The Innovator's Cookbook Part 5

Social innovation has yet to pa.s.s through a similar revolution. But many are beginning to recognize that more systematic approaches pay dividends by speeding up the spread of effective solutions and reducing social costs. It is also becoming apparent to many that the key industries of the twenty-first century-health, education, and child care and eldercare, each of which will be a far larger share of GDP than information technology or cars-will require very different approaches, partly because they are so deeply shaped by public policy, and partly because they depend so much on coproduction by the user, patient, or learner.

We have proposed some of the new mechanisms and methods that may be needed. In fields where governments are the main purchasers, the more deliberate funding of outcomes rather than outputs, and the encouragement of genuine contestability, can help. But these are unlikely to be sufficient. We therefore advocate what we call "innovation accelerators": funds for seeding ideas supported by teams that combine understanding of policy contexts with understanding of business design, growth, and management (the Young Foundation's Launchpad team demonstrates how these can work in practice). We also have advocated more deliberately designed s.p.a.ces in public services that encourage experimentation (such as the UK's public service zones that allowed national rules to be broken, and rewarded results rather than compliance) and incubators that deliberately focus on mining new technologies for social applications.

In all of these, social innovation is likely to be most successful when there is close involvement of people with the strongest understanding of needs and where there are sophisticated metrics of success that can reward rapid learning and evolving end goals.

The good news is that this field is advancing rapidly, moving beyond the phase of anecdotes and enthusiasms, and beyond the twin vices of excessive faith in government action on the one hand and excessive faith in heroic individuals on the other. Instead it is addressing in a more systematic way some of the barriers that stand in the way of change. Through our work at the Young Foundation, we have found that there is growing interest in this field around the world-from China, whose leaders recognize the need to speed up solutions to their profound social challenges, to the Scandinavian countries that have led the world in social innovation over the past two decades and are keen to preserve their position. It is still an emerging field, with much to learn as well as much to achieve.

NOTES.

1 Rare exceptions include Tudor Rickards, Stimulating Innovation: A Systems Approach (London: F. Pinter, 1985); J. Gerhuny, Social Innovation and the Division of Labour (London: Oxford University Press, 1983); M. Njihoff, The Political Economy of Innovation (The Hague: Kingston, 1984).

2 Michael Young, inspiration for the Young Foundation, was judged by Harvard University's Daniel Bell as the world's "most successful entrepreneur of social enterprises," and in his work and his writings he antic.i.p.ated today's interest in social enterprise and the broader question of how societies innovate. For example, see M. Young, The Social Scientist as Innovator (Cambridge, Ma.s.s: Abt Books, 1983).

3 Childline was founded in Bombay in 1996; by 2002 the organization was working in thirty cities. For a full account, see D. Bornstein, How to Change the World: Social Entrepreneurs and the Power of New Ideas (Oxford, UK: Oxford University Press, 2004).

4 Renascer provides care to poor children after they are discharged from a hospital. By 2002, Renascer had a.s.sisted six thousand children, and successor organizations a.s.sisted a further ten thousand people. Now the challenge is to transform Renascer into a reference and training center sp.a.w.ning and supporting cells across Brazil. For a full account, see D. Bornstein, How to Change the World.

5 CIDA believes itself to be the world's only "free," open-access, holistic, higher-educational facility operated and managed by its students. Students perform all functions, from administrative duties to facilities management. Two key features of the university are (1) its partnerships with a great number of businesses in the design and delivery of all programs, and (2) the requirement of all students to return to their rural schools and communities during holidays to teach what they have learned. For a full account, see Bornstein, How to Change the World. See also http://www.cida.co.za (accessed May 24, 2006); Lucille Davie, "Jo'Burg's Best Kept Secret," April 8, 2002 (http://www.joburg.org.za/apn/2002/klipiviersberg.stm; accessed on May 24, 2006); and Andrea Vina.s.sa writing on http://www.workinfo.com/free/Downloads/243.htm> (accessed May 24, 2006).

6 For comparisons between business and the social sector in making organizations great, see http://www.jimcollins.com/lib/articles.html#.

7 For details about the open-source business model, see The Economist, "Open, but Not as Usual," http://www.economist.com/business/displaystory.cfm?story_id=5624944 (accessed May 24, 2006).

8 For example, see E. de Bono, Lateral Thinking-Creativity Step by Step (London: Perennial Library, 1970).

9 See Global Ideas Bank, http://www.globalideasbank.org/site/home/. The top five hundred ideas that will change the world are at http://www.globalideasbank.org/site/store/detail.php?articleId=178. For a list of similar organizations, see Stuart C. Dodd Inst.i.tute for Social Innovation, http://www.stuartcdoddinst.i.tute.org/innovationlinks.shtml (accessed May 26, 2006).

10 See generally: Poverty Action Lab, http://www.povertyactionlab.org/;Social Action Laboratory, http://www.psych.unimelb.edu.au/research/labs/soc_actionlab.html; Affirmative Action Laboratory, http://www.naledi.org.za/pubs/2000/indicator/article4.htm; Innovation Lab Copenhagen, http://www.innovationlab.net/sw4918.asp; Civic Innovation Lab, http://www.civicinnovationlab.org/; Eastman Innovation Lab, http://www.eastman.com/innovationlab/; MIT Community Innovation Lab, http://web.mit.edu/cilab/; ETSU Innovation Lab, http://www.etsu.edu/innovationlab/.

