Innovations Publications

Toward a Smarter Future: Building Back Better with Intelligent Civil Infrastructure -- Smart Sensors and Self-Monitoring Civil Works

Toward a Smarter Future: Building Back Better with Intelligent Civil Infrastructure -- Smart Sensors and Self-Monitoring Civil Works

Abstract:

Stephen Goldsmith, Betsy Gardner, and Jill Jamieson; August 2021 

 

The United States needs to build better infrastructure. The current repairs and replacements are disorganized and patchwork, resulting in unsafe, costly, and inequitable roads, bridges, dams, sidewalks, and water systems. A strategic, smart infrastructure plan that integrates digital technology, sensors, and data not only addresses these issues but can mitigate risks and even improve the conditions and structures that shape our daily lives.

 

By applying data analysis to intelligent infrastructure, which integrates digital technology and smart sensors, we can identify issues with the country’s roadways, buildings, and bridges before they become acute dangers. First, by identifying infrastructure weaknesses, smart infrastructure systems can address decades of deferred maintenance, a practice that has left many structures in perilous conditions. Sensors in pavement, bridges, vehicles, and sewer systems can target where these problems exist, allowing governments to allocate funding toward the neediest projects.

From there, these sensors and other smart technologies will alert leaders to changes or issues before they pose a danger—and often before a human inspector can even see them. The many infrastructure emergencies in the U.S. cost thousands of lives and billions of dollars each year, so identifying and fixing these issues is a pressing security issue. Further, as the changing climate leads to more extreme weather and natural disasters, the safety and resiliency of the country’s infrastructure is an immediate concern. Sensor systems and other intelligent infrastructure technology can identify and mitigate these problems, saving money and lives.

In addition, intelligent infrastructure can be layered onto existing infrastructure to address public health concerns, like monitoring sewer water for COVID-19 and other pathogens or installing smart sensors along dangerous interstates to automatically lower speed limits and reduce accidents. It can also be used to improve materials, like concrete, to reduce the carbon footprint of a project, ultimately contributing to better health and environmental outcomes.

Finally, addressing inequities is a major reason to utilize intelligent infrastructure. Research shows that people of color in the U.S. are exposed to more pollutants, toxic chemicals, and physical danger through excess car emissions, aging water pipes, and poor road conditions. The implementation and funding of these intelligent infrastructure projects must consider where—and to whom—harm has traditionally been done and how building back better can measurably improve the quality of life in marginalized and vulnerable communities.

While there are challenges to implementing a sweeping intelligent infrastructure plan, including upfront costs and security concerns, all levels of government play a role in achieving a safer society. At the federal level, with infrastructure funding bills being debated at this moment, the government must look beyond roads and bridges and consider that intelligent infrastructure is a system: upheld, connected, and integrated by data. Through grants, incentives, and authorized funding, the federal government can effect monumental change that will improve how all residents experience their daily lives. At the state level, budgeting with intelligent infrastructure in mind will encourage innovative approaches to local infrastructure. And on a municipal level, cities and towns can invest in comprehensive asset management systems and training for local workers to best utilize the intelligent infrastructure data.

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Last updated on 08/20/2021

2020 State of Digital Transformation

Citation:

Eaves, David, and Lauren Lombardo. 2020. “2020 State of Digital Transformation”.
2020 State of Digital Transformation

Abstract:

David Eaves, Lauren Lombardo, February 2021 

Starting in 2018, every year, the State of Digital Transformation report documents the main lessons from a Digital Services Convening hosted at Harvard Kennedy School. In 2020, Harvard Kennedy School and Public Digital hosted a series of discussions on the coronavirus digital response. These gatherings, which included a wide range of digital service groups, highlighted success stories, lessons learned, and tools that digital teams could leverage or repurpose. 

This year's report highlights some of the new possibilities discussed at the convening and provides further reflections on crisis response. 

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Last updated on 02/19/2021

Deploying the Once-Only Policy: A Privacy-Enhancing Guide for Policymakers and Civil Society Actors

Deploying the Once-Only Policy: A Privacy-Enhancing Guide for Policymakers and Civil Society Actors

Abstract:

Naeha Rashid, November 2020 

The once-only policy (OOP) is increasingly seen by some digital government experts as central to establishing a national digital government strategy and as a gateway to next-generation government services. Once-only is so called because users (citizens, residents, and businesses) have to provide diverse data only one time when in contact with public administrations; after the initial data transfer, different parts of government can internally share and reuse this data to create public value and better service for users. 

Members of the digital government community are excited by the potential of OOPs to create public value and reduce the cost of government, and I want to help governments harness this potential. I am also deeply concerned by the potential for OOPs to concentrate and increase state power and the negative impact this could have on individuals’ privacy, freedoms, and capacity to dissent. 

The goal is to harness the benefits of OOP while minimizing the risks, to create a world in which the power of the state is counterbalanced by the power of its citizenry. This document outlines the key policy questions and concerns that must be addressed by governments intending to implement an OOP. It is designed to help stakeholders—including policymakers in government and interested parties in civil society—ask key questions during the development of OOP-facilitating infrastructure, specifically identity- and data-sharing mechanisms, and the development of OOP strategy. 

This document is not to intended to encourage or prescribe a specific pathway of development, but to consolidate and present a compendium of the key considerations at each stage. This work is based on an extensive literature review across the areas of privacy, identification, data sharing, and OOP; interviews with experts in the field; and mini case studies highlighting different lessons of implementation from five countries—the Netherlands, Estonia, the UK, Canada, and Australia—with diverse approaches and at very different stages of OOP maturity. 

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Read the Deploying the Once-Only Policy Supplement

Last updated on 12/08/2020

Getting Value from Workforce Stimulus Investments: What Works in Youth Workforce Programs and How to Grow the Evidence Base

Getting Value from Workforce Stimulus Investments: What Works in Youth Workforce Programs and How to Grow the Evidence Base

Abstract:

Jane Wiseman, November 2020 

The current economic crisis will likely inspire federal investment in training for unemployed and underemployed Americans. When funds are made available for youth workforce development, transparent reporting and publication of results data should be required. User-friendly reports should be created that enable unemployed and underemployed Americans to see which training providers achieve the best results, much as the current College Scorecard helps youth and their families evaluate colleges. This will benefit program recipients, the taxpayer, and society at large. Evidence about what works for youth workforce development is still in an early stage of maturity, so upcoming investments present an opportunity to advance the state of knowledge. With this data and insight, future investments can continue to fund effective programs and ineffective ones can be discontinued.

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Last updated on 11/13/2020

The 2020 Election Season and Aftermath: Preparation in Higher Education Communities

Citation:

Leonard, Herman B. "Dutch", Arnold M. Howitt, and Judith B. McLaughlin. 2020. “The 2020 Election Season and Aftermath: Preparation in Higher Education Communities”.
The 2020 Election Season and Aftermath: Preparation in Higher Education Communities

Abstract:

Herman B. "Dutch" Leonard, Arnold M. Howitt, and Judith B. McLaughlin; October 2020 

There is widespread uncertainty and heightened anxiety on higher education campuses and elsewhere about what might happen during the 2020 election season in the United States. At every turn, we see elevated emotions and anxieties generated by the election process and related events, together with the potential for disruption of various kinds in the election process itself – before, during, and/or after the end of voting on November 3. This is compounded by the possibility of uncertainty, perhaps over many days or even weeks, about who has won various contests and about who will take office.

A wide range of scenarios related to the election process and possible election outcomes have been described in mainstream media, in social media, and in other forums. Given the considerable (and, generally speaking, desirable) involvement and energy invested in these events within higher education communities among faculty, staff, students, and alumni, a number of these scenarios might well result in situations on campuses, in higher education communities, or in the surrounding communities where they reside that would call for institutional response. Many campus leaders and management groups are now thinking through what might be necessary or desirable and figuring out what they might usefully do in advance to prepare to provide the best response possible. Obviously, the difficulties of planning for the many possible circumstances that might confront us are compounded by the fact that all of this is taking place during an ongoing (and, indeed, now intensifying) pandemic accompanied by calls for racial justice and police reform. In this brief note, we suggest some ideas that might be helpful for higher education communities organizing themselves in the face of these uncertainties.

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Last updated on 10/29/2020

The Analytics Playbook for Cities: A Navigational Tool for Understanding Data Analytics in Local Government, Confronting Trade-Offs, and Implementing Effectively

The Analytics Playbook for Cities: A Navigational Tool for Understanding Data Analytics in Local Government, Confronting Trade-Offs, and Implementing Effectively

Abstract:

Amen Ra Mashariki and Nicolas Diaz, August 2020 

Properly used data can help city government improve the efficiency of its operations, save money, and provide better services. Used haphazardly, however, the use of analytics in cities may increase risks to citizens’ privacy, heighten cybersecurity threats, and even perpetuate inequities.

Given these complexities and potentials, many cities have begun to install analytics and data units, often head by a chief data officer, a new title for data-driven leaders in government. This report is aimed at practitioners who are thinking about making the choice to name their first CDO, start their first analytics team, or empower an existing group of individuals.

