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Panel: Using Social Science to Unlock the Pan-Human Capacity for Innovation
Organizer:
Henry D. Delcore, Ph.D.
Associate Professor of Anthropology
California State University, Fresno
The three contributors to this panel have all crossed disciplinary boundaries in an attempt
to expose students to the potential for cross-disciplinary work in developing innovative solutions
to human problems. Henry Delcore, an anthropologist, works with engineering colleagues to
join entrepreneurship, engineering and anthropology students on product design teams. Khanjan
Mehta, an electrical engineer, collaborates with women‘s studies colleagues on social
entrepreneurship projects in East Africa. Designer Leslie Speer works with business,
engineering and design students on new product development. While each has, to some extent,
their own way of framing their challenges and results, all attest to the ways that engagement
among designers, engineers and social scientists can lead to innovative products that have a
chance to make it in the marketplace. In different ways, each makes the case for including
rigorous social science methodologies in the product design process, through employing
ethnography to explore users‘ needs or, more broadly, use of social analysis to understand to the
social context of products and the conditions for their success.
Paper: Ethnography and Innovation in Interdisciplinary Student Teams at Fresno State
By Henry D. Delcore, Ph.D.
Associate Professor of Anthropology
California State University, Fresno
Introduction
In 2007-2008, some colleagues and I launched an initiative to combine students from
engineering, entrepreneurship and anthropology into interdisciplinary E-Teams. Supported by
NCIIA, the overall goal of our initiative is to bring entrepreneurship into the curricula of the
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colleges of social science and engineering on my campus. A more specific goal I have as an
anthropologist is to showcase the way that concepts and methods of my own discipline can lead
to better, more innovative products that have a chance in the marketplace.
The value of interdisciplinary teams in the business context has become well recognized
(Parker 1994, Page 2007). Recent works have also lauded range of experience (see Kelley
[2005] on ―T-shaped people‖), styles of thought (Martin [2007] and Gardner [2006] on
―integrative‖ and ―synthesizing‖ thinkers, respectively), and work practice (see for example
Kelley [2005] on the benefits of ―cross pollination‖) that imply the value of interdisciplinary
work. In product design, particularly, interdisciplinary teams have become widely accepted in
practice, and anthropologists have become nearly standard additions to the teams active at major
design firms and corporations. Finally, interdisciplinary initiatives have become common in
higher education, though the pedagogical benefits of interdisciplinarity remains a site of some
debate among educational researchers (see Lattuca, Voight and Fath 2004).
The question is, where does anthropology fit into the interdisciplinary efforts in business
and education? In this paper, I share what I think my discipline has been able to bring to the
interdisciplinary table. I focus first on the role of anthropology in innovative product design, and
then describe the work of anthropology students in an interdisciplinary course at Fresno State. I
conclude with some student learning outcomes data and reflect on the successes and challenges
that have come from teaming such different students and disciplines together.
Sources of Innovation
Over the last twenty years, product designers have turned increasingly to field-based user
research to uncover new opportunities and to develop innovative products. The reasons for the
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turn toward user research and user-centered design lie in new market conditions. Companies
face intense international competition and rapid shifts in consumption preferences. As Squires
and Byrne put it: ―…companies have to manufacture the right commodities and deliver them in
the right way to the right consumers at least four out of ten times every year – just to stay
solvent‖ (Squires and Byrne 2002:xiv). Further, markets today are characterized by an
unprecedented degree of specialization and segmentation, multiplied many times over by the
wide cultural diversity in users in both domestic and international markets. Designers and
product managers can neither assume that they are socially or culturally close to users nor that
they can keep up with consumer trends, and have thus turned to user research and user-centered
design for help.
However, while there are many ways to study users, and not all are equally productive of
innovative insights. Psychological research, for example, has its place in the development and
marketing of products, but it is constrained by two fundamental problems (see van Veggel
[2005] for a fuller discussion). First, psychological research often relies on work in controlled or
experimental environments that do not mirror real use contexts. Second, and more basic, the unit
of analysis for psychology is the individual. However, humans, the most social of all the social
species, do not live, work, innovate or create as individuals. Life, work and play are profoundly
social and cultural. Because of fundamental disciplinary assumptions, psychological approaches
tend to slight the collective aspect of human experience. (A related, though not necessary
outgrowth of dependence on psychological methods is the fundamental attribution error; see
Mariampolski [2006:23-24].)
Another source of information about users can come from large-scale survey-based
studies. Again, this style of research has its place, particularly when it is finally time to go to
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market and one needs information about the demographic of the target market. However, large-
scale survey-based work is deficient as a method for understanding users during the product
design process. First, whatever else surveys do, their questions always enshrine the researcher‘s
assumptions about important behaviors and attitudes. Hence, they tend to tell a lot about what
the researcher has deemed important. Second, even when the researcher‘s questions are on the
mark, a survey tells us about the current state of user perceptions, and not about the next big,
innovative product opportunity. Henry Ford is widely quoted as saying, ―If I had asked people
what they wanted, they would have said faster horses.‖ Ford‘s comment captures the fact that
consumers are on the whole neither anxious nor even able to tell us about deep levels of
dissatisfaction with current products (see Mariampolski 2006:26-29). Finally, one cannot derive
an accurate picture of human behavior by asking people what they do. For example, because
people mostly behave without conscious reflection, they cannot accurately self-report on that
behavior. In short, what people say they do and what they do are two different things. (See also
Norman [1999:Chapter 9]; Norman applies the problem of self-reporting to focus groups.)
While all these research strategies have a role in product development and marketing,
product managers and designers have found them wanting, and have increasingly turned to
anthropology, and its characteristic research strategy, ethnography. At its base, ethnography is
about studying users ―in the wild‖ – in their natural habitat – to see what they are actually doing
and saying in context.
The urge to meet users where they are, whether at home, work or play, has indeed
become widespread. At the National Collegiate Inventors and Innovators Alliance annual
meeting in 2008, Paul Polak introduced us to his exemplary work in developing countries.
Polak‘s commitment to first hand engagement with people, their lived needs and desires, and
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their ideas for solutions has produced some innovative and effective results in poverty reduction
(see Polak 2008). Closer to home, many of you will know the IDEO story through the writings
of Tom Kelley (see Kelley 2001 and 2005). IDEO is but one example of a leading design firm
that has taken the idea of first hand engagement with users as its touchstone for innovation.
Much of the work Polak, IDEO and others are doing is consistent with some of the main themes
of ethnography.
However, in the product design world, user research professionals are raising serious
questions about the extent to which ―ethnography‖ has been appropriated as a buzzword, rather
than a full-blown research strategy. Hence, I take time below to specify the full extent of the
benefits of ethnography to product design. I am neither preaching methodological purity nor
criticizing those who have made real, measureable strides toward engaging users in product
design. Instead, my goal in the next section is to make an argument for the benefits of
ethnography in its most robust form, as a total research approach (see Mariampolski [2006] for
one of the fullest sustained treatments of the value of ethnography as a total approach).
Ethnography: Inductive, Emic and Collective
Ethnography is one kind of research approach that involves firsthand, field-based study
of a group of people. However, ethnography is not simply ―fieldwork.‖ Ethnography is a set of
theoretical assumptions and related methodological insights that aim for a particular kind of
knowledge about humans. Today, I will highlight three crucial aspects of ethnography and the
kind of data it tends to uncover.
First, ethnography is inductive. This means that it is usually not hypothesis driven, but
instead highly open-ended. As my colleague, James Mullooly, likes to say, ethnography is about
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going out and looking for, we‟re not sure what. We take the lead from the data itself. This
means that an ethnographer often goes to the field with an issue or problem, but without a
hypothesis or set of specific questions to answer. Instead, after a period of open-ended
observations, the ethnographer builds the relevant research questions, based on initial findings.
Ultimately, we build, from the data, conclusions about our questions.
Induction is useful in research around the design of innovative products. Opportunities
for innovation are often hidden in areas where the researcher knows little, or where the
researcher‘s assumptions about what is important may hinder openness to inspirational insight.
