldn’t say that most folks are unrealistic, maybe just appropriately naïve. For example, I once worked with a “paper path engineer” at a printer manufacturer who wanted interview subjects to express a preference between a top-feed or side-injection (or something technically specific but otherwise arcane). I was touched by his eagerness for user-centered design but I had to work with my direct client to help them all get some clarity about what we were going to ask and what we were going to learn and how that was going to inform their design decisions.

EM: Ok we have to ask this question – why the picture of three young men playing the drums in a marching band on page xvi?

All Rights Reserved

SP: All my photographs from actual user research are confidential (and typically not that well composed) so we decided instead to use my street photography showing pictures of people doing the ordinary things that people do. While not artifacts from the interviewing process, we felt they represented the same philosophy of finding fascination in the mundane. Of course, you may see something different in those images!

EM: What is the craziest thing that has happened during an interview?

SP: Sharing stories about what happens on when you’re in the field is such a great thing for practitioners to be doing for each other. I’ve been curating a series of War Stories on my blog where different researchers relate the different experiences they’ve had. (And I’m always interested in more, so let me know if you’ve got one – ). My War Story – It’s All Going to Burn – is about a research participant who eventually became more interested in proselytizing than answering our questions and it was quite a struggle to extricate ourselves without betraying the rapport that we had worked so hard to create. The participant was certainly not honoring that relationship, but I still felt like I had to. It was profoundly uncomfortable but certainly hilarious afterwards.

EM: In your 18 years in this business, what has been some of the biggest shifts that you have witnessed in the field?

SP: When I entered the field, it was barely a field. There was no community, there were few people practicing, and there wasn’t a lot of demand for the work. I think the growth in the user experience field, through the web and then mobile devices has really pulled us along. Of course, there are researchers working in categories I have less visibility into so their shifts would be different. I saw insights about customers regarded as a luxury in the 2001 recession and thus low demand; but in 2008 companies talked about trying to innovate their way through the downturn and so insights and design were no longer expendable ingredients in product development.

EM: Thanks for allowing us to interview you! How often do you get to experience this role reversal?

SP: Not often enough. I think it’s such a great experience for interviewers to be interviewed. About 2 years ago I had two back-to-back experiences in being interviewed. One was about a piece of software I was struggling with. The other was about my professional trajectory. In the first, I felt like dirt. In the second, I felt like a superstar. I still haven’t really worked it out but it made me think about how, despite of our great rapport and stellar empathy, the things we’re asking people to talk about are going to have a real impact on them. Of course, I feel great about this and appreciate all your thought-provoking questions

Ethnography Matters readers can take advantage of an exclusive 20% discount off the list price of Interviewing Users: How to Uncover Compelling Insights­. Use the coupon code ETHMAT2013 upon checkout when ordering the book through the Rosenfeld Media website.

David Ayman Shamma

Editor’s note: In the last post of the Ethnomining‘ edition, David Ayman Shamma @ayman gives a personal perspective on mixed methods. Based on the example of data produced by people of Egypt who stood up against then Egyptian president and his party in 2011, he advocates for a comprehensive approach for data analysis beyond the “Big Data vs the World” situation we seem to have reached. In doing so, his perspective complements the previous posts by showing the richness of ethnographic data in order to deepen quantitative findings.
David Ayman Shamma is a research scientist in the Internet Experiences group at Yahoo! Research for which he designs and evaluate systems for multimedia-mediated communication.

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There’s a problem we face now; the so called Big Data world created an overshadowing world of numerical data analysis leaving everyone else to try to find a coined niche like “small data” or “long data” or “sideways data” or the like. The silos and fragmentation is overwhelming. But really, it’s just all data. Regardless of the its form or flavor, there are people who are experts at number crunching data and people who are experts at field work data. Unfortunately, the speed at which data science moves is attractive and that’s part of the problem; we don’t get the full picture at speed and everyone is racing to produce answers first.

A few months ago, in a conversation with a colleague, he told me “you don’t know what you don’t know, especially when it’s not there.” We were looking for a way to automatically surface a community of photographers on Flickr who didn’t annotate their photos. They didn’t use any titles or tags or any annotations what so ever. But they were clearly a strong and prolific community. If there was some way to automatically identify them, then we could help connect them.

Now, finding metrics for social engagement in unannotated data is not an impossible task when provided with some signal in the data that has some correlation, statistical or otherwise, to the effect you’re trying to surface. But in some cases, it’s just not possible. What you need is just not there; therein is a problem. In other cases, it’s much harder to surface features when you don’t know what they look like.

When you have a lot of data, finding that unexplainable prediction through algorithmic statistics becomes easier. It doesn’t explain why and it doesn’t always work.

Enter Ethnography to answer the why and find out what things might look like—surfacing findings in the age of big data. When I was invited to write a post on Ethnography Matters, I decided to illustrate this through a personally motivated example.

In the late January of 2011, the people of Egypt stood up against then President Hosni Mubarak and his National Democratic Party. They wanted employment, a fair government, and an end to the 30 year long emergency law which had removed most of their civilian rights. Undoubtedly, you read about it somewhere. At the time, my mother was in Cairo visiting her 100+ year old mother. So this left me glued to the only source of news I could find—a rather buggy Al Jazeera video stream. U.S. news agencies were slow to start some sparse coverage. Somewhere in-between, it was burning up on Twitter.

A visualization of Twitter activity directed towards Tahrir by aymanshamma

Immediately, there was a problem: The #jan25 hashtag created a maelstrom on Twitter, all the while, in an act that was as simple as powering off a server closet, the Internet had been cut from the majority of Egypt. Twice a day, I’d call to the landline in my grandmother’s chateau and read the current news to my mother. All they had was the state run TV which was running B-roll from the 90s of Tahrir and reporting everything was fine. After I told her what was happening in the news, she’d fill me in to what was going on in-situ.

Now, at the time, my day job had me researching the shape of live events and TV shows on Twitter; I switched my corpus to the revolution. There was a lot of data. Tweets, retweets, hashtags, URLs, news stories and photos (both authentics and fakes), and people communicating at mass. The news agencies went a fuss with a revolution facilitated by social media. News reports varied from the west, claiming social media created the revolution, to the east, citing several social & economic factors which predicted the eruption.Two dynamics were at play. First, to be clear, the online community curation described by Wael Ghomin and the extension of the April 6th movement was surely a force factor. However, on the ground, I was hearing another story. The accounts on how people communicated and acted without SMS, cell phones, or the Internet.

What is it that we don’t know? I’ll start with two questions.

• First, how do people congregate in growing numbers without technological infrastructure.
• Second, how do people communicate without technology.

Over the next year I spoke with many people from relatives to friends from random Egyptians to a documentary filmmaker who had captured hours of footage and interviews during the uprising. All to see how people organize and communicate under distress when technology is cut and hence what we can’t measure from looking at the data itself. Both these questions were answered rather uniformly amongst everyone.

And so I asked people, how did you wind up in Tahrir Square? It became apparent that congregation is rather obvious. People were heading downtown on foot. It’s winter, so its not hot out. At some minimal mass, one will start to notice a lot of people moving or migrating in a direction if you’re looking out your window to check on what’s that sound. Social media, cell phones, word of mouth all contributed here.

Tahrir Under Revolution photos by حسام الحملاوي CC BY-NC-SA 2.0

That first day was impressive as the square overfilled in a police state where congregation is illegal. Unable to comprehend what was happening, the government shut off the Internet and cellular service and took over Egyptian run satellite TV. There was no cell, no SMS, no Internet, no email, no social media with some minor exceptions. A few savvy people pointed their dishes to pick up other TV providers or had cell coverage through some lesser 3rd party networks.

The next day the crowd grew in numbers. Where are these people coming from? Obviously, if you turn off the Internet and take over the TV, you’ll spend more time looking out the window. You’ll see protesters marching to the square. Curious, many people left their homes to follow them. Not to protest but just to see what’s going on. To spectate.

I found that the transformation from spectator to protester is critically dependent on one thing: a police force that does not differentiate between the two. Spectators watch as police as they took action against the protesters. And then the police turned action to bystanders. People spoke about no longer being spectators. They were participants in a protest by virtue of ocular proximity. The next day, they return to scene as part of the cause. More people in migration, more new spectators follow. And so the revolution grows in number.