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About the authors

Amen Ra Mashariki is the Global Director of the Data Lab at WRI. There he works across programs, international offices and centers to identify data solutions to turn big ideas into action to sustain our natural resources—the foundation of economic opportunity and human well-being. Amen Ra is also a Data + Digital fellow at the Beeck Center for Social Impact and Innovation where he partners with academic, public and private sector thought leaders to shape best practices and strategies on how to use data to maximize impact in our communities.

Prior to this, Dr. Mashariki has served as Head of Machine Learning at Urbint, adjunct faculty at NYU’s Center for Urban Science and Progress (CUSP), Fellow at the Harvard Ash Center for Democratic Governance and Innovation, Head of Urban Analytics at Esri, Chief Analytics Officer for the City of New York, Director of the Mayor’s Office of Data Analytics at the City of New York, White House Fellow, and Chief Technology Officer for the Office of Personnel Management of the United States.

Amen earned a Doctorate in Engineering from Morgan State University, as well as a Master and Bachelor of Science degree in Computer Science from Howard and Lincoln University respectively.

Nicolas Diaz Amigo is a graduate from the Master in Public Policy program at Harvard Kennedy School. He has had research and fellow roles at the Bloomberg Harvard City Leadership Initiative and at digitalHKS. Professionally, he served as the first Coordinator of Public Innovation at the Mayor’s Office in Santiago, Chile, City Hall and has consulted for cities and local government organizations across the world on the topics of public sector innovation, data analytics, digital transformation, performance management, budgeting, and process improvement.

About the series editor

David Eaves is a lecturer of Public Policy at the Harvard Kennedy School where he teaches on digital transformation in Government. In 2009, as an adviser to the Office of the Mayor of Vancouver, David proposed and helped draft the Open Motion which created one of the first open data portals in Canada and the world. He subsequently advised the Canadian government on its open data strategy where his parliamentary committee testimony laid out the core policy structure that has guided multiple governments approach to the issue. He has gone on to work with numerous local, state, and national governments advising on technology and policy issues, including sitting on Ontario's Open Government Engagement Team in 2014–2015.

In addition to working with government officials, David served as the first Director of Education for Code for America — training each cohort of fellows for their work with cities. David has also worked with 18F and the Presidential Innovation Fellows at the White House providing training and support.

Acknowledgements

This report has been possible with the sponsorship of digitalHKS, a project at Harvard Kennedy School that studies the intersection of digital technologies and governance. The authors are grateful for the generosity of the public servants who provided case studies. Additionally, many individuals provided invaluable feedback to earlier version of this report, including   Kadijatou Diallo, Tommaso Cariati, Westerley Gorayeb, Natasha Japanwala, Lauren Lombardo, Michael McKenna Miller, Nagela Nukuna, Emily Rapp, Naeha Rashid, Imara Salas, and Blanka Soulava. This report is an independent work product and views expressed are those of the authors.

About the Ash Center

The Roy and Lila Ash Center for Democratic Governance and Innovation advances excellence and innovation in governance and public policy through research, education, and public discussion. By training the very best leaders, developing powerful new ideas, and disseminating innovative solutions and institutional reforms, the Center’s goal is to meet the profound challenges facing the world’s citizens. The Ford Foundation is a founding donor of the Center. Additional information about the Ash Center is available at ash.harvard.edu.

This research paper is one in a series published by the Ash Center for Democratic Governance and Innovation at Harvard University’s John F. Kennedy School of Government. The views expressed in the Ash Center Policy Briefs Series are those of the author(s) and do not necessarily reflect those of the John F. Kennedy School of Government or of Harvard University. The papers in this series are intended to elicit feedback and to encourage debate on important public policy challenges.

This paper is copyrighted by the author(s). It cannot be reproduced or reused without permission. Pursuant to the Ash Center’s Open Access Policy, this paper is available to the public at ash.harvard.edu free of charge. 

Executive Summary

Properly used data can help city government improve the efficiency of its operations, save money, and provide better services. Used haphazardly, however, the use of analytics in cities may increase risks to citizens’ privacy, heighten cybersecurity threats, and even perpetuate inequities.

Given these complexities and potentials, many cities have begun to install analytics and data units, often head by a chief data officer, a new title for data-driven leaders in government. This report is aimed at practitioners who are thinking about making the choice to name their first CDO, start their first analytics team, or empower an existing group of individuals.

In the following pages, we provide city leaders with:

  • Definitions. To understand what an analytic team in city government looks like, as well as presenting alternative team structures in the realm of data, digital government, and innovation.
  • Principles. The attitudes and mindsets that are useful when trying to enact ambitious change in local government, such as ensuring executive buy-in and seeking allies outside of government.
  • Plays. The organizational, strategic, and tactical considerations that a city must think about for starting and supporting an analytics team. These are presented in a sequential order: how to set up a team for success, building up from scratch, managing the day-to-day, as well as important considerations (like privacy and ethics) that should be present throughout.

1. Introduction: The potential use and misuse of data analytics in city government 

Imagine a world where our cities not only deliver the services that we expect from them, from weekly trash collection to running our schools to supporting local businesses, but also tailor those services to each of its citizens. Like Netflix recommending the next show you should watch based on your previous views or Amazon steering you to a product you didn’t even know you needed, local governments could connect citizens who request a service with other social programs they qualify for.

Imagine a city hall not only reacting to problems — a student dropping out of school or a building catching on fire — when they occur, but using data to identify risks and take preventive measures before they happen.

These are not pipe dreams. Municipal departments already possess an abundance of data, from utility bills to tax records to school enrollment histories, though the value of that data is often locked away in silos. City analytics, a discipline that combines operations research and data science,has the potential to unlock the big insights behind the big data and move local governments toward higher efficiency and effectiveness in the provision of services and the prevention of social ills.

When it comes to the use of advanced analytics, the public sector needs to catch up to the progress seen in the private sector over the past few decades. But strictly copying private sector practices is not the right approach. There are considerations for dealing with data collected by a public institution. With all the potential analytics hold for improving the delivery of local services, its risks must also be carefully examined by analysts, the senior leaders who oversee their work, and civil society at large. A misuse of analytics may pose cybersecurity threats, threaten privacy, or reinforce existing inequities.

Lessons from NYC: Breaking silos increased the need for cybersecurity

To exemplify the risks of misusing analytics, let’s take the example of cybersecurity. A few years ago, New York City was considering improving its monitoring system for underground assets such as sewage pipes that were being tracked by several agencies, each with its own software system and database. Bringing all of those together into a unique system would have allowed for more efficient management. But while a breach of any particular databases would not be particularly catastrophic, having the city’s entire underground mapped by bad actors would be a major threat. The standards for how safely data is stored and shared internally had to be reexamined.

Doing analytics in government also comes with unique barriers, such as the difficulty of hiring individuals with the right technological background or moving an organizational culture that does not always welcome innovation.

But that doesn’t mean there is no path forward. In fact, an increasing number of cities are beginning to systematically incorporate analytics, often in the form of new teams headed by leaders with titles like chief data officer, chief analytics officer, or chief performance officer. This playbook examines successes and failures, and shows what hard choices have so far been made along the way. An analytics team must face difficult questions that do not have clear answers: Who do we hire first? How do we prioritize our projects? How much time should we spend communicating our successes? By illuminating some of the trade-offs cities have faced, we hope this document will help city officials find a strategy that works for their own context, limitations, and objectives.

In sports, it is important for a coach to understand the wide variety of plays that may come in handy in different circumstances. A playbook provides a sense of orientation in a context of high complexity. What should happen at the start of the game, what do we do when we are in overtime, etc. But just like in sports, understanding the generic plays is not enough to win the game. It’s all in the execution and flexibility in adapting to whatever resources are available.

The lessons in this playbook rely heavily upon Amen Ra Mashariki’s experiences as head of the Mayor’s Office of Data Analytics (MODA) in New York City, where he led a team of nine analysts and policy specialists. To illustrate some of the lessons throughout this document, we will call out these insights in boxes like the one on the previous page. But we have also put these ideas to the test by consulting some of the leading professionals in the field, who have generously provided case studies that illustrate the potential and barriers of urban analytics.

One thing readers should be wary of is the temptation to think that every problem can be solved with data and technology. Using analytics heedlessly may even make some problems worse. The intention of this report, therefore, is to allow for a critical application of sophisticated tools. We will address several dimensions of those tools including learning how to identify which problems are suited for an analytics approach, understanding potential issues, setting up the right team to tackle those issues, and making sure the team gets the right resources for success.

This document is structured as follows. We start by defining what an analytics team is and what it is not. Then we highlight principles that guide successful teams. Finally we will highlight specific plays: the key trade-offs, questions and frameworks that an analytics team in local government must consider in order to effectively pursue its mission.

This playbook won’t give you all the answers for starting an analytics team. Instead, it is are meant to orient you toward questions that allow you to connect the work you want to do with whatever is important and feasible right now. The skill sets of your employees, the legal framework you are operating under, and even the political cycle will mold your journey. We have tried to offer some thoughts and ideas, but ultimately you will have to decide which plays to focus on at each time. To get better at the game, you have to start somewhere.