11 G. Mulgan, "Government and Knowledge," Evidence and Policy Journal 1:2 (May 2005), pp. 215226.

12 C. Markides and P. Geroski, Fast Second: How Smart Companies Bypa.s.s Radical Innovation to Enter and Dominate New Markets (San Francisco: Jossey-Ba.s.s, 2005).

13 R. M. Walker, E. Jeanes, and R. O. Rowlands, "Measuring Innovation-Applying the Literature-Based Innovation Output Indicator to Public Services," Public Administration 80 (2002), pp. 201214.

14 D. Albury and G. Mulgan, Innovation in the Public Sector (London: Strategy Unit, Cabinet Office, 2003).

15 Two good general sources are the Stanford Project on Emerging Companies, http://www.gsb.stanford.edu/SPEC/index.html (accessed May 25, 2006), and the Wharton School's Innovation and Entrepreneurship, http://knowledge.wharton.upenn.edu/index.cfm?fa=viewCat&CID=12.

16 J. P. Murmann, Knowledge and Compet.i.tive Advantage: The Coevolution of Firms, Technology and National Inst.i.tutions (London: Cambridge University Press, 2004); E. von Hippel, Democratising Innovation (Cambridge, Ma.s.s.: MIT Press, 2005); R. Baumol, The Free-Market Innovation Machine: a.n.a.lyzing the Growth of Miracle Capitalism (Princeton, N.J.: Princeton University Press 2003).

17 R. Lester and M. Piore, Innovation-the Missing Dimension (Cambridge, Ma.s.s.: Harvard University Press, 2004).

18 For a thorough a.n.a.lysis of open-source methods and their great potential, see G. Mulgan and T. Steinberg, Wide Open: The Potential of Open Source Methods (London: Demos and the Young Foundation, 2005).

19 In the UK, the In Control pilots delivered under the government's policy Valuing People and now recommended for wider adoption is a good example of innovation in the new relationship between user and suppliers. Prime Minister's Strategy Unit, Improving the Life Chances of Disabled People, January 2005, p. 93; David Brindle, "Controlling Interest," Society Guardian, March 2, 2005; See also http://www.in-control.org.uk/ (accessed May 25, 2006).

20 See, for example, Stanford Social Innovation Review, http://www.ssireview.com (accessed May 25, 2006); the Social Innovation Forum, http://www.wfs.org/innovate.htm (accessed May 25, 2006); Government Innovators Network, http://www.innovations.harvard.edu (accessed May 25, 2006) ; Changemakers, http://www.changemakers.net (accessed May 25, 2006); Leader to Leader Inst.i.tute, http://www.pfdf.org/innovation/ (accessed May 25, 2006).

21 For innovations in the delivery of public services, see for example: P. Alc.o.c.k, T. Barnwell, and L. Ross, Formality or Flexibility? Voluntary Sector Contracting (London: National Council for Voluntary Organizations, 2004); S. Osborne, Voluntary Organizations and Innovation in Public Services (London: Routledge, 1998). For general capacity building, see E. Evans and J. Saxton, Innovation Rules! A Roadmap to Creativity and Innovation for Not-for-Profit Organizations (London: NFP Synergy, 2004).

22 Mulgan, et al., "In and Out of Sync: Growing Social Innovaions" (NESTA and the Young Foundation, London, 2008). See "The Open Book of Social Innovation." (NESTA and the Young Foundation, London, 2010).

23 D. Leat, Replicating Successful Voluntary Sector Projects (London: a.s.sociation of Charitable Foundations, 2003); Community Action Network's beanstalk program http://www.can-online.org.uk (accessed May 25, 2006).

This paper draws on a report t.i.tled "Social Silicon Valleys: A Manifesto for Social Innovation," available for download from .

Venturesome Consumption AMAR BHIDe.

Why is the United States a good place to innovate? The question has attracted considerable attention in recent years, particularly in Europe and j.a.pan. Much of the writing on this topic emphasizes "supply side" factors such as the availability of venture capital, the IPO (initial public offering) market, the rule of law, and the enforcement of intellectual property rights. In this article, I will offer a complementary, "demand side" perspective, focusing on the frequently neglected role that consumers play in the multiplayer innovation game.

My interest in the purchase and use of the new technologies dates to 1982, when, as an employee of the consulting firm of McKinsey & Co., I worked on a study to help the European Union promote the IT industry. The team focused almost entirely on what the EU could do to help the producers of IT equipment through grants, subsidies, and tax breaks. Among the questions extensively debated was who was friend or foe: were U.S. companies that had extensive operations in Europe sufficiently European to deserve the EU's largesse? My efforts to broaden the scope of the study to include the behavior and needs of IT users-who were all in Europe-were futile. I was the lowest-ranking consultant on the team, and the clients for the study had no interest. I then wrote a Harvard Business Review article about the nature of the demand for innovative products, but it had a similarly negligible impact.1 My views have subsequently been informed by my studies over the last twenty years of new and emerging ("entrepreneurial") businesses. Obviously, entrepreneurs are more willing to innovate-and devote resources to marketing and selling their innovations-if they antic.i.p.ate a large market for their product. Developers of products that have to be tailored for a particular market or require costly sales efforts are naturally concerned about whether customers will be receptive. But that's not all: I have observed the subtle role of customers, which goes beyond the decision whether or not to buy. As we will see in this article, they play an important "venturesome" role, rather like the one played by the developers of the products they use.