Of course this isn’t the only factor. I spoke with one person who went to the square after Mubarak gave a speech days into the protest where he claimed to Egypt ‘you are all my children.’ This drove him to the protest which was peaceful and quiet until a mass of weaponized men on horse and camelback swarmed into the crowd. This person told me it was the moment he felt most betrayed by the government. He too said this made him realize he was now part of the revolution.

Curfews and access military checkpoints appeared over this time frame. A game started amongst the people: get past the checkpoints to fetch a photo with a tank in Tahrir. At this time, gang riots broke out (though most everyone felt they were staged by the government). The first night, one person told me, the whole street was looted by motorcycle gangs. Every shop. Every place. ATM machines broken open. Big burly guys on motorcycles speeding off with new ladies handbags by the dozen. His neighbor upstairs was yelling from the window “thieves thieves.” And he was speaking back to her from the neighboring balcony back “Shhh! Don’t or they will break in here.”

The next morning in Mohandessin, an area of Giza, they stepped outside and quite walked around to find people who looked like neighbors—simply put, people that looked familiar. They met and grouped up on the street. One person asked if everyone was armed. He said “I don’t have any weapons.” The neighbor goes into his garage, comes back and hands them metal plumbing pipes. They barricaded the street and used a local passwords to let people in and out. The first night was rough but they secured the street.

By the end of the week, the whole neighborhood of Mohandessin was locked down by the community with barricades and passwords and safepoints. This was happening all over Cairo and in other cities. One longtime resident of Alexandria told me he had passwords for pretty much the whole city. Though oddly never bothered to get the password for his own neighborhood which caused him to get stopped; he figured he’d know the person on guard.

Almost everyone said local TV started the endeavor with a call on the now more independent state run news for local watch groups. The reporters were suggesting people band together to save the city from the criminals. Information disseminated from building to building through communication organization. A local shopkeeper or a neighbor who would make connections and then build the information network thusly. By the end of the first day, blocks would be civilian protected and by day two the city was self policed.

Tahrir Post Revolution by aymanshamma

Cairo rapidly became a mesh network of community safe houses, checkpoints, and passwords. People organized night patrols to ensure safety, but they were faced the problem of with communication and coordination in a dense city with no cell phones or SMS or even CBs. Instead, people around the city turned to using the city itself for communication. They’d organize a few groups to patrol. Each group would have a different sort of “weapon”: pans, pipes, sticks, and the like. A few groups would be “at large.” So a patrol on a beat might need help or see a disturbance. They would sound a percussive alert by banging whatever particular device they were carrying.

Sound doesn’t travel well in a dense urban city, unless you have a good vantage point to hear. Cairo is a city of minarets, and that was the solution. The towers where muathen once stood to call people to prayer have all been modified with amplified loudspeakers. In a city where you’re never too far from a mosque, minarets provided ample coverage to relay information. The people walking beats used noisemakers signal local disturbances; each noise was a signature for a neighborhood. In the air, people were coordinated by the amplified verbal signals moving from minaret loudspeaker to minaret loudspeaker.

Discovering how communities organize, grow, and communicate under times of distress is difficult even when technology hasn’t been cut. While many things surfaced on Twitter during the revolution, like the Hardees in Tahrir being used as a safe house, many questions were left unexplained or assumed to be the work of online social networking.

This is where ethnography matters–by surfacing what to look for in the big data and highlighting what might be salient trends and features despite not being dominant. And mostly, by identifying people’s motivations and giving a deeper understanding of why things happen. From there we can start to unravel the complex communication structures at play and define new metrics informed by human action. The effort is ongoing, as we surface what has been done and what we now know through, it still says we don’t know.

It’s not a race, it’s a partnership, a marriage. The goal isn’t to get to the end as quickly as possible but rather to work together over time and build a richer world. We should strive to find these links between the quantitative and qualitative, and leave the silos which have us fragmented as a research community.

Rachel Shadoan

Editor’s note: This post for the April ‘Ethnomining‘ edition comes from Rachel Shadoan and Alicia Dudek. Following on the past posts about hybrid methods, this one features another interesting case study involving an on-line role-playing game. Their work correspond to a different approach, based on visualizations, than what we saw in the two previous posts.

Rachel Shadoan @RachelShadoan likes to find answers to interesting questions, and build interesting things using those answers. Currently she is answering interesting questions in the Intel Labs using a combination of data visualization, data mining, and ethnographic techniques.

Alicia Dudek

Alicia Dudek @aliciadudek is a design ethnographer and user experience consultant. Her passion is  finding unusual solutions to the usual problems. Currently, she is finding unusual solutions for Deloitte Digital, where she specializes in engaging stakeholders in research insights through participatory design workshops.

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This is one of the visualizations we created for the research. The horizontal axis is date; the vertical axis is time of day as recorded by the Plant Wars server. Each mark on the chart represents a single instance of in-game training. In Plant Wars, a player can train their plant in one of three areas–speed, defense, or attack. The different colors of the marks corresponds to the characteristic being trained, while the radius of the mark encodes the number of stat points received from the training. The time shift can be seen clearly in this visualization: prior to June, this player starts playing in earnest around 16:00 server time. By October, the player has somewhat settled on starting play around 10:00 am.

A few weeks into our study of Plant Wars, an online text-based fighting RPG developed by Jon Evans of Artful Dodger Software, we encountered a mystery. We had visualized the server log data that records the players’ in-game activities, and discovered a pattern as obvious as it was inexplicable: in June 2009, the top Plant Wars players began slowly shifting the time of day in which they were playing. Over a period of six months, the time that the top players started playing each day shifted by nearly six hours. We poured over the server log data, checking the processing code for errors, for time zone issues, for any possible explanation of this shift in play pattern. Using only the server log data, we came up empty-handed. What was going on?

This mystery appeared during our final project for an MSc in Design Ethnography at the University of Dundee, in which we were exploring research techniques that make use of the strengths of both numbers and stories. During our time at Dundee, we had encountered the work of ken anderson, Dawn Nafus, Tye Rattenbury, and Ryan Aippersprach of Intel [1], in which participant tracking data was visualized and incorporated into ethnographic interviews as a scaffolding for participants to hang their stories on. This approach appealed to us, as it leveraged Rachel’s background in computer science and Alicia’s passion for visual communication, so we began looking for an opportunity to explore its possibilities.

Time, however, was limited—we  knew we would be unable to build tracking software, track participants, analyze the data, and conduct an ethnography in the span of the few months we had to complete the project. Thus, we needed an opportunity with existing data stores. The Plant Wars developer, whom Alicia knew from her undergraduate days, was kind enough to open his system logs to us for visualization and analysis, and his player community to us for interviews and co-design.

Thus, we embarked on a study to understand both how the Plant Wars players played and why they played. Visualizing the data generated by the player’s in-game actions provided the map, answering the how and what questions. Interviewing the participants and participating in the game ourselves provided the key to that map, answering the why questions.

Before embarking on the data analysis, we announced the research to the player community and offered the opportunity for players to opt out. One of the players declined to have his data included: Jon stripped his information from the data before transmitting it to us for analysis. The data, spanning from January 2009 to June 2010, was a time stamped record of each action a player took, from training their plant for battle to participating in the in-game marketplace. The most frequent players could have 50,000 instances of training or more. Once we had the data, we processed it using Java. Largely, this consisted of reading in the text files exported from the server, splitting each user’s data into separate files, and translating the timestamp from 12-hr time to 24-hr time. Once that was completed, we began experimenting with visualization. Because the Plant Wars community was spread across the world, most of the interviews we would be conducting remotely. For this reason, we looked at creating web-based interactive visualizations. We cycled through a variety of tools, finding prefuse flare to be too slow to handle as many data points as we had and processing a bit to involved to learn within our time constraints. In the end, we put interactivity aside, settling on the unlikely Microsoft Excel. Excel gets short shrift as a visualization tool, but we found it to be both powerful (it could handle half a million data points, with a tolerable amount of whirring and laptop-gear grinding), and flexible.  Instead of aggregating and abstracting the data, we opted to keep the visualizations as close to the player activity as possible. Using date as the horizontal axis and time of day as the vertical axis, we plotted each instance of player activity, watching the players’ daily patterns evolve over time. We constructed two varieties of visualizations. One variety used data from the whole community, the other, only an of individual player’s data. The cross-player visualizations we found to be interesting but not revelatory, especially considering the difficulty in dealing with visualizing the large number of data points. The visualizations of individual player’s patterns soon found their way into interviews.

