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Companies strive to develop and produce exactly what customers want, when they want it — and to accomplish all of that with no risk of overstocks. But such a manufacturing nirvana has become increasingly difficult to attain, given customers’ quickly changing preferences, the heterogeneity of their demands and the resulting microsegmentation of many product categories. Today, many consumer goods companies have been forced to accommodate smaller markets, as these niches often provide the only path to growth and escape from heavy price competition.
At the same time, forecasting the exact specifications and potential sales volumes of new products is becoming more difficult than ever. Recent studies have confirmed the problems of new product commercialization,1 with newly launched products suffering from notoriously high failure rates, often reaching 50% or greater. The main culprit has been a faulty understanding of customer needs. That is, many new products fail not because of technical shortcomings but because they simply have no market. Not surprisingly, then, studies have found that timely and reliable knowledge about customer preferences and requirements is the single most important area of information necessary for product development.2 To obtain such data, many firms have made heavy — but often unsuccessful — investments in traditional market research.
There is an alternative. Some companies have begun to integrate customers into the innovation process, for example, by soliciting new product concepts from them and pursuing the most popular of those ideas.
About the Research
Our research utilized a multilevel approach based on in-depth case studies. For each of the cases presented, the manager in charge of the collective customer commitment method was the primary source of information. We also conducted semistructured interviews with other members of management. Muji was studied from 2001 to September 2005, and Threadless was observed from 2004 to September 2005. For both companies, we followed several product development processes in real time, and we retraced numerous others to get information about the origins of the ideas, the evaluation phase, the voting mechanism and the generation of customer commitment. We analyzed customer comments and surveyed members of the communities for feedback and information about their participation in the product development process. This information was supplemented by data from secondary sources, including newspaper and magazine articles as well as interviews with outside experts.
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1. See R. Balachandra and J.H. Friar, “Factors for Success in R&D Projects and New Product Innovation,” IEEE Transactions on Engineering Management 44, no. 3 (1997): 276–287; G.L. Urban and J.R. Hauser, “Design and Marketing of New Products,” 2nd ed. (Englewood Cliffs, New Jersey: Prentice Hall, 1993); J. Poolton and I. Barclay, “New Product Development from Past Research to Future Applications,” Industrial Marketing Management 27, no. 3 (1998): 197–212; W.H. Redmond, “An Ecological Perspective on New Product Failure: The Effects of Competitive Overcrowding,” Journal of Product Innovation Management 12, no. 3 (June 1995): 200–213; and K. Tollin, “Customization as a Business Strategy: A Barrier to Customer Integration in Product Development,” Total Quality Management 13, no. 4 (July 2002): 427–439.
2. J. Henkel and E. von Hippel, “Welfare Implications of User Innovation,” Journal of Technology Transfer 30 (January 2005): 73–87. Refer also to M.E. Adams, G.S. Day and D. Dougherty, “Enhancing New Product Development Performance: An Organizational Learning Perspective,” Journal of Product Innovation Management 15 (September 1998): 403–422; G. Bacon, S. Beckman, D. Mowery and E. Wilson, “Managing Product Definition in High-Technology Industries: A Pilot Study,” California Management Review 36 (spring 1994): 32–56; and R.K. Teas, “Expectations as a Comparison Standard in Measuring Service Quality: An Assessment of a Reassessment,” Journal of Marketing 58 (January 1994): 132–139.
3. The origins of the idea can be traced back to Kohei Nishiyama and Yosuke Masumoto, industrial designers from Tokyo. In the 1990s, they pioneered the idea with their company Elephant Design. The core element of the company is its Web site www.cuusoo.com (cuusoo means “ideal” or “daydream” in Japanese). Here consumers can post ideas for desired products. One idea, for example, came from a copy editor who used his home as an office and wanted a discrete microwave, a plain white box. That seemed to be an odd request, but when the company showed a virtual prototype, many users expressed interest. A similar system, called “custom mass production,” is described by G. Elofson and W.N. Robinson in “Creating a Custom Mass-Production Channel on the Internet,” Communications of the ACM 41 (March 1998): 56–62. Here, users first negotiate on a particular product design, find consensus about a solution that fits the desires of all and auction the resulting design to interested manufacturers.
4. For a good review of research on customers as sources of innovation, see E. von Hippel, “Democratizing Innovation” (Cambridge, Massachusetts: MIT Press, 2005). These customers are often organized in communities by a manufacturer or intermediary; see M. Sawhney, E. Prandelli and G. Verona, “The Power of Innomediation,” MIT Sloan Management Review 44 (winter 2003): 77–82; and F. Piller, P. Schubert, M. Koch and K. Moslein, “Overcoming Mass Confusion: Collaborative Customer Co-Design in Online Communities,” Journal of Computer-Mediated Communication 10, no. 4 (2005), http://jcmc.indiana.edu/vol10/issue4/piller.html
5. A company with a very similar business model is Buutvrij from Utrecht, Netherlands (www.buutvrij.com).
6. For a good review of the inefficiencies of traditional market research, see R. Burke, “Virtual Shopping: Breakthrough in Marketing Research,” Harvard Business Review 74 (March–April 1996): 120–129.
