Nciia 2009 Delcore Mehta Speer

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 1

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 2

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 3

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 4

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 5

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. 6

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. 7

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, 8

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 9

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 10

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 11

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, 12

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. 13

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.‖ 14

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 15

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. 16

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 17

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. 18

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 19

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 20

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 21

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 22

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 23

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. 24

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. 25

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 26

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. 27

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. 28

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 29

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.” 30

“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 31

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.” 32

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 33

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 34

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 35

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 36

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 37

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. 38

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 39

“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

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 41

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 42

Nciia 2009 Delcore Mehta Speer

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