Meanwhile, on the ethnographic side of the fence, we were immersing ourselves in the Plant Wars experience: playing Plant Wars, participating in the forums, and building relationships with other players. As we developed a feel for the community, we sought out particular players for interviews. Once a player had agreed to an interview, we created a series of visualizations of that player’s data, showing their training and battling behavior over time. The interviews, most conducted by Skype, were divided into halves: we began with open-ended discussion of Plant Wars and gaming in relation to the player’s life. Then, utilizing screen-sharing, we introduced the the data visualizations, asking the participant to explain the patterns therein. We used those stories to annotate the visualizations, creating artifacts that present both the how and the why of the patterns present.

This is the participant that solved the mystery for us. The shift in time, present not just in his playing patterns, but also in the patterns of the other top players, turned out to be a result of this player graduating from high school and adopting an erratic sleep schedule.

Which brings us back to our mystery. After much angsting over the possible cause of the strange time-shift in the patterns of the top Plant Wars players, we posed the question in the interviews. One of the top players, a mathematician whose careful training ratios are beautifully explicit in his visualized data, agreed with us that it was likely some bizarre bug in our processing code, or perhaps a server migration. It wasn’t until interviewing another top player, who had graduated from high school in June 2009, that we identified the true cause. After graduating, he told us, his sleep schedule had become much more erratic. Because the top players have few other challenging sparring partners in the game, their sleep schedules had shifted along with the recent graduate’s, so they would be able to battle each other. In the end, the relationships the players had with each other was the driving force behind that–and many other–patterns in their play.

In the end, the visualizations helped us access a world of player strategy and interaction that we would otherwise never have known existed. They provided the launching point for questions we didn’t even know we wanted to ask. But without the accompanying ethnography–the stories to hang on the visualization’s patterns–they’re just pretty pictures, providing little special insight of their own.

[1] Anderson, K., Nafus, D., Rattenbury, T. and Aipperspach, R. (2009), Numbers Have Qualities Too: Experiences with Ethno-Mining. Ethnographic Praxis in Industry Conference Proceedings, 2009: 123–140. doi: 10.1111/j.1559-8918.2009.tb00133.x

Check out past posts from guest contributors! Join our email groups for ongoing conversations. Follow us on twitter and facebook.

Fabien Girardin

Editor’s note: This post for the April ‘Ethnomining‘ edition comes from Fabien Girardin @fabiengirardin who describes his work with networked/sensor data at the Louvre Museum in Paris. Based on this inspiring case study, he discusses the overall process, how mixed-methods are relevant in his work, and what kind lessons he learnt doing this.

Fabien Girardin is Partner at the Near Future Laboratory, a research agency. He is active in the domains of user experience, data science and urban informatics.

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Visitor congestion at the Louvre Museum, picture by Fabien Girardin

At the Near Future Laboratory we like to experiment and to go in different directions from the typical technology consultancy. We thrive on the involvement of multiple practices, and bet on the unordinary when it comes to question formulation, data collection and solution creation. After completing my PhD in Computer Science, I left the bounded disciplines of academia to embrace learning and connecting to the other “fields”, the other ways of knowing and seeing the world. Along with partners Julian Bleecker, Nicolas Nova and a network of tactical scouts, we formed a technology-based practice that combines insight and analysis, design and research, and rapid prototyping to transform ideas into material form.

Over the past 5 years, I have led investigations that aim to extract knowledge from the byproducts of people’s digital activities (i.e. network data, also often called digital shadows or digital footprints). That intangible material can take the form of logs of cellular network activity, aggregated credit card transactions, real-time traffic information, user-generated content or social network updates. Over time my contributions have evolved into helping transform this type of big data into insights, products and services. Whether applied for a client or as part of our self-started initiatives, this practice requires the basic skills of a “data scientist” (data analysis, information architecture, software engineering and creativity) along with a capacity to engage at the intersections with a wide variety of professionals, from physicists and engineers to lawyers, strategists and designers. The transversal incline of investigations on network data requires understanding the different languages that shape technologies, reporting on the context of their use, and describing people’s practices. The model of inquiry blends qualitative field observations with quantitative evidence often extracted from logs.

The investigation with network data involves multiple practices and skills from engineering, to statistics, design, strategy planning, product management and ethnography; picture by Fabien Girardin

Past projects have led us to exploit untapped data sources, uncover opportunities to transform data into insights, and materialize new services or products. Our method first contemplates datasets and techniques to approach our objectives. Then we develop tangible solutions that engage the project stakeholders in exploring different scenarios and solutions. It is through the experiences of  people with knowledge of the project domain that we are able to extract possible near-future changes and opportunities.

Practically, I like to showcase our project for the Louvre Museum a couple of years back. Not only because I have fantastic memories of the breathtaking environment, but mainly because we learned a lot from the use of network data to provoke qualitative knowledge.

The Louvre is by far the most visited museum in the world with 8.5 million visitors and more than 40.000 visitors on peak days [1]. In Paris, it is one of the main drivers of the “cultural enthusiasm” that is an inherent feature of the city.  In consequence, the museum witnesses levels of crowding that, beyond a certain threshold, can be described as “hyper-congestion”. This phenomenon has some direct negative consequences on the quality of the visitor experience as well as on the organization and management of the Museum (e.g. increased stress level of the security staff).

The Study, Evaluation and Foresight Department of the Museum performs extensive surveys, audience analysis and on-site observations to ensure a good visiting experience. However, the information they collect only partially feeds the visitor flow models necessary to setup and evaluate some of the museum strategies. That was the reason they approached us. They wanted to investigate new solutions to their concerns with “hyper-congestion”. In response, we (1) investigated the collection of new empirical data on the flows and occupancy levels of visitors in key areas of the Louvre, and (2) developed diagnostic indicators to capture changes in visitor behaviors relative to the congestion in the museum.

In collaboration with our friends at the real-time traffic information provider BitCarrier, we designed sensors that audited the presence of Bluetooth-enabled mobile phones on a key trail that leads to the Venus de Milo. The analysis of the collected longitudinal measures of presence and flows of visitors led to the development of an indicator that unveiled areas in which the congestion of a room changes the presence and flow of visitors. While unprecedented in the history of the Louvre, some results produced more questions than answers. We faced a new set of inquiries that quantitative evidence from sensors could not answer, but that field observations could address. For instance, what events provoked the congestion, what aspects of the visiting experience were affected, and why did some rooms show no symptoms of hyper-congestion?

Location of the sensors at key areas of the museum; picture by Fabien Girardin

We returned to the visualizations produced as part of our data analysis. Yet this time, we did not prepare them for the decision makers but for the security staff. They were a unique source of on-site information on visitor practices and flow management strategies — an unstructured contextual knowledge that only specific questions help expose. So we setup meetings at the museum and used our data visualizations to have the staff qualify the results of the audits. Their evidence explained some irregularities and completed the understanding of visitor behaviors. For instance, a door periodically closed was a source of radical changes in visitor flows.

A security officer at work at the Louvre; picture by Fabien Girardin

In that experience, we learned the types of questions that analysis of network data can answer. For instance, “how many observations can we produce”, “what do the data tell us about a population”, “what kinds of evolution can we measure over time”, “can we categorize these evolutions”, “what are the trends and the outliers” or “what are the flows that connect different places”. In the context of network data however, it is a big assumption to see the world as consisting of bits of data that can be processed into information that then will naturally yield some value to people. Quantitative data analysis and visualization techniques will answer some questions but prompt many more. Indeed, the understanding of an environment such as the Louvre goes beyond logging machine states and events. In consequence, my work takes a critical perspective on the limitless capabilities of Big Data that some assume . At this stage we are still often trying to figure out: 1) What parts of reality can quantitative data reveal? 2. What we can do with this limited view of reality?

Early in the process, analyzing the relationship between the level of congestion and visitors’ staying time at key areas of the museum; picture by Fabien Girardin

The qualitative view from the staff at the Louvre reinforced the quantitative measures and consolidated our overall knowledge of hyper-congestion at the museum. In other words, the articulation between qualitative insights and sensor measures enabled us to refine our understanding of the phenomenon. However, I have not seen yet a set of good practices for using quantitative data mining to inform qualitative inquiries, or for using qualitative observations to inform the definition of quantitative queries.

