Towards Timely Public Health Decisions to Tackle Seasonal Diseases With Open Government Data

Curated on Posted on by Stefaan Verhulst
Paper by Vandana Srivastava and Biplav Srivastava for the Workshops at the Twenty-Eighth AAAI Conference on Artificial Intelligence : “Improving public health is a major responsibility of any government, and is of major interest to citizens and scientific communities around the world. Here, one sees two extremes. On one hand, tremendous progress has been made in recent years in the understanding of causes, spread and remedies of common and regularly occurring diseases like Dengue, Malaria and Japanese Encephalistis (JE). On the other hand, public agencies treat these diseases in an ad hoc manner without learning from the experiences of previous years. Specifically, they would get alerted once reported cases have already arisen substantially in the known disease season, reactively initiate a few actions and then document the disease impact (cases, deaths) for that period, only to forget this learning in the next season. However, they miss the opportunity to reduce preventable deaths and sickness, and their corresponding economic impact, which scientific progress could have enabled. The gap is universal but very prominent in developing countries like India.
In this paper, we show that if public agencies provide historical disease impact information openly, it can be analyzed with statistical and machine learning techniques, correlated with best emerging practices in disease control, and simulated in a setting to optimize social benefits to provide timely guidance for new disease seasons and regions. We illustrate using open data for mosquito-borne communicable diseases; published results in public health on efficacy of Dengue control methods and apply it on a simulated typical city for maximal benefits with available resources. The exercise helps us further suggest strategies for new regions that may be anywhere in the world, how data could be better recorded by city agencies and what prevention methods should medical community focus on for wider impact.
Full Text: PDF“

Sharing Data Is a Form of Corporate Philanthropy

Curated on Posted on by Stefaan Verhulst

Matt Stempeck in HBR Blog:  “Ever since the International Charter on Space and Major Disasters was signed in 1999, satellite companies like DMC International Imaging have had a clear protocol with which to provide valuable imagery to public actors in times of crisis. In a single week this February, DMCii tasked its fleet of satellites on flooding in the United Kingdom, fires in India, floods in Zimbabwe, and snow in South Korea. Official crisis response departments and relevant UN departments can request on-demand access to the visuals captured by these “eyes in the sky” to better assess damage and coordinate relief efforts.

DMCii is a private company, yet it provides enormous value to the public and social sectors simply by periodically sharing its data.
Back on Earth, companies create, collect, and mine data in their day-to-day business. This data has quickly emerged as one of this century’s most vital assets. Public sector and social good organizations may not have access to the same amount, quality, or frequency of data. This imbalance has inspired a new category of corporate giving foreshadowed by the 1999 Space Charter: data philanthropy.
The satellite imagery example is an area of obvious societal value, but data philanthropy holds even stronger potential closer to home, where a wide range of private companies could give back in meaningful ways by contributing data to public actors. Consider two promising contexts for data philanthropy: responsive cities and academic research.
The centralized institutions of the 20th century allowed for the most sophisticated economic and urban planning to date. But in recent decades, the information revolution has helped the private sector speed ahead in data aggregation, analysis, and applications. It’s well known that there’s enormous value in real-time usage of data in the private sector, but there are similarly huge gains to be won in the application of real-time data to mitigate common challenges.
What if sharing economy companies shared their real-time housing, transit, and economic data with city governments or public interest groups? For example, Uber maintains a “God’s Eye view” of every driver on the road in a city:
stempeck2
Imagine combining this single data feed with an entire portfolio of real-time information. An early leader in this space is the City of Chicago’s urban data dashboard, WindyGrid. The dashboard aggregates an ever-growing variety of public datasets to allow for more intelligent urban management.
stempeck3
Over time, we could design responsive cities that react to this data. A responsive city is one where services, infrastructure, and even policies can flexibly respond to the rhythms of its denizens in real-time. Private sector data contributions could greatly accelerate these nascent efforts.
Data philanthropy could similarly benefit academia. Access to data remains an unfortunate barrier to entry for many researchers. The result is that only researchers with access to certain data, such as full-volume social media streams, can analyze and produce knowledge from this compelling information. Twitter, for example, sells access to a range of real-time APIs to marketing platforms, but the price point often exceeds researchers’ budgets. To accelerate the pursuit of knowledge, Twitter has piloted a program called Data Grants offering access to segments of their real-time global trove to select groups of researchers. With this program, academics and other researchers can apply to receive access to relevant bulk data downloads, such as an period of time before and after an election, or a certain geographic area.
Humanitarian response, urban planning, and academia are just three sectors within which private data can be donated to improve the public condition. There are many more possible applications possible, but few examples to date. For companies looking to expand their corporate social responsibility initiatives, sharing data should be part of the conversation…
Companies considering data philanthropy can take the following steps:

  • Inventory the information your company produces, collects, and analyzes. Consider which data would be easy to share and which data will require long-term effort.
  • Think who could benefit from this information. Who in your community doesn’t have access to this information?
  • Who could be harmed by the release of this data? If the datasets are about people, have they consented to its release? (i.e. don’t pull a Facebook emotional manipulation experiment).
  • Begin conversations with relevant public agencies and nonprofit partners to get a sense of the sort of information they might find valuable and their capacity to work with the formats you might eventually make available.
  • If you expect an onslaught of interest, an application process can help qualify partnership opportunities to maximize positive impact relative to time invested in the program.
  • Consider how you’ll handle distribution of the data to partners. Even if you don’t have the resources to set up an API, regular releases of bulk data could still provide enormous value to organizations used to relying on less-frequently updated government indices.
  • Consider your needs regarding privacy and anonymization. Strip the data of anything remotely resembling personally identifiable information (here are some guidelines).
  • If you’re making data available to researchers, plan to allow researchers to publish their results without obstruction. You might also require them to share the findings with the world under Open Access terms….”

How Three Startups Are Using Data to Renew Public Trust In Government

Curated on Posted on by Stefaan Verhulst

Mark Hall: “Chances are that when you think about the word government, it is with a negative connotation.Your less-than-stellar opinion of government may be caused by everything from Washington’s dirty politics to the long lines at your local DMV.Regardless of the reason, local, state and national politics have frequently garnered a bad reputation. People feel like governments aren’t working for them.We have limited information, visibility and insight into what’s going on and why. Yes, the data is public information but it’s difficult to access and sift through.
Good news. Things are changing fast.
Innovative startups are emerging and they are changing the way we access government information at all levels.
Here are three tech startups that are taking a unique approach to opening up government data:
1. OpenGov is a Mountain View-based software company that enables government officials and local residents to easily parse through the city’s financial data.
Founded by a team with extensive technology and finance experience, this startup has already racked up some of the largest cities to join the movement, including the City of Los Angeles.OpenGov’s approach pairs data with good design in a manner that makes it easy to use.Historically, information like expenditures of public funds existed in a silo within the mayor’s office or city manager, diminishing  the accountability of public employees.Imagine you are a citizen who is interested in seeing how much your city spent on a particular matter?
Now you can find out within just a few clicks.
This data is always of great importance but could also become increasingly critical during events like local elections.This level of openness and accessibility to data will be game-changing.
2. FiscalNote is a one-year old startup that uses analytical signals and intelligent government data to map legislation and predict an outcome.
Headquartered in Washington D.C., the company has developed a search layer and unique algorithm that makes tracking legislative data extremely easy. If you are an organization that has vested interests in specific legislative bills, tools by FiscalNote can give you insights into its progress and likelihood of being passed or held up. Want to know if your local representative favors a bill that could hurt your industry? Find out early and take the steps necessary to minimize the impact. Large corporations and special interest groups have traditionally held lobbying power with elected officials. This technology is important because small businesses, nonprofits and organizations now have an additional tool to see a changing legislative landscape in ways that were previously unimaginable.
3. Civic Industries is a San Francisco startup that allows citizens and local government officials to easily access data that previously required you to drive down to city hall. Building permits, code enforcements, upcoming government projects and construction data is now openly available within a few clicks.
Civic Insight maps various projects in your community and enables you to see all the projects with the corresponding start and completion dates, along with department contacts.
Accountability of public planning is no longer concealed to the city workers in the back-office. Responsibility is made clear. The startup also pushes underutilized city resources like empty storefronts and abandoned buildings to the forefront in an effort to drive action, either by residents or government officials.
So What’s Next?
While these three startups using data to push government transparency in the right direction, more work is needed…”