Although users' role in the innovation games if often neglected, my overall thesis is not new. Several economic historians have examined the close relationship between technology adoption and economic development. Among them are Mokyr2 and Rosenberg and Birdzell,3 who argue that the West grew rich first because people there were more open to new technologies than elsewhere. I use contemporary examples to argue that adopting technology, especially of IT by the service sector, continues to play a critical role in maintaining the prosperity of the United States and other advanced countries.

My argument also incorporates the notion of what is often now called "absorptive capacity" for innovations. The term has been used in the economic-development literature at least since the early 1960s to refer to the limited capacity of "backward" countries to put new investments (and the innovations they may embody) into productive use. Cohen and Levinthal4 applied the term to the ability of individual firms to effectively absorb new technologies, and this usage has since become commonplace. Although their definition is broad, Cohen and Levinthal and subsequent researchers focus mainly on high-tech firms, examining, for instance, how internal R&D efforts help firms use research produced in university labs. I focus on organizations (and individual consumers) that have no formal R&D efforts and who use mid- and ground-level products rather than high-level scientific knowledge.

CONTRIBUTIONS TO PRODUCT DEVELOPMENT.

MIT's Eric Von Hippel has been a leading proponent of the view that innovation often starts with users, particularly the so-called lead users, rather than the manufacturers of products. In 1988 Von Hippel reported that users had developed about 80 percent of the most important innovations in scientific instruments, as well as most of the major innovations in semiconductor processing. In Democratizing Innovation, published in 2005, Von Hippel writes that "a growing body of empirical work shows that users are the first to develop many and perhaps most new industrial and consumer products."

The book recalls Adam Smith's observation that manual laborsaving machines were invented by "common workmen" who "naturally turned their thoughts toward finding out easier and readier methods of performing" simple operations.5 Von Hippel cites other examples of important innovations led by users: basic machine tools such as lathes and milling machines, oil refining, and the most widely licensed chemical processes.

In consuming products, Von Hippel provides examples from sports such as snow boarding, mountain biking, and high-performance wind surfing, which got its start when compet.i.tors in traditional wind-surfing events modified standard boards to do jumps. Their modifications were then used in boards used for normal wind surfing. Similarly, Von Hippel reports that mountain biking started in the early 1970s with young cyclists who built their own bicycles out of strong frames, balloon tires, and drum brakes from motorcycles for rough, off-road use. A fragmented cottage industry began supplying such cycles for those who didn't want to a.s.semble their own machines: it wasn't until mountain biking had grown to a sport with half a million adherents that mainstream suppliers got into the act. Von Hippel also argues that, in general, "the contribution of users is growing steadily larger as a result of continuing advances in computer and communications capabilities."

In my research of entrepreneurial businesses over the last twenty years, I have not found user-led innovation to be wide-spread. At the same time I have observed that users do often play an important "venturesome" role in the development of new products even if they don't lead or initiate the development.

In the current study of VC-backed businesses I saw virtually no evidence of user-led innovation except in the very broad sense that most innovators do put themselves in the shoes of users (but if we were to count that as user-led innovation, the category would mean nothing). Nor did I encounter much user-led innovation in my previous research on Inc. 500 companies, nor in several hundred other ad-hoc studies I have undertaken. This could be an artifact of my samples, of course. Or it could be that claims about the ubiquity of user-led innovation may be pushed by a "man-bites-dog" bias in the academic literature-studies of producer-led innovation would not excite much interest.

The current study of venture-backed businesses did, however, reveal other important roles that users play in the innovation game. Developers, especially developers of mid-level products, engaged closely with so-called alpha or beta users. The engagement was far more intense than is common in focus groups and market research questionnaires (which involve hypothetical questions) or even in taste tests (with actual products). Users partic.i.p.ated in ongoing dialogue with development teams that helped determine the attributes of the product or services that was ultimately sold.

Developers might start with the core component of a solution to an important problem faced by potential customers, but in their dialogue with users learn about complementary functions that must be added to the core to make it work. Or developers might conceive of a product with many functions, but learn that some features add more cost than value. Similarly, customer dialogue can contribute to designing an effective user interface; as the success of Google's search engine and Apple's iPod shows, the look and feel of a product can be as important to its utility as the technical features that lie "under the hood." According to many of our interviewees, many things learned from interactions with customers were incorporated into their products rather than their core idea (or patent), and this was the most valuable source of their intellectual property.