2. Definitions

In their desire to move toward data-driven organizations, well-intentioned public managers may fail to fully grasp what they are getting themselves into. Not all organizations need an analytics team, but by providing a clear sense of what analytics teams are and what they are trying to accomplish, we hope to make it easier for senior officials to choose whether to pursue this path.

2.1. What an analytics team is

Analytics teams may take different names and vary in size, scope, and mission across different jurisdictions.[1] Our basic definition of an analytics team in local government is a specialized group that applies data analysis to uncover insights with the hope of improving the operations of city departments.

In practice, what we most often find is a team between one and 20 employees that has been formally integrated in the bureaucracy. This team will leverage data-intensive tools such as machine learning or mapping to define, evaluate, and propose solutions to public problems. Its mission statement is usually some variation of “improving the outcome of what the city does to create more public value for constituents at lower cost” — though the most pressing areas to tackle to deliver public value will change depending on where you are and whom you ask.

2.2. What an analytics team is not

Other data-driven management and digital-government adjacent groups can take these forms:

  • A traditional information technology (IT) team that maintains technology assets and keeps systems running
  • A performance management team that works across departments to define the relevant metrics for success
  • A digital service team tthat ensures interoperability of the data, such as allowing members of one department to easily access data from other departments
  • An open data team that maintains an online portal aimed at sharing city data sets with the general public
  • A data governance team that sets citywide standards and convenes analysts across the city to build a citywide data culture

Note that these functions can be complementary to the work of an analytics team. In some places there may be overlap (for example, a chief data officer may set open data policies), and cities may choose to prioritize some of these over others.

3. Principles

While no single blueprint can work for every city, you will find throughout this report some common principles that underlie any effort to bring more analytical thinking to local governments. Teams should:

  • Commit to better service delivery. An analytics team must be driven by a desire to make government work better for its citizens in a transparent and accountable way.
  • Be both the disrupter and the listener. Given the nascent state of analytics in government, analytics teams may have to act like internal entrepreneurs who question the way things are done. But this desire for disruption must be paired with a profound curiosity to understand the nuances and challenges that led to the status quo.
  • Start with the problem, not the solution. An analytics team should avoid the temptation to run around with fancy tools in search of places to apply them. Instead, its strategic outlook and tactical moves should be centered around pressing challenges faced by the city or its individual departments. And when a need is found, a sense of practicality and viability should supercede the drive for sophistication. Simple is better than complex.
  • Ensure executive buy-in. As talented and persuasive as data-driven public servants may be, support from key stakeholders at the top is essential. Whatever your specific institutional arrangement, buy-in from your mayor, her chief of staff, the city manager, or someone sufficiently high up will allow you to overcome the resistance to change you’ll encounter along the way.
  • Work in the open. The work should not be top secret. The projects undertaken should be considered part of a conversation about public service delivery that is appropriately communicated within city hall and with the public. Blog posts can help explain the aim of each project and code can be posted online for scrutiny. A a commitment to transparency should ensure that those seeking information about a process or its results can easily access it.
  • Find allies. You will require allies both inside and outside the organization. In this playbook we will discuss in detail ways you can engage with department heads to create quick wins, when to extend ties to academia, and how the press can come in handy.
  • Quickly deliver value, but think long term. The team will need to rapidly demonstrate what it is bringing to the table and deliver quick wins. However, team members must also be aware that to create even more value they need to think about long-term investments in infrastructure and changes to the work culture. An effective manager must carefully consider both time frames simultaneously. 

4. The plays

 

4.1. Setting up the right team for success

This section begins by looking at the most relevant part of your analytics effort: the people behind it and how they should be organized.

4.1.1 Step zero: Making the case for data analytics

How do you argue the need for an analytics team?

Before beginning to establish an analytics team, stakeholders may need to be persuaded. Whether it is a city administrator, a councilwoman, or the general public, a convincing case must be made that a new team will help the city reach its goals.

Jane Wiseman, CEO of the Boston-based management consulting firm Institute for Excellence in Government, in studying cities investing in analytic efforts,[2] points toward multiple types of value that can be attributed to data teams:

  • Fraud detection cost savings
  • Efficiency improvements that reduce costs
  • Accuracy improvements that reduce costs
  • Increased revenue capture
  • Efficiency improvements that improve outcomes
  • Operational changes that increase safety
  • Increased faith in government due to more transparency

Naturally, not all stakeholders will care equally for every one of these. A city administrator may be more concerned with cutting costs than with transparency, for example. It is important to tailor the message in a way that considers particular stakeholder interests.

On the issue of improving city finances, a McKinsey study[3] on the use of data analytics in government to find fraud found that the return of investment could be as high as 15 times the cost. Wiseman also points toward two municipal data teams that self-reported their return on investment (ROI): The Louisville Metro Government calculated a five-to-one return for analytics efforts and the Cincinnati Office of Performance and Data Analytics calculated a $6.1 million added value to the city in two years of operation, a nine-to-one return.

4.1.2 Defining structure: Decentralized or centralized?

Should the analytics team be in one department or agency or spread out among several?

An analytics team may be a single central office that takes on projects across the city (centralized model) or a collection of employees  who are spread among various departments (decentralized model).

To decide between the two models, a useful rule of thumb is to think about what types of projects would generate the most immediate value for senior sponsors.

If you want to use data to tackle an issue that is handled by a single department (e.g., crime prevention, which is the responsibility of the police department), then a decentralized model, with analysts that sit permanently in that department, will allow for more sophisticated and in-depth research.

On the other hand, if your aim is to address a challenge where different agencies share responsibility (e.g, you want to know which buildings to target for inspection in a city that splits code enforcement tasks among the fire department, housing, etc.), then you should establish a centralized, dedicated unit. Having analysts who work with multiple departments will avoid task duplication and also reap the benefits of breaking down data silos instead of having each department create from scratch its own models with partial data.

In “Data-Driven Government: The Role of Chief Data Officers,”[4] published by the IBM Center for the Business of Government, Wiseman offers a systematic comparison of the centralized and decentralized models for government agencies, as seen in the following table.

 

 

Centralized

Decentralized

 

Chief data officer (CDO) focus

  • Analytics resources in a single team under the CDO’s leadership
  • CDO team provides data and analytics services to key executives and managers, functioning as an internal consultant
  • Team works in partnership with executives and managers to define scope and project needs
  • Some bureaus or agencies — typically the better resourced or statistics-driven ones — may have their own analytics resources, but the majority rely on the centralized CDO team
  • CDO team creates distributed capacity across government by embedding talent in bureaus through training and coaching
  • CDO team creates tools, platforms, and data standards that speed adoption of data skills in bureaus
  • Each bureau/agency/office is responsible for developing its own analytics capability, which can range from budget and policy analysts who can complete basic descriptive statistics and dashboards to analysts with the skill to perform data science tasks such as predictive analytics

 

Ideal for

  • Specialized skills or subject matter expertise needed for highly technical work
  • Analytics projects that require a high degree of confidentiality, such as investigations
  • Large-scale enterprises with similar or low-complexity operations spread across many bureaus, divisions or geographies
  • Agencies with a high level of existing data skill or broad adoption of data literacy, such as scientific or statistical agencies

 

Benefits

  • Centralized pool of analytics talent allows sharing of specialized skills across the enterprise from a common hub, which saves money since highly trained analytics staff can be expensive for government
  • Efficiencies are gained via peer support and collaboration among team members
  • Centralized team is better able to standardize tools and processes across government, which can save time and money and help develop deeper expertise in the chosen tools and methods
  • Team can facilitate cross-organizational data initiatives due to its enterprise-wide view of data assets and needs
  • Leaders and managers in bureaus have more control over their analytics resources, may get more timely responses to their requests, and may also more immediately deploy analytics insights
  • Analysts embedded in bureaus develop subject matter expertise that makes them valuable to their leadership and speeds time to results
  • Embedded analysts can foster greater adoption of data culture across enterprise, which can lead to faster organizational culture change
  • Skills gained in self-service analytics are transferable across government, spreading benefit

 

Limitations

  • Slow growth of sustainable analytics talent in the bureaus
  • Can be challenging to achieve scale with a small centralized team, as surge capacity may need to be deployed for a high-priority task
  • Putting decision-making and control of analytics in the hands of bureau heads leads to uneven attention and results, with some investing heavily and others giving it low priority or not appointing an analytics officer unless compelled to do so
  • Decentralized model limits peer cohorts for data-focused employees and may results in a more limited career ladder

 

 

 

 

 

Case study: Chicago’s CDO has a centralized mandate[5]

The first U.S. city to have a chief data officer (CDO) was Chicago. After briefly being part of the mayor’s office, the position was then moved to the Department of Innovation and Technology.

Tom Schenk Jr. served as the city’s second CDO and as deputy director of IT, which gave him both a centralized mandate to drive data analytics and the operational responsibility for maintaining and upgrading the city’s databases and digital platforms.