The advantage of the inductive approach, then, is that it opens us up to the new, the unexpected,
or what Donald Rumsfeld famously popularized as the ―unknown unknowns.‖ It is precisely
these unexpected insights that are often hidden by deductive approaches aimed at proving or
disproving a specific hypothesis.
Second, ethnography aims to highlight the way the world looks like from another‘s point
of view. Ethnography is not about what how the researcher acts in the world or what he or she
thinks about the world. Ethnography is about how the research subject, or user, acts in and
thinks about the world. If the goal is to derive innovative product ideas from the lived reality of
users themselves, then ethnography‘s focus on the other‘s point of view can deliver the kind of
user-driven insights we seek.
As an aside, ethnography can aid the entrepreneur in avoiding one of the key sources of
failure: the assumption that one knows one‘s customer. Business advisors tell entrepreneurs:
―You are not your customer.‖ In other words, the entrepreneur should not assume to know what
customers want or how they think and act. Instead, customer needs and desires should be an
open question, and ethnography, with its user-eye focus, can help provide the answers.
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Finally, ethnography seeks insight into collective norms and practices, the things shared
among members of some group. Since human life is social and cultural, we ignore the collective
aspect of our lives, work and play at our own peril. Here, I would point to the pioneering work
done by anthropologist Lucy Suchman and her colleagues at Palo Alto Research Center (PARC)
in the 1980s (Suchman 2007). For example, in their classic study of the copy machine, Suchman
and Jeannette Blomberg found that peoples‘ interactions with and impressions of copy machines
depended heavily on the social and worksite context in which the machine was situated. Solving
user consternation with early copy machines was therefore not just a technical or design
problem, but a social problem, as well. Likewise, ethnography, with its focus on human
behavior in groups, can turn up opportunities that would otherwise remain hidden in the
collective aspects of human life.
To summarize, ethnography, properly done, is an inductive approach that leaves space for
discovering the unexpected. The methods used in ethnography stress open-ended observations
and informal interviewing over surveys, formal interviews and focus groups. Ethnography aims
for the other‘s point of view. In product design, this means ethnography is about the user‘s point
of view, as a source for innovative opportunities and ideas. Finally, ethnography seeks insight
into collective (social, cultural) life, not individual psychology.
Next, I highlight two specific cases of ethnography in product design. In the first
example, involving Intel, ethnography helped researchers uncover innovative, down-home
solutions to user problems on which product designers can build. In the second, I will discuss an
instance in which Proctor and Gamble researchers used ethnography to turn up an opportunity
for product design to address an under-recognized consumer need.
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The Intel Study of Green Homeowners
Microchip manufacturer Intel has a large user research group that has set a high bar for
quality user research kin the technology industry. Recently, Intel conducted an ethnographic
study of 35 green homeowners: people who have structured their homes around sustainability
issues. Intel is betting that green homeowners are the lead adopters of green products. When
green consumption goes mass market, Intel wants its products to be positioned to sell – and they
are looking to lead adopters like green homeowners for new product ideas (Hasbrouck and
Woodruff 2008).
The ethnographic study turned up at least two significant findings. First, the researchers
probed the social and cultural context of green homeowners. They found that some areas of life
are the site of intense green analysis and activity. Food, for example, is a topic of traditional
environmentalist concern, and green homeowners tended to know a lot about sustainable food
choices from their social interactions with other environmentally-astute consumers. However,
computing is a site of comparatively little green elaboration, which Intel‘s researchers attribute to
the long-standing ―dark green‖ mentality that tends to portray technology as an environmental
problem. However, a newer ―bright green‖ trend in green thinking is on the upswing. ―Bright
green‖ perspectives emphasize the potential for technology to positively contribute to
ameliorating sustainability problems. But this is a relatively new trend in environmentalist
thought and practice. Consequently, the team found green homeowners willing to think about
technology as potentially helpful, but unsure about their options when it came to green
computing. In a second, related finding, the team discovered green homeowners engaged in a
range of improvisational practices around computing and electronic technology aimed at
attacking energy use problems. For example,
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Some participants were very concerned about ―phantom loads‖ (energy that is
consumed by devices when they are off or in stand-by mode). A common strategy
for addressing phantom loads was to plug devices into a surge protector and then
cut off power to the devices when they were not in use by turning off the surge
protector. This suggests some opportunities for device design—features such as
fast wake-up or other energy management functions… (Hasbrouck and Woodruff
2008)
The homeowners‘ use of power strips to cut down on phantom loads is a classic example of the
consumer work-around to address problems with existing products. Work-arounds like this one
are hard to discover through survey research, in part because consumers are not consciously
reflecting on their behaviors, they do not consider them relevant, or they cannot imagine a
product that solves their problem. However, ethnographic research – with its inductive spirit and
open-ended observations – opens the door to discovery of just these kinds of user-level
innovations. From the insights gained through their ethnography of green homeowners, the Intel
researchers are recommending product features that allay fears about phantom loads.
The Ethnography of Laundry
Proctor and Gamble has earned a reputation as an innovation-driven company (see Lafley
and Charan [2008]). P&G has earned its reputation in part through its emphasis on high-quality
user research, including the use of ethnography.
How do you innovate on a product as stodgy and apparently well-worn as laundry
detergent? For years, P&G used focus groups and surveys to probe its customers‘ thought about
laundry and detergent. The conventional wisdom about laundry was that it was all about getting
clothes clean, and P&G dutifully emphasized the cleaning power of its detergents. Eventually,
P&G also fielded ethnographic studies aimed at finding opportunities for new and better P&G
products. The researchers visited people in their homes and conducted open-ended observations
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of their activities. One team noticed that the actual behaviors of people around laundry did not
match their explicitly stated and exclusive concern for getting clothes clean. For example, the
researchers observed people turning clothes inside-out. Asked why, they responded that they
found the behavior to help save the color of their clothes. Armed with this insight, the
researchers recommended that P&G explore ways to make detergent that not only cleaned, but
protected color, the birth of Color Guard technology.
In this example, consumers once again failed to tell P&G about their laundry concerns. It
took open-ended observation to discover the consumer work-around for the problem of faded
clothes, which led to product innovation and renewal for P&G detergents.
Interdisciplinary Teams at Fresno State
In 2007-2008, I team taught, with a colleague from Electrical and Computer Engineering,
a course called, ―Engineering for People and Markets.‖ The course had the same students and
projects active both fall and spring semesters. We recruited a total of nine students into the class.
Most students were graduating seniors. The students formed two teams, each with two or three
engineering students, one entrepreneurship student and one anthropology student. (The course
continues in 2008-2009 on a semester-length basis, with 14 students in four teams in fall, 2008.)
The engineering students‘ senior design project ideas formed the core of each team project,
though the original ideas changed substantially in the course of the year.
The main work of the course occurred around the design of two electrical devices and the
production of a working prototype, which was required by the engineering senior design course
in which the engineers were simultaneously enrolled. In class, the two instructors lectured little,
instead relying heavily on guest speakers from other departments and the community, who
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brought expertise on topics such as patent law and equity to the students. We also emphasized
presentation skills and team-building, and continually encouraged the students to test their ideas
against the needs of users and commercial feasibility.
My findings about the learning outcomes of the course should be taken with the self-
selected nature of the students in mind. In recruiting students, my colleagues and I spoke at
relevant engineering, entrepreneurship and anthropology courses and to some students one on
one. The students who chose to take the course were all high-performing students who were
willing to take a risk on an innovative but untested course. Thus, I suspect that the students who
enrolled were among the most progressive students in all three disciplines, with a relatively high
tolerance for uncertainty and capacity for creativity.