The contribution of customers to the development process tends to continue after the first commercial launch. As Rosenberg (and others) have pointed out, products can evolve so much over time that their relationship to antecedents may be unrecognizable. The first automobiles were so rudimentary that they could only be used by a "few buffs riding around the countryside terrifying horses."6 Today's personal computers have come a long way from the pioneering Altair; its aficionados derived less practical use from their machines than did turn-of-the-century automobile buffs. Lacking basic input or output devices (such as keyboards and printers), Altairs could not even scare horses. According to Rosenberg, "learning by using" by customers often plays a significant role in transforming products from rudimentary to refined.7 Users may also find new applications for existing technologies. A typical automobile, for instance, now contains scores of embedded microprocessors. Similarly, consumer electronics companies have also embedded microprocessors in household appliances, sound systems, and telephones. Producers of laptops, PDAs, and electric vehicles have found new uses for innovative battery technologies. As users try to adapt new technologies for their specific applications, the technologies may gain new features (in addition to a larger market) that make them more versatile and less expensive. In other words, the initiative of users can make technologies developed for a few markets into more general purpose platforms.d BEARING "UNMEASURABLE AND UNQUANTIFIABLE" RISKS According to Knight's theory, the essence of entrepreneurship involves responsibility for uncertainty-facing unmeasurable and unquantifiable risk rather than betting on situations where the odds have been well established by prior trials. But it is not just the producers of an innovation who face Knightian uncertainty-purchasers also cannot form objective estimates of their risks and returns.

One source of uncertainty lies in whether an innovation actually does what it is supposed to do. A product that works in the lab or in a few beta sites may not work for all users because of differences in the condition of its implementation; a product that works fine at the outset may fail later. An innovation, like a theory, can never be proven to be "good"-at any moment, we can only observe the absence of evidence of unsoundness. Repeated use of a product may bring to the surface hidden defects that cause malfunctions, increase operating costs, or pose health and safety hazards to the user or the environment.

Unantic.i.p.ated technical failures injure not only developers but users of innovations. In many products and services, failures can cost users many times the purchase price. Defects in a wordprocessing or email package that costs just a few hundred dollars may wipe out many years of invaluable files and correspondence. Even if data isn't lost, the costs of transferring files to a new software package-and learning how to use it-can be substantial. Similarly, a defective battery in a laptop can start a fire that burns down a house (this did, in fact, happen to a friend). Tires that wear badly can have fatal consequences. A security hole in its servers can cripple an online brokerage, and the belated discovery of the hazards of asbestos can lead to tens of billions of dollars in removal costs.

Consumers face risk if they invest in new products that work perfectly well for them but fail to attract a critical ma.s.s of other users. If that happens, vendors (and providers of complementary add-ons) often abandon the product and stop providing critical maintenance, upgrades, and spare parts. Or vendors may go out of business entirely-a common occurrence in IT. Customers may be left stranded if upgrades and new releases don't have "backward compatibility" with their forebears, or if a new technology makes an old product obsolete.

Customers also face Knightian uncertainty about the value of an innovation in relation to its price. In the schema of neocla.s.sical economics, consumers have a gigantic, well-specified utility function for all G.o.ds, extant as well as not yet invented. Therefore, when an innovation that serves a new want (or a new combination of old wants) appears, consumers consult their utility functions, as they might a tax table, and know exactly its worth to them. To my knowledge, there is not empirical basis for such an a.s.sumption. In fact, evidence from "behavioral" researchers such as George Lowenstein points in exactly the opposite direction: people don't have a clue about the value of things they have never experienced. When researchers ask subjects how much they would pay for some novel experience, such as kissing their favorite movie star, they receive whimsical responses, anch.o.r.ed to some irrelevant piece of data just planted in the subject's mind by the researcher, such as Social Security numbers. One interpretation of these behavioral experiments is that people are irrational; another is that they simply don't know and blurt out the first thing that comes to mind to earn their five dollars for partic.i.p.ating in the experiment. ("Snappy answer to stupid questions," a long-ago feature from Mad magazine, comes to mind.) Behavioral research has been criticized for experiments in which subjects, unlike actors in the real world, have no stake in the outcome, but in this instance the experiments do seem to correspond to reality. It is improbable, for instance, that anyone who wears gla.s.ses or contact lenses has a firm grasp of the economic value of (successful) corrective laser surgery, or that someone who has a conventional TV can gauge the value of switching to a higher-definition digital product. Indeed, I am skeptical that people who actually have laser surgery or buy a digital TV can quantify the value. Before or after a purchase, the enhanced utility is a shot in the dark, much like the value of the pleasure Lowenstein's subjects antic.i.p.ate from kissing movie stars. I personally have not seriously considered either laser surgery or buying a high-definition TV, but I have been enticed by the latest in the personal computer hardware and software for more than two decades. I have no idea of the value of my numerous upgrades (or for that matter, a good estimate of the time and opportunity costs I have incurred).

Similarly, although I have worried about-and periodically endured-the consequences of technical defects and abandonment of favorite programs by vendors, I have never actually made an effort to quantify the probability distributions. I cannot imagine being able to enumerate all the dire possibilities. People who have corrective eye surgery may ask about the probability that something might go wrong or that the operation won't give them 20/20 vision. But what basics could they possibly have for evaluating the consequences twenty or thirty years later?