These questions suggest that researchers and practitioners need to develop a coherent dialogue between the techniques used to collect information about people’s activities: both qualitative (e.g. audio and video recordings of action and interviews) and quantitative (e.g. network data). Besides in the work at the Louvre, I often find it necessary to be able to visualize temporary results very quickly, and communicate them to project stakeholders. In the industry, this kind of exploratory investigation needs to maintain a certain momentum; it needs to fail, fork or succeed early. As a consequence, more and more results of our investigations became interfaces or objects with a means of input and control rather than only static reports. This practice calls for its own set of tools to manipulate and visualize data.

Quick “sketch” in Quadrigram to share with the project stakeholders some early measures of occupancy levels and visitors flows; picture by Fabien Girardin.

At Near Future Laboratory we were struggling to combine tools that could allow our clients who have knowledge and data but not technical skills to prototype their own solutions and scenarios. That is until our friends at Bestiario  showed us a visual programming environment they were developing. We naturally contributed to what now has become Quadrigram, a tool specifically designed for iterative data exploration and explanation. Each iteration or “sketch” is an opportunity to find new questions and provide answers with data. Data mutate, taking different structures in order to unveil their multiple perspectives. For us, in our research process Quadrigram offers the opportunity to manipulate data as a living material that can be shaped in real time. This capacity not only concerns ‘data scientists’ but rather everybody with knowledge and ideas in a project that involves data.

Quadrigram is a visual programming language particularly designed for iterative data exploration and explanation; picture by Fabien Girardin.

It might be obvious to a community of ethnographers, but quantitative data are not sufficient to give full answers about people, their behaviors and their usage of technology. Yet the world of ‘data science’ and computer science still lacks sensitivity to the limitations of quantitative evidence and the models we can build from it. I have often been confronted by these limitations. Several of our projects with network data taught me that there are insights that only the articulation of sensor data and in-situ observations can provide.

On a more general level, the Louvre project confirmed our use of an approach that is closer to the academic researcher’s than to the consultant’s. It implies staying humble, not starting an investigation with a priori assumptions, and not being afraid to express doubts. When it comes to mixing techniques and methods, this posture of the researcher driven by doubt, but also confident in his/her methods, is what drives relevant insights.

……….

[1] Figures of 2009 when we performed the project

[2] See for instance The End of Theory: The Data Deluge Makes the Scientific Method Obsolete by Chris Anderson

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Rebekah Rousi

Editor’s note: This post for the April ‘Ethnomining‘ edition comes from Rebekah Rousi, @rebekahrousi who describes how the combination of qualitative and quantitative data collection was fruitful in her analysis of elevator usage. The post highlights the lessons she uncovered using both approaches.

Rebekah is a researcher of user psychology and PhD candidate of Cognitive Science at the University of Jyväskylä, Finland. With a background in visual arts and cultural studies, she is particularly interested in the psychology of user experience, affective human-technology interactions and the mental factors of design encounters.

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I don’t know who was more moved by the experience of elevator design, me or the 50 people I interviewed. A few years ago a leading elevator design and manufacturing company gave me the task of examining how people experienced and interacted with elevators. The scope included everything from hall call buttons, to cabin interior design and perception of technical design. When given the brief, the artistic director noted country specific design features (or omissions) and even mentioned that there may be observable elevator habits I would want to take note of. Then, on our bidding a corporate-academic farewell she added that I might want to consider the psychology of the surrounding architectural environment. With that, I was left with a long list of to-do’s and only one method I could think of that would be capable of incorporating so many factors – ethnography. Ethnographic inquiry provides a framework in which the researcher’s own observations and experiences of the phenomenon under study – in this case elevator users’ behaviour in relation to the elevators, other users and the surrounding architectural environment – can be combined with “insiders’” opinions and insights.

Westpac House Entrance; Picture by Rebekah Rousi.

Grenfell Centre entrance; Picture by Rebekah Rousi.

So, I undertook the study in two of Adelaide’s (Australia) tallest office buildings (see the building entrances above). I chose these buildings for several reasons: 1) they are both highrises in which elevator usage is a necessity; 2) they are both non-residential office buildings in which factors such as occupational well-being, health and safety, and socio-cultural dimensions including power relations and hierarchies come into play. In order to gauge and explain user behaviour in relation to the tangible and non-tangible dynamics of the spaces, it is necessary to study sites which are similar in purpose. Further, both buildings housed the same brand of elevators. And both had only recently undergone elevator upgrades.

The data collection consisted of two separate parts: the mini-interviews (or verbal questionnaires) which lasted two to five minutes; and the field observations. The mini-interviews comprised the following topics: background information; mental factors such as current mood and personality type loosely based on the Myers-Briggs Type Indicator (social, organised, intuitive and analytical); Likert-scale opinion rating of elevator design elements; design suggestions; preferences (elevators or stairs?); security and safety; and habits. The components I was looking at in the field observation were: waiting and operating habits; interaction with design; interpersonal interaction; and movement flow.

The observations were broken down into blocks in which I either sat outside the elevator banks watching people enter and exit elevators, or travelled up and down – attempting to blend in with the other users. It is debatable as to whether this is cause for ethical concern, as elevator users were not fully aware that I was studying them. However, the buildings’ occupants had been informed of the study beforehand. Some people even recognised me as the researcher who had come to spend a few days riding in the elevators. But, at least using the elevators myself made me understand the elevator experience from the position of a user. Other points of observation included the interior architecture and design of the ground floor lobby. Additional features such as security posts and wet floor signs were also noted.

Elevator interior of Westpac House; Picture by Rebekah Rousi.

Sculpture inspiring the pattern on the elevator interior back panel

RESULTS

Technical Design over the Decorative

By combining the mini-interviews with the observations I was able to gain an inside-outside perspective of the elevator user experience. It soon became obvious through the interviews as well as observations that the decorative properties of the elevator cabins did not maintain high priority in people’s consciousness. People actively engaged with features such as monitors at either side of the doors as well as mirrors which were located on the doors in one building, and side panels in the other. But, there were notable patterns even in this behaviour, which will be mentioned in a moment. The characteristics of the designs that were particularly mentioned by the 50 people interviewed, were mostly related to the technical design and mechanics. For one thing, in one building people noted their disconcertion by the sound of the wind in the elevator shafts. This constantly brought to their attention the height and speed at which they were travelling. Further, people mentioned their dissatisfaction at having to wait for the elevators to arrive after pressing the hall call button. Finally, floor skipping, or the elevator dropping past floors, was noted by many in reference to the previous elevators that were housed at one of the sites.

So on the whole, sentiments which were expressed by the interviewees related to the mechanics of the elevators and feelings of safety. Interestingly, statistical analysis of the quantitative data showed a positive correlation between perceived safety and security, and the interior control panel design. This may mean that users feel safer when they perceive their own level of control to be greater. This control element also was apparent when analysing the responses in relation to the elements featured at the sites. For instance, one of the buildings featured a security desk in the ground floor lobby, while the other did not. No negative experiences were mentioned by the occupants who used the elevators in the building sporting the security desk. All the negative experiences which were related came from occupants of the building without the security desk. Further, in addition to worries over the mechanics of the elevators – and articulated memories of the elevators which were replaced a few years earlier – people in the building without the security desk mentioned experiences where people would walk in from the streets, travel in the elevators and get off in the basement. A security keycard was not required to enter the basement and occupants perceived it as being unsecure. So, elevator users also felt threatened by external elements such as people who did not have any business in the building.

Hierarchy in Interaction

Yet, moving back to the interaction with elevator interior design elements, it was noticed that interaction went hand-in-hand with social organisation. As a result of 30 elevator journeys (15 in each building) a clear social order could be seen regarding where people positioned themselves inside the elevators and how they interacted with the design features, such as mirrors and monitors. More senior men in particular seemed to direct themselves towards the back of the elevator cabins. In front of them were younger men, and in front of them were women of all ages. Men watched the monitors, looked in the side mirrors (in one building) to see themselves, and in the door mirrors (of the other building) to also watch others. Women would watch the monitors and avoid eye contact with other users (unless in conversation) and the mirrors. It was only when the women travelled with other women, and just a few at that, that women elevator users would utilise the mirrors. One interviewee even mentioned that she only looked in the mirrors when there was no one else in the elevator.

