Socializing Big Data through BRPs

September 11, 2013

BTD

To start let’s consider two distinctions about organizational processes. Following Sig over at Thingamy, two basic types of processes exist: easily repeatable processes (ERPs) and barely repeatable processes (BRPs).

ERPs: Processes that handle resources, from human (hiring, firing, payroll and more) to parts and products through supply chains, distribution and production.

BRPs: Typically exceptions to the ERPs, anything that involves people in non-rigid flows through education, health, support, government, consulting or the daily unplanned issues that happens in every organisation.

As I noted in Social Learning and Exception Handling, BRPs result in business exceptions and take up almost all of the time employees spend at work. Interestingly, much of the writing I see on Big Data is about making ERPs more efficient or making guesses about when to expect occurrences of a BRP. In other words, both goals are really about making coordination of organizational efforts more efficient and/or effective.

How organizations coordinate their activities is essential to the way they function. What makes sense for the organization’s internal processes may not make sense in its ecosystem, and vice versa. These are distinctions that analysts of Big Data sometimes fail to note and consider.

For example, in The Industrial Internet the Future is Healthy, Brian Courtney notes the following about the use of sensors in industrial equipment and the benefits derived from storing at big data scale.

Data science is the study of data. It brings together math, statistics, data engineering, machine learning, analytics and pattern matching to help us derive insights from data. Today, industrial data is used to help us determine the health of our assets and to understand if they are running optimally or if they are in an early stage of decay. We use analytics to predict future problems and we train machine learning algorithms to help us identify complex anomalies in large data sets that no human could interpret or understand on their own [my emphasis].

The rationale behind using data science to interpret equipment health is so we can avoid unplanned downtime. Reducing down time increases uptime, and increased uptime leads to increases in production, power, flight and transportation. It ensures higher return on assets, allowing companies to derive more value from investment, lowering total cost of ownership and maximizing longevity.

In other words, Courtney’s analysis of the big data generated from sensors that constantly measure key indicators about a piece of equipment assumes the data ensures a decrease in downtime and an increase in uptime resulting in increases in production, power, flight and transportation. Yet, the implied causal relationship doesn’t translate to all cases, especially those involving barely repeatable processes (BRPs) that produce business exceptions. It is in BRPs that the real usefulness of big data manifests itself, but not on its own. As Dana Boyd and Kate Crawford note in Critical Questions for Big Data, “Managing context in light of Big Data will be an ongoing challenge.”

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Design and “Gamification At Work”

June 24, 2013

gamification_at_work

The Interaction Design Foundation is publishing Gamification At Work by Jankaki Kumar and Mario Herger for the public tomorrow. I just finished reading the book and taking notes thinking I might review it. However, rather than do a simple review of the book’s content, I decided to situate the major points from the book into a post on the general topic of gamification in the workplace.

I appreciate the opportunity to read the book’s early release and, if you haven’t yet seen it just click on the link to it above and you can access it as well. Hopefully you will also consider reading my own thoughts on how the points in the book fit into what is most aptly considered gameful design.

Gamification At Work is an interesting read for several reasons. Kumar and Herger not only cover the essential components of a well-thought approach to why playing games is not antithetical to getting work done. They add to that contribution by outlining a design strategy, which they refer to as Player Centered Design, and providing case-study insights from the SAP Community Network that add essential details to each part of their overall discussion.

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Social Media Robots, Personas, and Narrative Gaps in Qualitative Research

April 1, 2011

Back in 2006 Hugh Macleod offered the following point on Gapingvoid: “If people like buying your product, it’s because its story helps fill in the narrative gaps in their own lives.” At the time I thought it conveyed nicely the point made by Gerald Zaltman in How Customers Think that “companies should define customer segments on the basis of similarities in their reasoning or thinking processes” (p. 152) rather than constructs related to demographics. Hugh’s point made a lot of sense when I first read it and the point continues to gain in significance for me.

Hugh’s initial post sparked a range of interesting comments that I encourage anyone puzzled by the quote to read. The one point I’ll make about the topic is that nowhere in the post or the comments does anyone say what they mean by narrative gaps. I’ll attempt to clarify the concept below because it doesn’t simply mean stories. Stories that fill narrative gaps do so by purposively or accidentally creating personal curiosity, imagination, intrigue, or mystery for people experiencing them.