One team, dubbed the Control Freaks, designed an improved voice-activated remote
control. The anthropologist on the team did a classic ethnographic study of TV-watching habits,
spending time with people in their homes during times of high TV use. There, she was able to
observe the multiple and competing activities of people, of which TV is one part. A toddlers
plays in the living room, a teenager does homework on a computer, someone is heating up dinner
in the kitchen, and a woman watches TV. In several cases she found the pain point was the cable
on-screen TV guide. Hierarchical, clumsy, and slow, the users wrestled to get information out of
it. One of her major moments of design insight came when one of the subjects said, ―I love John
Travolta.‖ From this, the student realized that a good voice activated remote could bypass all the
clumsiness of the on screen menu. The remote might allow the user to program the device with
her favorite things, like ―John Travolta‖ or ―The Family Guy,‖ so that later, when the user said,
―John Travolta,‖ an LCD screen on the remote could display every place to find him on TV
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during the next 24 hours. She took her insight back to her colleagues and eventually convinced
them that a favorites voice command feature should be considered in the design of their product.
On the Control Freaks team, several of the engineering students were initially skeptical
about the contributions their anthropologist team mate might make. Eventually, they were won
over to her approach to user research, in part by participating in the research themselves. Using
a strategy that ethnographers in industry use with clients, the anthropology student took several
of her engineering colleagues along on the home visits. The engineers came to see the open-
ended, inductive approach as valuable by witnessing the production of relevant insights in the
interactions among their research team and the subjects. Some of the mystery of the
anthropologist‘s magic receded, and her methods became more legitimate in the eyes of her
colleagues.
The kinds of product design insights derived from ethnographic studies like this must be
taken in the proper light. Ethnographic research on users is meant to be inspirational. A user‘s
improvisational work-around or submerged desire for (in this case) simplicity and control can
provide inspiration for innovation in the design process. Ultimately, every design feature must
face other tests, like technical feasibility, cost of production and marketability. Indeed, the
anthropology student in this case learned a lesson in technical feasibility when the team ran ouot
of time and resources before they could engineer a prototype that actually incorporated the
favorites voice command feature. Finally, before such a product would actually be built, other
methods of research ought to be deployed to find out if, indeed, there is a commercially-viable
market for the product and its design.
On the other team, the Grubmasters, four students collaborated to design an interactive
restaurant pager that would entertain restaurant patrons while they waited for tables. In this case,
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the anthropology student fielded a ―wait journal,‖ in which subjects drawn from our campus‘
MBA program logged their experiences with waiting over a one month period. At the end of that
time, the student visited a restaurant and dined with each subject to debrief them on their
experiences. He also conducted open-ended observations in the waiting areas of busy local
restaurants.
One important finding of the research concerned a difference in the experience of waiting
between American and international MBA students. The anthropology student found that the
international students were more accepting of wait times, and even viewed them as a time for
reflection and recovery from their usual busyness. While this finding is preliminary, the research
nonetheless revealed that the ethnographic method can uncover the kind of data that
entrepreneurs need to appeal to culturally diverse, globalized markets.
The Grubmaster team showed the fullest measure of mutual participation in the design
process. The final design incorporated features inspired by the ethnographic observations, as
well as those that furthered the commercial feasibility of the proposed venture. The device they
designed included the capacity to deliver restaurant menus, coupons, games, ads and movie
trailers. They incorporated many of these features to further the content-driven business model
of the venture, in which restaurants would lease the devices, but the main revenue stream came
from delivering content to the waiting patrons.
Based on the soundness of their business plan, the Grubmasters took second place in the
business plan portion of the Interprofessional Projects competition at Illinois Institute of
Technology in May, 2008. The Control Freaks, for their part, won the design competition at the
Institute of Electrical and Electronics Engineers Region 6 Central Area Meeting in San Jose on
that same month.
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Student Outcomes
Finally, I want to present some of my student outcomes data. The students in the class
were required to keep journals throughout the year, and encouraged to reflect on the
interdisciplinary aspect of the course. Prompt questions included, ―What, if anything, have you
learned about the value of your own or other disciplines to the product design process?‖ and
―How has your project been shaped by the varying perspectives and disciplines of team
members?‖
First, our biggest successes came in the progress the engineering students made toward
seeing commercial viability and market factors are central to the work of engineering.
An engineer: ―After the [fall] semester was over, I had a new realization that
engineering wasn’t the only player in this game, it might not even be the
biggest player.… Human research, business applications, marketing, these are
major things in getting a product to sell.... Our goal is to have our product better
than our competitors, but without the right marketing and business plan we
will fail even if our product is better.‖
The second area of outcomes success involved engineers championing the importance of
designing for users.
An engineer: ―Through participation and observation of all the on-going team
design work, I am realizing the significance of designing for the user…. I have
recently been thinking in terms of how much desire people would actually have to
use something that I helped create…. After all, what is the point of designing
something if nobody will want to use it?‖
The third area concerns a more ambiguous set of data about interdisciplinary work and
work styles. On one hand, I believe most students eventually saw the benefit of interdisciplinary
work as a way to increase the pool of knowledge available to the team.
An engineer: ―Ever since our first group meeting, I began to understand that
people with different backgrounds can provide different perspectives and
ideas as fresh minds always help in the product brainstorming process.‖
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However, I also saw some ambiguous entries about disciplinary differences.
An engineer: ―After working with [the entrepreneur and the anthropologist], I
was very pleased and intrigued with the way their brains operated. They had
different ways of thinking than an engineer normally would.‖
The same engineer went on to say of his anthropologist team mate:
―From [the anthropologist‘s] field, things are much more difficult to understand
and interpret into my own world. It has been very difficult to decode or decipher
exactly what he is thinking at any time because a million ideas are always
running through his head.‖
In self-view and to some extent, reality, engineers tend to be highly focused on what they see as
practical, working results. To add to this disciplinary tendency, the engineers in the class had to
produce an actual working prototype, a requirement that grew out of the fact that the class
projects were also engineering senior design projects. In spite of this, the anthropology students,
and to some extent, the entrepreneurship students, were very comfortable throwing around ideas
that often over-shot time and resource constraints. I believe some anthropology and
entrepreneurship students were, in part, displaying a high tolerance for ambiguity, by dint of
personality, disciplinary training, or both. I believe the engineer who made the ―million ideas‖
comment was encountering just such a team mate, and was not quite sure what to do with him,
seeing him as entertaining, bewildering, or, at worst, impractical.
What about the other side? The anthropology students in the class complained to me that
their input had limited impact because the engineers were always telling them, ―Hey, that‘s a
good idea, but remember, this thing has to work.‖
Yet, recent findings made by my co-panelist, Leslie Speer, and her colleagues reveal that
―successful teams have some representation on both ends of the [tolerance for ambiguity]
spectrum. This allows them to explore widely during periods of divergence, and narrowly when
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convergence is required‖ (Cobb et al. 2008:6-7). Hence, while different cognitive styles and
disciplinary work habits require great patience, tolerance and compromise on the part of
interdisciplinary team members, the struggle to work together may, in the end, be worth it.
One other well-known attribute of engineers, their work ethic, also showed up in the
journals. An anthropology student wrote: ―My engineers are like pack mules. The schedule
they keep would shame a pro athlete.‖
In conclusion, my colleagues and I have had some success in bringing entrepreneurial
and innovation-driven approaches into the social science and engineering curricula. The course
that forms the core of the initiative is being offered again this year, and is in the process of being
considered for inclusion in our General Education curriculum on campus. I‘ve seen some solid
ethnographic work by the anthropology students, and a growing appreciation among engineering
students for the importance of user-centered design and market considerations to product design
process. Students from all disciplines have come to see the value of multiple perspectives and
conceptual toolkits to innovation. While differences in style have caused some consternation,
both of last year‘s teams finished their projects and received significant external recognition of
the quality of their work. Along the way, the students achieved a relatively relativistic approach
to their differences, which warms my anthropologist‘s heart.
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Sources Cited
Cobb, Corie L., Alice M. Agogino, Sara L. Beckman and Leslie Speer
2008 Enabling and Characterizing Twenty-First Century Skills in New Product Development
Teams. International Journal of Engineering Education 24(2):420-433.
Gardner, Howard
2006 Five Minds for the Future. Boston: Harvard Business School Press.
Hasbrouck, Jay and Allison Woodruff
2008 Green Homeowners as Lead Adopters: Sustainable Living and Green Computing. Intel
Technology Journal 12(1):39-48.
Kelley, Tom with Jonathan Littman
2001 The Art of Innovation: Lessons in Creativity from IDEO, America's Leading Design
Firm. New York: Currency/Doubleday.