Further, interviewees seemed somewhat aware of these dynamics. Both men and women mentioned how they would either purposely stare at other elevator users to draw attention, or that one woman in particular would enter the elevator and stand facing the back, rather than the doors, which other users found disconcerting. Thus, people related a sense of playfulness at recognising and purposelessly disrupting usage norms and hierarchies. Another elevator user who was quite anxious about elevator travel mentioned that upon entering the cabin she always stood perfectly still, believing that any sudden move may cause the elevator to drop. She noted how her children were amused by this belief and purposely would jump when they were travelling to draw a reaction from their mother.

Perceived versus Real Time

What was most interesting to discover when conducting this study was the relationship between psychological perception and the material reality. Through combining the mini-interview results with the observations of waiting behaviour for instance, it could be seen that people perceived time that was spent waiting as being longer than it really was. Observation of elevator hall calls for one hour (62 people) revealed that 50% of people stepped into the elevator within less than one second of pressing the hall call button. Twenty-six per cent stepped into the elevator within two to five seconds of pressing the button. Ten per cent stepped in within six to ten seconds, six per cent within 11 to 15 seconds, and eight per cent needed to wait over 15 seconds. This follows findings of numerous studies dealing with the difference between perceived and actual waiting times (see e.g. Bae and Kim 2011, Jones and Peppiatt 1996, as well as Maister 1985).

Grenfell Centre elevator banks; Picture by Rebekah Rousi.

Westpac House elevator banks; Picture by Rebekah Rousi.

Defensible Spaces

Also, the types of responses that were given by participants varied from building to building. While no significant differences were statistically observed between buildings or variables such as gender, personality type, mood etc., qualitatively, the occupants of the building which featured the security desk in the ground floor lobby did not refer to any negative experiences or opinions about the elevators of the building, even though this building sported the same brand of elevators and had a recent refurbishing history, similar to the other building. In the building without the security desk, people were much more willing to participate in the study, but they also readily recalled past negative experiences. This leads me to wonder about architectural psychological theories such as that of defensible space (Newman 1972, 1996; MacDonald and Gifford 1989) whereby control, or perceived control, is established over property to deter criminal activity. Or at least, in the case of these buildings, the presence of live security staff, or lack thereof, determined the level of experienced safety and security. Security cameras are all very well, but at the end of the day it is only the people who can help you. This was in a way confirmed when an interviewee recounted an experience of being trapped in one of the elevators. She noted that it already was an ordeal to be stranded in an elevator, but her anxiety increased when she pressed the emergency button and was served by someone at a help desk in another state, who was not aware of where this particular building was located.

Points for Consideration

Aside from these findings, a number of issues came to mind in light of the role and ethics of the researcher. I was one of these ‘outsiders’ who had entered the building. People in the building with the defensible space defined by the security desk were more reluctant to participate in the study, possibly: a) due to lack of time; or more likely b) because they were wary of me and my intentions. Although the property managers had informed building participants via email that I would be conducting a study in the buildings, I had not gained permission from every individual I had observed. Moreover, most of us feel uncomfortable if we are aware that someone is watching – formerly or otherwise. Further, to highlight my position and role in society is also important. I was in Adelaide, Australia as a visiting researcher from Finland. I was born and raised in Adelaide, so I do not differ from most of the study’s subjects in terms of language and accent. But I am a Caucasian woman in her thirties, who was perceived by some as a market researcher seeking to obtain a quota of research respondents (which was mentioned in passing comments when people stated that they would ‘help me achieve my quota’) and by others as perhaps a silent rule breaker. I tended to forget myself when I stood in the elevators, generally standing towards the back of the elevator in line with senior male staff members. And likewise, looking at others in the cabin rather than at the ground or monitors as most of the other women did.

Implementing ethnographic measures to study the user experience of elevators and their architectural surroundings has certainly been a learning curve. Based on my above-mentioned realisations, being aware of one’s social position, and behaving in a way which complies with the environment in which the study takes place are points to be mindful of when undertaking similar studies in the future. Furthermore, through adopting a mixture of qualitative and quantitative techniques, a more detailed and explanatory impression of the situation may be obtained. This methodological approach is definitely worthwhile. But lastly, regarding the nature of the usage purpose of elevators – to seamlessly move people from one space/floor to the next – the very point of conducting research to explore user experience came to mind. Experience occurs and exists in the mind. In order to recall it, we need to be conscious of it. If we are asking people to comment on their experiences, we are asking them to be conscious or mindful of them. In the case of elevators, successful usage means that a person has been transported smoothly without interruption and in essence, should not be consciously aware of the human-design transaction, other than that the flow of their movement is continuous without interruption. By asking them to comment on their experiences, we are asking them to be conscious of design interactions which should not necessarily be consciously perceived. Generally, in these user instances people are only conscious of negative experiences as they interrupt their movement flow. So, possibly new paradigms and approaches to user experience should be established which account for the desired effect of no conscious experience.

Acknowledgements/ Credits

I would really like to thank Tekes, the Finnish Funding Agency for Technology and Innovation for funding the Theseus II project, through which I had the opportunity to visit Australia and collect valuable data and experiences. Thanks to the propriety managers of Westpac House and Grenfell Centre in Adelaide for allowing me to study the buildings’ elevators. Special thanks goes to Anne Stenros and KONE elevators for initiating and inspiring the study. And thank you very much Professor Pertti Saariluoma for all these opportunities.

References

Bae, G. and Kim, D-Y. (2011). The Effects of Offering Menu Information on Perceived Waiting Time: The Case of a Casual Dining Restaurant in Korea. In Proceedings of 16^th Graduate Student Research Conference in Hospitality and Tourism 2011, University of Massachusetts, Amherst. http://scholarworks.umass.edu/gradconf_hospitality/2011/Presentation/33/

Jones, P., & Peppiatt, E. (1996). Managing perception of waiting times in service queues. International Journal of Service Industry Management, 7(5), 47-61.

MacDonald, J. and Gifford, R. (1989). Territorial Cues and Defensible Space Theory: The Burglar’s Point of View. Journal of Environmental Psychology, vol. 9, pp. 193-205.

Maister, D. (1985). The psychology of waiting lines. in Czepiel J.A., Solomon M. and Surprenant C.S. (Eds), The Service Encounter, Lexington Books, MA.

Newman, O. (1973). Defensible Space: People and Design in the Violent City. London: Architectural Press.

Newman, O. (1996). Creating Defensible Space. US Department of Housing and Urban Development, Washington DC. http://huduser.org/portal/publications/def.pdf

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Image from Fabien Girardin

After the two previous editions (Openness and Stories to action), it’s now time for our April edition on combining qualitative and quantitative data.

While ethnography generally draws on qualitative data, it does not not mean that quantitative approaches shouldn’t be employed in the research process. Combining the two leads to a “mixed-method approach” that can take various forms: data collection and analysis can be either separated or addressed together, and each of them can be used in service of the other. Of course, this isn’t new in academic circles and corporate ethnography but there seems to be a renewed interest lately in this topic.

One of the driving forces of this renewed interest is the huge amount of information produced by people, things, space and their interactions — what some have called “Big Data“. The large data sets created by people’s activity on digital devices has indeed led to a surge of “traces” from smartphone apps, computer programs and environmental sensors. Such information is currently expected to transform how we study human behavior and culture, with, as usual, utopian hopes, dystopian fears and *critical sighs* from pundits.

Although most of the work of Big Data has focused on quantitative analysis, it is interesting to observe how ethnographers relate to it. Some offer a critical perspective, but others see it as an opportunity to create innovative methodologies to benefit from this situation. See for instance the notion of “Ethnomining” described by Aipperspach et al. (2006) in their insightful paper Ethno-Mining: Integrating Numbers and Words from the Ground Up:

Ethno-mining, as the name suggests, combines techniques from ethnography and data mining. Specifically, the integration of ethnographic and data mining techniques in ethno-mining includes a blending of their perspectives (on what interpretations are valid and interesting and how they should be characterized) and their processes (what selections and transformations are applied to the data to find and validate the interpretations).

For these researchers, such integration is meant to highlight new understandings and potentially inspire design in human-computer interaction research. We recently featured a series from Wendy Hsu, an ethnographer who uses data mining and GIS techniques along with ethnographic research.

