1

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

2

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

3

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

4

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

5

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

6

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.

7

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.

8

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,

9

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

10

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

11

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

12

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,

13

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.

14

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.‖

15

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

16

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.

17

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

18

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.

19

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

20

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

21

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

22

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

23

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

24

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.

25

References:

ABET. "Criteria for accrediting engineering programs (2008-2009)." ABET, Inc, 2007.

Granovetter, Mark. Getting a Job: A Study of Contacts and Careers. Chicago: University of Chicago

Press, 1995.

Mehta, Khanjan. "Lessons from the Field: Setting up a windmill based business in rural Kenya."

Proceedings of the NCIIA 12th Annual Meeting. Dallas, TX: NCIIA, 2008. 169-177.

Von Hippel, E. ""Sticky Information" and the Locus of Problem Solving: Implications for Innovation."

Management Science, 1994.

26

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

27

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.

28

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.

29

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

30

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.”

31

“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

32

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.”

33

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

34

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

35

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

36

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

37

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 "Everybody talks about their successes, but the failures, the mistakes, are the most

interesting things. Our wrong assumptions lead to the best learning." 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

38

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.

39

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

40

“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

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 Technology Rhode Island School of Design

Product Design and Development Business, Engineering, Design

1995 University of California, Berkeley California College of Arts

Managing the New Product Development Process

Business, Engineering Industrial Design

1995 University of Michigan Integrated Product Development Business, Engineering

1998 North Carolina State University began

Integrated New Product Development Lab

Business, Engineering, Industrial Design

2000/ 2001

Arizona State University Cross-functional Research Planning and Design, Cross-functional Conceptual Prototyping

Business Industrial Engineering Industrial Design

2002 University of Illinois at Chicago Interdisciplinary Product Development Business, Engineering, Industrial Design

2003 Columbia University Parsons School of Design

Design and Marketing of Luxury Products

Business, Design

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)

Year Mission Statement

Customer/ User Needs

Concept Generation

Concept Selection

Prototyping and 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

42

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 "Story Telling" 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 "Story Telling" 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

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

Date

Se

ma

nti

c C

oh

ere

nc

e

High performing Team B Low Performing Team C

Sep -16 Dec -7Nov -21Oct -28Oct -16Oct -10Oct -8

S1 S2 S3 S4

Avg=0.53 Avg=0.48 Avg=0.51

Avg=0.43

Avg=0.21

Avg=0.45

Avg=0.07Avg=0.25