Kelley, Tom with Jonathan Littman
2005 The Ten Faces of Innovation. New York: Doubleday.
Lafley, A.G. and Ram Charan
2008 The Game-Changer: How You Can Drive Revenue and Profit Growth with Innovation.
New York: Crown Business.
Lattuca, Lisa R., Lois J. Voight and Kimberly Q. Fath
2004 Does Interdisciplinarity Promote Learning? Theoretical Support and Researchable
Questions. The Review of Higher Education 28(1):23–48.
Mariampolski, Hy
2006 Ethnography for Marketers: A Guide to Consumer Immersion. Thousand Oaks, CA:
Sage Publications.
Norman, Donald A.
1999 The Invisible Computer: Why Good Products Can Fail, the Personal Computer Is So
Complex, and Information Appliances are the Solution. Cambridge, MA: MIT Press.
Page, Scott E.
2007 The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and
Societies. Princeton and Oxford: Princeton University Press.
Parker, Glenn M.
1994 Cross-Functional Teams: Working With Allies, Enemies, and Other Strangers. San
Francisco: Jossey-Bass Publishers.
Polak, Paul
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2008 Out of Poverty: What Works When Traditional Approaches Fail. San Francisco:
Berrett-Koehler.
Squires, Susan and Bryan Byrne
2002 Introduction: The Growing Partnership between Research and Design. In Creating
Breakthrough Ideas: The Collaboration of Anthropologists and Designers in the Product
Development Industry. Susan Squires and Bryan Byrne, eds., pp. xiii-xviii. Westport, CT:
Bergin and Garvey.
Suchman, Lucy
2007 Human-Machine Reconfigurations: Plans and Situated Actions. 2nd edition. New York
and Cambridge, UK: Cambridge University Press.
van Veggel, Rob J.F.M.
2005 Where the Two Sides of Ethnography Collide. Design Issues 21(3):3-16.
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Paper: Riding in Dala-Dalas with Social Scientists
Prof. Khanjan Mehta
College of Engineering
Penn State University
I am an engineer and proud generalist who engages in social entrepreneurial ventures in an
international setting – primarily in East Africa. From 2004-2007, I led an interdisciplinary
venture in Kenya where students from various disciplines at Penn State University, Bowling
Green State University, University of Nairobi and Kochia Development Group (a CBO in
Kenya) collaborated to develop a robust and sustainable hybrid power system for rural
communities in western Kenya. The objective was to build the system in Kenya using Kenyan
resources and set up a profit-driven business around it to ensure economic sustainability. The
project culminated in July 2007 with the construction of the pilot windmill system and
implementation of the preliminary business plan.
While working on this project, I realized that the primary challenges on the project were not on
the engineering side (the technology existed more than 200 years back) but on the cultural,
social, and ethical aspects. Understanding the social environment, assessing social impact,
recruiting and retaining champions, and most importantly inculcating ―business sense‖ in the
partnering communities were some of the core challenges (Mehta 2008). The root cause of all
these problems was that we did not know how to deconstruct the social situations which form the
foundation of the problems that we were trying to address with technology solutions.
In product development parlance, we were not effective at uncovering the ―sticky information‖
related to the societal context of the problem. Sticky information refers to information that is
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difficult to replicate and diffuse because it is embodied in the people, places, societal constructs,
organizations and other contextual entities. This sticky information helps identify key
stakeholders, constraints and resources to be considered in the design process leading to
sustainable solutions. For social entrepreneurial ventures, the product, the design process as well
as the implementation process have to be designed with consideration to the societal context. The
sticky information needs to be uncovered and embedded in the project from the
conceptualization stage. As the information gets stickier, the location of the sticky information
forms the locus of problem-solving activities (Von Hippel 1994). I realized that these activities
can be done more effectively by collaborating with social scientists. The lessons learned on the
project in Kenya are part of the genesis for two current initiatives in collaboration with social
scientists.
The first one is an education and outreach project in Tanzania in collaboration with faculty from
the Women's Studies department. We have developed a six-credit course/internship sequence
focusing on technology-based social entrepreneurship in Tanzania. Social Entrepreneurship
encompasses the power and practicality of capitalism, inclusiveness of socialism and passion and
critical eye of feminism. The pedagogical model for this program draws from the three
philosophies to provide students with a compelling context to explore and appreciate the
complexities of social problems and develop, deploy, and assess innovative and practical
technology solutions that create sustainable value for the partnering communities. The class of
14 students spent three weeks in Tanzania in Summer 2008. My team focused on concept
validation, business plan validation, and pilot testing of a networked healthcare system. The
collaboration model and lessons learned while working on this collaboration are explained in a
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paper titled ―Multidisciplinary Social Entrepreneurship Education Model: If Capitalism,
Socialism and Feminism in concert strive, will Social Entrepreneurship thrive?‖ (under review
for NCIIA annual meeting).
In developing communities, an individual‘s ―who you know‖ network provides significant
advantages in social, economic or political situations (Granovetter 1995). On another
multidisciplinary research project, we are using social network analysis to examine ―who you
know‖ social and economic network knowledge systems among rural women agro-entrepreneurs
in Northern Tanzania and the role cell phones play within these networks. We are trying to
understand the practical connections between social networks and cell phones in creating
sustainable cooperative business models, sharing market information and identifying
entrepreneurial champions. One of my specific interests is trying to understand and articulate the
requirements and opportunities for a technology-based ‗social network support system‘ to enable
the entrepreneurs to utilize, strengthen and expand their social and economic networks. The
concepts and findings are presented in a paper titled ―Cell phones and Social Networks: Defining
new opportunities and discovering champions for entrepreneurial ventures in developing
communities‖ (under review for NCIIA annual meeting).
The biggest challenge working on these initiatives has been the vocabulary in the different fields
and understanding each other‘s perspectives. Umpteen times we have been referring to the same
concepts and meaning the same thing but realizing it only after long discussions. After all those
lost hours, I was convinced that we needed to develop a pitch to summarize the idea and get
everyone on the same page quickly. The pitch would be especially beneficial when getting other
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researchers and students onboard. However, I have realized that those discussions were actually
very important because they were also trust-building measures. The pitch will be very difficult to
develop because the human beings we are working with are much more complex than products
and business models.
I found that social scientists are extremely nuanced in their use of language – while I think and
talk ―spiritually‖ and use concise and precise words to pepper my photos and diagrams. Working
with social scientists, I discovered that the reason certain concepts were very difficult to get
across to the Tanzanians was because equivalent concepts did not exist in Swahili – their primary
language. In spite of being fluent in five languages (and getting by in three others), this was a
revelation to me! That realization made me think critically about the appropriateness of the word
―inculcate‖ when referring to ―business sense‖. It also led to more appreciation for TRULY
participatory and collaborative design and the need for working together to develop processes
which would enable that.
We learned in Kenya that ensuring equity from and between the various stakeholders involved in
the project was critical to ensure project sustainability and instill a sense of pride and ownership.
The primary challenge during business planning for social ventures for impoverished
communities is finding the sweet spot between the time equity, money equity and sweat equity
from the various stakeholders. This necessitates a complete understanding of the stakeholders
and the kinds of equity they can invest in the venture. A better understanding of the social
environment can lead us to marginalized stakeholders and resources not considered earlier. It is
important to develop a business plan (equity scheme) that creates value for everyone and not
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reinforce traditional 'winners' and 'losers' or destabilize the power structure just to create new
'winners' and 'losers'. Social scientists can help engineers and entrepreneurs rethink the paradigm
of business in various social contexts and develop effective strategies from conceptualization
through implementation to assessment to ensure that they are truly creating sustainable value and
doing no harm.
I take particular pride in working with students to design, build and deploy innovative systems,
products, processes and business models. My work is objective-oriented and driven by value
creation, ideology and adventure. There is a sense of urgency in the engineering and especially
the entrepreneurial worlds. I do not see the same emphasis on outcomes and sense of urgency in
the social science world. Maybe my shortcoming is that as an engineer, I am trained to see what
is tangible and/or mathematical. The outputs from the social sciences are not as tangible as those
from the engineering and business worlds. However, there is too much emphasis on
deconstruction and criticizing and not enough on construction and implementation of the
knowledge to build a better world. Research for research sake is a challenge across academia but
I was very surprised to find it as prevalent in the social sciences.
