The Smartest Places on Earth

by Antoine van Agtmael

  The collection, analysis, management, and leverage of all this information is generally known as “big data,” and along with many benefits, it raises many prickly questions regarding privacy and security. And the collection of data is becoming more pervasive, such that it is no longer the exclusive domain of information technology companies. In both Europe and the United States, producers of various kinds of hard goods are adding service-oriented products to their portfolios. By leveraging new technologies such as embedded sensors, these companies are collecting vast quantities of data to create new customer services.

  In 2003, a project driven by the Federation of Finnish Technologies, the Finnish government, and Tekes,24 the Finish agency that finances innovation, helped a number of companies make the transition from being providers of specific solutions to becoming “value partners.” Thirty companies took part in the initiative, including Kone, Wärtsilä, Nokia, Finn-Power, Fastems, and ABB.

  The example of Kone, an elevator manufacturer, illustrates the results of the project. The company, which had long offered elevator maintenance services, developed a set of solutions that helped its customers better understand the flow of people in highly populated buildings, such as offices and hospitals. The company began working with contractors and architects on a design for a medical facility—including, of course, the distribution of elevators—incorporating input from doctors and nurses to optimize movement within the buildings. Ultimately, Kone reimagined itself as much more than an elevator maintenance company but rather as a “people-flow” company. This new focus is readily apparent in the skills required of its employees, who must possess client-facing skills in addition to their technical capabilities.

  As the Internet of Things grows in ubiquity, it will further increase our capacity to gather data from a global network of billions of connected objects and devices. To be effective, however, we will need to settle on a set of standards and protocols for data sharing so that the massive amount of information being created can be communicated flawlessly among systems and machines. In 2014, the Internet Industry Consortium—an open-membership group including companies such as Intel, Cisco, IBM, AT&T, and GE—was founded to develop this framework. In Germany, a similar initiative was announced by the federal government in early 2013 under the name Industry 4.0, referencing the Fourth Industrial Revolution of the Internet of Things.25

  The avalanche of data that modern technology provides is one of the reasons that traditional sector distinctions have become increasingly blurred. As we discussed in the introduction, the idea of information technology, service, manufacturing, and agriculture as separate branches of the economy or industries is outdated. The future economy will be dominated by smart manufacturing, that is, the fusing of information technology and new technologies, materials, and discoveries with these traditional branches, built on a foundation of sharing brainpower.

  Much More to Come

  In this chapter we have touched on only a few key areas of activity that are related to some of the most important twenty-first-century challenges we face—and, in particular, those that are being developed and will continue to be refined through the sharing of brainpower, and the use of sensors and chips and advanced materials, as well as the phenomenon of smart manufacturing. There is no doubt that these activities will change—and, we believe, improve—the societal structures that define our lives.

  Beyond the technologies and processes involved, there is the profound change that is taking place in the way people address our greatest challenges—through sharing brainpower and collaborative decision making. In the brainbelts we have studied, we see that a collaborative and entrepreneurial spirit has awakened in politicians, scientists, professors, and students, and it will have far-reaching consequences for the way organizations, societies, and economies function. Local political leaders will gain influence and prestige, and federal authorities will increasingly become facilitators (if they choose not to get in the way). We even believe that the dominant assumption of our working life—that globalization is accelerating whether we like it or not—is coming into question. Automation will make cheap labor increasingly irrelevant. As new materials replace long-used commodities (as carbon takes over from aluminum in aircraft, and bio-materials substitute for carbon-based plastics), there will be less need to ship production components, semifinished products, and finished goods around the world. Food, clothing, and shoes will once again be made closer to home. Local production will grow and global trade will slow. In other words, globalization will not accelerate forever; it will reach a peak and then level off and even decline. Worldwide, brainsharing and collaboration will increase in variety and degree, creating stronger ties between old and new economies, transforming traditional workplaces into innovation zones, and remaking rustbelt areas into brainbelts.

  If, that is, we can successfully address a number of key practical issues—including education and training, policy, funding, and culture—that are essential to supporting and spreading the practice of sharing brainpower.

  Chapter Six

  AWAKENING THE BEAUTIES

  Could Your Region Be One of the Smartest Places on Earth?

  Somewhere, something incredible is waiting to be known.

  —CARL SAGAN, ASTRONOMER

  We have entered a new era in which many forces are at play: the sharing of brainpower, smart manufacturing, the simultaneous interaction between thinking and making, the rise of the brainbelt, and the decline of the low-cost labor advantage. But this new era is still patchy in places and struggling to emerge against a backdrop of structures, practices, organizations, skills, and attitudes left over from earlier times. This new era, like other transformational moments before it, did not come about as the result of a grand plan or globally unified effort. How could it have? The new era evolved, happened, was pushed.