Narrative gaps in our personal stories are resolved through other stories about our own experience, perhaps with a product or service, that help us make sense of the feelings evoked. Specifically, Hugh noted in a later post that people fill in narrative gaps with meanings they construct from their own stories. It is on this point that the concept of personas becomes relevant to narrative gaps and to a recent conception of how to use social media robots, especially DigiViduals™, in qualitative research. Moreover, in this respect I suggest that the challenges involved are analogous to key ones faced by industrial robotics.

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Failing to See Money Hiding in Plain Sight

October 4, 2010

I’ve discussed ethnography, especially digital ethnography, several times here taking note that, whether we use ethnography in marketing  or design research remains irrelevant to the methods employed. What matters is whether we develop the research questions around the assumption that sociocultural practices provide the data source for answers. Ethnographers research settings, situations, and actions, with the goal of discovering surprising relationships. The most surprising relationships though are often hiding in plain sight, right under our noses.

I was recently pointed to a video from a link in the Yahoo Group Anthrodesign. The video, by Amy Krouse Rosenthal, provides a unique example of insights about people we can glean from designing situations that transgress established sociocultural practices. I actually watched it three times, and not because Time listed it in the top five viral videos of the week…kind of like people (at least some people) did when the moonwalking bear video came out. Rather, my interest in it was how the mere observation of the actions taken by pedestrians leads us to experience surprise. More on this below. For now, let’s consider the video itself.

After sticking labels on 100 one dollar bills, with a unique message written on each, and clipping those dollar bills to individual leaves on a tree, Ben, Brian, and Amy video recorded how people respond to money hanging on a tree as they walk by it on a street.  The narrator, Amy,  indicates no crowds showed up to grab all the money they could get, though a few did take more than one dollar at a time. Most people who took money, a minority, pulled a couple of dollars, or one, and moved on.

(UPDATE: You will need to click on the Watch on YouTube link to see the video. Some proprietary thing I’m sure) 😉

Amy offers two lessons learned from the Money Tree:

  1. That people routinely walk by a “tree filled with free money” without even noticing
  2. That people can look at a tree filled with money and not even see it

The Money Tree offers an example of what social psychology, but especially ethnomethodology, refers to as a breaching experiment. Breaching experiments typically involve a researcher breaking a rule about everyday life and then analyzing other people’s response. The Money Tree exemplifies a situation designed to break a tacit understanding about money and sidewalks.

“Money doesn’t grow on trees”, is a phrase most people in Chicago (the location of the Money Tree) probably know. We don’t routinely see money hanging from a tree along a sidewalk. It is certainly more common, as the bicyclist’s experience in the video shows, to see money on a sidewalk. And, I’d wager, most of us just think someone lost it. In other words, merely by setting up the situation to violate the pedestrians’ tacit knowledge of what walking down a sidewalk entails, the videographers show us something about people.

At the same time that the video offers us a surprising experience, it sure would be interesting to know what people who failed to take money were thinking. Anyone else find this interesting?

Posted by Larry R. Irons

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Video Analysis for Experience Design: The Video Card Family Game

July 12, 2010

From "A Journey Round My Skull's" photostream on Flickr

 Digital ethnography is an increasingly feasible research technique as smartphones decrease in cost and more people carry them around. The photographic capability of smartphones is an important resource in making digital research ubiquitous, giving people the ability to capture images and record observations as they go about their everyday lives, and characterize those observations for ethnographers. 

Of course, taking photographs and sharing them online as part of a diary or journal for ethnographic research predates smartphones. Smartphones simply increase the likelihood that an everyday experience is recorded as a representation of the moment in which it occurs. Nevertheless, the video recording capabilities of smartphones afford collaborators an opportunity for representing experience in a manner previously unavailable to ethnographic research. 

I’ll discuss the range of implications for ethnography posed by the ubiquitous access to video recording capabilities by ordinary people in another post in the near future. For now, my discussion focuses on how to use video in ethnographic research to inform product/service design. 

Video of people using products or services is one of the most challenging data resources used in ethnographic research. Playing and replaying video segments for review is time-consuming and, depending on the number of people involved and the type of activity recorded, difficult to distil into agreed-upon insights. 

I recently read several chapters from Sarah Pink’s Visual Interventions: Applied Visual Anthropology, thoroughly enjoying all of them. One chapter in particular though, Video Ethnography Under Industrial Constraints, by Werner Sperschneider, really caught my attention. Werner spells out a technique (the Video Card Game) for analyzing video in design research that I remembered reading about several years ago but, at the time, didn’t really give a lot of thought to.   