Organizations that purchase expensive systems do often expend many person-years' effort to evaluate their costs and benefits. For example, Columbia Business School recently acquired a new "courseware" platform. A committee was formed, long Requests for Proposals issued, shortlists made, vendor proposals studied, consultants retained . . . but for all the effort and availability of the finest a.n.a.lytical minds, the value of the new courseware was-and will remain-elusive. The monetary value of enhancing student satisfaction and learning and of saving faculty time can only be a blind guess. Similarly, although the out-of-pocket costs of purchasing a system played a role in picking a vendor, the magnitude of the much larger "all in" opportunity costs (e.g., the time of faculty and staff) of switching to any new courseware platform were unfathomable.

a.s.sessing the costs and benefits of enterprise-wide software and systems used by corporations that are many times the size of the Columbia Business School is even more difficult. As the sidebar "Evaluating ERP Systems" indicates, the off-the-shelf enterprise software rarely matches the practices and processes that it is supposed to facilitate or automate. Rather, organizations have to extensively modify and adapt both the software and their practices. The costs of modifying the software, and the frequently more problematic "reengineering" of the practices, are very hard to pin down. So are the benefits: these are supposed to include not just the improvements realized through automation, but also the adoption of superior practices.

Evaluating ERP Systems According to the current Wikipedia entry on the topic, ERP (enterprise resource planning) software is used for the "control of many business activities, like sales, delivery, billing, production, inventory management, quality management, and human resource management." The systems are supposed to integrate many functions, including "manufacturing, warehousing, logistics, Information Technology, accounting, human resources, marketing and strategic management." In principle, all these activities and functions use a single database rather than, for instance, the human resources department and the payroll department maintaining records on the same employee in two different and incompatible databases.

Most ERP systems are not built to suit-rather they are based on packages provided by software companies such as Oracle and SAP. The premise of such systems, according to Eric Roberts, professor of computer science at Stanford, is that "software systems are expensive and complex. What's more, the expense of a software system lies almost entirely in its development; once a system is built and tested, the marginal cost of delivering that same system to other users is typically quite small. The concentration of cost in the development phase creates a strong incentive to share development expenses over a large user base. If it costs $10 million to develop a system, it seems foolish for a single inst.i.tution to bear that cost alone. Given that the bulk of that $10 million represents development, it makes far more sense-at least in theory-for a consortium of inst.i.tutions to purchase software from a vendor that can then distribute those costs over the community of users."8 There is, however, a catch, writes Roberts: "The success of any enterprise system depends on refashioning the business practices of the inst.i.tution to match the software rather than trying to change the software to accommodate the idiosyncrasies of the inst.i.tution. Changing the software violates the underlying economic a.s.sumption that allows for the reduction in cost. If each inst.i.tution tailors the system to suit its needs, the cost advantage vanishes."

Enterprise software vendors claim that their systems incorporate the best possible business practices. Therefore, customers gain significant advantages if they refashion their business practices to fit the standard package. But in fact, although the packages draw their "best practices" from a variety of industries and situations, there can be a considerable gap between the best-practice configuration available in the package and the practice that works best for a particular organization. In The ABCs of ERP, Christopher Koch comments, "While most packages are exhaustively comprehensive, each industry has quirks that make it unique. Most ERP systems were designed to be used by discrete manufacturing companies (that make physical things that can be counted), which immediately left all the process manufacturers (oil, chemical and utility companies that measure their products by flow rather than individual units) out in the cold."

In fact, it is simply infeasible for organizations to adopt all of the specified best practices. Therefore, they usually compromise: organizations change some of their best practices to suit the system, but they also "struggle" to "modify" core ERP programs to their needs, writes Koch. All this makes it extremely difficult to a.s.sess the value or the costs. Koch writes that "the value of the systems is hard to pin down because... the software is less important than the changes companies make in the ways they do business. If you use ERP to improve the ways your people take orders and manufacture, ship and bill for goods, you will see value from the software. If you simply install the software without trying to improve the ways people do their jobs, you may not see any value at all-indeed, the new software could slow you down by simply replacing the old software that everyone knew with the new software that no one does."

Similarly, there "aren't any good numbers to predict the costs because the software installation has so many variables, such as: the number of divisions it will serve, the number of modules installed, the amount of integration that will be required with existing systems, the readiness of the company to change, and the ambition of the project-if the project is truly meant to be a battering ram for reengineering how the company does its most important work, the project will cost much more and take much longer than one in which ERP is simply replacing an old transaction system. There is a sketchy rule of thumb that experts have used for years to predict ERP installation costs, which is that the installation will cost about six times as much as the software license. But this has become increasingly less relevant.... Research companies don't even bother trying to predict costs anymore.

GROUND-LEVEL DEVELOPMENT.

The effective use of innovation usually requires acquiring or developing ground-level know-how. There are very few products that humans can use immediately: we have to acquire the knowledge, and sometimes the taste, for almost everything that we consume in our daily lives-we must learn how to brush our teeth, tie our shoelaces, knot ties, savor espressos, and drive cars. An innovative biometric lock opened by swiping one's fingers over a sensor eliminates losing or fumbling with keys, but there is a catch. As Anne Eisenberg (who reviewed the product for the New York Times) discovered, after installing the lock, she could not recall the finger-swiping technique the next day. "I swiped and swiped," she writes, "but the door wouldn't budge. Many speeds and angles can be used in swiping a finger I gradually realized, and I could no longer recapture the technique I'd used the night before." Swiping a finger isn't necessarily harder than turning a physical key in a conventional lock; but as Stephanie Schuckers, a professor of electrical and computer engineering points out, people have already learned to use standard locks: "We are all trained how to use keys, from when we are young."9 Differences in how products are used require consumers to do more than just acquire the knowledge of a "standard technique"-they have to develop ground-level know-how tailored to their specific requirements. For instance, users of spreadsheets don't just acquire the knowledge of standard pull-down menus and commands; they also have to develop, or at least modify, their own templates and models. Furthermore, mid-level products that are jointly used by several individuals often require the development of ground-level organizational know-how as well as technical know-how-as previously mentioned, the use of enterprise software requires the development of new processes and practices as well as adaptation of the software itself. And because processes and practices can vary considerably, each organization has to develop its own.