Another driving force underpinning the renewed interest in mixed-methods may also be the result of cross-disciplinary programs in different universities. This hypothesis is based on my personal experience visiting different places in Europe and in the US where I have noticed an increasing number of courses about ethnography and qualitative research in computer science departments and design schools. Graduate students are being asked to understand the value of different approaches and to strive to integrate them for their own purposes. Hence the work on “ethnomining” by researchers from a Computer Science division at UC Berkeley.

That being said, the mixed-method approach, whether involving large data sets or not, is not so straight-forward. There are potential problems worth exploring. The most important issues lies in the fact that qualitative and quantitative methods do not necessarily mix easily at the epistemological level: how do positivist assumptions embedded in quant research mix with more interpretive standpoints? Another problem also consists in the triangulation process between data: should they only be to the service of one another? Or is it possible to collect and analyze both types of data in a more integrative way? Then what does all this mean in a practical sense? Finally, as discussed by danah boyd and Kate Crawford, the large data sets we can use have their own challenges around what is considered to be “truth.” They point out that ”what is quantified does not necessarily have a closer claim on objective truth“.

Building on these discussion, this month’s “Combining qualitative and quantitative data” theme will give an overview of current opportunities and issues. The post series will not focus only on ethnomining, but it will show various case studies and perspectives on the implications of mixed-methods approaches. Here are some posts that we have coming up in this edition:

• Rebekah Rousi (@RebekahRousi) will describe how she combined questionnaire results with on-site observations to investigate how people experienced their interactions with elevator designs.
• My colleague Fabien Girardin (@fabiengirardin) will show how he used sensor data to yield field observations in a study for Le Louvre in Paris.
• Rachel Shadoan (@RachelShadoan) and Alicia Dudek (@aliciadudek) will describe the results from their research on Plant Games, an online Role Playing Game.
• Alex Leavitt (@AlexLeavitt) will discuss his research on Tumbler using a computational ethnography perspective.
• Tricia Wang (@triciawang) is going to share her thoughts about the opposite of Big Data, in what she calls “thick data”.
• David Ayman Shamma (@ayman) from Yahoo! Research will describe his personal perspective on the topic.

For each of these blogposts, beyond the results and the authors’ viewpoints, I think the most fascinating bit concerns the motivation to combine qualitative and quantitative methods, as well as the role played by the research focus in this choice. Many of the issues were brought up in contributing editor Jenna Burrell’s series, “The Ethnographer’s Complete Guide to Big Data.” We hope this month’s edition continues to extend the conversations around ethnography and big data.

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We’re looking for guest contributors for Jenna Burrell’s May edition on talking to companies and organisations about ethnographic fieldwork. Check out the upcoming themes to see if you have something to submit!

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Adriana Valdez Young

Editor’s note: In the last post of the Stories to Action edition, urban research designer Adriana Valdez Young @thepublicagency tells us how she used stories gathered from ethnographic research to design a game for architects and planners.  Her “action,” a game called Arrivalocity, allowed users to access stories from her fieldwork. Although not all “actions” turn out as we expect. Adriana shares with us how she would approach this process if she were to do this again. All designers and researchers can learn from her very open and honest reflection. 

Adriana Valdez Young makes creative learning and research platforms that engage people with their city. She is the co-founder of English for Action in Rhode Island, helped launch KARAJ in Beruit and is the co-editor of Betta, an architecture zine on lifestyle and conflict.

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An individual storefront subdivided from 1 to 8 businesses over the course of 3 years.
(Courtesy of Nicolas Palominos & LSE Cities 2012)

Introduction

One day in Eindhoven for a lighting workshop. The next day, back to London for a one-hour walk down the street, followed by six hours drawing plans for a boutique hotel, art cinema, and food market to present to city officials. This is how a group of architecture firms spent two days in the spring of 2012 shaping a gentrified vision for Rye Lane (Olcayto 2012).

Designers, planners and developers shape our cities, yet they can spend little to no time in the field before delving into decision making. In the context of culturally-complex and rapidly changing streets, the results can be generic and damaging characterizations, leading to bland and detrimental designs.

As a researcher with the ‘Ordinary Streets’ project at LSE Cities, I spent several months in 2012 learning about the culture of trade on Rye Lane – a dense, multicultural high street in the neighborhood of Peckham, South London. Rye Lane is a street where businesses and shoppers regularly out-maneuvered tight spaces and budgets. It is an entrepreneurial and cultural destination, where a newly arrived immigrant can rent an outdoor market stall for a daily rate of £10 – using only a mailing address and a mobile number to secure a permit; where a woman can buy exactly the same foods she cooked, hair style she wore and movies she watched in Lagos – all in the same shop; and where a refugee from Iraq manages a store that he subdivided from one to eight micro businesses – each one run by immigrants.

In this ongoing retail remix, business owners sliced through glass storefronts to add service windows and street displays to sell mobile phones, DVDs and popcorn. They put up temporary walls to partition a single property into a grocery store, hair salon and eyelash bar. They made plywood and plexiglass cabins at the rear of their shops to house more intimate trades like money transfers. While these ad-hoc design interventions are common in emerging economies, they conflicted with London’s official planning norms and aspirations. In the eyes of local officials and the mainstream media, Rye Lane carried a stigma as dangerous, discounted, messy and overall, as failing (The Economist 2012).

A single store hosting a mobile phone vendor and custom dressmaker – with a view out to Rye Lane.

A single store hosting a mobile phone vendor, dressmaker, and a booth for money wires at the rear of the shop (not pictured).

A single store hosting a mobile phone vendor, a butcher, and a grocer, sharing an open air entrance from Rye Lane.

Playing to Plan
I wanted to create a way for planners, politicians and other outsiders of influence to consider Rye Lane’s street-level innovations as culturally and economically successful. I also wanted to encourage architects and planners to increase their appreciation for the design sensibilities of informal, flexible and multicultural businesses. My hope was that if planners could navigate the street through the stories of entrepreneurs and neighbors, they would support planning interventions that reinforced rather than squashed existing retail cultures.

To make this happen, I decided to build a game. A few years ago, I made card games for planners in Mumbai to gather public feedback on the new master plan. Unlike written surveys or formal interviews, games invite people to escape reality, test new skills and have fun. They also help to break down social and economic barriers to participation. In particular, location-based games encourage players to explore their environment and make new connections between what they see around them and what they envision to be possible. As a street polarized by contested design visions, cultural stereotypes and illicit activities, a game seemed like a non-threatening, productive platform for both planners and the public to engage with.

Before I started designing, I outlined these goals for the games:

•     To serve as a fun, engaging platform to access stories and insights from my field work;
•     To encourage empathy, curiosity and conversation;
•     To avoid simplistic or romantic notions of business practices, spaces and people;
•     To make explicit connections to specific planning questions and how they impact cultures of trade;
•     To be winnable within 45 minutes to one hour;
•     To offer post-game opportunities for analysis and sharing;
•     To be a scaleable and replicable learning tool in other urban contexts (e.g. public engagement processes, educational workshops, or design charrettes);
•     To create a feedback loop between researchers and participants who may not otherwise see how their contributions influence a study.

To meet these goals, I designed three mobile games that invite players to take the role of a refugee starting a new business, a young mother raising a family and a planner re-designing public spaces. I built the games using the free and open source platform 7scenes, which allows you to script a Google Maps based narrative that can be freely downloaded and played on an iPhone, iPad or Android phone. Since the platform is GPS-activated, players must be on the street in order for the game to run.

Aerial view of all 199 shops on Rye Lane, colours indicate multiple businesses per store.

Arrivalocity
The first person I met on Rye Lane was Nasser, a young Afghan refugee who arrived to London in 2003 without any work experience. Advised by relatives to head to Peckham in search of a job, he first apprenticed at a local food shop before partnering with a friend to run a fruit and vegetable stand on Rye Lane. He paid £10 a day to rent a 2 x 3 meter spot in a small plaza. He had ambitions to expand to run another business from an indoor market stall. Nasser’s story shared commonalities with several other entrepreneurs I interviewed, each of whom were able to use the daily and weekly rental schemes, loose permitting requirements, and the collective culture of micro-incubation to launch their own businesses.