This centralization of responsibilities allowed Schenk and his team not only to push for concrete data analytics projects, but also to take control of data governance. They began building a data inventory of the entire city and optimizing the data infrastructure for easier analytics in the future.

Being able to inventorize the data was essential for setting up future successes. However, Schenk warns that quick wins are an absolute necessity. “Stuff will get hard and you will need to ask a lot of people [for help],” he says. “An inventory of data will take a lot of time and effort, and both residents and internal stakeholders will not perceive its value until you show some progress and real, tangible results.”

Schenk and his team also had to consider how to choose which projects to spend time on. To decide, the team worked closely with the University of Chicago, creating a framework to screen projects and assess the data maturity required for meaningful analysis in conjunction with the master of science program in Computational Analysis & Public Policy.[6]

A longer write-up of this case can be found in the annex.

 

4.1.3 Who to hire

Who is the first person you hire for your analytics team? What about the second, third, and fourth?

There is no predetermined profile or career progression for the team members in an analytics office. One reason for that is the need for teams that cover a wide variety of tasks, from project management and performing complex analyses to knowing how to build effective cooperation with the domain experts and more.

An article published in the Harvard Business Review in 2019 noted that data science teams in the private sector often attempt to discover “profound new business capabilities,” and because of this such teams must be made up of generalists who are focused on learning and iteration rather than specialists who do only one thing efficiently.[7] This argument can be made even more strongly for local governments because of the immense quantity and complexity of the services they provide.

For your first team member, consider looking for someone within the organization who has some local experience, rather than hiring out of a prestigious economic-analysis consultancy or data science firm. Even if this is a job that will require a good understanding of analytical methods, the first employee’s main challenge at first will be effectively navigating the tacit idiosyncracies of a political and organizational environment. An urban planner at the transportation department, for example, may have better insight into both the current challenges the city is facing and whom to partner with to get stuff done. Keep your eyes open.

When considering further hires, around analytics offices across the world, it is common to find professions as diverse as:

  • Data scientists
  • Urban planners
  • GIS managers and analysts
  • Political scientists
  • Social science researchers/analysts
  • Mathematicians and statisticians

Some skill sets that will be valuable regardless of previous occupation will be empathy (to understand the challenges of others), communication (to work effectively in collaborative teams), and curiosity (to always be looking out for status quo thinking that needs to be challenged).

Keep in mind that cultural diversity adds to the strength of the team (especially if it mirrors the diversity in your city) and will help avoid analytic projects with blindspots in issues such as race, differences among neighborhoods, etc. For more on this, see the passage on algorithmic bias in section 4.4.2, “The pitfalls of analytics.”

4.1.4 How to hire

How do you overcome some of the challenges in attracting talented and motivated individuals to local government?

Once you start looking outside the organization, it will not be easy to hire who you want. Young, ambitious professionals well-versed in analytical skills may feel more at home in a small start-up than in a big, clunky bureaucracy. A McKinsey article about trends in the workforce[8] highlighted the importance millennials put on flexibility, the availability of mentor relationships, and the autonomy to tackle their own projects — qualities not usually associated with the public sector.

Moreover, there is the issue of money; usually the public sector has strict rules about how much to pay people according to their place in the organization chart, and the average starting salaries for data scientists is often higher than what most agency heads earn — so highly skilled professionals will be offered significantly less than what they could earn elsewhere.

One advantage that you do have is the ability to offer impact and purpose. You can structure your portfolio of projects in a way that gives each analyst the opportunity to work on complex urban challenges that may affect the lives of thousands of citizens, while bringing forth new methodologies and ideas. Team members may also have access to high-level individuals in the city. But this also requires you to create a workflow with the proper autonomy for everyone on your team.

Local universities and colleges are an important resource. Whether you are located in a small city or a large metropolis, there should be a college nearby with a data science program. A few universities even offer specialized programs, such as the University of Chicago’s Master of Science in Computational Analysis and Public Policy[9] and New York University’s Urban Analytics track for its Master of Urban Planning.[10] At the very least, your local educational institution should have a statistics program. If searching locally bears no fruit, you might look into specialized networks for connecting the public sector with academia such as the MetroLab Network[11] and the Data Science for Social Good Fellowship at Carnegie Mellon University.[12]

Lessons from NYC: Accepting a faster changing team

At times, the traditional model of structuring a team in local government may need to be reconsidered. In New York City, Amen knew that if he hired young people he would not be able to retain them for long. So he kept a team with high turn-over and a frantic schedule of projects, offering his team the ability to work with autonomy on high-stakes issues.

           

 

Effectively engaging educational institutions means giving them access to interesting data sets and projects. For professors and students, getting their hands on real data for analysis is incredibly enticing. Graduate students must often do capstone projects with real-world clients in order to graduate. Finally, you may use this as an opportunity to create a pipeline for talent, offering student internships that may turn into full-time jobs by graduation. Regardless of the specific approach you take, hiring should be a continuous task. You may have to be constantly looking at resumes, nurturing your relationships with academia, going to classes to meet with students, looking for interns, etc.

4.2. Starting from scratch

Once in place, your analytics team will need to get started quickly. This will mean sorting out difficulties and finding a way to demonstrate value quickly. This section goes in depth into those crucial first steps.

4.2.1 How to find your first project

 How do you spot a “minimum viable product” ?

Your first analytics project is important. It will provide an opportunity to prove the value of the team to leadership and to senior officials throughout the city, so you should start not with a solution in mind but with a real problem that the city is facing — ideally, a challenge that has been clearly identified as a priority by leaders.

To further build the case for the analytics team, it should be a problem that can be tackled by integrating data sets from across multiple agencies. This will show the value of breaking data silos and will probably uncover problems of poor data collection. Furthermore, problems where the data is scattered are often complex policy issues that require deeper thinking — something that may have been ignored so far.

Finally, this cannot be an intellectual exercise only. Although there is plenty of value in visualizing a problem that may have been hidden from the view of stakeholders, to truly cement your first project as a success you should work with your partners toward a clear strategy for delivery. Do not assume that this will happen on its own. Talk with partnering departments beforehand to clarify how analytical results can help with the implementation or piloting of operational innovations.

From the very beginning, identify partners across the entire city government who see the worth of your work. They may be senior officials or new employees. Regardless, make them your data champions. Empower them. But do not forget to communicate to the top; the senior advisor or chief of staff to the mayor may be very busy in her day-to-day, but she should still be frequently updated on what you are doing.

 

Case study: Piloting London’s Office of Data Analytics[13]

In 2016 a pilot began for the London Office of Data Analytics (LODA). It was orchestrated by the Greater London Authority; 12 of the 36 London boroughs; Nesta, an innovation NGO; and ASI, a data science firm.

LODA found its first project by asking for suggestions from the participating boroughs. Then, a workshop session was conducted to collaboratively assess the projects based on:

  • Money saving potential
  • Availability of data
  • The ability to produce insights and delivering results within two months
  • The ability to solve the problem without personal data sets

After the issue selection process, the pilot focused on one use case: leveraging predictive analytics to identify multiple occupations in houses that did not have the appropriate licenses. By combining data sets from multiple sources, the team sought to point inspectors toward infractors.

Ultimately the project was unable to produce meaningful insights, but it did help inform a protocol for data-sharing among the boroughs.

A longer write-up of this case can be found in the annex.

 

4.2.2 Making the case for more funding

How do you argue for more money?

Every budget appropriation process is different, as the financial, political, and technical idiosyncrasies play out. However, the more clarity there is in the analytics team’s mission, the easier it will be to iterate that mission and construct a compelling narrative. It helps if the mission is closely aligned with the intentions of senior leaders. Often, analytics teams get stuck trying to do a little bit of everything, which muddles the argument for recurring funding.

You should be aware of the downside to following performance indicators, though, since important outcomes are often not measured. Performance indicators will usually point you toward things that are already being done by each department, potentially blinding you to exploring solutions that may not fit neatly within the existing bureaucratic structure. On the other hand, focusing on improving upon existing solutions may make the potential implementation more straightforward. This is a tension that you will have to navigate constantly.

Once you have finished your first project you may choose to scale your work in either vertically, by growing the complexity of the analysis you provide to your partners (i.e., moving from describing trends in data sets to predictive work to prioritize resources), or horizontally, by growing the number of agencies with which you are collaborating.

Lessons from NYC: Look at performance indicators

A logical alternative would be to make sure the projects that the team implements are tied to performance indicators. For example, when Amen was leading the New York City team, they only worked on projects that were part of the yearly quantitative goals that had to be reported to the mayor’s office and to the city at large. If a department had a proposition, the analysis had to have a logical and explicit way to move the numbers toward a goal. This discipline made it easier for the analytics team to track its impact in terms of city priorities met and dollars saved, thus making the case for growth.

 

As the analytics team begins to find a comfortable place in the organization, it should consider how to transition into a sustainable workflow that delivers the most value. This section helps to illustrate what you can expect the team’s day-to-day to look like. What sort of projects can the team offer? How does it prioritize projects? How should other departments be brought into the fold? And, how do you shift from merely reacting to thinking about the long term?