The Video Card Game draws from the “Happy Families” childrens’ card game, a game in which players collect families of four cards as they ask one another in turn for cards of a particular archetype. The goal of “Happy Families” is to collect a family of four cards, forming a stack. Collecting the most stacks makes you the winner.  

Werner provides an overview of how researchers in user-centered design at the Danish industrial manufacturer, Danfoss A/S, initially created the Video Card Game as a method for combining ethnographic and visual research methods using video. Design researchers, Margot Brereton, Jared Donovan, Stephen Viller, at the University of Queensland, as well as Jacob Buur and Astrid Soendergaard, of  the University of Southern Denmark, and the University of Aarhus, respectively, also provide case studies of its use. 

Family Resemblance and the Video Card Game

The Video Card Game’s design provides a collaborative space of interaction for researchers, designers, and design collaborators to co-create insights for product and service design, using video as a primary source of insight. The rendition of the game offered here refers to it as the Video Card Family Game for the explicit purpose of making it clear that Ludwig Wittgenstein’s concept of family resemblance is a key criteria in the gaming process for deciding to which themes a video card belongs. Using the concept of family resemblance to analyze video enables design researchers to organize, prune, and interpret actions taken in their research with collaborators in the field, providing actionable ideation outcomes.  

When playing the Video Card Family Game the key is remembering that, even though the cards give the video a tangible mode of expression, the images remain on relatively small cards, whether on the surface of a table or attached to a poster on the wall. One can imagine an interactive wall display like Microsoft’s Surface that minimizes the legibility problem. Short of such a solution however it is important to keep in mind the spatial limitations imposed by rendering video representations of action onto tangible video cards arranged on tables or walls. 

Keep reading if you are curious about how the Video Card Family Game is played in the context of video analysis for design research. 

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Ethnography and Ubiquitous Digital Research

February 4, 2010

Ethnographers are traditionally known for immersing themselves in the everyday lives of people and paying attention to the details and context of their activity. Anthropologists after Malinowski considered extended participant observation in the lives of the people they studied a prerequisite for analyzing culture. However, in the last few decades of the twentieth-century ethnographers began to consider their analysis increasingly as a challenge of interpreting cultural phenomena rather than explaining their variation.

With the increasing availability of the Web, researchers using computer-mediated communication, i.e. digital, devices in their projects label their work under a range of categories. I’ve discussed ethnography several times before, the first taking note of the trend toward virtual anthropology and the next talking about the significance of Tom Boellstorff’s ethnography of Second Life, followed by a couple of posts about ethnography’s relationship to empathy and globalization.

In 2003, Cheskin’s Davis Masten and Tim Plowman characterized digital ethnography as the next wave in understanding the consumer experience in Design Management Journal. To my way of thinking they were correct in asserting that, “Digital Ethno enables participants to convey the real-time richness of their own lives and environments.”

Along with any new wave in understanding people’s experience comes a range of neologisms intended to clarify the multiplicity of research options that emerge. Kozinets recently suggested that the use of ethnography in computer-mediated research activities is best described as Netnography, a neologism he dates from 1996. He argues for the use of the term, netnography, in the following way:

Netgography differs from other qualitative Internet research techniques in that it offers, under the rubric of a single term, a rigorous set of guidelines for the conduct of computer-mediated ethnography and also, importantly, its integration with other forms of cultural research (p. 15)

However, as Kozinets suggests, the 2008 survey of Intenet users done by the Annenburg Digital Futures Project found that 56% of the members of online community members meet other members of their online community face-to-face. And, as Kozinets further notes, the Annenburg research did not include social networking sites, making the figures conservative ones since, as Brian Solis recently noted, social networking combined with geo-location and augmented reality applications is bridging the online and offline interaction. Kozinets insists that this simply means research must blend ethnography and netnography to study the intermix of online and offline activity.

I won’t go into all the reasons I think Kozinets thinking on the relation between netnography and ethnography fails to persuade. Suffice it to say that, to my mind, as Web 2.0 increasingly permeates peoples’ everyday lives, the term netnography fails to sufficiently describe the way ethnography works in a consumer environment where digital devices are  ubiquitous.

As people increasingly access the Web and engage online communities on the go, the notion that this is happening on the net seems quaint. If any term is needed other than ethnography, I’d suggest digital ethnography remains the most fitting. When we consider mobility as part of a ubiquitous computing environment, defining the relationship between space and place increasingly requires analyzing social practices rather than simply distinguishing a time and location for an activity.