I built the Arrivalocity game based on the stories of four small business entrepreneurs (including Nasser) whom I interviewed over the course of several months. In this game, players take on the role of a recently arrived refugee from Afghanistan and have up to one hour to find a room to rent, buy a mobile phone, learn how to send money home to their family and find a job or identify a business they want to test. At the start of the game, players are given a ‘wallet’ with a suggested budget and a map of locations they can visit in any order (view the game book). With assistance from the Refugee Council, players have a budget of £75/week to rent a room off Rye Lane, in addition to £500 in savings they can use for start-up costs for their own business. Players can visit 12 locations and complete challenges to earn points that will determine whether they are ready to start their own business or if they should apprentice first. They visit indoor markets, street vendors and stores, where they are rewarded for learning the regulations and loopholes of trade and zoning laws. The game aims to gives players a sense of the resources offered on Rye Lane that are conducive to small-scale entrepreneurship and staying connected to one’s home country.

Screenshots from the Arrivalocity game as it appears on web and mobile platforms.

Future Replays

Although I was successful in designing games based on the stories I gathered, I did not meet my goals of engaging architects, planners or other city makers in experiencing Rye Lane through these narratives. Without a compulsory conduit for participation – such as a conference, charrette, or community campaign – the games performed more as a data visualisation tool than an advocacy platform. While the games have the potential to facilitate empathy, insights, and actions, I would make significant shifts to my game design process to increase their future impact and application to other urban contexts:

1. Open Collaboration
As ethnographers, we can fall prey to a ‘no detail left behind’ mentality. We get excited about all we’ve observed in the field and can over-share. For future iterations, I would scale back my own content to act as a call for participation rather than a completed story. To do this, I would engage businesses as co-designers and co-owners of the game rather than solely as content providers and approvers. Unlike reports, journal articles and other traditional research products, the games do not have to be finished works – they can exist as mutable conduits for stories and actions. While the games were an effective tool to illustrate my own urban planning vision, more platform iterations are needed to include multiple perspectives. For example, the local planning authority currently lacks an inclusive platform to gather feedback on the planning process. Based on my initial game prototypes, I would propose developing a data gathering and sharing platform using a similar open source framework capable of receiving and  media, such as videos, photos and written comments via email and SMS. Community groups, business associations and others could then curate media content to create their own games and tours of Rye Lane that illustrate their understanding of the street and vision for future developments.

2. Street Props
Rye Lane is a street saturated with mobile vendors and users. However, the project could have benefitted from more analogue corollaries for participation. In addition to the printed game books I produced, I would consider using physical props, such as a bulletin board, stickers, notecards and other materials to give participants a tangible medium to add insights and stories in both building and playing the games. For example, a poster-size map showing game locations could be displayed in a storefront. It could display the game narratives and then invite the public to add more stories to the same locations. As people add content to the physical game board, I could then add this content to the mobile version. This public installation could also help demonstrate broad participation, build momentum, and spark street-level conversation that generates another qualitative data set. I also could have integrated physical props into my initial research collection, using maps, photos and other visuals I reserved for the game design as a way of guiding interviews and soliciting feedback.

3. Partners

Partners beget participation. In a future gaming exercise, I would build more time into my fieldwork plan to involve partners in the design and testing process from the beginning. For example, I could collaborate with a small business association, planning firm or advocacy group to enhance their existing outreach and research goals. The games could be integrated into charrettes, consultation workshops or other public engagement efforts. With stronger partnerships, invested game testers would have been built into the process from the get-go, and a more focused set of participation goals and outcomes could strengthen the game narratives. I also would like to explore using the games as an educational tool for urban planning and design students. Students could collaborate to gather stories and build pieces of the game narratives in addition to running the play tests. The game design process could be an exercise in developing qualitative research methods and participatory planning skills.

FIELDWORK

For readers interested in the two rounds of fieldwork I completed to design and test the games, here are the details.

The Street – Fieldwork Part 1

For six months, I went to Rye Lane 1-3 times a week, for an average of 5-8 hours. As part of the LSE Cities group, I collaborated with three architects to survey and map the street. We began by visiting each of the 199 shops and collecting the following information from the owner or manager: country of birth, languages spoken, number of employees, number of businesses per store, number of years the business has been open, and if the store was leased or owned. We found that 1 in 4 shops hosted more than business, and that traders originated from 20 different countries and 89% spoke 2 or more languages. This initial survey created a baseline snapshot of multiculturalism and dynamic business offerings to argue for the the street’s vitality.

While other team members worked on maps and drawings to visualize socioeconomic data from our survey and the census, studied nearby public and cultural institutions, and interviewed city officials, my focus was to gather qualitative insights into business practices by photographing shop interiors and selecting six businesses to observe in depth. These locations included a money shop, a realtor, a street vendor, a children’s clothing store, a women’s clothing store, and a mini-souk. There, I talked with the owners, managers and co-workers about how they set up their businesses, the financial, political and design challenges they faced, and their views on the cultural and economic prospects of the street. At each location, I made 1-2 visits to lead formal interviews and take photographs, and then returned 3-4 times to observe how businesses engaged with customers, to deliver printed copies of the photos I took, and to review information and images that I would later publish in the games. I also took note of the work-in-progress aesthetic and strategy of subdivisions. False walls, booths, kiosks and service counters were constructed with makeshift, mismatched and repurposed materials, making it apparent that stores were not unified or completed works, but rather were evolving and experimental. Design interventions to open a new business within an existing shop were as minimal as a salon chair and a sign in the window advertising the chair’s rent as £75 per week or a cardboard box with SIM cards and a phone service poster atop a freezer of fish. More permanent installations included plexiglass and sheetrock booths that had locking doors and separate electricity hook-ups to house money traders, travel agents and custom jewelers.

Most of the traders I interviewed had been laid off from jobs in larger companies or unable to find work before starting or joining an independent venture on Rye Lane. Those who sub-divided their shops explained the need to diversify their business offer to appease changing customer needs, lower overhead costs, and offset slow periods regularly faced by particular trades such as travel agencies and fresh produce. Owners of micro-businesses within the larger stores enjoyed affordable and flexible rent structures, low upfront investment costs, and shared customer flows with neighboring businesses (e.g. to reach the money transfer booth at the back of one shop, customers had to walk by a mobile repair counter and a dressmaker).

Beyond making good business sense, the traders and customers I interviewed viewed the subdivisions as a way to replicate the market environments of their home cities. Subdivided stores created a souk-like environment that culturally resonated with shoppers and shop owners who hailed from cities in India, Asia and the Middle East, where dense and dynamic informal markets dominate the street. On the other hand, two owners who ran high-end clothing shops since the mid 1980s told me that they intentionally avoided subdividing their shops to distinguish their image from discount retailers. They regularly declined offers from people looking to set up mini mobile shops in their storefronts, offering rents between £50 to £200 per week, because they viewed subdivisions as messy, cheap and legally precarious. Overall, while the culture of subdivisions facilitated incremental growth, entrepreneurship and low vacancy rates, I learned that these micro-businesses not only had a negative reputation with city officials, but also among their more established neighbors.

Detail from the Shopomama game book.

Game Design – Action Part 1
Next, I spent one month designing and testing three mobile games. In addition to Arrivalocity, here is how I translated real stories from the field into two other fictional gaming scenarios.

Shopomama
Real Story: I spent time hanging out a Cash & Carry shop, which between 2009 and 2012 had been gradually subdivided to host eight businesses. Apart from learning how one 16-year-old from Afghanistan managed the property, I observed how many mothers came to shop at this mini-souk because of the convenience and comfort of one-stop shopping, flexible lay-away plans, the multilingual salespeople, and the welcoming attitude toward children. As city planners and local leaders were considering altering zoning laws to restrict owners from sub-leasing their stores to multiple tenants, I aimed to convey the cultural and social importance of mixed businesses for local shoppers.

Game Scenario: As a mother of two who has recently moved to Rye Lane from Lagos, players are tasked with the weekend shopping for the family. With two kids in tow, players have up to one hour and £150 to shop for the following: ingredients to cook dinner for five, special occasion clothing for the entire family, a Nollywood DVD, and a manicure (view the game book). Along the way, players also find a place to access free WIFI and change their baby’s nappy. At the start of the game, players have a ‘wallet’ with with a suggested budget and a map of locations they can visit in any order. Players experience the social amenities, affordable prices and other conveniences that subdivided shops offer to families.