Chief Executive of Nesta on the Future of Government Innovation

Curated on Posted on by Stefaan Verhulst

Interview between Rahim Kanani and Geoff Mulgan, CEO of NESTA and member of the MacArthur Research Network on Opening Governance: “Our aspiration is to become a global center of expertise on all kinds of innovation, from how to back creative business start-ups and how to shape innovations tools such as challenge prizes, to helping governments act as catalysts for new solutions,” explained Geoff Mulgan, chief executive of Nesta, the UK’s innovation foundation. In an interview with Mulgan, we discussed their new report, published in partnership with Bloomberg Philanthropies, which highlights 20 of the world’s top innovation teams in government. Mulgan and I also discussed the founding and evolution of Nesta over the past few years, and leadership lessons from his time inside and outside government.
Rahim Kanani: When we talk about ‘innovations in government’, isn’t that an oxymoron?
Geoff Mulgan: Governments have always innovated. The Internet and World Wide Web both originated in public organizations, and governments are constantly developing new ideas, from public health systems to carbon trading schemes, online tax filing to high speed rail networks.  But they’re much less systematic at innovation than the best in business and science.  There are very few job roles, especially at senior levels, few budgets, and few teams or units.  So although there are plenty of creative individuals in the public sector, they succeed despite, not because of the systems around them. Risk-taking is punished not rewarded.   Over the last century, by contrast, the best businesses have learned how to run R&D departments, product development teams, open innovation processes and reasonably sophisticated ways of tracking investments and returns.
Kanani: This new report, published in partnership with Bloomberg Philanthropies, highlights 20 of the world’s most effective innovation teams in government working to address a range of issues, from reducing murder rates to promoting economic growth. Before I get to the results, how did this project come about, and why is it so important?
Mulgan: If you fail to generate new ideas, test them and scale the ones that work, it’s inevitable that productivity will stagnate and governments will fail to keep up with public expectations, particularly when waves of new technology—from smart phones and the cloud to big data—are opening up dramatic new possibilities.  Mayor Bloomberg has been a leading advocate for innovation in the public sector, and in New York he showed the virtues of energetic experiment, combined with rigorous measurement of results.  In the UK, organizations like Nesta have approached innovation in a very similar way, so it seemed timely to collaborate on a study of the state of the field, particularly since we were regularly being approached by governments wanting to set up new teams and asking for guidance.
Kanani: Where are some of the most effective innovation teams working on these issues, and how did you find them?
Mulgan: In our own work at Nesta, we’ve regularly sought out the best innovation teams that we could learn from and this study made it possible to do that more systematically, focusing in particular on the teams within national and city governments.  They vary greatly, but all the best ones are achieving impact with relatively slim resources.  Some are based in central governments, like Mindlab in Denmark, which has pioneered the use of design methods to reshape government services, from small business licensing to welfare.  SITRA in Finland has been going for decades as a public technology agency, and more recently has switched its attention to innovation in public services. For example, providing mobile tools to help patients manage their own healthcare.   In the city of Seoul, the Mayor set up an innovation team to accelerate the adoption of ‘sharing’ tools, so that people could share things like cars, freeing money for other things.  In south Australia the government set up an innovation agency that has been pioneering radical ways of helping troubled families, mobilizing families to help other families.
Kanani: What surprised you the most about the outcomes of this research?
Mulgan: Perhaps the biggest surprise has been the speed with which this idea is spreading.  Since we started the research, we’ve come across new teams being created in dozens of countries, from Canada and New Zealand to Cambodia and Chile.  China has set up a mobile technology lab for city governments.  Mexico City and many others have set up labs focused on creative uses of open data.  A batch of cities across the US supported by Bloomberg Philanthropy—from Memphis and New Orleans to Boston and Philadelphia—are now showing impressive results and persuading others to copy them.
 