As Johanna Brewer and Paul Dourish observe, “space is not simply an ‘inert container’ for the places of everyday experience; rather, space itself is the outcome of particular ways of reasoning about and representing the world.” Brewer and Dourish note, for example, that research on mobile messaging used to coordinate meet-ups or other rendezvous allow for people to show-up using a proxy form of participation before they get to the physical meeting. Additionally, the recent research by Hope Jensen Schau, Albert M. Muniz, Jr., and Eric J. Arnould, How Brand Community Practices Create Value from the Journal of Marketing explicitly approaches brand communities using a range of qualitative techniques, including netnographic, to study participants across several years both online and off.

My inclination regarding ethnographic methods is to endorse the point of view offered in Sunderland and Denny’s Doing Anthropology in Consumer Research. They note,

…ethnography is not a method per se, but rather a collection of methods…In commercial consumer research circles, one sometimes hears various rules, on the order “it is only ethnography if there is observation,” or “video,” or “multiple meetings,” or “sufficient time,”…or…(filled in with any number of favorite and idiosyncratic rules. But what seems most accurate about ethnography as a companion mode of discovery in cultural analysis is that as a methodology it must be viewed through, and seen as permeated with, the sociocultural. (p. 50, my emphasis)

In other words, the specifics of the methodology matter less than its purposive application. Following Geertz, Sunderland and Denny contend, the methodologies employed, whether participant observation, focus groups, in-depth interviews, diaries (online or offline), village censuses, surveys, or maps, “are not ‘ethnographic’ per se, but…are made so by the intellectual framing of the task” (p.52).

The purpose of ethnographic research is as important as the methods used, as long as the sociocultural context remains in focus. For example, whether we use ethnography in marketing  or design research remains irrelevant to the methods employed. What matters is whether we develop the research questions around the assumption that sociocultural practices provide the data source for answers.

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Ethnography, Globalization, and Experience Design

December 2, 2009

Rosetta Stone

One of the most visited posts on this blog is titled, Empathic Research Methods and Design Strategy. Indeed, if you google or bing “empathic research”, the post pops to the top few links, or vey close, often even ahead of IDEO. My aim in that post was to add to points made by Adam Silver, a Strategist at Frog Design, noting that globalization and digitalization in the 1990s resulted in product and service interfaces with more culturally diverse and geographically distributed customers. The combination of these economic and social forces led designers to search for new methods to augment artistic intuition about form and function. Considerations of form and function also required attention to feel, emotions, features, and interactivity attuned to the needs, wants, and beliefs of users/customers. The power of ethnographic research to discern empathic insights by observing and interpreting people’s cultural activity is now widely recognized.

Recognizing the implications of globalization for design and marketing is certainly not new. The now classic book, The Design Dimension, by Christopher Lorenz, explained the crux of the point as early as 1986. Lorenz noted that,

…globalization does not mean the end of market segments, but their explosion to worldwide proportions. Far from declining, the number of market segments may actually increase…Though industrial designers frequently can – and do – substitute for the absence of marketing imagination. In most companies the most potent force for imaginative marketing and product strategy is a real partnership between marketing and design (pp. 146-147).

 The significance of Lorenz’ point came back to me recently while reading “How does our language shape the way we think?, by Lera Boroditsky, an Assistant Professor of Psychology, Neuroscience, and Symbolic Systems at Stanford University. Boroditsky’s research into language and thought complements a key point made in Malcolm Gladwell’s book Outliers, Gladwell informs us that one basic reason exists for the tendency of Chinese students to outperform others in math skills. Quite simply,

Take a look at the following list of numbers: 4,8,5,3,9,7,6. Read them out loud to yourself. Now look away, and spend twenty seconds memorizing that sequence before saying them out loud again.

If you speak English, you have about a 50 percent chance of remembering that sequence perfectly. If you’re Chinese, though, you’re almost certain to get it right every time. Why is that? Because as human beings we store digits for about two seconds at a time. We most easily memorize whatever we can say or read within that two second span. And Chinese speakers get that list of numbers—4,8,5,3,9,7,6—right almost every time because—unlike English speakers—since the Chinese language allows them to fit all those seven numbers into two seconds.

Whereas Gladwell’s interest is in the way language and culture affect our view of talent, Boroditsky is interested in whether, and how, language shapes the contours of thought itself, the kinds of questions people who speak a language are able to ask, and the kinds of significant symbols they recognize. Boroditsky’s research looks at an old question, and controversy, in anthropology and sociolinguistics — the Sapir-Whorf hypothesis.

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