 

4.3.1 Understanding the multiple uses of analytics: Repertoire of actions

What can you use analytics for?

Once an analytics team is in place and has one or two projects under its belt, it should begin to look for other ways it could add value to ongoing projects, and how to let other departments understand what services the team can offer to help them do their work.

The table below is adapted from work performed by New York City’s Mayor’s Office of Data Analytics, and includes the categories of data analysis projects and real-use cases for a variety of city needs.

 

 

Why would we want to do it?

Example application

Prioritizing

Where to go first?

Ranking a list according to certain criteria can enable more efficient use of resources. Useful when [getting to the worst things]? earlier can mitigate potential negative effects.

To assist the Department of Education’s work to make all schools ADA-compliant, MODA used DOE data to prioritize which schools to renovate in order to reduce the number of students with disabilities who needed to use buses 

 

Scenario Analysis

What if?

Considering alternative events and their possible outcomes can help policymakers find the best course of action and plan for a greater range of possible policies.

As part of the Mayor’s Office of Long Term Planning and Sustainability’s research for a new commercial composting policy, MODA predicted how much waste local businesses would generate under various  regulatory thresholds.

Anomaly Detection

What is out of the ordinary?

Some processes can be improved by identifying and investigating outliers. Useful when looking for the exception is more feasible than examining every case.

Registration records of all kinds may have a number of files that display unusual characteristics. Flagging and examining those records may reveal procedural oversight or fraudulent transactions.

Matching

What goes with what?

Matching can optimally pair two groups against a certain set of constraints. Useful for equitably distributing limited resources.

When the appointment scheduler for IDNYC was backlogged with duplicate requests, MODA helped match applicants to times and locations based on indicated preferences.

Estimating

How much will a project cost?

Projects can be planned more effectively when time, materials, and costs are estimated in advance. Useful for quantifying the costs and benefits of new programs.

MODA worked with the Department of Housing Preservation and Development to estimate the resource requirements and program outcomes for a new set of Enhanced Contractor Review procedures.

Targeting

Where to look?

Targeting can narrow an operational domain to enable better resource allocation. Useful for identifying a subset for a specific intervention.

MODA created a model to help identify buildings that have displayed a pattern of unsafe living conditions. This enabled the Tenant Harassment Prevention Task Force to follow up with inspections and enforcement actions when necessary.

 

4.3.2 Picking the right projects

How do you choose what to work on?

At some point, you will have to choose between multiple projects that are asking for the analytics team’s resources and attention. Look for projects with the right:

  • Partners: Do you have buy-in from stakeholders to try new solutions and put insights into practice?
  • Data: Is there meaningful data that could lead to insights?
  • Impact: Will the analysis help illuminate a solution for a problem that is relevant?

Chicago’s approach was codified in a form given to technical departments that requested help from the analytics team,[14] allowing users to quickly assess a number of alternatives. Not every city necessarily needs to develop its own questionnaire, as the day-to-day of project intake may be more messy, but there should be some sense of which projects advance the analytics team’s mission and the overall goals of the administration.

Look for performance metrics. If, prior to the collaboration, there is some measurement of whatever problem is being solved or service is being improved, that will help make the case for the value of the team in the form of dollars saved, extra customers served, or whatever metric is relevant.

Consider scope. Some projects may be multi-year collaborations on complex policy areas, while others may have quicker turnarounds. You may want a combination of both in your repertoire.

Finally, mayoral priorities must be a consideration. Most mayors and city administrators will have a strategic plan or list of goals. These are a good start for finding projects that have a mandate to innovate and the appropriate resources for implementation.

4.3.3 Working with other departments

How can the analytics team be an effective partner to others?

By definition, a city’s analytics team is a partner to other departments.

This is important to keep in mind because it should dictate the attitude taken when relating to internal stakeholders. After all, if anything goes wrong, it’s the department that’s directly implementing a service that usually gets blamed, not the analyst. Avoid the negative spotlight. Don’t assume a project that is fascinating to you will be of interest to whichever commissioner or project director you want to pitch it to. Understand their priorities and avoid politically sensitive subjects when you don’t have the appropriate cover.

Instead, when approaching potential partners actively listen to their goals and concerns. When you do have an idea to bring up, make sure to frame it in a way that is attuned to their interests: “We would love to sit down and discuss how data could help you handle this problem or achieve this target.”

Another good practice in early exploratory meetings is to provide a variety of ways of helping. For example, you could:

  • Provide advisory functions upon request
  • Help research a particularly thorny question through data
  • Offer training to people in the department if they have to use data or a specific software tool in their day-to-day functions
  • Assist in developing a procurement strategy for tools that would best serve their need and allow for better analysis

Finally, remind your partners that you will be in the background and will do whatever it takes to make sure they get recognized for the success of the project.

4.3.4 Data stewardship

How do you think about data management?

Eventually, the team will need to start thinking beyond building effective collaborations that lead to fruitful projects and toward setting the right data infrastructure, or how data is managed, organized, and governed. This is known as data stewardship, and it may be vital to the long-term success of your analytics team.

Some cities, like Boston, have installed centralized data warehouses built in collaboration with contractors and maintained internally (see case study below). Such a tool may or may not be the best alternative for your city; what’s most relevant is the concerted and iterative effort to rethink the city’s data infrastructure, and how that can be connected to the mission of the analytics team.

 

Case study: Boston’s implementation of a centralized data warehouse[15]

The City of Boston has implemented its own centralized data warehouse, which serves as a repository for different databases that can be used throughout several departments. It was built over a period of three years with a contractor hired through a competitive bidding process. The project started small, encompassing a handful of databases, automating the loading of data into the system as much as possible, and expanding from there. Today, more than 30 departments have their data up and running.

Boston decided to make this investment in data infrastructure primarily for two reasons. First, to create a central repository (a single source of “truth”) and avoid the duplication of data across several departments. Second, to shift the work of data analysts from tracking down and cleaning data to adding value to the data by, for example, understanding the operational implications behind each project or ensuring the robustness of the analysis.

Boston’s warehouse has been instrumental in implementing one of the city’s priorities: its Vision Zero for eliminating fatal and serious car crashes, [16] which combines data sets from multiple stakeholders.

A longer write-up of this case can be found in the annex.

 

4.3.5 Pushing projects to production

How can you turn insights into value?

In whatever realm the analytics team in your city may hope to make a difference, it should ultimately strive to not only create insightful analysis, but also to develop products or tools that are useful for other employees of the city and that (either incrementally or radically) change their day-to-day operations. This requires more resources and a larger team, but it is the key to delivering impact and innovation.

In trying to address this challenge, the boss at Transport for London’s data team (see case study below) uses philosophies that are not always common in local government: agile development — a way of organizing work around iteration and quick prototypes — and the introduction of product management to oversee the continuous and iterative improvement of the applications that generate business value, as opposed to project management where projects have start and end dates.

Case study: Transport for London and Leveraging Data Products[17]

As the chief data officer of Transport for London (TfL), Lauren Sager Weinstein heads a team of 70 people, including data scientists, product managers, software developers, and data architects. The team is relatively new in the organization, and part of its mission is to centralize the creation of tools that use the vast amount of data generated by London’s transportation network — from traffic information to traffic-signals data to costumer data — while preventing the creep of siloed data tools that traditionally didn’t interact with one another.

TfL’s analytics team is particularly concerned in creating organizational change, since if there is no connection to actual operations that will be affected, then there is no real business value. To do this, they have adopted strategies such as:

  • A  product management mindset, where product managers continue to work closely with operational experts who use the results of an analytics project
  • An agile methodology to their projects, which includes the creation of minimal viable products with defined outcome metrics
  • A commitment to transparency, privacy, and clear communication of their work and its value to the general public

A longer write-up of this case can be found in the annex.

4.3.6 Branding and communications

How should you communicate the analytic team efforts?

You need to be proactive about communicating the work of the team.

One reason is that an effective branding strategy will help you with the other challenges we have pointed out: attracting the right talent to the team, building meaningful partnerships with other departments, and securing appropriate resources.

Another reason is that there may be (often well-founded) skepticism and challenges to using methods such as predictive analytics in government. If these fears are not addressed they may paralyze the work of the team.

The most appropriate strategy for the analytics team will likely depend on a combination of the organizational choices and the current state of the conversation. It will require different approaches in different situations; depending, for example, on whether you are working on concrete operational issues or pursuing one of the mayor’s priorities, which is likely to have a marketing strategy of its own.

In any case, be prepared to explain in simple terms what you are trying to accomplish, while also having considered the implications of your work (see Section 4.4.2, “The pitfalls of analytics”).

As much as possible, make your data, code, and insights publicly available. Academic institutions will probably be willing to partner up and further analyze your results, which will help you spread the information to an even wider audience as well as validate your approach.

4.4. Important considerations

In this section we include other key concepts that will be vital for the analytics team. Although we offer only a brief explanation for each of these challenging concepts, we believe that the people behind analytics in government should keep open discussions surrounding how to remake government from a platform perspective, the importance of open data and sharing, the ethical considerations behind this work, and, above all, the understanding that when poorly managed, these projects can actively cause harm.

