The Smartest Places on Earth

by Antoine van Agtmael

  There is also no option, in Europe or the United States, but to move away from traditional forms of manufacturing toward smart manufacturing. As we discussed in the first chapter, these two approaches to making things look very different.

  These characteristics go well beyond issues of technical process and organizational structure: they affect the cultural and social norms. The emphasis on teamwork, creativity, information sharing, and interdisciplinary relationships—all driven by a sharp market focus—will turn traditional hierarchical systems and organizational cultures upside down. But the changes can be made successfully, and universities and hospitals are at the forefront of the shift.

  As we’ve discussed, the emergence of a new model of brainsharing inevitably happens at least in part as the result of large forces, particularly necessity, but leadership is essential to hasten the process and make it more effective. Leaders must learn to manage companies with a higher percentage of professionals on the payroll than ever before. These are people with strong opinions and deep affiliation with their discipline. They respond more to inspiring visions than to the commands of formal authority. The leader must recognize that innovation and collaboration cannot be motivated or evaluated by financial targets alone and must set greater goals by identifying new markets to conquer and new products to create. Efficiency will always be necessary, but effectiveness will be the paramount concern.

  It is relatively easy for leaders to try different organizational forms and embrace new ways of thinking when times are good—when the economy is strong, the industry is expanding, and the company is achieving good results. When pressure mounts, however, leaders tend to fall back onto old habits, asserting their power and playing people off against one another. The challenge for leaders facing tough times will be to use brainsharing to find new ways forward, by bringing together the ideas of diverse individuals and groups, who will explore quirky ideas and offer unorthodox approaches. If leaders reject creativity and multidisciplinary collaboration during difficult times, the result can be destructive. But those who succeed in handling situations that are difficult—and even situations that threaten existence—through sharing of brainpower will further strengthen the organization and make it more capable of facing the next challenge.

  Conclusion

  WE MEET AT THE END

  We have come to the end of our journey. It brought us to unlikely places in the United States and Europe that had transformed from rustbelts to brainbelts. This phenomenon surprised us at first, because the vibrancy in the brainbelts had not shown up yet in the statistics. As we discussed in the last chapter, this reveals a deficiency in our metrics that must be remedied so that policy makers have the instruments they need to make smart decisions.

  At the start of our journey, we two authors had very different perspectives on what was happening in the brainbelts. Fred saw the primacy of a new process of innovation through the intense sharing of brainpower. Antoine was intrigued by the use of new technologies and the creation of smart new products. In the end, our perspectives merged into a common view: the brainbelt phenomenon involved connecting people in a new process (brainsharing) as well as connecting the digital world of IT, data analytics, and wireless communications with new and old ways of “making things” to create new technologies and products (smart production). The hundreds of people we met and talked with crystallized and inspired our thinking. They helped us shape our conclusions that economies that were not long ago dismissed as being outdated are in fact entering a revolutionary new phase and that the global competitive advantage is shifting from cheap to smart.

  For the United States and Europe, this means that many activities that had been outsourced will return to home shores. This is good news. After decades of the cheap-labor advantage, the new competitive edge will derive from a very different kind of economic and industrial trump card. The rising demand for smart products of all kinds will require the sharing of brainpower in development and smart-manufacturing methods in the making. Manufacturing will not so much “return,” then, as be reinvented. The new manufacturing will be highly automated, and products will be created to custom specifications, in small batches, and as physically close to the customer as possible. As demand increases for smart products and the new ways of working and manufacturing are adopted, more and more brainbelt areas will emerge. Beyond those discussed in our book, we’re already seeing where they are developing, as we mentioned in the Introduction.

  The rise of the brainbelts and the spread of automation are sure to have a disruptive effect on the current areas of low-cost manufacturing, particularly China, and it will also have an impact on who will have the best opportunities for employment in the United States and Europe. And that leads us to the burning question people asked us over and over as we were working on this book: what will happen to jobs?

  This is an age-old concern. Ever since the Industrial Revolution, fears—sometimes bordering on panic—have caused people to worry about the future for jobs. Over the past few decades, we watched as millions of manufacturing jobs disappeared and we heard about China becoming the manufacturing center of the world. Then, the deep economic crisis of 2008, and robots, added further fuel to the fiery debate. How would people make a living? What jobs would be available in the future? Now we may ask whether the benefits of brainsharing and the smart, new economy will spread beyond the top 1 percent to the middle class or whether income and wealth inequalities will become more exaggerated.

  The further hollowing out of the middle class, which is a particular problem in the United States, although it is also happening elsewhere, could not only exacerbate existing social tensions but also slow the growth of consumer demand and undermine efforts to improve the standard of living for all. Although the threat to the well-being of the middle class is partly attributable to the economic crisis of 2008 and, before that, the decline of the power of trade unions, it remains a question whether rustbelts can be revitalized quickly enough—and in enough places—to reverse a decline that has separated winners from losers, based mostly on education and location.

