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In an increasingly international and interconnected economy, Seattle was global before global was cool.

The region’s competitive global assets include internationally competitive firms, strategically important ports and one of the nation’s largest foreign-born populations.

Still, today’s unique economic moment demands an extra measure of purposeful global engagement.

As cities and metropolitan areas begin to emerge from the Great Recession, leaders are realizing the need to restructure the economy — to move from one based on debt and consumption to one powered by production and innovation.

At the same time, most economic growth over the next decade will occur outside of America’s borders. As of 2009, the combined economies of Brazil, India and China eclipsed that of the United States and now account for more than one-fifth of the global economy. By 2018, their share is expected to surpass one-quarter.

The developing world, with a rapidly rising middle class, represents a huge market opportunity for American firms. China and India alone are expected to increase their urban populations by more than 500 million over the next 20 years, which naturally leads to a rise in their consumer classes. By 2050, Chinese and Indian consumers will account for more than half of all middle-class consumption worldwide, up from just 2 percent in 2000.

These growing metropolises will also require massive investments in infrastructure and face huge challenges as they expand, challenges that U.S. firms have the expertise to solve — in transportation and mobility, in sustainability and clean energy, in information technology and software.

America’s metropolitan areas are uniquely positioned to take advantage of this dual challenge through increased trade and investment. The top 100 metro areas not only produce three-quarters of our gross domestic product, they also concentrate our most innovative firms, our research institutions and universities, and the majority of our skilled workers.

So how does the central Puget Sound region stack up? Recently, I came to Seattle as part of the Global Cities Initiative, a joint project of the Brookings Institution and JPMorgan Chase. This initiative aims to catalyze a shift in economic development priorities and practices that would result in more globally connected metropolitan areas and more sustainable economic growth.

The metro area has a strong platform for trade: firms such as Boeing, Microsoft, and Amazon; world-class research assets including the University of Washington and the Fred Hutchinson Cancer Research Center; and a strong legacy of globally oriented leadership, with a wide coalition, including public, private and civic leaders, actively promoting a regional strategy for global engagement.

The data bear this out: While Seattle is the 15th largest metro area in the United States, it has the sixth highest export total, sending more than $47 billion in goods and services abroad in 2012. These exports are overwhelmingly driven by globally competitive clusters in aerospace and information technology.

Partly due to this industry specialty, Seattle’s economy is also highly innovative and uniquely oriented toward science, technology, engineering and math: More than one-quarter of jobs in the metro are in STEM occupations, the fourth highest share of any metropolitan area in the country.

Still, in such a competitive and dynamic global economy, no metro area can afford complacency. In order to maintain its position in the global economy, Seattle needs to get serious about global engagement.

First, focus on global trade and investment. Continue the collaborative efforts of your public, private and civic leaders to focus economic development strategies on growth abroad. In Seattle earlier this month, regional leaders committed to expanding these efforts, joining the Global Cities Initiative’s Exchange, through which the metro area will develop a strategy to increase foreign direct investment in key industries.

Second, invest in what matters. To compete globally, metro areas must be strong at home. In Seattle, this means shoring up your workforce-development pipeline so that local residents have a path to good jobs in advanced industries. It also calls for a regional approach to financing and delivering transportation solutions that not only reduce congestion at home, but also improve your connections abroad.

Finally, metropolitan leaders must look beyond their own borders, identify their trading partners, and build relationships to increase both trade and investment. For example, as part of the Global Cities Initiative, Chicago and Mexico City entered into a first-of-its-kind economic partnership that builds on the extensive economic, social, cultural linkages between the two metros to make both more prosperous.

There are promising efforts under way in the region, as the King County Aerospace Alliance has started collaborating with Aéro Montréal so that the two aerospace clusters can be more competitive.

Simply put, in today’s economic landscape, every city is a global city. The success of regional economies hinges on their engagement throughout the global economy. Seattle has an enviable hand to play; but success is not inevitable.

This opinion piece originally appeared in the Seattle Times.

Last month, we experienced yet another breakthrough in the epic battle of man against machine. Google’s AlphaGo won against the reigning Go champion Lee Sedol. This success, however, was different than that of IBM’s Deep Blue against Gary Kasparov in 1987. While Deep Blue still applied “brute force” to calculate all possible options ahead, AlphaGo was learning as the game progressed. And through this computing breakthrough that we can learn how to better leverage the data revolution.