What ‘urban physics’ could tell us about how cities work

Curated on Posted on by Stefaan Verhulst

Ruth Graham at Boston Globe: “What does a city look like? If you’re walking down the street, perhaps it looks like people and storefronts. Viewed from higher up, patterns begin to emerge: A three-dimensional grid of buildings divided by alleys, streets, and sidewalks, nearly flat in some places and scraping the sky in others. Pull back far enough, and the city starts to look like something else entirely: a cluster of molecules.

At least, that’s what it looks like to Franz-Josef Ulm, an engineering professor at the Massachusetts Institute of Technology. Ulm has built a career as an expert on the properties, patterns, and environmental potential of concrete. Taking a coffee break at MIT’s Stata Center late one afternoon, he and a colleague were looking at a large aerial photograph of a city when they had a “eureka” moment: “Hey, doesn’t that look like a molecular structure?”
With colleagues, Ulm began analyzing cities the way you’d analyze a material, looking at factors such as the arrangement of buildings, each building’s center of mass, and how they’re ordered around each other. They concluded that cities could be grouped into categories: Boston’s structure, for example, looks a lot like an “amorphous liquid.” Seattle is another liquid, and so is Los Angeles. Chicago, which was designed on a grid, looks like glass, he says; New York resembles a highly ordered crystal.
So far Ulm and his fellow researchers have presented their work at conferences, but it has not yet been published in a scientific journal. If the analogy does hold up, Ulm hopes it will give planners a new tool to understand a city’s structure, its energy use, and possibly even its resilience to climate change.
Ulm calls his new work “urban physics,” and it places him among a number of scientists now using the tools of physics to analyze the practically infinite amount of data that cities produce in the 21st century, from population density to the number of patents produced to energy bill charges. Physicist Marta González, Ulm’s colleague at MIT, recently used cellphone data to analyze traffic patterns in Boston with unprecedented complexity, for example. In 2012, a theoretical physicist was named founding director of New York University’s Center for Urban Science and Progress, whose research is devoted to “urban informatics”; one of its first projects is helping to create the country’s first “quantified community” on the West Side of Manhattan.
In Ulm’s case, he and his colleagues have used freely available data, including street layouts and building coordinates, to plot the structures of 12 cities and analogize them to existing complex materials. In physics, an “order parameter” is a number between 0 and 1 that describes how atoms are arranged in relationship to other atoms nearby; Ulm applies this idea to city layouts. Boston, he says, has an “order parameter” of .52, equivalent to that of a liquid like water. This means its structure is notably disordered, which may have something to do with how it developed. “Boston has grown organically,” he said. “The city, in the way its buildings are organized today, carries that information from its historical evolution.”…