My primary collaborators on the social networks research project are the directors of the Inter-
institutional Consortium for Indigenous Knowledge (ICIK) at Penn State. Indigenous knowledge
- the ways of knowing, seeing, and thinking that are passed down orally from generation to
generation reflect thousands of years of experimentation and innovation. I have started to realize
the immense value of this knowledge not only for the conceptualization, validation and
implementation of entrepreneurial projects but also in our quest for solutions to problems facing
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humanity on a global scale. Social scientists can take the lead in discovering and validating this
knowledge and working with engineers and entrepreneurs to harness it for community
development.
The Accreditation Board for Engineering and Technology (ABET) has emphasized the
importance of social factors in engineering education and practice. One of the program outcomes
for baccalaureate degree programs is ―an ability to design a system, component, or process to
meet desired needs within realistic constraints such as economic, environmental, social, political,
ethical, health and safety, manufacturability, and sustainability (ABET 2007). My newfound
sensitivity to semantics exhorts me to convince my colleagues in engineering to consider society
as an enabling context rather than a constraint. With more courses on user-centered design,
humanitarian engineering and social entrepreneurship, we may be able to bridge this gap and
create value for society at the same time.
One of the most important things I have learned is that collaborations of this type are not
between colleges or departments. The collaborations are really personal relationships between
the individuals involved and that‘s why I have written this essay as a personal note. I truly
believe that there are phenomenal opportunities for engineers, businesspeople and social
scientists to work together to provide exciting opportunities to students and unleash innovation;
innovation that truly matters. My experience working with social scientists has taught me that the
biggest challenges, wildest adventures, and best learning moments for innovators and problem
solvers are out in the world conversing with real people with funny problems and fascinating
stories. The circuits, computer programs and commercialization strategies are details.
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References:
ABET. quot;Criteria for accrediting engineering programs (2008-2009).quot; ABET, Inc, 2007.
Granovetter, Mark. Getting a Job: A Study of Contacts and Careers. Chicago: University of Chicago
Press, 1995.
Mehta, Khanjan. quot;Lessons from the Field: Setting up a windmill based business in rural Kenya.quot;
Proceedings of the NCIIA 12th Annual Meeting. Dallas, TX: NCIIA, 2008. 169-177.
Von Hippel, E. quot;quot;Sticky Informationquot; and the Locus of Problem Solving: Implications for Innovation.quot;
Management Science, 1994.
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Paper: Innovation as Art: Observations from Ten Years of an Interdisciplinary
New Product Development Course
By Leslie E. Speer, San Jose State University
and
Sara L. Beckman, University of California, Berkeley
These days it is true that new product development is the lifeblood of most organizations. In
2004, U.S. companies derived 28.0% of their revenues and 28.3% of their profits from new or
derivative products introduced in the past five years.i Service companies lagged goods producing
companies, deriving only 24.1% of their revenues and 21.7% of their profits from products
introduced in the past five years.ii Nonetheless, companies have decreased investment in new-to-the-
world products from 20.4% of their portfolios in 1990 to 11.5% in 2004, and instead increased
investment in additions, modifications and improvements to existing products lines from 40.8% to
61.4%.iii Recent examination of ―blue ocean‖ strategies suggests that companies must resume
investing in innovation to grow and be profitable: 63% of revenues and 38% of profits are derived
from the 14% of new business launches that innovatively fill gaps in the market.iv Our collective
consulting and teaching experience suggests that many companies have lost their ability to innovate
effectively, and are struggling to relearn the fundamentals. In this paper, we review those
fundamentals via the lessons learned from the students in our classes on new product development, in
the hopes of providing a basic primer to those organizations wishing to reacquaint themselves with
the innovation process.
There are a number of courses offered at universities and colleges around the U.S. that strive
to teach students in engineering, business and design what the innovation process entails and to
engage them in cross-disciplinary innovation teams to experience and learn about the process (Table
1). This paper focuses on one such course offered jointly by professors from the University of
California at Berkeley and San Jose State University, and on the lessons learned by students from
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that class over a five year period from 2001 through 2006. Students in ―Managing New Product
Design and Development‖ participate in cross-disciplinary teams of four to six students who are
asked to take an idea through to first-pass prototype during the fifteen-week semester. Students
propose their own ideas for projects, and form teams around shared interests. The teams then proceed
through the basic steps in an innovation process: development of a mission statement, understanding
of customer and user needs, concept generation, concept selection, prototyping and testing, and basic
financial analysis.v They are coached throughout the semester by faculty as well as design coaches
recruited from local industry, and present their final designs at a tradeshow at the end of the semester
that is judged by industry experts.
One of the critical elements of any course is to assess how much the students have learned
during the semester. To determine what they have learned, and to give students a chance to reflect on
their experiences with the innovation process, we ask them to prepare a set of Post-It notes on which
they write the salient lessons learned during the semester. They bring these notes to the last class and,
in teams that cut across projects, they share the notes, cluster them and discuss similarities and
differences in the lessons learned. The exercise elicits meaningful reflection and conversation, and
provides course faculty with insight as to what the students took away from the team projects.
We collected the student-generated Post-It notes for the past five years, categorized them and
captured the common lessons learned. Of the 1,976 lessons learned 47% are associated with the
innovation process itself and the other 53% with the dynamics of working in cross-disciplinary
teams. We focus most of this paper on the process lessons learned, and briefly summarize the
highlights of what the students learned about team dynamics at the end.
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Process Management Lessons Learned
Table 2 shows the breakdown of process lessons learned by category. Nearly 40% of the
lessons learned are around understanding customer and user needs, partly due to the fact that
customer/user-experience design is a focus of the course, but also because students recognize it as
such a central and difficult element of the design process. The other lessons learned are relatively
evenly spread among mission statement development, concept generation, concept selection, and
prototyping and testing. We examine each of these categories, integrating students‘ lessons learned
(in quotes) with updates from recent research on innovation management and highlighting key
lessons that in our experience practitioners in many organizations are struggling to learn or relearn.
Mission Statement Development and Management
Research on product definition practices at Hewlett-Packard found that the mission
statement, a succinct description of the value proposition of a product or service, is critical in framing
a team‘s work and was missing in a number of failed projects.vi The students learn this each year as
well: ―Having a clear target user group and product description (i.e., a clear mission statement) is
essential for maintaining coherence through the design process.‖ Good mission statements tell a
―compelling story,‖ explore ―project meaning,‖ or describe ―what would make the product an ‗icon‘
for the target market.‖ Mission statements are critical in scoping the team‘s work: “Don‟t try to be all
things to all people… pick a segment you can fulfill, and focus accordingly. Don‟t waiver.” But
remaining focused is not always easy. Practitioners regularly talk of ―feature creep,‖ of the
interference of senior management in project definition, or the lack of direction from a well-
conceived product portfolio plan to guide the project‘s development.
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On the other hand, a mission statement cannot remain static throughout a project. Instead, the
team thoughtfully and constantly modifies it as they learn more about the market. “Be willing to
modify your mission statement. Sometimes what you think originally just doesn‟t make sense as you
progress.” Understanding markets and segmenting them is critical in mission statement formulation
and reformulation. Some mission statements change quite radically as teams search for meaning
based needs. One team, upon learning more about the meaning of manicures, migrated from a focus
on the ergonomic design of a fingernail polish bottle to design false nails with electronics embedded
in them that allow a user to change nail color with the press of a button. Some firms with which we
work lack mechanisms or structure to escalate information important to changing a mission statement
to the appropriate levels, while others are unable to get beyond fundamental – e.g., a low cost, high
quality product for the low end market – descriptions to provide more motivating and interesting
mission statements that tightly connect to a meaning-based user need.
