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2017 Chicago Forum Workshop
Innovation and Data: Building the Best Global Cities
As we look toward the future, some of the world's preeminent experts on innovation and data--including corporate executives, data analysts, investors, lawyers, mayors, and economists--are asking what global cities must do to refine their approaches to improving data quality and usage. Five priorities emerged through their conversation at the 2017 Chicago Forum on Global Cities that warrant further exploration at all levels:
Cities around the world face unprecedented requests for data to remain competitive. Residents, companies, and policymakers are demanding complex services in cities, which in turn requires increasingly complex governance. These developments are only possible by effectively collecting, analyzing, protecting, and applying quality data.
In much of the world, however, data is missing or of questionable quality. Among the more than 3,000 cities in the world with more than 100,000 residents, only 150 to 200 cities, mostly in developed countries, have even a functional baseline when it comes to collecting and using data. Basic facts such as how many streetlights a city has, how much energy or water is lost or wasted through utilities, or who owns vacant or under-utilized lots, buildings, and private infrastructure is unknown. In the few global cities that have baseline data, the data quality is often inconsistent. Because cities use different data variables, definitions, and collection processes, effective inter-city collaboration and benchmarking is difficult.
To examine what data can and can’t do for global cities, a group of leaders—including corporate executives, data analysts, investors, lawyers, mayors, and economists—came together in a private workshop at the 2017 Chicago Forum on Global Cities. The following is the problem statement around which the workshop was framed and a summary of discussion highlights, which include challenges that remain top of mind for the world’s leading experts on technology and innovation.
Problem statement
Throughout history, the prosperity of global cities has rested on technology and innovation. In the face of exponential change, every facet of life in a global city will feel the impact of new technologies and data usage, creating the opportunity to reshape social economic structures and the liveability of cities.
Planned change, rather than disruption, should mean we avoid being hit by the (self-driving) bus. Global cities are looking to maximize the benefits of innovation while avoiding unintended consequences. For this, cities might seek to retool their regulatory frameworks to have a more nimble and adaptable response to innovation and the rising availability of big data opportunities. What can and can’t data do for global cities?
Discussion highlights
It is crucial that cities take ownership over data collection and use, while being open to sharing effective systems and models with other global cities. Standardization of data provides a constant challenge but should not be a barrier to innovation. So, what does it mean to address complex data structuring and standardization issues in practice?
Standardize data platforms within a city. Data standardization within city agencies has huge benefits. Cities can make more informed decisions with reliable and comprehensive data. Cities can also benchmark progress and evaluate the impact of new investments or interventions. Cities that do not standardize data platforms risk increased inefficiency, redundancy, and costs down the road.
One method of standardization is to create a centralized data platform for all city agencies and the suite of metrics it collects. For example, creating a central payment portal for all agencies not only frees up manpower devoted to payment processing at each agency but also creates a standardized, centralized data repository for city finances.
For further discussion:
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How can city officials agree on a standard data collection method and platform?
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Who will be responsible for maintaining the integrity of the data? How will policy making decisions using data be made and approved?
Recognize when data does not need to be standardized, nor systems overhauled. A “building inspection” variable in Chicago, for example, means something very different than a building inspection in an earthquake-prone city. It is important to recognize that not all data needs to be standardized to be useful globally. Rather, it is important to have a common language, or framework, to discuss data and let the distinctions be defined by each city.
Moreover, data-driven solutions require a commitment to constant improvement—they are not a one-time fix. To create perfectly standardized data platforms across cities through one big push is impractical. Cities have real-time, immediate demands from citizens, and they usually do not have the bandwidth to experiment with solutions or the budget to overhaul their data systems. Cities leaders need to see data innovation and everyday problem solving as two sides of the same coin, integrating and improving data collection as they seek to solve their city problems.
For further discussion:
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What margins of standardization flexibility for data collection can city governments live with?
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How can coalitions of cities agree on instances when data does or does not need to be standardized? Where are examples where standardization is not a necessity?
Use pressing challenges as opportunities to improve data systems. City resources are often too limited to conduct data research simply for the sake of research. By using data innovations to address pressing problems, cities can make breakthroughs and demonstrate real-time benefits. In 2012, for example, Chicago overhauled the city’s security and surveillance systems as it prepared to host the 2012 NATO summit. Rather than create temporary security measures, it used the opportunity to modernize and implement new security data systems for the city—just as many cities use hosting an event like the Olympics as an excuse to overhaul infrastructure.
Natural forces such as blizzards, floods, and heat waves also present opportunities, and very real challenges, for cities to learn and improve systems and to further integrate data with city operations. By reframing urban challenges as data opportunities, and using sound frameworks, cities are increasingly able to provide the complex services and quality of life that their residents demand.
For further discussion:
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What are some upcoming events in your city that could serve as a framework for data innovations? How might they be applied to future scenarios?
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What would be required to get city leaders on board for testing and implementing the outcomes of data research?
Share effective models among cities. Model sharing among or between cities need not wait until data sets are written in stone. Cities can follow guidelines, rather than hard measurements and inflexible algorithms. For example, if New York creates a successful data-driven program that helps reduce energy usage, other cities should be able to attempt similar programs of their own, even if they lack the exact data inputs used by New York. This approach provides maximum flexibility and moves cities toward greater data and framework harmony, if not metrics standardization.
For further discussion:
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How will cities effectively share and implement these models with one another? What type of process, forum, or discussion should take place?
Ensure data transparency. No matter the scale of city data collection, it should be available to third-party researchers and algorithm developers. Transparency allows for higher-volume data testing and produces more recommendations to improve data than can be produced in-house by resource-strained city management. While cities should share data and promote transparency, they nevertheless should always own their data.
For further discussion:
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What regulatory parameters do cities need to ensure their data is not shared too widely or with the wrong parties?
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How would data be collected and delivered to thirty-party researchers and other relevant parties?
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States and national governments look to cities for data innovations—they are where pressure to adapt is greatest and where innovation happens quickest. Innovation for infrastructure and technology relies on cities’ commitment to quality data and sharing insights across global boundaries. Collecting pure data is difficult. But global leaders who strive to develop data systems that correspond to their cities’ needs and comply with solid governance are on their way to uncovering opportunities to reimagine cities’ capabilities and improve residents’ standard of living.
What is your city doing to adapt to innovation and data opportunities? Join the conversation @ChicagoForum.
The 2017 Chicago Forum on Global Cities was made possible by the following forward-thinking companies: AbbVie, UL, Grant Thornton, Hyatt Hotels Foundation, Motorola Solutions, United Airlines, and USG Corporation.
Save the date, June 6-8, for the 2018 Chicago Forum on Global Cities. Learn more at chicagoforum.org.