7. See M.E. Adams, G.S. Day and D. Dougherty, Journal of Product Innovation Management 15: (winter 2002) 403–422; and V. Mahajan and J. Wind, “New Product Models: Practice, Shortcomings and Desired Improvements,” Journal of Product Innovation Management 9, no. 2 (June 1992): 128–139.
8. M. Fisher and A. Raman, “Reducing the Cost of Demand Uncertainty Through Accurate Response to Early Sales,” Operations Research 44 (January–February 1996): 87–99.
9. D.M. McCutcheon, A.S. Raturi and J.R. Meredith, “The Customization-Responsiveness Squeeze,” Sloan Management Review 35, no. 2 (winter 1994): 89–99.
10. With regard to postponement, see D. Gupta and S. Benjaafar, “Make-to-Order, Make-to-Stock, or Delay Product Differentiation? A Common Framework for Modeling and Analysis,” IIE Transactions 36 (June 2004): 529–546; and H. Skipworth and A. Harrison, “Implications of Form Postponement to Manufacturing: A Case Study,” International Journal of Production Research 42, no. 10 (May 15, 2004): 2063–2081; with regard to customization, see M. Agrawal, T.V. Kumaresh and G. Mercer, “The False Promise of Mass Customization,” McKinsey Quarterly 38, no. 3 (2001): 62–71; P. Zipkin, “The Limits of Mass Customization,” MIT Sloan Management Review 42 (spring 2001): 81–87.
11. Yamaha teamed up with Engine Inc., a competitor of Elephant Design (see reference 3). Engine focuses on fashion items and the merchandizing of movie and comic characters (its 2004 sales topped ¥570 million). Registered users can submit “please, make this” posts, that is, ideas for new products, on the company’s Web site, www.tanomi.com (the name derives from the Japanese term tanomikomu, meaning requesting, referring both to the consumers’ requests to produce a design and the manufacturers’ requests that consumers purchase the product before production). Once copyright and production feasibility are cleared by a company board, the idea is published to the entire community for evaluation, together with a price and minimum order quantity for its commercialization. In addition, Engine allows other manufacturers to post innovative product concepts directly to its community.
12. For an analysis of the reasons that markets are becoming more heterogeneous, see S. Zuboff and J. Maxmin, “The Support Economy: Why Corporations are Failing Individuals and the Next Episode of Capitalism” (London: Viking Penguin, 2002).
13. Domains with large information asymmetries between individual users and manufacturers have been called “low-cost innovation niches,” that is, fields where information held locally by individual users strongly motivates them to contribute actively to a new development; see E. von Hippel, “Democratizing Innovation.” With regard to the problem of information transfer, see E. von Hippel, “‘Sticky Information’ and the Locus of Problem Solving,” Management Science 40 (April 1994): 429–439; and S. Ogawa, “Does Sticky Information Affect the Locus of Innovation? Evidence from the Japanese Convenience-Store Industry,” Research Policy 26, no. 7–8 (July–August 1998): 777–790.
14. Muji is the retail brand name of Ryohin Keikaku Co. Ltd. of Tokyo. Once a part of the Seiyu department store chain, it is now independently listed on the Tokyo Stock Exchange. Muji has expanded globally, with 148 stores in Japan, 16 in the United Kingdom, five in France, six in Hong Kong and one in Italy. Muji sales in fiscal 2004 totaled ¥127 billion with operating profits of ¥12 billion.
15. For a good review of conventional product development practices at Muji, see P. Reinmoeller, “Dynamic Contexts for Innovation Strategy: Utilizing Customer Knowledge,” Design Management Journal 2, no. 1 (2002): 37–50.
16. The application of the collective customer commitment method was facilitated by Elephant Design (see reference 3).
17. The “Freedom Shelf” has annual sales of ¥70 million, and the portable lamp has annual sales of ¥69 million (compared with average sales of ¥24 million for comparable conventional products in this category). The project was conducted in the period from September 2002 to December 2003. Ultimately, eight themes were considered; among those, three were commercialized. Retail prices were set at ¥1,000 to ¥19,000, and the minimum required lot sizes were between 50 and 300 units.
18. The Threadless team also goes through each short-listed design to ensure that no cheating was involved by analyzing the IP addresses and IP chains for voters and the respective scores given.