Data, Technologies & Context: How the practice of government is changing
Government continues to be the residual claimant of intractable public problems like air quality, public health or sustainable development. However, the context of public policy and management is changing with the advent of more and different kinds of data and the technologies and tools that can be brought to bear on them. For example, in Chicago Is Your Big (Friendly) Brother, Susan Crawford, former Special Assistant for Science, Technology, and Innovation Policy in the Obama Administration describes the City of Chicago’s Array of Things project. Building on advances in nanotechnologies and sensors to gather data about the city, the Array of Things project will place up to 400 sensors within the city in an experiment to detect light, sound, air quality, and other ‘things’ that affect quality of life. This data will then be made available, in open formats, for a variety of users free of charge.7 The hope is that having data about the things we cannot always see, or that government does not currently collect, will spur entrepreneurs to develop innovative mobile applications that can help citizens walking down a street learn there is ice ahead or that one neighborhood has higher levels of pollen than another so asthma sufferers can avoid situations that could have adverse and costly health effects. Crawford concludes that, “Investing time and money in data makes sense, and it is changing how local government works.”8 In Philadelphia, Mayor Michael Nutter just announced the creation of an Open Innovation Lab for City Employees.9 Director of the lab, and Chief Innovation Officer, Adel Ebeid, described how the lab will run in 90-day increments, prompting employees to consider a range of topics, from geo-spatial analysis, to public health, poverty and economic development. The goal is to get public employees working together and learning new skills to solve complex problems.
Non-profit agencies working on behalf of communities around the world are also using new tools and methods and engaging with government practitioners. Moving from a local to national and international scale, the Millennium Institute (MI), a global non-profit founded in 1983 focuses attention on global sustainability issues. MI makes accessible system dynamics modeling tools and other analytic techniques to help national leaders, especially in developing countries, use systems thinking and tools to analyze and understand the interconnectedness among economic, social, and environmental factors, and issues of environmental sustainability, peace and security.10 The Millennium Institute has created Threshold 21 (T21)11, a dynamic simulation tool designed to support comprehensive, integrated, long-term national development planning. Using various models and computational tools, T21 supports comparative analysis of different policy options, and helps users to identify the sets of policies that tend to lead toward desired development goals. MI has created more than 15 unique, customized T21 models in countries such as Malawi, Mozambique, Bangladesh, United States, and Italy. In Jamaica, for example, MI worked with the government to create a custom T21 model focused on economic growth and industrialization. The tool helped leaders envision more holistic approaches to sustainable growth.
At the global level, polio eradication has been a major public health goal for decades. In 1988, when 350,000 children per year were being paralyzed by the polio virus, the World Health Assembly committed to eradicating polio by the year 2000.12 13 Today, the US Center for Disease Control (CDC) alone spends more than $100 million annually along with significant public employee resources to achieve polio eradication. CDC maintains high standards for developing evidence-based policies and cost-effective use of its resources. Consequently, in 2001, CDC collaborated with the non-profit Kid Risk Project to use a range of computational and modeling techniques to develop integrated analytical models to evaluate the global risks, benefits, and costs of policy choices for polio eradication. For more than a decade, leaders at the World Health Organization (WHO) and CDC have benefited from the intelligence and evidence generated by the Kid Risk Project. To date, the annual burden of the disease has been reduced by more than 99%, to less than 2000 cases of paralysis annually. But critical questions remain: “Is total polio eradication worth the continuing investment? What would happen if we stopped investing in eradication? How can we best prevent/control outbreaks in polio-free countries?” “What, if any, vaccine should we use after global polio eradication?”14Dr. Bruce Aylward assistant director-general of Polio, Emergencies and Country Collaboration at WHO said, “This work has been fundamental to so much of what’s happened in the polio eradication program over the last few years, and it has helped to support many of our decisions over the last decade to bring the world much, much closer to one where future generations will never know the terror of this disease.”15
These types of initiatives, from New York City’s municipal fire prevention to national strategies for sustainable growth and development, to global health challenges can be supported, evaluated, and improved by government data collection, and by public, private, and civic analysis and data use everywhere in the world. Unfortunately, popular excitement about the prospects for newly available data and tools often overshadows an appreciation for their limitations, gaps, and risks.
On the technological front, computational and simulation tools are becoming simultaneously more sophisticated, easier to use, and increasingly available. However, big questions remain about suitability, cost, and usability of the tools and the capability and skills to choose and use them effectively. Data visualization techniques, for example, can expand our ability to display and disseminate complex temporal and spatial information and communicate evidence, but they can also contain biases that distort important aspects of data trends, impacts, evidence and meaning. Models rest on key assumptions that are not always made explicit or tested against current or historical evidence.
On the data front, innovations in information collection, analysis, synthesis, and dissemination are changing the type, amount, and quality of policy-relevant information. But, are these data fit for the many types of uses for which we need them? Data quality is a many-faceted concern that involves understanding and evaluating factors such as accuracy, granularity, timeliness, and comprehensiveness against a given use. For example, data on whole populations of interest (e.g., all Medicaid claims), or data collected from social media sites (e.g., mentions of illness or disease outbreaks on Twitter) or from monitoring devices such as scanners and sensors, are becoming more readily available but they confuse traditional distinctions between data samples and populations. Administrative data reflects the policy and organizational context for its creation, and although it can be quite valuable for different kinds of analysis, it may not be described or managed in ways that make it valid for additional uses. Perhaps most important, new information policies are needed for governing in a data-rich, interconnected world.
12Modlin, John F. "The bumpy road to polio eradication." New England Journal of Medicine 362, no. 25 (2010): 2346-2349.
13Aylward, Bruce, and Rudolf Tangermann. "The global polio eradication initiative: lessons learned and prospects for success." Vaccine 29 (2011): D80-D85.
14Story was presented by Dr. Duintjer Tebbens at the May 9, 2014 workshop and further elaborated using published documentation.
© 2003 Center for Technology in Government