Mission statements play an important role in team process and efficiency. “The mission
statement process was quite useful in forcing us to make explicit some of our assumptions of what we
were going to work on. One interesting result was that we found we had significant differences about
what those assumptions were. The mission statement provided us a framework in which to debate
and resolve our differences.” As we discuss in the section on team dynamics, the student teams
represent the ultimate in ―organic‖ team structures. In such teams, a guiding mission statement is
critical. This shows up in research on communications among team members. Successful teams have
greater agreement about their projects and what they are trying to accomplish at milestones or
deliverable due dates, but diverge more widely between milestones than do less successful teams.vii
Figure 1 shows the semantic coherence of communications among team members for two teams in
the class, one high performing and the other low performing. The high performing team questions its
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mission statement, exploring alternatives extensively between critical milestones, but reaches strong
agreement at the milestones. The low performing team, on the other hand, rarely has strong
convergence on its direction and shows declining convergence as it reaches product delivery.
In short, the mission statement – whatever it may be called in a given organization – must be
derived from the firm‘s broader product or service portfolio strategy, must lead to shared
understanding among members of the team about what they are doing, must be changed judiciously
as new information is collected, and must be the focus of healthy debate by the team throughout the
development process.
Customer and User Needs Understanding
Studies of product success and failure over the past thirty plus years have shown that
understanding customer and user needs is critical to product success, and that lack of understanding it
the greatest failure mode for new product development.viii Selective examination of 70 winners of
IDSA‘s Industrial Design Excellence Awards for contribution of those products to business also
showed that the fuel that fires real innovation – and with it business success – is concern for the
customer‘s real needs.ix The students learned well about the importance of understanding customer
and user needs: “It is very easy to believe that you know your market, when in fact you don‟t.”
“Listen, listen and listen again.” “Sometimes it‟s OK to build it and they will come. But usually it‟s
not.” They also recognized that user research must be done throughout the development process, not
just at the beginning: “Assessing/updating user needs never ends!” “Get feedback from
experts/users: problems that you hadn‟t thought of always come up during implementation.”
Students learned specifically the value of observational and ethnographic research to unearth
needs and potential solutions. “Ask why – find out what‟s behind customers‟ certain behavior.”
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“Observation and past stories can give hints to latent needs.” “While quantitative research has its
place, we felt that the qualitative research we did – particularly videotaping our prospective
customers in situ – was irreplaceable.” In particular, they saw observational research as providing
insight into the context in which their solutions would be used: “There is no substitute for at least an
approximation of ethnographic research. Watch people doing the tasks and in the context you are
designing for.” “We are not only designing a new physical product, but a part of people‟s life.” And,
they learned the value in capturing user needs information in personas: “Ground the conversation on
an „individualization‟ to avoid the bias that each member envisions themselves as the end user.”
A number of teams found it difficult to cope with such individual biases on the teams:
“Personal knowledge of an activity for which you are doing research can give you a biased view of
user needs.” They learned that “What customers say doesn‟t always equal what they do” and that it
is sometimes difficult to listen to customers and still keep the team motivated: “Don‟t get too excited
by your ideas, customers may completely disagree.” “The results of our customer needs analysis
were „somewhat discouraging‟ because we found out that most customers were not very interested in
some of our „cool ideas.‟ But, we were successful in more clearly identifying the true needs of our
potential customers.”
The students also learned that understanding customer needs doesn‘t stop with observation
and interviews, but that the interpretation of the data gathered is critical. “[It‟s] difficult to translate
user statements to user needs.” “While asking the customer what they want sounds simple and
logical, someone still needs to interpret. Even following the best process around, if there is not
insight /empathy /intuition, it‟s all for naught.” “Many times customer needs are all over the map,
making it difficult to judge which needs to focus on.” Interpretation, or extracting insights from
customer data, is a difficult task that is highlighted as one of the most critical ones in the ―design
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thinking‖ process.x In fact, the ability to really listen to customers, and take dissonant information
into account, is non-trivial for many organizations. Research shows that individuals, when
confronted with a problem – in this case information about customer and user needs that is dissonant
with their beliefs – will often choose to discard the anomalous evidence or hope the inconsistencies
will go away. Groups, on the other hand, tend to focus their conversations on the inconsistent
findings, sometimes leading to conceptual change or real discoveries.xi Processing customer and user
needs information to generate insight as a multidisciplinary group may be critical to the innovation
process.
In sum, understanding customer and user needs is at the core of successful product and
service development, but is not done well in a large number of firms. Further, in our experience
many firms engage in what we call arms length customer and user needs assessment. These firms
are so focused on collecting statistically significant data that they fail to fully understand their
customers as they could through more ethnographic or observational research. Other firms,
particularly in California‘s Silicon Valley where our schools are located, have been technology
focused for so long they struggle to shift their development processes to be more customer
experience driven. The lessons the students learn are highly relevant: invest heavily in understanding
customer and user needs throughout the product development process, dig deeply to understand why
the customers do what they do, carefully interpret the information and frame it to identify important
needs on which to focus the development effort, and use the information to keep all team members
from reverting to their own personal biases about what the product should or could do. “Be patient,
teasing out all customers‟ needs is a slow process, but one that is critical to a successful product
development.”
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Concept Generation
The basic rules of brainstorming can be found on various websites and in many books on
innovation and creativity.xii Yet, there is considerable evidence that groups do not abide by these
rules and thus significantly reduce their idea generation productivity. xiii Our experience working
with practitioners in concept or idea generation exercises corroborates this research. Despite being
given very direct instruction about how to brainstorm, many practitioner groups revert to the classic
approach used daily in conference rooms around the world of giving one person a pen and making
that person the idea recorder. Ideas are stifled as the person filters, struggles to keep up, and others in
the room argue with each idea. Participants also often lack a sense of ―psychological safety‖ in
which to put forth different or seemingly radical ideas.xiv
Well over half of the students‘ lessons learned about concept generation were focused on the
structure of brainstorming sessions, the tools used and how to use them to achieve the best results.
Students felt strongly that “brainstorming works best if done individually AND as a group (versus
only in groups)”. They found that using organized approaches to brainstorming resulted in the
highest quantity of ideas – “analyzing new ideas with a matrix can lead to more ideas rather than
less” and “post-its provide a terrific way to conduct an idea generation session”. Early on, teams
often reverted to what they were used to – talking and arm waving – but quickly learned that
“forcing yourself to come up with ideas (sketches, models, names) yields surprisingly good results”
and “brainstorming and concept generation is much easier when working with visual people.”
The students learned that “innovation has many sources”. “Use outside stimulation…. Many
interesting connections can be created between seemingly very different products or ideas.” More
importantly, taking lessons learned from the customer/user research phase and applying them to the
concept development phase afforded some teams a level of continuity and goals. “The real trick is to
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convert an idea into a perceivable value to the customer.” “Don‟t neglect the emotional aspects of a
product experience.” Concept generation with a team taught some students a lot about themselves as
well as the value of having different mindsets on the team to “push people outside their comfort
zone”. One team member remarked “I need to quiet my pragmatic mind in order to allow creativity
(mine and others) to flow”. All students concurred, “Working in a multidisciplinary team generates
a greater diversity of concepts than just an engineering team, a business team or a design team”.
It is during concept generation that the teams began to learn about the art of managing the
divergence and convergence cycles of the innovation process. “Product development has
characteristics of an art” and that “design is the art of negotiation.” Recent Ph.D. research by
Caneel Joyce at the Haas School of Business examines the need for closure and tolerance for
ambiguity, and finds that successful teams show greater diversity among team members in these
personal characteristics. In short, the tension between those with high need for closure or high
intolerance for ambiguity and those on the other end of the scale is important to successful innovation
outcomes. The challenge, of course, is managing that tension within the teams. Classic MBA
training both attracts students who have high need for closure and teaches analytical methods for
reaching closure, while classic design training attracts those with high tolerance for ambiguity and
lower need for closure and teaches synthetic methods for coping with ambiguity. Those teams that
understand, appreciate, and leverage these differences perform better in the end.