  In general, we believe that the concern about the loss of jobs, for the middle class and for the society as a whole, is ill-informed and misguided. It’s ill-informed because we are much better at counting the number of lost jobs than the newly created ones. And it’s misguided, because it misses the main point. The real concern is not that there will be no jobs, but that there will be a lack of trained workers to fill them. (The worry is also futile, because so many of the “lost” jobs were antiquated and would not have lasted, even without the job exodus to China.) The real concerns should be about slow wage growth and wage inequality and, in the longer run, job training and education inequality.

  Not only is the concern about jobs not new, neither is the profound rejuggling of jobs that we are now facing—so usual is it that we could call it “the old normal.” Over the centuries, each successive wave of innovation (from the steam engine to the Internet) has led to job losses and made certain skills obsolete, even while each wave has also led to a higher standard of living. Joseph Schumpeter called this “creative destruction.” We have seen this time and time again. At the time of the American Revolutionary War, farmers made up 90 percent of the labor force. By 1900, that number had shrunk to 38 percent, and by 2000, it was down to 2 percent,1 even though far more food is now produced. Over 200,000 elevator operators in Manhattan alone were put out of work by automatic elevators. Typists, telegraph and switchboard operators, milkmen, and bank tellers—the examples of jobs that have been replaced and absorbed in the economy are too numerous to mention. Painful, concentrated job losses from factory closings, financial crisis, and outsourcing understandably make the news, but the more diffuse creation of all kinds of new jobs often goes unnoticed. Economic history is full of examples of how adjustment and resilience are underestimated, and those characteristics are evident again today: they are the catalysts that bring rustbelts back and turn them into brainbelts.r />
  It’s easier and more politically advantageous to blame job losses on China, however, than to accept that factories (like farms before them) have become much more efficient and that the jobs they depended on are no longer necessary or relevant. For example, the 94,000 people working in the steel industry in 2012 produced 14 percent more steel than nearly 400,000 workers did in 1980,2 and a typical GM employee now makes twenty-eight cars per year, four times the seven cars of Detroit’s glory years in the 1950s. Painful adjustment, yes. The end of the car and steel industries, no. Moreover, prosperity is a direct result of constantly improving productivity.

  In their book Race Against the Machine, Erik Brynjolfsson and Andrew McAfee point to a “polarization of labor demand”—meaning that there has been an increase in demand for high-skilled jobs and for low-skilled jobs, and less demand for everything in between—and this has kept payrolls flat for decades and put downward pressure on labor’s share of the economy. From our discussions in the United States and Europe, together with studying reams of labor statistics, we agree that “the good news is that this has radically increased the economy’s productive capacity.” The bad news is that it “does not automatically benefit everyone in a society.”3

  There are plenty of winners, therefore, but not everyone falls into the winning category. That has been as true in the past as it will be in the future. Education has been the key difference. For example, those with a high school education or less (which describes people who held more than half of the manufacturing jobs in 2000) have been the main victims. During the 2000–2012 period, people with a community college degree, occupational degree, or graduate degree gained a higher percentage of manufacturing jobs, and that trend is expected to continue and even accelerate.4

  We believe that the predictions of millions of further job losses in manufacturing are wildly exaggerated, at least in the United States and Northern Europe, and they are based on looking in the rearview mirror. These losses have been taking place since the 1980s and are largely behind us.5 There are, in fact, only 740,000 production-line workers (once the heart of manufacturing) left in the United States, a miniscule 6 percent of the total jobs in manufacturing.6 The future impact of automation in the old economies will instead be felt mostly in service jobs.7 And not all of those jobs will be low-skill. Data analytics will create many new jobs, but the need for sophisticated pattern recognition will affect many existing ones as well, including those of radiologists, translators, interpreters, spies, and analysts.

  Another big difference between the last few decades and the next few will be the shift in demographics. We are still captive to an outdated understanding of demographics that originates in the postwar baby boom. The sudden six-year rise in unemployment induced by the 2008 economic crisis made us lose sight of the fact that more experienced workers in the current generation of baby boomers in the United States began to retire in 2011. Three million more people retired in 2013 than did in 2007. An aging population tends to push the so-called labor-force participation rate down further, whether economic times are good or bad.8

  Now let’s turn to the other side to the story: the many new jobs—both high-skilled and low-skilled—that have been created as a result of innovation. Where are these new jobs? They are to be found not only in advanced manufacturing, the Internet, software, R&D, and bioscience—where they will keep growing—but in the additional jobs these industries create in support and partner industries and businesses. Today, as many as one-tenth of all jobs in the United States belong to the “innovation sector,” as many as there are in manufacturing. Not only is the innovation sector itself labor-intensive but, as Berkeley economist Enrico Moretti shows in his book The New Geography of Jobs, for each new urban high-tech job, there is a huge multiplier of five additional jobs that are created outside the high-tech sector. Three of these jobs are for professionals such as doctors, lawyers, and yoga instructors, and two of them are for lower-wage nonprofessionals such as waiters and store clerks.9