Research10 on the adoption of client/server technology doc.u.ments the importance of developing multifaceted ground-level know-how (which Bresnahan and Greenstein call "co-invention").e Bresnahan and Greenstein found that companies in the vanguard of adoption were in science and engineering-based industries that were "least tied to complex business procedures." The slowest adopters were in industries with great "organizational complexity," where "organizational adjustment costs were highest. Adjustment costs, rather than the benefits of client/server systems, seemed to drive the adoption of the technology.

Innovators who develop mid-level "combinations" require different skills and human capital than do researchers who work on high-level scientific problems. Similarly, users who have to develop ground-level know-how require yet another set of skills-while technical knowledge is certainly necessary, managerial and organizational knowledge is crucial, and there are policy implications of these differences. But here I want to emphasize the following similarity: both the developers and users of innovations often require a high degree of venturesome or entrepreneurial resourcefulness in problem solving.

Developers of innovation often face situations that require such resourcefulness in the following sense: although the situation may be similar to ones the innovator has faced before, it also contains novel elements, so the innovator cannot simply repeat what has worked in the past. Experience (or "human capital"), which we may think of as the acc.u.mulated knowledge of similar past situations, helps, but it is not enough. An innovator is more than just a skilled and knowledgeable surgeon performing difficult but routine arthroscopic knee surgery. The innovator must also act resourcefully in the face of novel situations with a can-do att.i.tude, imagination, willingness to experiment, and so on.

Consuming something novel does not always require resourceful problem solving. Drinking a new soft drink or showing up for an appointment for corrective surgery is not especially demanding. Other kinds of consumption-such as a.s.sembling a model airplane-may require patience, dexterity, and experience, but as long as the instructions are clear and complete, they do not require resourcefulness or creativity. Indeed, creative deviations from prescribed instructions can lead to undesirable outcomes. But not all innovations come with clear and complete instructions. High-tech products, especially those with complex architectures and features, rarely do, and deriving utility from them requires a great deal of resourceful problem solving.

Manuals for Windows-based personal computers and software, for instance, are famously bewildering. This is not mainly because of the incompetence of the authors of the manuals. In considerable measure, the sometimes bewildering instructions reflect the complexity of the internal architecture of the systems, the many options and features they contain, and the difficulty of antic.i.p.ating how the components will interact. But whatever the cause of that impenetrability, my experience has been that the alluring features of new products rarely work "out of the box" if one simply follows the instruction manual. I have spent countless hours getting new gizmos to work, or trying to stop inexplicable crashes. And the toil is far from mechanical: I have to guess what might be wrong, conduct experiments, and troll through postings of user groups on the Internet trying to find solutions to similar problems. Moreover, figuring out how something is supposed to work is often only half the battle: in many innovations, users have to figure out how to make the product work well for them. In the case of innovations such as enterprise software, the figuring out involves the solving of technical and organizational problems. Experience and effort is helpful, even necessary. But as "Using ERP Systems" indicates, because the problems tend to be idiosyncratic, the solutions require a great deal of resourcefulness as well.

Using ERP Systems The effective use of complex enterprise software requires solving both technical and organizational problems. As Koch writes: The inherent difficulties of implementing something as complex as ERP is like, well, teaching an elephant to do the hoochy-kootchy. The packages are built from database tables, thousand of them, that IS programmers and end users must set to match their business processes; each table has a decision "switch" that leads the software down one decision path or another . . . [F]iguring out precisely how to set all the switches in the tables requires a deep understanding of the . . . processes being used to operate the business.

Inevitably, business processes themselves have to be "reengineered." Users who want to take advantage of off-the-shelf software packages must align their processes with the "best practices" built into the software. To have a system that is truly enterprise-wide, organizations have to figure out processes that work best across their different units. Inevitably, individuals and organizational subunits resist changing the way they do things; and even if they don't, business processes and their a.s.sociated information systems cannot be changed overnight. Therefore, in addition to figuring out what their business processes should ultimately look like (and how the "switches" in the software need to be set to match the processes), organizations also need to resolve how they will overcome resistance to change and make the transition from "legacy" processes and systems.

Consultants who have implemented ERP systems in the past can help ameliorate these problems. However, the issues facing different organizations are never identical, so the consultants and their clients have to solve many novel problems. Moreover, ERP packages and the other applications-for instance supply-chain, customer-relationship-management (CRM), and e-commerce software-that ERP is supposed to complement also change frequently, which adds to the difficulty of deriving a tried-and-tested formula for implementation. Researchers and industry experts who have expended considerable effort to investigate what works and what doesn't have been unable to get beyond long and wooly lists. Somers and Nelson formulated a list of twenty-four "critical success factors," starting with "top management support" and including items such as "project team competence," "interdepartmental cooperation," and "clear goals and objectives."11 For obvious reasons, such lists do little to obviate the need for situation-specific problem solving.