Business Models That Take Advantage of Open Data Opportunities

Curated on Posted on by Stefaan Verhulst
Mark Boyd at the Programmeableweb: “At last week’s OKFestival in Berlin, Kat Borlongan and Chloé Bonnet from Parisian open data startup Five By Five moderated an interactive speed-geek session to examine how startups are building viability using open data and open data APIs. The picture that emerged revealed a variety of composite approaches being used, with all those presenting having just one thing in common: a commitment to fostering ecosystems that will allow other startups to build alongside them.
The OKFestival—hosted by the Open Knowledge Foundation—brought together more than 1,000 participants from around the globe working on various aspects of the open data agenda: the use of corporate data, open science research, government open data and crowdsourced data projects.
In a session held on the first day of the event, Borlongan facilitated an interactive workshop to help would-be entrepreneurs understand how startups are building business models that take advantage of open data opportunities to create sustainable, employment-generating businesses.
Citing research from the McKinsey Institute that calculates the value of open data to be worth $3 trillion globally, Borlongan said: “So the understanding of the open data process is usually: We throw open data over the wall, then we hold a hackathon, and then people will start making products off it, and then we make the $3 trillion.”
Borlongan argued that it is actually a “blurry identity to be an open data startup” and encouraged participants to unpack, with each of the startups presenting exactly how income can be generated and a viable business built in this space.
Jeni Tennison, from the U.K.’s Open Data Institute (which supports 15 businesses in its Startup Programme) categorizes two types of business models:

  1. Businesses that publish (but do not sell) open data.
  2. Businesses built on top of using open data.

Businesses That Publish but Do Not Sell Open Data

At the Open Data Institute, Tennison is investigating the possibility of an open address database that would provide street address data for every property in the U.K. She describes three types of business models that could be created by projects that generated and published such data:
Freemium: In this model, the bulk data of open addresses could be made available freely, “but if you want an API service, then you would pay for it.” Tennison pointed to lots of opportunities also to degrade the freemium-level data—for example, having it available in bulk but not at a particularly granular level (unless you pay for it), or by provisioning reuse on a share-only basis, but you would pay if you wanted the data for corporate use cases (similar to how OpenCorporates sells access to its data).
Cross-subsidy: In this approach, the data would be available, and the opportunities to generate income would come from providing extra services, like consultancy or white labeling data services alongside publishing the open data.
Network: In this business model, value is created by generating a network effect around the core business interest, which may not be the open data itself. As an example, Tennison suggested that if a post office or delivery company were to create the open address database, it might be interested in encouraging private citizens to collaboratively maintain or crowdsource the quality of the data. The revenue generated by this open data would then come from reductions in the cost of delivery services as the data improved accuracy.

Businesses Built on Top of Open Data

Six startups working in unique ways to make use of available open data also presented their business models to OKFestival attendees: Development Seed, Mapbox, OpenDataSoft, Enigma.io, Open Bank API, and Snips.

Startup: Development Seed
What it does: Builds solutions for development, public health and citizen democracy challenges by creating open source tools and utilizing open data.
Open data API focus: Regularly uses open data APIs in its projects. For example, it worked with the World Bank to create a data visualization website built on top of the World Bank API.
Type of business model: Consultancy, but it has also created new businesses out of the products developed as part of its work, most notably Mapbox (see below).

Startup: Enigma.io
What it does: Open data platform with advanced discovery and search functions.
Open data API focus: Provides the Enigma API to allow programmatic access to all data sets and some analytics from the Enigma platform.
Type of business model: SaaS including a freemium plan with no degradation of data and with access to API calls; some venture funding; some contracting services to particular enterprises; creating new products in Enigma Labs for potential later sale.

Startup: Mapbox
What it does: Enables users to design and publish maps based on crowdsourced OpenStreetMap data.
Open data API focus: Uses OpenStreetMap APIs to draw data into its map-creation interface; provides the Mapbox API to allow programmatic creation of maps using Mapbox web services.
Type of business model: SaaS including freemium plan; some tailored contracts for big map users such as Foursquare and Evernote.

Startup: Open Bank Project
What it does: Creates an open source API for use by banks.
Open data API focus: Its core product is to build an API so that banks can use a standard, open source API tool when creating applications and web services for their clients.
Type of business model: Contract license with tiered SLAs depending on the number of applications built using the API; IT consultancy projects.