  What really struck us on our journey through the brainbelts, however, was that on the local and regional levels there were always ideas and a willingness to take action, even if federal initiatives in the United States or (to a lesser extent) European-wide efforts sometimes languished. People found ways to break loose from the stagnation and negative thinking that had been prevalent in the rustbelts. Individuals with vision and commitment brought institutions, authorities, and companies together.

  Necessity played a major role in the rise of the brainbelt phenomenon. The need for jobs, revenue, and clout—combined with the complexity of technologies and a lack of resources—forced people and groups to put aside their differences, step over their organizational barriers, and reach out to unaccustomed colleagues, in order to collaborate on research, share knowledge, and work together to make things and push forward initiatives. This sharing of brainpower across an ecosystem of participants to achieve innovation is very different from the kind of innovation that is so talked about these days—the kind that Apple, Google, Amazon, and other iconic technology leaders practice. These players already possess the talent and resources to build internal innovation engines. They are not weighed down by the memory of stagnation or hampered by the presence of abandoned facilities or faltering infrastructure. What they lack they can acquire. They do not need to open up, share knowledge, reveal their secrets, reach compromises, and forge win-win deals. Indeed, they continue to operate as “lonely heroes.” They have power and influence. Such companies may form partnerships and allegiances, but they remain at the center of them. They call the shots.

  Although we tend to revere the lonely hero, there are limitations and drawbacks to the model. The lonely hero organization can amass too much power, squash outside innovation when it becomes threatening, limit the range of action of partners, become complacent, and put a chokehold on consumers. Brainbelts may not be as tidy in their process or as burnished in their image, but they have every bit as much (or more) potential to create breakthroughs and game-changing technologies and products as any lonely hero.

  However, in order to fully realize the potential of the world’s brai
nbelts, to awaken beauties that are currently slumbering, and to extend and leverage the practices of sharing brainpower that have been pioneered in those innovation hubs, there are many of those leftover structures and practices we need to think about, alter, clear away, or improve. We need to start with the recognition that today’s innovation is more bottom up than top down. It takes place mostly at the local level, in proliferating brainbelts where academia and business share brainpower and are hard at work to invent and design the smart products that address the challenges of the twenty-first century. But national (or, in the case of Europe, European Union) brainbelt initiatives that support the continuous process of innovation through funding of fundamental research, challenge grants, an emphasis on crosscutting technologies, teamwork and collaboration, and modernization of physical and digital infrastructure—these remain immensely helpful. The payoffs in innovation from top-down support from DARPA and EU programs to Chinese and South Korean innovation policies stand out. National government support for innovation should no longer be mired in ideological debates. Moreover, the thrust of education and training programs must be rethought. More funding needs to find its way to potential brainbelt areas. Organization design, leadership, and cultural attitudes and assumptions need to be adapted. And, very important, we must find better ways to measure and evaluate the performance of collaborative activities such as brainsharing, even in the early stages. Here are a few thoughts about where we are now on these issues and how we might make change.

  Policy and Guidelines

  The idea that a country should have a common framework and policies to stimulate and support innovation in brain-belts is hardly a radical one. On the contrary, almost every country in the world has a set of innovation guidelines and objectives, with one notable exception: the United States. Why is it that, in the world’s largest economy, politicians and business leaders seem to have an allergic reaction to the notion of a national innovation policy? Perhaps it’s because things seemed to be working pretty well without a national policy in places like Silicon Valley, where entrepreneurs and researchers were quick to claim credit for projects that would not have happened without government funding. Or perhaps it’s because such policies are sometimes confused with industrial policy, which focuses on specific industries or economic sectors and is often seen as a form of governmental interference in private enterprise. But the goal of innovation policy is not to regulate or to interfere but rather to encourage, motivate, and support innovation.

  Critics love to cite government’s failures, such as the support for solar-cell maker Solyndra, but there are far more examples of successful government participation in helping innovation than there are of misfires. However, even without a fully articulated national policy, the US government has pursued many initiatives over the years to promote growth and innovation in areas as diverse and as world-changing as transistors, lasers, the Internet and search engines, jet propulsion, space exploration, drones, horizontal drilling for oil/gas, new materials, robots, and the autonomous car.

  Over the last decade or so, the federal government has been sharpening its focus on innovation. As early as 2006, the National Science Foundation (NSF) began to issue warnings about the risk of cutting back on basic R&D. The 2012 Presidential Task Force on Advanced Manufacturing highlighted the need for the creation of manufacturing institutes (they were eventually implemented by the Obama administration, with the first one for 3D printing opening in Youngstown, Ohio, in 2012 and the second one for digital manufacturing and design in Chicago in 2014). But while Congress dithered and debated over policy, governors and mayors found ways to take action on their own, supporting innovation initiatives in their states and cities, and collaborating across political party lines. Sharing brainpower, after all, is an inclusive and nonpartisan activity.