The mixed record of ERP systems also points to the difficult problems users must solve to realize the potential benefits. Holland and Light point out that successful implementations at pioneer New Media Technologies and Monsanto have been well publicized, but "less successful projects have led to bankruptcy proceedings and litigation."12 Similarly, Plan and Wilc.o.c.ks note the success of ERP at companies such as Cisco as well as "spectacular" failures at Hersey Foods and FoxMeyer and disappointments at Volkswagen, Whirlpool and W.L. Gore.13 NOT QUITE FREE.

Economists often believe that innovations are a gift to consumers. Stanford's Paul Romer writes that innovators "have brought the cost of a transistor down to less than a millionth of its former level. Yet, most of the benefits from those discoveries have been reaped not by the innovating firms, but by the users of the transistors. In 1985, I paid a thousand dollars per million transistors for memory in my computer. In 2005, I paid less than ten dollars per million, and yet I did nothing to deserve or help pay for this windfall."

My a.n.a.lysis suggests a slightly different view. In all likelihood, users do secure the lion's share of the benefit for successful innovations. But not all innovations are successful. Apple's iPod has been a resounding success for both the company and its customers-its Lisa and Newton were not. When products fail, the downside faced by users in the aggregate (and sometimes even individually) in innovations ranging from corrective laser surgery to enterprise software matches or exceeds the downside of the innovator. Indeed, one important challenge faced by innovators is to persuade entrepreneurs to take a chance on innovations in the absence of any hard demonstration that the returns are worth the risks.

One of the notable features of the modern innovation system lies in the great many individuals and organizations that are willing to be so persuaded. At the dawn of the automobile era, only a few very rich buffs served as guinea pigs. Now, the not-so-well-off borrow against their credit cards-or spend what they "save" by buying paper napkins in bulk at Walmart-to take their chances on laser surgery and flat panel TVs without much foreknowledge of the utility of their purchase. Similarly, large corporations run by the book with the help of squadrons of financial a.n.a.lysts will spend tens of millions of dollars on enterprise software based on the crudest of guesses of costs and benefits.

Even late adopters who only buy tried-and-tested products don't get a free ride. Romer sells himself-and other computer users-short in declaring that they have "done nothing" to deserve the windfall of lower prices. Large markets and the prospect of their continued growth have helped drive down prices. And markets have grown because individuals and companies have invested in learning how to use computers and developed ground-level know-how. The investment is not trivial. The prices of computers have declined, but their complexity hasn't. Feature bloat may, in fact, have made computers and programs harder to use. Yet the number of people who have made the effort-possibly incurring opportunity costs many times the purchase price of their equipment and software-has over the years continued to grow. Users who build their own templates and models for spreadsheet and database programs now number in the tens of millions, whereas the teams at Microsoft who develop such products number in the thousands.

A Mult.i.tude of User Programmers Scaffidi, Shaw, and Myers (from Carnegie Mellon's school of computer science) use a variety of sources to estimate the number of end users of computers and end-user programmers in the United States. They get a lower bound estimate of 55 million computer users in 2005 by multiplying the number of individuals in different occupational categories in 2005 by the percentage of computer users in that category in 1989. For instance, in 2005, there were about 36.7 million workers in the "managerial and professional" category, and 56.2 percent of such workers used computers in 1989, leading to an estimate of 20.6 million "managers and professionals" using computers in 2005. But as Scaffidi and coauthors point out, the percentage of computer usage in the different categories has increased significantly since 1989. For instance, the percentage of managers and professionals using computers grew from 56.2 percent in 1989 to over 70 percent in 1997. Extrapolating from these trends, the researchers arrive at an estimate of 81 million users of computers at work in 2005. They note that other estimates are even higher-for instance, a Forrester Research survey commissioned by Microsoft estimated that 129 million people in the United States between the ages of eighteen and sixty-four used computers at home or at work in 2003.

Scaffidi and coauthors also highlight the growth of some kind of programming by end users. Since 1989, the Current Population Survey (CPS) conducted by the Bureau of Census has included questions such as "Do you do programming?" and "Do you use spreadsheets or databases?" Here, too, we find substantial increases: The percentage of U.S. workers who said they used spreadsheets grew from about 10 percent in 1989 to over 30 percent in 1997. Similar increases were reported in the usage of databases. Between 1997 and 2001, "Usage of end user programming environments continued to explode, with over 60 percent of American end user workers reporting that they 'used spreadsheets or databases' in 2001. This amounted to over 45 million end users of spreadsheets or databases." Increases in the proportion of workers who reported they "did programming" were relatively modest, rising from about 10 percent of the workforce in 1989 to 15 percent in 2001. Nonetheless, the estimated 11 million workers who reported that they did programming was more than five times less than the two million programmers in the United States in 2001.14 Of these software professionals, two-thirds worked for IT-using companies rather than IT-producing companies.15 CONCLUDING COMMENTS.

In the North-South trade models-as in most mainstream economic theories-users of new technologies are at once pa.s.sive and omniscient. They play no role in the development of innovations, but once innovations appear, users know whether they should buy the offering and what they should pay. Even in Schumpeter's theories (which in other ways challenge mainstream models), the innovator is the star, while those who imitate or modify have secondary parts. Consumers don't appear in the cast.