Startup: OpenDataSoft
What it does: Provides an open data publishing platform so that cities, governments, utilities and companies can publish their own data portal for internal and public use.
Open data API focus: It’s able to route data sources into the portal from a publisher’s APIs; provides automatic API-creation tools so that any data set uploaded to the portal is then available as an API.
Type of business model: SaaS model with freemium plan, pricing by number of data sets published and number of API calls made against the data, with free access for academic and civic initiatives.

Startup: Snips
What it does: Predictive modeling for smart cities.
Open data API focus: Channels some open and client proprietary data into its modeling algorithm calculations via API; provides a predictive modeling API for clients’ use to programmatically generate solutions based on their data.
Type of business model: Creating one B2C app product for sale as a revenue-generation product; individual contracts with cities and companies to solve particular pain points, such as using predictive modeling to help a post office company better manage staff rosters (matched to sales needs) and a consultancy project to create a visualization mapping tool that can predict the risk of car accidents for a city….”

Portugal: Municipal Transparency Portal

Curated on Posted on by Stefaan Verhulst

“The Municipal Transparency Portal is an initiative of the XIX constitutional Government to increase transparency of local public administration management toward citizens. Here are presented and made available a set of indicators regarding management of the 308 Portuguese municipalities, as well as their aggregation on inter-municipal entities (metropolitan areas and intermunicipal communities) when applicable.
Indicators
The indicators are organized in 6 groups:

    • Financial management: financial indicators relating to indebtedness, municipal revenue and expenditure
    • Administrative management: indicators relating to municipal human resources, public procurement and transparency of municipal information
    • Fiscal decisions of municipality: rates determined by the municipalities on IMI, IRS and IRC surcharge
    • Economic dynamics of the municipality: indicators about local economic activity of citizens and businesses
    • Municipal services: indicators regarding the main public services with relevant intervention of municipalities (water and waste treatment, education and housing)
    • Municipal electoral turnout: citizen taking part in local elections and voting results.

More: http://www.portalmunicipal.pt/”
 

A framework for measuring smart cities

Curated on Posted on by Stefaan Verhulst
Paper by Félix Herrera Priano and Cristina Fajardo Guerra for the Proceedings of the 15th Annual International Conference on Digital Government Research: “Smart cities are an international phenomenon. Many cities are actively working to build or transform their models toward that of a Smart City. There is constant research and reports devoted to measuring the intelligence of cities through establishing specific methodologies and indicators (grouped by various criteria).
We believe the subject lacks a certain uniformity, which we aim to redress in this paper by suggesting a framework for properly measuring the smart level of a city.
Cities are complex and heterogeneous structures, which complicates comparisons between them. To address this we propose an N–dimensional measurement framework where each level or dimension supplies information of interest that is evaluated independently. As a result, the measure of a city’s intelligence is the result of the evaluations obtained for each of these levels.
To this end, we have typified the transformation (city to smart city) and the measurement (smart city ranking) processes.”

The Quiet Movement to Make Government Fail Less Often

Curated on Posted on by Stefaan Verhulst

in The New York Times: “If you wanted to bestow the grandiose title of “most successful organization in modern history,” you would struggle to find a more obviously worthy nominee than the federal government of the United States.

In its earliest stirrings, it established a lasting and influential democracy. Since then, it has helped defeat totalitarianism (more than once), established the world’s currency of choice, sent men to the moon, built the Internet, nurtured the world’s largest economy, financed medical research that saved millions of lives and welcomed eager immigrants from around the world.

Of course, most Americans don’t think of their government as particularly successful. Only 19 percent say they trust the government to do the right thing most of the time, according to Gallup. Some of this mistrust reflects a healthy skepticism that Americans have always had toward centralized authority. And the disappointing economic growth of recent decades has made Americans less enamored of nearly every national institution.

But much of the mistrust really does reflect the federal government’s frequent failures – and progressives in particular will need to grapple with these failures if they want to persuade Americans to support an active government.

When the federal government is good, it’s very, very good. When it’s bad (or at least deeply inefficient), it’s the norm.