In short, concept generation requires paying close attention to the process itself so that ideas
are solicited from all team members and idea production is free flowing, creating a sense of
psychological safety within which team members feel comfortable putting forth new or different
ideas, using outside stimuli – whether people, artifacts, or ideas, remaining focused on value
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generation for the customer, and balancing the team‘s need for closure with its ability to live with
ambiguity.
Concept Selection
Research on concept selection finds that there is no difference between the quality of ideas
generated and that of those selected. In other words, while teams generate a wide range of ideas, they
tend to select ones that are average. Apparently, while people are capable of identifying ideas that
are both original and feasible, they do not spontaneously use both criteria. When left on their own,
they gravitate towards useful and feasible, but unoriginal ideas.xv This startling finding suggests a
need to understand the concept selection process much better.
We surveyed a handful of the design firms with which we work closely on their approaches
to concept selection and found that they were largely informal. While clearly focused on meeting
pre-defined criteria – ―The selection process goes back to the business definition. How best does the
concept and proposed design reduce the risk inherent in any innovation process, meet the needs of
the defined customer and ultimately stimulate the customers to part with their money?‖ – they
confessed to ―a LOT of subjective ‗what feels right‘ after the concepts have met that criteria.‖ Many
firms use ―multi-voting‖ during which individuals present at the meeting are each given a number of
votes to be cast for ideas they support for further development. Few of them, however, really think
through the critical assumptions underlying multi-voting: each person‘s vote should get equal weight,
all important criteria (e.g., manufacturability, serviceability) are adequately represented by those
present, the voice of the customer is well understood and represented, and everyone shares a
common view of the direction or mission of the project. Less used methods, such as the Pugh
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concept selection method,xvi increase the analytical rigor of the concept selection process but may be
seen as overly bureaucratic or painfully slow and detailed.
The students‘ lessons learned begin to shed some light on this critical activity. Whereas
business and engineering students are generally taught to make decisions based on facts or statistics,
design students are generally taught to make decisions based on intuition or gut feeling. Anecdotal
evidence suggests that the Myers Briggs profiles of business, engineering and design students display
this distinction as well. Business and engineering students tend to have more thinking and judging
styles, while design students tend to be better characterized as feeling and perceiving. This
divergence in approaches and cognitive styles often caused difficulty for the teams during the
concept selection stage. “In the concept selection process, assigning the ratings and weights to each
selection criteria is very subjective”. Some students found it difficult to “remain detached from
concepts, but stay focused when choosing” and that “concept selection is more difficult when many
people are voting”.
Some teams used selection matrices to make decisions as the team was having difficulty
coming to consensus on their own. Other teams used them as a test bed, to test the decision they had
already made. Though some individuals still felt that “gut feeling can be a good indicator of an
idea‟s viability” a larger number of students realized that “decision matrices are useful tools, but
must be refined and interpreted as any statistical framework”. Going back to “solicit opinions of
representative customers” in this phase was perhaps the strongest lesson learned. “The product that
the group felt was the best was not the best for the customer”. “Concept selection can be very
arbitrary when you have a room full of engineers, MBAs and designers. Let the customer decide.”
This link back to the customer was an important breakthrough for many of the teams as they were
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able to use the customer as a point to rally around, speed up, and make very clear the concept
selection process.
Concept selection is a critical, but often ill-understood step in the innovation process.
Successful concept selection requires that participants be clear about, and share understanding of, the
selection criteria, and that they are careful not to overweight feasibility over originality. Using more
explicit, quasi-analytical methods for concept selection helps. Involving customers in concept testing
and evaluation keeps a focused on customer needs rather than on its own internal criteria.
Prototyping and Testing
Project teams spend an average of 77% of their time on experimentation and related analysis
to resolve uncertainties including: technical uncertainty that arises from the exploration of materials,
production uncertainty that exists when they don‘t know if something can be efficiently, effectively
produced, need uncertainty that is created by rapidly changing customer needs, and market
uncertainty that comes from the dynamics of the marketplace.xvii Testing and experimentation is thus
a critical tool for new product development teams. Although the students in these innovation classes
generally engage in only one large experimental cycle, new product and service development is
arguably an iterative process of ongoing experimentation and testing.xviii As Alex Lee, president of
OXO says quot;Everybody talks about their successes, but the failures, the mistakes, are the most
interesting things. Our wrong assumptions lead to the best learning.quot; xix
The students noted that it was vital to “get to testing early” and that “even incomplete
prototypes can be very informative”. “A prototype tells you how it will work, but using the prototype
shows you how it really works”. ”Consumers don‟t always know what they want at first, but they
know what they like”. They were often “amazed at how different people use the same product and
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see radically different sides of it” and learned that “how a prototype is presented may bias a user‟s
opinions”. The ability to target prototypes effectively allowed the teams to link the prototyping to
areas focused on the customer, in addition to manufacturing and robust performance. “Making
extreme models and showing them separately allow one to see the strengths and weaknesses of each
model; using this information, one can integrate parts of each extreme model to build one, efficient
model to accommodate various needs.”
Many teams noted that testing with the user revealed flaws in their design that brought them
back to the table, but that in the long run “rapid prototyping is a robust method to narrow in on the
use needs and evaluate how product design satisfies user needs”. Teams engaged in paper
prototyping, mechanical prototyping (works-like), aesthetic prototyping (looks-like), and even
experience prototyping (systems and retail experiences). In each case the testing process engaged the
teams in ways they did not expect but all teams agreed that “proper prototype testing is essential for
good feedback” and that “some of the best ideas come out through testing”.
Rapid prototyping technologies used in the practitioner environment are often cost
prohibitive for multiple iterations and thus often left out of the development process due to
constrained budgets. Customer testing at the prototype stage is rarely utilized in the practitioner
world due to cost and accessibility issues. These barriers often result in solutions that, once past the
research and concept development stage, are often not tested again on customers until the product is
on the shelf. The teams in this course learn the value of inexpensive, iterative prototype testing and
the value of getting feedback from the customer all along the development process. In sum,
prototyping and testing, used throughout the innovation process, provide critical feedback to the
development team, and are an important way to engage customers.
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Organization and Team Dynamics Learning
There is a long history of organizational behavior research that describes two stylized
organizational structures: a ―mechanistic‖ structure works best under stable conditions such that it is
possible to allocate tasks according to formal job descriptions, formal information systems, and
standard procedures. As uncertainty increases, however, more ―organic‖ structures are required that
allow for ongoing adjustment and redefinition of tasks as required.xx Many have argued that highly
innovative environments require organic organizational designs. Recent research suggests closer
examination of organic structures, and finds that while fluid definition of tasks is associated with
rapid response to change, fluid definition of the mission of the team is detrimental to team
performance.xxi
The student teams in new product development classes are classic examples of highly fluid,
organic teams. They often operate without designated leaders, or are led by students managing
without authority. They assert that, on the one hand, “successful teams don‟t always have a clear
leader or hierarchy” and that “shared leadership can make a team more unified.” On the other
hand, they found that “leadership, rotating, constant or otherwise is imperative” and importantly
that “sometimes someone has to be bossy.” For these highly organic teams to be successful,
particularly lacking strong hierarchical leadership, they require shared visions of what they are trying
to accomplish, in this case in the form of a mission statement as discussed earlier.xxii
The students learned that “team building takes time,” particularly in “understanding
everyone‟s strengths and skills. Often our „specialties‟ are not our [team‟s] strongest need.” They
recommend that teams “have a framework for MBAs, engineers, and designers to learn how each
other work” such as the Myers-Briggs and cognitive style tests that we use to launch the new teams
each semester. Through such tests and explicit attention to one another‘s skills, they learned that
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“none of us had all competencies but everybody was useful at every step.” “The synergy of a jelled
cross-functional team brings to the table a variety of expertise and creative brain power. When
combined and focused, any problem will be solved.”