The neocla.s.sical and Schumpeterian models both fail to do justice to the role of users. In a system where innovations are carried out by numerous players, the producers of innovations are, except for the end consumers, also users of higher-level or "adjacent" innovations. Users-including those at the end of the line-often play a venturesome or "entrepreneurial" role in the design of new products, bearing "unmeasurable and unquantifiable" risks and developing ground-level knowledge. Therefore, contrary to the high-level research-centric view, the willingness and ability of users to undertake a venturesome part plays a critical role in determining the ultimate value of innovations. The venturesomeness of customers also encourages innovators to optimize their offerings for customers' needs and to invest in marketing to them.

NOTES.

1 Bhide, Amar. 1983. "Beyond Keynes: Demand Side Economics." Harvard Business Review 61, no. 4 (JulyAugust): 100110.

2 Mokyr, Joel. 1990. The Lever of Riches: Technological Creativity and Economic Progress. New York: Oxford University Press.

3 Rosenberg, Nathan, and L. E. Birdzell Jr. 1986. How the West Grew Rich: The Economic Transformation of the Industrial World. New York: Basic Books.

4 Cohen, W. M., and D. A. Levinthal. 1989. "Innovation and Learning: The Two Faces of R& D." Economic Journal, September, pp. 36996.

5 Smith, Adam. 1776. An Inquiry into the Nature and Causes of the Wealth of Nations. Modern Library edition. New York: Random House, 1937.

6 Rosenberg, Nathan. 1976. Perspectives on Technology. New York: Cambridge University Press.

7 _____. 1982. "Learning by Using." In Inside the Black Box: Technology and Economics . New York: Cambridge University Press.

8 Roberts, E. 2004. "Here Be Dragons: The Economics of Enterprise Software Systems." Letter to Members of the Faculty Senate, Stanford University, May 27.

9 Eisenberg, A. "The Door Key That Can't Be Misplaced," New York Times, June 10, 2007.

10 Bresnahan, Timothy F., and Shane Greenstein. 1996. "Technical Progress and Co-invention in Computing and the Use of Computers." Brookings Papers on Economic Activity: Microeconomics 1996:178.

11 Somers, T. M., and K. Nelson. 2001. "The Impact of Critical Success Factors across the Stages of Enterprise Resource Planning Implementations." Proceedings of the 34th Hawaii International Conference on System Sciences (HICSS-3), Maui, Hawaii, January 36. CD-ROM.

12 Holland, C. P., and B. Light. 1999. "A Critical Success Factors Model for ERP Implementation." IEEE Software MayJune , 3035.

13 Plant, R., and Leslie P. Willc.o.c.ks. "Critical Success Factors in Internation ERP Implementations: A Case Research Approach." London School of Economics and Political Science Working Paper, May, 2006.

14 Scaffidi, Chris, M. Shaw, and B. Myers. "Estimating the Numbers of End Users and End User Programmers." Proceedings of the 2005 IEEE Symposium on Visual Languages and Human-Centric Computing. FL?HCC'05. 18. http://ieeexplore.ieee.org/Xplore/login.jsp?url+/iel5/10093/32326/01509505.pdf?arnumber+1509505.

15 Arora, Ashish, Chris Forman, and Jiwoong Yoon. N.d. "Software," in Innovation in Global Industries: U.S. Firms Competing in a New World, ed. Jeffrey Macher and David C. Mower. Washington, DC: National Academies Press.

INNOVATORSAT WORK.

A Conversation with Brian Eno Brian Eno is a musician, producer, artist, writer, and technologist whose ideas have had an astonishingly wide impact on our culture since the early 1970s. His solo and collaborative records with artists like David Byrne and John Cale have helped inaugurate new genres of music, including ambient generative music, as well as pioneering techniques that became essential to modern sampling. As a producer, he has a long track record of creating essential new sounds with some of the most famous musicians in the world: David Bowie, the Talking Heads, U2, and Cold play. His art installations have been showcased at locations around the world, and he has even collaborated with the game designer Will Wright to create the generative soundtrack for the game Spore.

SJ: I'm looking at this card deck of "Oblique Strategies" that you created with Peter Schmidt many years ago, and the little introduction to the set says the cards arose out of "observations of the principles underlying what we were doing." So I guess that's where I want to start: you've had this extraordinarily innovative career in multiple fields. Do you see some underlying principles behind the way you have come upon new ideas?

BE: Anyone who's had children will know that the urge to create-to make something from nothing-is innate. You can't stop kids from doing it: they're perpetually inventing. Sometimes we manage, through our education systems, to multiply that energy: often we manage to stifle it. The trick for me isn't about showing people how to be creative as though they've never been like that before, but rather trying to find ways of recontacting the natural playfulness and curiosity that most people were born with. There are quite a few facets to this, but a very big part of it involves moving away from the idea that "creativity" is an exclusively individual thing, that it springs up in certain gifted individuals, entirely from their imaginations. The more you look at the history of art and science, the more you notice that it is as much to do with the contingencies of the time: the technologies that were around, the conversations that were taking place and so on. This isn't to say that there are no differences between minds, but rather that those differences might be of another order than pure "processing power": they might have a lot to do with the sheer luck of where you happened to be born, of who said what and when, of what tools were available to you.