The evidence is abundant. Of the 11 large programs for low- and moderate-income people that have been subject to rigorous, randomized evaluation, only one or two show strong evidence of improving most beneficiaries’ lives. “Less than 1 percent of government spending is backed by even the most basic evidence of cost-effectiveness,” writes Peter Schuck, a Yale law professor, in his new book, “Why Government Fails So Often,” a sweeping history of policy disappointments.

As Mr. Schuck puts it, “the government has largely ignored the ‘moneyball’ revolution in which private-sector decisions are increasingly based on hard data.”

And yet there is some good news in this area, too. The explosion of available data has made evaluating success – in the government and the private sector – easier and less expensive than it used to be. At the same time, a generation of data-savvy policy makers and researchers has entered government and begun pushing it to do better. They have built on earlier efforts by the Bush and Clinton administrations.

The result is a flowering of experiments to figure out what works and what doesn’t.

New York City, Salt Lake City, New York State and Massachusetts have all begun programs to link funding for programs to their success: The more effective they are, the more money they and their backers receive. The programs span child care, job training and juvenile recidivism.

The approach is known as “pay for success,” and it’s likely to spread to Cleveland, Denver and California soon. David Cameron’s conservative government in Britain is also using it. The Obama administration likes the idea, and two House members – Todd Young, an Indiana Republican, and John Delaney, a Maryland Democrat – have introduced a modest bill to pay for a version known as “social impact bonds.”

The White House is also pushing for an expansion of randomized controlled trials to evaluate government programs. Such trials, Mr. Schuck notes, are “the gold standard” for any kind of evaluation. Using science as a model, researchers randomly select some people to enroll in a government program and others not to enroll. The researchers then study the outcomes of the two groups….”

i-teams

Curated on Posted on by Stefaan Verhulst

New Report and Site from NESTA: “Last year we were aware of the growing trend for governments to set up innovation teams, funds, and labs. Yet who are they? What do they do? And crucially, are they making any difference for their host and partner governments? Together Nesta and Bloomberg Philanthropies set out to answer these questions.
Drawing on an in-depth literature review, over 80 interviews, and  surveys, i-teams tells the stories of 20 teams, units and funds, all are established by government, and all are charged with making innovation happen. The i-teams case studied are based in city, regional and national governments across six continents, and work across the spectrum of innovation – from focusing on incremental improvements to aiming for radical transformations.
The i-teams were all created in recognition that governments need dedicated structures, capabilities and space to allow innovation to happen. Beyond this, the i-teams work in different ways, drawing on a mix of methods, approaches, skills, resources, and tackling challenges as diverse as reducing murder rates to improving education attainment.
The i-teams report details the different ways in which these twenty i-teams operate, but to highlight a few:

  • The Behavioural Insights Team designs trials to test policy ideas, and achieved government savings of around 22 times the cost of the team in the first two years of operation.
  • MindLab is a Danish unit using human centred design as a way to identify problems and develop policy recommendations. One project helped businesses to find the right industry code for registrations and demonstrated a 21:1 return on investment in savings to government and businesses.
  • New Orleans Innovation Delivery Team is based in city hall and is tasked with solving mayoral challenges. Their public safety efforts led to a 20% reduction in the number of murders in 2013 compared to the previous year.
  • PS21 encourages staff to find better ways of improving Singaporean public services. An evaluation of PS21 estimated that over a year it generated 520,000 suggestions from staff, of which approximately 60 per cent were implemented, leading to savings of around £55 million.

Alongside the report we have launched theiteams.org a living map to keep track of i-teams developing and emerging around the world, and to create a network of global government innovators. As James Anderson from Bloomberg Philanthropies says, “There’s no reason for every government to start its innovation efforts from scratch.” There is much we can learn from what is underway, what’s working and what’s not, to ensure all i-teams are using the most cutting edge techniques, methods and approaches….”