4.4.1 Open data

How can you use open data requirements as an advantage?

Across many jurisdictions, there is an increasing legal or political mandate for open data policies.[18] In New York City, for example, legislation approved in 2012 demands that all departments upload their data using open data standards. The push has often been led by civil society with the aim of increasing transparency and predicated upon established principles such as accessibility, timeliness. and completeness.[19] Governments may also have an interest in publishing their data as it may lead to civic innovations.

The call for open data within city hall, whether as a formal decree or an informal demand, can be a great way to speed up the potential for analytical work by giving you more data sets to play around with and build the data infrastructure of the city. But you should consider some caveats.

  • Not all mayors and city managers will be equally receptive (or pressured) to push open data. Therefore, the willingness of departments to comply may vary. Understand the history of your city’s open data efforts, the current landscape, and the applicable laws and regulations to open data, and adapt accordingly.
  • Even if there is a clear mandate, you should watch out for potential duplication. If there is a legal requirement, there may be an office separate from the analytics team that has been set up to help departments with open data compliance. Thus, certain departments may have to send around the data multiple times.
  • Adding data to an open data portal is costly. It will probably involve an active process of data cleaning to scrub away any personally identifiable information.
  • You will have to do some thinking around your users. Most open data efforts assume that there is a standard generic user and they tailor their efforts to whatever is most convenient to the city.

Lessons from NYC: Considering multiple consumers of open data

In reality, you may have different types of users, with different skill sets and different understanding of what data is useful or not. When Amen was in MODA, he commissioned the social impact firm Reboot to do a study that found at least six personas or types of users who were using, or could potentially use, their open data portal — mappers, liaisons, interpreters, explorers, bystanders, and community champions.

 

Several companies offer prepackaged open data solutions that may be cheaper than building your own portal from scratch, but one thing to consider before committing to one is whether that solution has the right users in mind. Another alternative may be inviting citizens to give input into the city’s open data policies; it’s more expensive but you will reap the benefits of a co-created solution that engages the community.

4.4.2 The pitfalls of analytics: Privacy, security, and algorithmic bias

What should you, the team, and city leadership watch out for?

As governments start to ingest ever-growing quantities of data, new pitfalls appear. The more granular, rich, and timely your data, the more it will grow in usefulness for analytics, and the higher the risk of potential breach or misuse. Entirely new literatures have emerged over the past decade surrounding the challenges of privacy, security, and bias in algorithms, and universities have created graduate programs for professionals to specialize in these areas. Here we only offer a glimpse of the general things to consider.

Privacy

There is an inherent tension between transparency and privacy, even when you are careful with personally identifiable information. As more and more information is made available in open data portals, concerns arise that something like data on parcels can be linked to individual behaviors. And even if you attempt to anonymize or de-identify certain data sets, studies show that information can be reidentified with a lot more ease than was once thought.[20]

It is important to listen, respond to the concerns of citizens, and ensure that protocols are put in place in accordance with national, state, and local laws. Understand too that agencies that produce and control data may have their own concerns. Different departments may have different privacy requirements and if you are trying to bring that information into a centralized system, you should be aware of all the limitations.

Cybersecurity

In recent years the number of cyber attacks targeting state and local governments has grown considerably in the United States and around the world. The role of the chief information security officer (CISO) has been getting more attention.[21]

This presents two relevant considerations for the analytics team. First, it should understand that bringing information together under a centralized data infrastructure may create additional vulnerabilities. In the United States, some data types (such as medical information) have specific standards for security that must be met.

Second, the team needs to understand who has the mandate to deliver cybersecurity, which depends on the city’s structure. In some jurisdictions this mandate may not even be realized yet and may need to be created. If there is an IT team that is separate from the analytics team and they has been charged with maintaining data security, that team should be a close partner in helping the analytics team plan the next step for the city’s data infrastructure.

Algorithmic bias

Many academic and journalistic articles have been published in the past couple of years regarding the fairness of algorithmic decision-making. Some worry that black box algorithms built on faulty data may perpetuate or even accentuate patterns of inequality already in place. Others retort that with the right precautions and oversight, data can lead to a fairer distribution of resources by being quicker to identify those who need them or by predicting where an intervention can have the largest impact.

Some local governments are taking steps. New York City enacted an ordinance to monitor its automated systems,[22] and states like Vermont are developing guidelines.[23]

While there are no simple solutions at the moment, a good starting place is transparency. Having a scrutable open-source library of every project and auditing any automated decision-making system in the city should help create some trust. One useful resource to consider is the Open Data Institute’s Data Ethics Canvas,[24] which encourages analytics teams to be thoughtful about the primary purpose of any project and consider those who may be negatively affected by it.

5. Summary: Data analyst, go out there and listen

In the summer of 2015, cooling towers were killing people in New York City. Legionnaires’ disease is a form of bacterial pneumonia spread through the inhalation of infected water vapors, and several sites in the South Bronx saw enough cases in July and August that it became the biggest outbreak of the disease in the city’s history. Public health officials mandated the inspection and disinfection of all cooling towers in the area, but there was no official record of where such towers were located.

            MODA was called to help.[25] There had been a dozen fatalities and the city was scrambling to identify and begin tracking all the existing towers. Many departments tried to get as much information as possible in a variety of ways, from creating a self-registration portal to dialing building managers to physically inspecting buildings, resulting in disparate data sets with no “ground truth.”

By quickly pulling together all the information gathered, MODA was able to create a single, reliable data set for the inspections to work from as well as predictive models to find the missing towers. An early machine-learning model had enough predictive power to find approximately 90 percent of all cooling towers in New York. This allowed the city to move quickly, stopping the spread of the disease in a matter of weeks.

Of course, not every project is so dramatic. Some projects may seem more mundane. Some may never be implemented. But they are all important. As MODA’s support in the Legionnaires’ disease crisis illustrates, adding more analytical capacity is increasingly important as cities must adapt to the growing complexity of whatever urban challenges they are facing, and ultimately provide value to citizens. Being able to find previously unseen value in your data sets, ensure that city operations are tied to increases in performance, prove the value of new policies with data, and understand the limitations and pitfalls of these approaches so that they are used responsibly will inevitably go from being seen by city leadership as nice-to-have to must-have.

6. Annex

6.1. Case study: Chicago’s CDO has a centralized mandate[26]

Tom Schenk Jr. became the second Chief Data Officer (CDO) to serve in Chicago, after having played roles in the private, public, and academic sectors and publishing a book on data visualization. His arrival came just after the department had just been moved from the mayor’s office to the Department of Information Technology (DoIT), a department with highly qualified staff but a lot of attrition, which had operational responsiblity for maintaining and upgrading every single database and major digital platform used by other departments. The appointment gave Schenk dual roles as both CDO and deputy director of IT.

Dual roles that converge

Because he had to understand the ins and outs of the systems that were serving the rest of City Hall, these dual responsibilities provided a tactical advantage. Tom and his team optimized their systems while also molding them to be more responsive to the needs of future analytics teams. This reduced the barriers between analysts and IT professionals, and whenever a database was hard to access, Tom could easily get his team to give access and solve the issue.

Being able to inventorize the data was essential for setting up future successes. However, Schenk warns that quick wins are an absolute necessity. “Stuff will get hard and you will need to ask a lot of people [for help],” he says. “An inventory of data will take a lot of time and effort, and both residents and internal stakeholders will not perceive its value until you show some progress and real, tangible results.”

As CDO, Schenk undertook a broad variety of projects, from predictive analytics to open data to automation. One of his most notable projects was a predictive algorithm that identified where kids were most likely to suffer from lead poisoning before they were 1 year old.

Selecting projects as a centralized analytics unit

As a centralized data analytics unit, how to choose which projects to spend time on was a constant question. The team worked closely with the University of Chicago. In conjunction with the Master of Science in Computational Analysis & Public Policy, they created a framework to screen projects and assess the data maturity required for meaningful analysis.[27] Although the criteria were very explicit, the project intake remained flexible as the team evaluated the availability of data, the potential impact, and the ability for the partnering unit to operationalize the problem, or what they would do after the analysis was conducted.

Effective projects through collaboration

Another publicized initiative was a predictive model for food inspection evaluations.[28] This model, which aimed to optimize the procedure for inspecting restaurants and resulted in critical violations being found seven days earlier, sprouted as part of a grant awarded by Bloomberg Philanthropies to Chicago as part of the Mayor’s Challenge.[29] It later became a collaborative partnership between the Chicago Department of Innovation and Technology (DoIT), the Department of Public Health (CDPH), the Civic Consulting Alliance, and Allstate Insurance.

Schenk also spearheaded the creation of a robust open data policy and hosted hackathons to promote the use of city data and get the community engaged.

An example of the difficulties of collaboration came from one project that intended to predict where illegal cigarettes sales occurred. Because of the nature of the issue, the relevant data were collected by both the county and the city, and getting different levels of government (which have different data collection and standardization practices) onboard required significant coordination. Because the project was not able to get to concrete results early on, it eventually got sidetracked and discarded.