  Still, we believe that a set of initiatives along the lines of various proposals made by presidential commissions and think tanks for the federal government in the United States and various national agencies (and also for the European Commission) would further spur and support innovation. We suggest, in particular, to:

  • Develop guidelines and articulate best practices for regions and localities that want to create a positive environment for brainsharing ecosystems. The practices developed in Akron, Eindhoven, Portland, and Dresden are useful models.

  • Provide incentives and rewards for groups that take an interdisciplinary, collaborative approach to the creation of technology products and services. The Swiss example of bioscience in Zurich is illustrative. One idea is to encourage that some goods and services be purchased from brainsharing entities.

  • Encourage and facilitate public-private partnerships based on the model of the German Fraunhofer Institutes.

  • Favor open innovation platforms when providing funding. The Open Innovation Pavilion of the US Air Force Research Laboratory is a good example, as is the Horst Institute in Eindhoven.

  • Enable educational institutions to serve as antitrust umbrellas, through tax-code revisions and new guidelines, in a way similar to SUNY Poly’s NanoTech Complex or the Akron Model.

  • Provide financial support, expertise, and incentives for the transformation of rustbelt areas, facilities, and infrastructure into twenty-first-century innovation districts, as North Carolina did when it revitalized the old tobacco factories and established the Research Triangle Park.

  • Remove regulatory barriers that prevent the testing and adoption of innovations such as the self-driving car, as California, Nevada, and Florida have in the United States and Sweden and Germany have done in Europe.

  • Encourage the use of new technologies and products through regulations and incentives. Examples include accepting payment by smartphone for government transactions and incentivizing charging stations for electric vehicles.

  • Recognize brainbelts, the sharing of brainpower, and smart manufacturing with awards and praise. For example, Startbootcamp has initiated a program for young entrepreneurs in five European cities and Israel.

  The Need for New Metrics for Efficiency, Productivity, Creativity, or…?

  We are convinced of the far greater pervasiveness of technology, but the productivity statistics have been dismal the last dozen years. I have not heard these two observations satisfactorily reconciled, but we have to figure it out.

  —LAWRENCE SUMMERS, HAMILTON PROJECT CONFERENCE ON THE FUTURE OF WORK, FEBRUARY 2015

  Former treasury secretary and Harvard economist Lawrence Summers is not alone in recognizing a big hole in the statistics that policy makers rely on to evaluate the economy and its performance. Martin Bailey, a Brookings scholar and former chairman of the Council of Economic Advisers, along with its current chairman, Jason Furman, expressed similar concerns when we asked them about the issue, as did Federal Reserve Board member Lael Brainard. They agree that we do not currently have the tools to effectively gauge how we’re doing in terms of efficiency and productivity, let alone understand the status of our efforts in innovation, creativity, and other important aspects of economic activity. In Europe, researchers have long complained that the models used by organizations—such as the Central Planning Bureau in the Netherlands—are missing something important but have been told, essentially, to mind their own business. The European Commission has made a start on the issue by engaging a group of leading economists to review the current evaluation methods and come up with recommendations for better ones. The work will involve a major study and may take two years or more to complete.1

  Nobody likes to admit to flying blind or even to operating without the right navigational instruments, but, given that so many people acknowledge the problem, it’s hard to understand why there is such a lack of urgency to tackle the issue. It was in 1987 that MIT professor and Nobel laureate Robert Solow famously quipped that “you can see the computer age everywhere except in the productivity statistics.”2 That was well before the advent of the smartphone and apps like Google Search, Wikipedia, and Google Maps, which
are supposed to be huge time-savers and productivity boosters. We have devices that enable us to connect with anyone (or anything) from anywhere; we can access vast stores of knowledge remotely and almost instantly; we can navigate our way from point A to point Z without getting lost or wasting time folding and refolding maps. At the National Institutes of Health and major pharma companies, robots can accomplish complicated trials of new compounds in a few round-the-clock days, tests that a human lab technician would need a decade or more to complete. Not only does the robotic approach save time and money, it opens up possibilities. As NIH director Francis Collins has said: “There are too many potential leads to take them on one at a time.”3

  It is hard to argue that all of these technologies and tools have not helped our productivity in truly revolutionary ways. Yet Solow’s MIT colleague Erik Brynjolfsson and many others have wondered why the productivity statistics don’t support the argument. Is there perhaps a time lag between the introduction of a technology and an improvement in results? Is it possible that the headaches that computers and information technology create are so big they offset the gains? Could it be that there as many winners as there are losers, so there isn’t a net gain? Or are there real gains, but our current methods of measuring them are inadequate, out-of-date, completely useless? Which of these explanations is the worst? What if our metrics are not taking into account the most dynamic and competitive part of developed economies?