In the game of Go, brute-force strategies don’t help because the total number of possible combinations exceeds the number of atoms in the universe. Some games, including some we played since childhood, were immune to computing “firepower” for a long time. For example, Connect Four wasn’t solved until 1995 with the conclusion being the first player can force a win. And checkers wasn’t until 2007, when Jonathan Schaeffer determined that in a perfect game, both sides could force a draw. For chess, a safe strategy has yet to be developed, meaning that we don’t know yet if white could force a win or, like in checkers, black could manage to hold on to a draw.

But most real-life situations are more complicated than chess, precisely because the universe of options is unlimited and solving them requires learning. If computers are to help, beyond their use as glorified calculators, they need to be able to learn. This is the starting point of the artificial intelligence movement.  In a world where perfection is impossible, you need well-informed intuition in order to advance. The first breakthrough in this space occurred when IBM’s Watson beat America’s Jeopardy! champions in 2011. These new intelligent machines operate in probabilities, not in certainty.

That being said, perfection remains important, especially when it comes to matters of life and death such as flying airplanes, constructing houses, or conducting heart surgery, as these areas require as much attention to detail as possible. At the same time, in many realms of life and policymaking we fall into a perfection trap. We often generate obsolete knowledge by attempting to explain things perfectly, when effective problem solving would have been better served by real-time estimates. We strive for exactitude when rough results, more often than not, are good enough.

By contrast, some of today’s breakthroughs are based on approximation. Think of Google Translate and Google’s search engine itself. The results are typically quite bad, but compared to the alternative of not having them at all, or spending hours leafing through an encyclopedia, they are wonderful. Moreover, once these imperfect breakthroughs are available, one can improve them iteratively. Only once the first IBM and Apple PCs were put on the market in the 1980s did the cycle of upgrading start, which still continues today.

In the realm of social and economic data, we have yet to reach this stage of “managed imperfection” and continuous upgrading. We are producing social and economic forecasts with solid 20th century methods. With extreme care we conduct poverty assessments and maps, usually taking at least a year to produce as they involve hundreds of enumerators, lengthy interviews and laborious data entry. Through these methods we are able to perfectly explain past events, but we fail to estimate current trends—even imperfectly.

The paradox of today’s big data era is that most of that data is poor and messy, even though the possibilities for improving it are unlimited. Almost every report from development institutions starts with a disclaimer highlighting “severe data limitations.” This is because only 0.5 percent of all the available data is actually being curated to be made usable. If data is the oil of the 21st century, we need data refineries to convert the raw product into something that can be consumed by the average person.

Thanks to the prevalence of mobile device and rapid advances in satellite technology, it is possible to produce more data faster, better, and cheaper. High-frequency data also makes it possible to make big data personal, which also increases the likelihood that people act on it. Ultimately, the breakthroughs in big data for development will be driven by managerial cultures, as has been the case with other successful ventures. Risk averse cultures pay great attention to perfection. They nurture the fear of mistakes and losing. Modern management accepts failure, encourages trial and error, and reaches progress through interaction and continuous upgrading.

Editor's note: This article is part of a series marking International Women's Day, on March 8, 2016. Read the latest from Global scholars on bridging the gender inequality gap, women’s well-being, and gender-sensitive policies in sub-Saharan Africa. 

This Tuesday, March 8, marks the first International Women’s Day since world leaders agreed last September to launch the Sustainable Development Goals (SDGs) for 2030. A more rounded conception of gender equality marks one of the SDGs’ most important improvements compared to their predecessor Millennium Development Goals (MDGs). Two SDG targets help to illustrate the broadening geopolitical recognition of the challenges. They also help to underscore how much progress is still required.

The inclusion of SDG target 5.3 adds one of the most important new priorities to the global policy agenda: to “eliminate all harmful practices, such as child, early and forced marriage, and female genital mutilation.” Until only a few years ago, the child marriage portion of this target had received only scant international attention. The driving force advancing the issue has been Girls Not Brides, a fast-gelling coalition that now includes more than 550 civil society organizations from over 70 countries. The initiative was first spearheaded by Mabel van Oranje, the dynamic international policy entrepreneur.

At a practical level, ending child marriage faces at least two major challenges. First, it is largescale. Every year, an estimated 15 million girls around the world are married before the age of 18. Second, it is highly complex. There are no simple solutions to addressing cultural practices with deep roots. Impressively, Girls Not Brides has already published a thoughtful theory of change to inform policy conversations, accompanied by a menu of recommended indicators for measuring progress. Regardless of whether this specific theory turns out to be correct, the coalition deserves significant credit for advancing public discussions toward practical action and outcomes. One can only hope that every constituency that lobbied for an SDG target presents similarly considered proposals soon. The advocates for ending child marriage have already registered some early gains. In 2015, four countries raised the age of marriage to 18: Chad, Guatemala, Ireland, and Malawi.