  We cannot fight the tide of history as industry and society change. Instead, we should recognize that innovation is what makes us competitive. It is an important motivator in the market economy, a much more important and sustainable one than greed. Remember that Lenin said that capitalists, motivated by the lust for profit, would sell rope to others who would turn around and use it to hang the capitalists.10

  As we come to recognize the innovation imperative, the concept of innovation will evolve. Although Schumpeter talked about creative destruction and we have become enamored of the idea of revolutionary, game-changing, out-of-the-box, breakthrough innovations, the fact is that much innovation is gradual and incremental. Gradually, then, we will come to think of innovation as a continuous and integrated process of renewal, product updates, and technology evolution—an oxygen that breathes new life and vibrancy into society, organizations, and regions. The process will, however, be harder to see than our current model, which places such value on disruptive and highly visible acts of creative destruction, and therefore it will be harder for some to cope with. Once again, the remedy will be found in education and training, with plenty of attention paid to the cultural and social aspects of an increased focus on innovation.

  As organizations and smart manufacturing concentrate in brainbelts and innovation hubs, individuals will need to focus on improving their adaptability. To add value in the new competitive environment, people will have to master a broad set of skills, many of them social. It will be the individual’s responsibility to be aware of changing requirements and adapt before their responsibilities and skills are no longer relevant. It will be the employer’s responsibility to help their employees acquire the needed skills to make the adaptation. In this way, employees will come to think of their work as a lifelong personal education program rather than just a job.

  The skills of the connector, in particular, will become increasingly valuable to companies, and especially to regional initiatives. They will be responsible for the social innovation needed to make the brainsharing approach and the smart-manufacturing methods function well. Working in multidisciplinary relationships redefines competition as between groups rather than between individuals. But groups must also learn from other groups, even as they compete with one another. That will require that connectors help people work to achieve their group’s goals while maintaining an attitude of openness and generosity. This is a rare combination of skills and qualities, and there is no doubt that companies will engage in a war for connectors, just as they have engaged in a war for technical talent.

  The changing face of the job market will have a huge impact on vocational training, which, as we discovered on our journey, had almost disappeared, especially in the United States. Although there are many local and regional programs to rebuild the vocational training system, a much wider initiative must be undertaken to promote technical education to help young people see that making things can be fun and challenging. Germany provides the best model for the world to follow. Germans have long been known as experts in machine building, and they feel a national pride in making reliable products. Vocational training is a fundamental part of their culture. Although their system is difficult to replicate, other countries can learn from it and adapt it to their own needs.

  Europeans, in turn, can learn from the United States, particularly in the way the US financial network supports start-ups and spin-offs and builds on the entrepreneurial spirit. Although venture capital is concentrated in Silicon Valley, Boston-Cambridge, and New York, the US capital market is integrated in such a way that its resources can easily be accessed by regions that need funding. In Europe, the capital markets are more fragmented than in the United States, which means that resources cannot be optimally directed to the regions that need them most, because of various allocation restrictions.

  What struck us both during our visits to the brainbelts was the pragmatism, ambition, and the collaborativeness of local and regional politicians, entrepreneurs, and scientists.
Collaboration was not a political or business buzzword, but rather a real activity often born, as we have seen, of necessity. Through collaboration, a new mix of market forces and local politics was created. Regional politicians became facilitators and connectors. Their pragmatic approach resulted in the creation of better policies and a longer-term perspective.

  Although brainbelt areas will take on many of the challenges that lie ahead, there are some investments and initiatives that must be undertaken by larger authorities, and often on a national level. Everywhere we went, for example, we saw the need for improved infrastructure, especially a nationwide energy grid that can handle the increasing decentralization of electricity production and a Wi-Fi broadband network that can handle the data explosion that the Internet of Things is already causing.

  National policy makers must also push forward initiatives that promote the interdisciplinary collaboration that scientists everywhere told us is a must to address the most complex challenges in chips, new materials, and life sciences. The Obama administration took a small step in this direction, with its $50 million investment in the National Additive Manufacturing Innovation Institute (NAMII). The small budget should not be seen as a limitation but rather as an incentive to bring different companies and universities together in joint research programs. In Europe, similar initiatives are centered in the applied research institutes, which smooth collaboration between companies and universities and between disciplines. Joe Gray, of OHSU in Portland, predicted that, within a decade, “the Nobel Prize will be given to a team instead of to an individual.”

  The enthusiasm for interdisciplinary collaboration and the sharing of brainpower that we witnessed on our travels was countered by the skepticism of others who fear that scientific freedom will be restricted and that basic research will be endangered. We took these concerns seriously. There will always be a need for basic research that is not required to lead directly or immediately to commercial products. Basic research is still the only path to the discovery and pursuit of new knowledge whose commercial potential is not certain but which may bring tremendous benefits to society in other ways. The Hubble telescope, for example, has generated vast quantities of information and insight about our universe over the years it has been operating in outer space, but it has not directly spawned new industries or revenue streams.