6.2. Case study: Piloting London’s Office of Data Analytics[30]

In 2016 a pilot began for the London Office of Data Analytics (LODA). It was orchestrated by the Greater London Authority; 12 of the 36 London boroughs; Nesta, an innovation NGO; and ASI, a data science firm.

Although it was modeled after New York City’s Mayor’s Office of Data Analytics, LODA faced an additional layer of complexity because each of London’s Boroughs had its own council, government structure, and data sets without any obvious standardization.

LODA found its first project by asking for suggestions from the participating boroughs. Then, a workshop session was conducted to collaboratively assess the projects based on:

  • Money saving potential
  • Availability of data
  • The ability to produce insights and delivering results within two months
  • The ability to solve the problem without personal data sets

Data to tackle common challenges

After a multistage project selection process, the pilot focused on one use case: leveraging  predictive analytics to identify multiple occupations in houses that did not have the appropriate licenses. By combining data sets from multiple sources, the team sought to point inspectors towards infractors.

One of the main questions the pilot sought to answer was whether this methodology would be easily scalable to all boroughs of the city or to other policy areas. As an ultimate goal, this provided the opportunity to intelligently design shared services and coordinate the action of different teams.

Data scientists from an external consultancy were brought onboard, as the data analytical capacity inside the boroughs was extremely limited and their analysts could not commit full time to this project. Internal and external analysts worked together to identify relatable data sets from building inspections, noise complaints, tax bands, etc.

Learning from failure

The LODA pilot failed to produce meaningful results or a scalable methodology.

One of the main barriers was that the boroughs collected widely varying data, and when they did collect the same data, they used different formats. This forced the team to create individual models for each borough. Much time had to be spent processing, cleaning, and merging the data. Moreover, the data sets weren’t properly geomatched; that is,there wasn’t a unique identifier for each property that allowed the merging of data.

From a data science standpoint, it was hard to carry out a predictive model because the variable of interest was only half-labelled; the team knew for certain when some houses fell in the “unlicensed multiple occupation” category, but didn’t know for certain when a house was definitely not in that category. This made assessing the accuracy of the model difficult.

Other challenges cited by the pilot group included:

  • Data quality: significant effort was devoted to cleaning; inability to geomatch certain data sets
  • Data availability: private rental data were missing or hard to access
  • Data warehousing: some boroughs did not have centralized business intelligence units or data warehouses and the data had to be pulled individually from different sections of the organization
  • Rarity of the predicted variable: The variable of interest was too rare in certain boroughs, which made the construction of a predictive model hard
  • Lack of capacity: Lack of available in-house expertise in the boroughs to work in both the data analytical portion and the implementation that should have followed

After the pilot, an information sharing protocol was signed by 12 of the boroughs and Mayor Sadiq Khan announced the creation of a City Data Analytics Programme to build on the connections made possible by the data partnership between boroughs.

6.3. Case study: Boston’s implementation of a centralized data warehouse[31]

The City of Boston has implemented its own centralized data warehouse, which serves as a repository for different databases that can be used throughout several departments. It was built over a period of three years with a contractor hired through a competitive bidding process. The project started small, encompassing a handful of databases, automating the loading of data into the system as much as possible, and expanding from there. Today, more than 30 departments have their data up and running.

Investing in data infrastructure

Why is Boston investing in its data infrastructure? On one hand, the city avoids conflicting reports of data by establishing a single repository of reliable information, which creates trust. Before establishing a centralized warehouse, several versions of the same data may have existed in different departments. For example, if the 311 phone line (which in many cities is the main aggregator for citizen requests and complaints) gets reports about potholes in the streets, it may keep a separate list and then pass it on to the Department of Transportation, which is in charge of filling the potholes. The 311 division and DOT may keep separate data sets, perhaps with different attributes. (Has the complaint been inspected? Has the citizen been contacted when his case is closed?) If you wanted to understand the entirety of the pothole operational performance, you would have to track down several different data sets held by different people in different departments, perhaps even in different formats.

This helps clarify a second advantage of a centralized warehouse: as you move toward enacting advanced analytics — whether by building dashboards, running predictive models, etc. —  a centralized model will save your analysts will considerable time and effort and their results will be more reliable. Because they don’t have to spend tracking down and cleaning the data, steps that could have taken weeks or months turn into days, and the analytics team can spend its time on activities that really add value, such as working with partners to understand the operational implications behind the data or ensuring the robustness of the analysis.

Boston’s warehouse has been instrumental in implementing one of the city’s priorities: its Vision Zero for eliminating fatal and serious car crashes.[32] This plan, which involves several departments (transportation, public works, police, and more), is built upon reporting, dashboards, and geospatial visualizations that rely upon data that is also collected by several stakeholders. By leveraging the data warehouse, the analytics team at the Department of Innovation and Technology was able to quickly and frequently provide information regarding traffic patterns, interventions at streets, reported incidents, and more.

Maria Borisova, one of the city’s software engineers who has been overseeing the warehouse implementation from its inception tells us that the technical details are relevant but not that hard to figure out. It is often working with other partners that requires thoughtfulness. Plenty of times Borisova’s counterparts at other city departments may have concerns about centralizing their data, worrying about the  accessibility, reliability, and safety of the new system. Patience, starting small and building iteratively, and showing value to your counterparts is vital, she says.

6.4. Case study: Transport for London and leveraging data products[33]

As the chief data officer of Transport for London (TfL), Lauren Sager Weinstein heads a team of 70 people, including data scientists, product managers, software developers and data architects. The team is relatively new in the organization, and part of its mission is to centralize the creation of tools that use the vast amount of data generated by London’s transportation network — from traffic information to traffic-signal data to costumer’s data — while preventing the creep of siloed data tools that didn’t interact with each other.

Creating real business value through analytics

The data science team at TfL seeks not only to understand data but also to create meaningful products that add business value to the organization. This requires an understanding of TfL’s strategic priorities,[34] such as expanding bus service to outer London and reducing carbon emissions, as well as of the operational complexity of the network. While keeping constant communication with other divisions of TfL, a data scientist may find an insight that could be used to improve more processes. After a proof of concept to test its usefulness, a team of developers may built a software tool around it and a dashboard to measure its outcomes. One of the several product managers may be in charge of ensuring that the tool continues to fulfill its goal and hit its targets.

To accomplish this, the team must work with an agile methodology, building minimal viable products with defined outcome metrics. It is essential that any partner(s) for a given project should have a clear articulation of what analysis they need and what it will be used for. Without a connection to actual operations that will be affected, there is no real business value. For example, to execute the city’s Vision Zero,[35] which seeks to eradicate road deaths by 2030, the transit division wanted to understand where bus speeding was most frequent to then take the right preventive measures.

Another of the team’s recent undertakings has been a pilot to test whether WiFi usability data (collected at tube stations) could help the organization’s understanding of traffic patterns and help create measures to avoid congestion, improve operations, and prioritize investments. With data coming from over 500 million connection requests, the team prototyped a series of solutions, including the display of approximate train congestion for passengers waiting on the station and others. By using an agile approach, TfL has been able to test both the technical and business value feasibility, and can now begin to consider moving to a production version of some of the ideas that were tested.

It is also worth noting TfL’s commitment to transparency — the results of pilots are published online —[36] and clear policies regarding privacy and the use of personal information[37].

 

[1] Jane Wiseman. (2017). Lessons from Leading CDOs: A Framework for Better Civic Analytics

[3] Susan Cunningham, Mark McMillan, Sara O’Rourke, and Eric Schweikert, “Cracking down on government fraud with data analytics,” October 2018, McKinsey & Company.

[5] Interview with Tom Schenk (October 2019).

[15] Interview with Maria Borisova, Data Engineering Manager at the City of Boston (February 2020).

[17]  Interview with Laura Sager Weinstein, Chief Data Officer at Transport for London (March, 2020).

[26] Interview with Tom Schenk (October, 2019).

[31] Interview with Maria Borisova, Data Engineering Manager at the City of Boston (February, 2020).

[33]  Interview with Laura Sager Weinstein, Chief Data Officer at Transport for London (March, 2020).

Last updated on 02/17/2021

Federal COVID‐19 Response Funding for Tribal Governments: Lessons from the CARES Act

Citation:

Henson, Eric, Miriam R. Jorgensen, Joseph Kalt, and Megan Hill. 2020. “Federal COVID‐19 Response Funding for Tribal Governments: Lessons from the CARES Act”.

Abstract:

Eric C. Henson, Megan M. Hill, Miriam R. Jorgensen & Joseph P. Kalt; July 2020 

The federal response to the COVID‐19 pandemic has played out in varied ways over the past several months.  For Native nations, the CARES Act (i.e., the Coronavirus Aid, Relief, and Economic Security Act) has been the most prominent component of this response to date. Title V of the Act earmarked $8 billion for tribes and was allocated in two rounds, with many disbursements taking place in May and June of this year.