Pech City
Real Story: I interviewed a local council member who complained that Rye Lane was ‘untidy’ and lacked the respectable businesses found on more prosperous London high streets. This attitude was also prevalent among long-term residents and business owners, who were uncomfortable with how new immigrant populations had rapidly altered the commercial culture of the street. I wanted to create a game to counter this perception of the street as economically failing and aesthetically ‘foreign,’ and show the importance of its independent stores as a foundation for innovation and resilience in a tough economic climate.

Game Scenario: Visitors to Peckham Rye Lane are invited on a walking tour of four of the city council’s real redevelopment sites, beginning at the rail station and ending at the cafe of the Rye Lane Market. The title riffs off Tech City in East London, a hub of tech-based companies that is celebrated as ‘Europe’s centre of innovation.’ Pech City guides the player to value the concentrated start-up culture driven by everyday tech needed to send money, messages and media around the world (view the game book). Along the tour, players have the opportunity to envision how the economic and mobile culture of the street could be scaled up to inform the upgrading of the four sites. Rather than prioritise historic preservation or make room for large chain stores, the tour illustrates how these commercial sites can instead host business incubators, cultural and media production facilities, and education and training programs that complement existing street trades.

Game testers with backgrounds in social work and community advocacy visit Nasser’s fruit stand and view video content about this location as they play Arrivalocity.

Game Testing – Fieldwork Part 2
When it came to testing the games, I reached out to the architects and city officials involved in the original two-day charrette that had provoked my design experiment. However, none of them agreed to play the games. Although I managed to interview an architect and a journalist who participated in the charrette, they told me they did not have time to play test the games. The remaining architects (whom I had no direct personal or professional connection to) either never responded to my emails and phone calls, or replied explaining they were too busy. I received the same response from several local politicians and city planners whom I also tried engaging. Perhaps asking professionals in demanding sectors to dedicate one hour to playing a game was too absurd of a request. However, if the games were to be included as a required exercise in a city-run charrette or urban design conference, maybe then would architects, planners and politicians be compelled to play.

The first reviewers of the games were the managers and owners of the six businesses I had profiled in my research. While they expressed interest in the potential of the digital platform to promote their businesses to a broader audience, but were skeptical that government officials would take the time to play them. This was an indicator of the ongoing alienation they had experienced from local political leaders and the planning process. During our interviews, they shared stories about politicians failing to consult them about future plans or to compensate them from business lost during public works improvements. In addition, I think this was also a reflection of their self-reliant attitude that had propelled them to start their own businesses and not rely on government interest or support. They suggested that the games would function better as a  physical bulletin-board, where businesses could post their own ideas and images of their stores that city officials could chose to factor into the planning process. Also, in the future, I would have had an impartial colleague test the games with the business owners, as they may have felt compromised sharing negative feedback with me after we had built up close relationships during my field work.

In the absence of planners and architects, I enlisted four colleagues to test the games: two community advocates from the public sector and two tech developers and designers. Only one of the tech designers lived near Rye Lane and was familiar with the area. She reviewed the game independently and then we discussed her feedback later in an in-person interview. With the other three outsiders, I accompanied them on their first visit to the street and gave them minimal instructions and prep, before they set off to play the games on their iPhones as I trailed their footsteps.

The two players with backgrounds in community advocacy and social work were enthusiastic about the games as educational and grassroots organizing tools. They not only enjoyed the experience of exploring the neighborhood, getting prompts to speak with people, and learning about the culture of business practices, they also appreciated how the game placed business owners in the position of experts and players in role as learners. One player, who led a bike safety campaign in Santiago, Chile explained that the games could be the equivalent of when her organization asked planners to ride bicycles and see for themselves what dangers exist for cyclists. They both stressed the importance of games as an opportunity to take on fresh perspectives beyond one’s professional lens. As these testers played as a pair, I observed how they were more comfortable throughout the game – conferring with each other to answer challenges, navigate the map, and discuss what they observed – and overall, showed more ease in approaching business owners. This social factor of play raised the importance of applying the games to collaborative learning and design settings, in which the game could spark narrative-based ideation.

The two players with tech backgrounds provided feedback on the user experience and possibilities for new platform iterations. One tester suggested the process could be much more efficient. Rather than play the game, community advocates could apply the game content in presentations to planners, city officials and other city makers. He did not see value in the game as an essential conduit for planners to gather the information themselves, but instead saw potential in the game as a strategy to more effectively crowdsource information to influence the planning process. The other tech tester who was more familiar with Rye Lane, suggested the game be used a design probe in a participatory workshop to envision the future of the street. She framed the game as a potential platform for businesses to add and discuss their ideas, and stressed the need for a physical corollary, such as a bulletin board at a central public space, where people could add ideas via the mobile platform and also in person. She also emphasized the importance of making the game a people’s project, and designing more opportunities for businesses and residents to appropriate the platform for their own purposes.

______________________________________________________

• Reaching Those Beyond Big Data by Panthea Lee @panthealee
• Isolated vs overlapping narratives: the story of an AFD by Heather Ford’s @hfordsa
• Performing Success: Ethnography and the risk of first impressions by Morgan Ames @morgangames
• The Chickens and Goats of Uganda’s Internet by An Xiao Mina @anxiaostudio

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, “Lausanne Pedibus” by Nicolas Nova, CC BY-NC on Flickr.

Running across this “pedibus” sign on the streets of Lausanne the other day made me think about the cultural implications for such practice.

Pedibus are commonly found in European cities such as Geneva, Lausanne or Lyon and one can see them as an intriguing type of school bus line that collects students at scheduled stops located in the city, except there’s no actual “bus”. Children are “picked-up” in accordance with a predefined and fixed timetable. They are then brought to school on foot by volunteers (parents or people from the neighborhood).

The name is a portmanteau word formed from the latin root “pedester” (which means “going on foot“) and “bus”. This semantic combination highlights the ambulatory character of the system, with the participants walking without any other mean of transport (that being said, I sometimes see kids on scooters when “in” the pedibus).

In general, pedibus systems can be created by urban institutions, or by a group of parents who are interested in a healthy and cheap way to deal with pupils’ schedules. Of course, such collective services are necessarily bound to the structure of urban environment. They are indeed more likely to be found in dense (and safe) city centers than sprawl-like suburbs, but one can also run across a pedibus in the countryside in France or Switzerland.

“Lausanne Pedibus” by Nicolas Nova, CC BY-NC on Flickr.

The pictures above have been taken in Lausanne, a Swiss city with a population of nearly 130’000 inhabitants making it the fourth largest city of the country and 41.38 square km2 (15.98 sq mi). The website about the pedibus in this town indicates that the network is 21 km/13 miles long with 40 “lines” (approximately 575 m/0.3 mile long).

These numbers are intriguing but that’s not what I’m most interested in. Looking at the picture above, several elements caught my eye:

• A very casual form of signage: it’s made of a wooden plaque with bright colors and a hand-drawn typeface, which is a bit unusual in Switzerland with its high standard of graphic design. It is also attached to existing urban infrastructures (signage, wall, etc.). This highlights the informal character of this system: disconnected from the other urban signs (which have a more structured visual identity). Pedibus stops like this one are sometimes removed during summer vacations, as if to tell us the temporary existence of this means of transport (and the rythm of the “school season”).
• Unlike other bus stops, the timetable is pretty basic and limited to certain moments of day: morning, end of morning, beginning of the afternoon and end of afternoon (based on school schedules).
• There’s a short description of what a pedibus is (with words and a drawing representing the bus): even if the system is 14 years old in Lausanne, it may tell us that it’s still important to explain what it is; probably for newcomers.

Beyond my interest in alternatives means of transports, I find pedibus systems fascinating for two reasons. First and foremost, they show the importance of bottom-up innovation as well as citizen participation. That’s probably what could be called a “Smart City” from a human perspective. Second, they also reveal how innovation can be based on “removing” elements from an existing system. In this case, and because it makes sense in terms of distance, this mean of transport corresponds with the removal of the main artifact that was involved in the process: the bus. I think that this is more than the “less is more” ethos commonly found in design circles, and which strives for minimalism. To some extent, the pedibus may be another example of “innovation through subtraction“, a sociological concept that I recently encountered in this research paper: “innovation founded on reducing a practice or ceasing to use – subtracting, detaching – a given artefact.“. From a design POV, I’m fascinated by this move: you take an existing technological system (e.g. school bus), you remove the main component (i.e. the bus), and then you try to find a workaround.

Do you see any other examples in your everyday life? Can you invent other examples of pedibus-like innovation with other technological artifacts/services?