The SDGs are also carrying forward the previous MDG priority of maternal health. Target 3.1 aims as follows: “By 2030, reduce the global maternal mortality ratio to less than 70 per 100,000 live births.” Formally this falls under Goal 3 for health and wellbeing, but it certainly represents a gender equality objective too. Part of that is by definition; mothers are female. Part of it is driven by the need to overcome gender bias; male decision-makers at all levels might overlook key health issues with which they have no direct personal experience.

As of the early 2000s, maternal mortality was too often considered a topic only for specialist discussions. One of the MDG movement’s most important contributions was to elevate the issue to the center stage of global policy. For example, former Canadian Prime Minister Stephen Harper made it a centerpiece among his own foreign policy priorities, including at the G-8 Muskoka summit he hosted in 2010.

Figure 1 shows an initial estimate of the gains across developing countries since 2000, as measured by maternal mortality ratios (MMR). The solid line indicates the actual rate of progress. The dotted lines indicate how things would have looked if previous pre-MDG trends had continued as of 1990-2000 and 1996-2001, respectively. (This is the same basic counterfactual methodology I have previously used for child mortality trends here and here, noting that maternal mortality data remain considerably less precise and subject to ongoing updates in estimation.)

The graph shows that developing countries’ average MMR dropped from approximately 424 deaths per 100,000 live births in 1990, down to 364 in 2000, and further to 233 in 2015. That works out to a 36 percent decline over the past 15 years alone, driven by acceleration in progress during the mid-2000s. Importantly, the value in 2015 was also at least 12 percent lower than it would have been under pre-MDG rates of progress—287 under 1990-2000 trends and 266 under 1996-2001 trends.

Figure 1: Developing country progress on maternal mortality, 1990-2015

Whereas the MDGs focused on developing countries, the SDGs apply universally to all countries. In that spirit, and slightly different from the previous graph, Figure 2 shows an estimate of the current global MMR trajectory for 2030, extrapolating the rates of progress from 2005 to 2015. Drawing from available data for 174 countries with a current population of 200,000 or more, the world’s MMR is on course to drop from approximately 216 in 2015 to 163 in 2030. This would mark a 25 percent improvement, but falls far short of the global MMR target of 70. (These calculations follow a similar methodology to my assessment last year of under-5 mortality trajectories.)

Figure 2: Global maternal mortality - current trajectory to 2030

Although the SDG for maternal mortality is set at a global level (unlike the country-level target 3.2 for child mortality), it is worth assessing how many individual countries are trailing the MMR benchmark of 70. The geographic nature of the global challenge is underscored in Figure 3. It lists the number of countries with MMR above 70 across the respective years 2000, 2015, and—on current trajectory—2030. As of 2000, 90 countries still had MMRs greater than 70. By 2015, this was down to 77 countries. By 2030, on current rates of progress, the relevant figure drops only slightly to 68 countries.

Most notably, the figure for sub-Saharan Africa remains unchanged between 2015 and 2030, at 44 countries, even though most of the region is already experiencing major mortality declines. Rwanda, for example, saw its MMR plummet from 1,020 in 2000 to 290 by 2015. It is on track to reach 106 by 2030. Meanwhile, Sierra Leone saw a decline from 2,650 in 2000 to 1,360 in 2015, on a path toward 768 in 2030. The challenge is not a lack of progress. Instead, it is simply that these countries have huge ground to cover to reach the ambitious goal. On current trajectory, 11 African countries are on course to have MMRs of 500 or greater in 2030.

Figure 3: Scoping progress on SDG 3.1

Number of countries with maternal mortality ratios > 70

Women and girls deserve more

Although these two targets for child marriage and maternal mortality embody only a small portion of the SDGs’ broader gender equality imperatives, they reflect crucial aspects of the overall challenge. On the positive side, they provide inspiration for the ways in which long-overlooked issues can rapidly gain political and policy traction. But they also underscore the scale of the task ahead. The global challenges of gender inequality—ranging from discrimination to violence against women to inequalities of opportunity—all require dramatic accelerations in progress. On this International Women’s Day, we all need to recommit to break from business as usual. Our mothers, sisters, daughters, and partners around the world all deserve nothing less. 

Note: The maternal mortality figures presented above have been updated subsequent to the original post in order to correct for a coding error discovered in the original country-weighting calculations for global trajectories.