Increasingly, practitioner teams are taking on the same organic form as innovation is taking
place across organizational and geographic boundaries with no single person wielding universal
authority over the effort.xxiii Thus, the students‘ lessons learned have wide applicability in industry. A
comment from long-term design coach, Darrel Rhea (Cheskin) makes this clear. “The biggest
problem the students have is facing the different ways of thinking that their respective
disciplines have. They are not used to collaborating period, and even less experienced to
collaborate with other people who think differently. These breakdowns in leadership, process,
teamwork, and collaboration are the identical ones I see experienced by professionals. The
designer wants to go draw in the corner or assert the answer from a creative standpoint, the
engineer wants explicit definitions on functional challenges, the MBA wants to control it, etc.
These teams mimic the real world realities they will face. So it is the interpersonal dynamics
surrounding diversity that causes the most breakdowns and present the most compelling
opportunities for growth.”
Conclusion
Innovation is critical to the growth of most industries, and on a grander scale to national well-
being. The fact that China is feverishly investing in dozens of new design schools, and is training ten
times as many designers as is the U.S. acknowledges the importance of design to national
competitiveness. The integrative, multi-disciplinary classes on design and innovation are critical to
educating U.S. students on both the design process and the team dynamics associated with the design
40

41.
process. Putting engineering students, business students, and design students in the classroom not
only closely mimics the teams that are built in industry but gives the students insight into how their
collaborators think about the same goal – very different but with the same intent. The lessons learned
in those classes are ones that are highly relevant to industrial practitioners as they learn to become
innovative once again. In short, “This is hard. Product development is a difficult process requiring
keen insight, open and creative minds, commitment to process, reliable data and team
negotiation.” The value of including tools, practices, and points of view of both analytical and
intuitive professions affords a new, invigorated way in which to think innovatively. Putting young
minds into this environment ensures that the future of product development has more to look forward
to than any of us can imagine. The interactions, discussions, negotiations, and results of the teams
over that last ten years have given us the deeper insights into how important it is to engage students
in this challenging multidisciplinary environment.
Year First Offered Schools Name of Course(s) Departments Involved
1988 Carnegie Mellon University Integrated Product Development Business, Engineering,
Design
1993 Massachusetts Institute of Product Design and Development Business, Engineering,
Technology Design
Rhode Island School of Design
1995 University of California, Berkeley Managing the New Product Business, Engineering
California College of Arts Development Process Industrial Design
1995 University of Michigan Integrated Product Development Business, Engineering
1998 North Carolina State University Integrated New Product Development Business, Engineering,
began Lab Industrial Design
2000/ Arizona State University Cross-functional Research Planning Business
2001 and Design, Cross-functional Industrial Engineering
Conceptual Prototyping Industrial Design
2002 University of Illinois at Chicago Interdisciplinary Product Development Business, Engineering,
Industrial Design
2003 Columbia University Design and Marketing of Luxury Business, Design
Parsons School of Design Products
Table 1: Schools Offering Integrated Courses on New Product Design and Development (Source: Corporate Design Foundation,
http://www.cdf.org/ed_multidisciplinary.php, May 22, 2006)
Mission Customer/ User Concept Concept Prototyping and
Year Statement Needs Generation Selection Testing Total
2000 13 53 18 18 28 130
2001 11 52 37 27 13 140
2002 7 33 13 21 24 98
2003 13 69 27 14 22 145
2004 15 43 27 13 18 116
2005 29 23 16 13 14 95
Total 88 273 138 106 119 724
12% 38% 19% 15% 16%
Table 2: Lessons Learned by Category
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42.
1.2
S1 S2 S3 S4
1
Semantic Coherence
0.8
0.6
Avg=0.51
Avg=0.48
Avg=0.53
0.4
Avg=0.45 Avg=0.43
0.2 Avg=0.21
Avg=0.25
Avg=0.07
0
Nov -21
Sep -16 Oct -8 Oct -10 Oct -16 Oct -28 Dec -7
-0.2
Date
High performing Team B Low Performing Team C
Figure 1: Semantic Coherence at Stages of Development (S1 = Preliminary investigation, s2 = Detailed investigation, S3 = Development and S4 =
Testing and Validation) (Shuang Song, Andy Dong, Alice Agogino, Time Variance of Design quot;Story Tellingquot; in Engineering Design Teams, Proceedings
of the International Conference on Engineering Design (ICED), the Design Society, 2003.)
i
2004 PDMA Report, http://pdma.org
ii
1997 PDMA Survey
iii
Cooper, Robert, “Your NPD Portfolio May Be Harmful to Your Business Health,” Visions, April 2005
iv
Kim, W. Chan and Renee Mauborgne, “Blue Ocean Strategy: From Theory to Practice,” California Management Review, Spring 2005
v
Students largely follow the process as laid out in Eppinger, Steven D. and Karl T. Ulrich, Product Design and Development, Irwin-McGraw
Hill, 2004.
vi
Wilson, Edith, “Product Definition: Keys to Successful Product Design and Market Acceptance,” in the Handbook of Technology
Management, ed. Gerard H. Gaynor, McGraw-Hill, 1996.
vii
Shuang Song, Andy Dong, Alice Agogino, Time Variance of Design quot;Story Tellingquot; in Engineering Design Teams (Proceedings of the
International Conference on Engineering Design (ICED), the Design Society). 2003.
viii
See for example Bacon, Glenn, Sara Beckman, David Mowery and Edith Wilson, “Managing Product Definition in High-Technology
Industries: A Pilot Study,” California Management Review, Vol. 36, No. 3, Spring 1994 and Zirger, Billie Jo and Modesto A. Maidique, “A
Model of New Product Development: An Empirical Test,” Management Science, Vol. 36, No. 7, July 1990.
ix
Goodrich, Kristina, “The Designs of the Decade: Quantifying Design Impact Over Ten Years,” Design Management Journal, Spring 1994
x
Owen, Charles L., “Design, Advanced Planning and Product Development,” 3rd Congresso Brasileiro de Pesquisa e Desenvolvimento em
Design, Rio de Janeiro, Brazil, October 26, 1998.
xi
Nijstad, B. A., & Levine, J. M. (in press). Group creativity and the stages of creative group problem solving. In K. van den Bos, M.
Hewstone, J. de Wit, H. Schut, & M. Stroebe (Eds.), The scope of social psychology: Theory and applications. Oxford, UK: Psychology
Press.
xii
See, for example, http://www.mindtools.com/brainstm.html,
http://projects.edtech.sandi.net/staffdev/tpss99/processguides/brainstorming.html,
http://www.brainstorming.co.uk/tutorials/brainstormingrules.html
xiii
Nijstad, B. A., & Levine, J. M. (in press). Group creativity and the stages of creative group problem solving. In K. van den Bos, M.
Hewstone, J. de Wit, H. Schut, & M. Stroebe (Eds.), The scope of social psychology: Theory and applications. Oxford, UK: Psychology
Press.
xiv
Edmondson, Amy C., “Managing the risk of learning: Psychological safety in work teams,” in International Handbook of Organizational
Teamwork, edited by M. West, London:Blackwell, 2002.
xv
Nijstad, B. A., & Levine, J. M. (in press). Group creativity and the stages of creative group problem solving. In K. van den Bos, M.
Hewstone, J. de Wit, H. Schut, & M. Stroebe (Eds.), The scope of social psychology: Theory and applications. Oxford, UK: Psychology
Press.
xvi
http://thequalityportal.com/q_pugh.htm
xvii
Allen, Thomas J., Managing the Flow of Technology: Technology transfer and the dissemination of technological information within the
R&D organization, MIT Press, 1977.
xviii
Thomke, Stefan, Experimentation Matters, Harvard Business School Press, 2003.
xix
Salter, Chuck, “OXO’s Favorite Mistakes,” Fast Company, October 2005.
xx
T. Burns and G.M. Stalker, The Management of Innovation, Tavistock, London, 1961.
xxi
McGrath, Rita Gunther, “Team, Task and Frame as Performance Correlates: New Evidence on Organizing Innovation Projects,” Columbia
University, Working Paper, April 14, 1995.
xxii
This classic understanding of how successful teams work is further developed in Katzenbach, Jon R. and Douglas K. Smith, The Wisdom
of Teams: Creating the High Performance Organization, Collins, 2003.
xxiii
Bahrami, Homa and Stuart Evans, Super-Flexibility for Knowledge Enterprises, Springer, 2004
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