This federal response has been critical for many tribes because of the lower socio‐economic starting points for their community members as compared to non‐Indians. Even before the pandemic, the average income of a reservation‐resident Native American household was barely half that of the average U.S. household. Low average incomes, chronically high unemployment rates, and dilapidated or non‐existent infrastructure are persistent challenges for tribal communities and tribal leaders. Layering extremely high coronavirus incidence rates (and the effective closure of many tribal nations’ entire economies) on top of these already challenging circumstances presented tribal governments with a host of new concerns. In other words, at the same time tribal governments’ primary resources were decimated (i.e., the earnings of tribal governmental gaming and non‐gaming enterprises dried up), the demands on tribes increased. They needed these resources to fight the pandemic and to continue to meet the needs of tribal citizens.

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Last updated on 07/24/2020

Policy Prototyping for the Future of Work

Citation:

Gustetic, Jenn, Carlos Teixeira, Becca Carroll, Joanne Cheung, Susan O’Malley, and Megan Brewster. 2020. “Policy Prototyping for the Future of Work”.

Abstract:

Jenn Gustetic, Carlos Teixeira, Becca Carroll, Joanne Cheung, Susan O'Malley, and Megan Brewster; June 2020

The future of work will require massive re-skilling of the American workforce for which current policy “toolboxes” for economics, labor, technology, workforce development and education are often siloed and antiquated. To meet the needs of tomorrow’s workers, today’s policy makers must grapple with these interdisciplinary policy issues.

This report describes a novel design-driven approach we developed to create policy “prototype” solutions that are inherently interdisciplinary, human-centered, and inclusive for the future of work. Using our design-driven approach, we collaborated with more than 40 interdisciplinary and cross-sector thinkers and doers to generate 8 distinct policy prototypes to support the future of work.

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Fiscal Strategies to Help Cities Recover—And Prosper

Citation:

Goldsmith, Stephen, and Charles “Skip” Stitt. 2020. “Fiscal Strategies to Help Cities Recover—And Prosper.” Ash Center for Democratic Governance and Innovation.
Fiscal Strategies to Help Cities Recover—And Prosper

Abstract:

Stephen Goldsmith and Charles "Skip" Stitt, May 2020 

Despite robust economies, many local officials entered 2020 already worried about budget balances that looked fragile in the short term and problematic in the long term due to enormous pension and health-care issues. Today, in the wake of COVID-19, clearly federal support is necessary, but it is also apparent that it cannot alleviate all the pressures on communities as responsibilities related to the pandemic skyrocket while revenues plummet.

While many public managers will rightly deploy a host of tactical cost-cutting measures, the most creative among them will explore deeper and more strategic changes, such as those presented herein, which will help address the current crisis while preparing their cities for the future. This paper suggests a transition to a culture deeply focused on data, incentives for city workers to produce internal reforms, public-private partnerships that monetize operational excellence, and rapid adoption of both new technologies and good ideas borrowed from other jurisdictions. These more deliberate and strategic approaches may be harder to implement but those offered here need not harm incumbent public employees nor negatively impact cities’ efforts to ensure access and equity. Rather, the strategies we outline should strengthen the efficiency and mandates of existing government offices while helping make cities more resilient and better prepared for tomorrow’s challenges.

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Last updated on 12/09/2020

2019 State of Digital Transformation

Citation:

Eaves, David, and Georges Clement. 2020. “2019 State of Digital Transformation”.
2019 State of Digital Transformation

Abstract:

David Eaves, Georges Clement; May, 2020

In June of 2019, the Harvard Kennedy School hosted digital service teams from around the world for our annual State of Digital Transformation convening. Over two days, practitioners and academics shared stories of success, discussed challenges, and debated strategy around the opportunities and risks digital technologies present to governments.

Teams that joined us for the summit used different approaches and methodologies in vastly different contexts. Some governments—such as those of Estonia and Bangladesh—were building on decade or more of experience refining already-advanced practices; others—such as the state of Colorado’s—were still getting ready to formally launch. Some had deep connections across their entire executive branch; others were tightly focused within a single agency.

Despite these differences, many key themes emerged throughout the convening. This paper contains reflections from the Summit. 

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Crisis Communications for COVID-19

Citation:

Leonard, Herman B. "Dutch", Arnold M. Howitt, and David Giles. 2020. “Crisis Communications for COVID-19”.

Abstract:

Herman "Dutch" Leonard, Arnold Howitt, and David Giles; April 2020

Communication with employees, customers, investors, constituents, and other stakeholders can contribute decisively to the successful navigation of a crisis.  But how should leaders think about what they are trying to say – and how to say it?

This policy brief lays out simple frameworks that can be used to formulate the messages that leaders can and should – indeed, must – convey to help their communities and organizations make their way forward as effectively as they reasonably can.

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Last updated on 04/28/2020

Crisis Management for Leaders Coping with COVID-19

Citation:

Leonard, Herman B. "Dutch", Arnold M. Howitt, and David W. Giles. 2020. “Crisis Management for Leaders Coping with COVID-19”.

Abstract:

Herman "Dutch" Leonard, Arnold Howitt, and David Giles; April 2020

In the face of the rapidly evolving coronavirus crisis that demands many urgent decisions but provides few clear-cut cues and requires tradeoffs among many critically important values, how can leaders and their advisers make effective decisions about literally life-and-death matters?  This policy brief contrasts the current “crisis” environment with the more familiar realm of “routine emergencies.” It argues that for crises, leaders need to adopt a more agile, highly adaptive, yet deliberate decision-making method that can move expeditiously to action, while retaining the capacity to iteratively re-examine tactics in light of decision impacts. This method can help the team take account of the multiple dimensions of the COVID-19 crisis and cope as well as possible with swiftly changing conditions.

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Last updated on 10/19/2020

Prioritizing Public Value in the Changing Mobility Landscape

Citation:

Goldsmith, Stephen, and Betsy Gardner. 2020. “Prioritizing Public Value in the Changing Mobility Landscape”.
Prioritizing Public Value in the Changing Mobility Landscape

Abstract:

Stephen Goldsmith and Betsy Gardner, January 2020

In this paper we will look at the values and goals cities affect with policies concerning connected mobility, and how to create a new framework that aligns with these objectives. First, we identify the transformative changes affecting cities and mobility. Second, we discuss in more detail the guiding values and goals that cities have around mobility with examples of these values in practice. Our next paper, Effectively Managing Connected Mobility Marketplaces, discusses the different regulatory approaches that cities can leverage to achieve these goals.

We recommend that cities identify various public values, such as Equity or Sustainability, and use these to shape their transit policy. Rather than segmenting the rapidly changing mobility space, cities should take advantage of the interconnectivity of issues like curb space management, air quality, and e-commerce delivery to guide public policy. Cities must establish a new system to meet the challenges and opportunities of this new landscape, one that is centered around common values, prioritizes resident needs, and is informed by community engagement.

In conclusion, cities must use specific public values lenses when planning and evaluating all the different facets of mobility. Transportation has entered a new phase, and we believe that cities should move forward with values- and community-driven policies that frame changing mobility as an opportunity to amend and improve previous transportation policies.

This paper is the first in the Mobility in the Connected City series.

Read the second paper "Effectively Managing Connected Mobility Marketplaces" 

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Last updated on 02/05/2020

Effectively Managing Connected Mobility Marketplaces

Citation:

Goldsmith, Stephen, and Mathew Leger. 2020. “Effectively Managing Connected Mobility Marketplaces”.
Effectively Managing Connected Mobility Marketplaces

Abstract:

Stephen Goldsmith and Matt Leger, February 2020

As new innovations in mobility have entered the marketplace, local government leaders have struggled to adapt their regulatory framework to adequately address new challenges or the needs of the consumers of these new services. The good news is that the technology driving this rapid change also provides the means for regulating it: real-time data. It is the responsibility of cities to establish rules and incentives that ensure proper behavior on the part of mobility providers while steering service delivery towards creating better public outcomes. Cities must use the levers at their disposal to ensure an equitable mobility marketplace and utilize real-time data sharing to enforce compliance. These include investing in and leveraging physical and digital infrastructure, regulating and licensing business conducted in public space, establishing and enforcing rules around public safety, rethinking zoning and land use planning to be transit-oriented, and regulating the digital realm to protect data integrity.

This paper is the second in the Mobility in the Connected City series. 

Read the first paper  "Prioritizing Public Value in the Changing Mobility Landscape"

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Last updated on 02/23/2021

Playbook: Government as Platform

Abstract:

Richard Pope, November 2019

Looking around the world, we can see a different approach to digital government. One of cross-government platforms that are beginning to break down organizational silos, save money and change the types of services that can be delivered to the public. This playbook is written for practitioners, from public sector product managers to chief digital officers, looking for approaches to implementing platforms in government. 

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Last updated on 01/24/2020

An Analysis of the Council of Arab Economic Unity’s Arab Digital Economy Strategy

Abstract:

Edited by David Eaves, October 2019

In this report, experts analyze the Council of Arab Economic Unity's comprehensive digital strategy for the Arab region. While some countries have individually launched digital economy roadmaps in recent years, the Arab Digital Economy Strategy offers a new opportunity to consider the benefits and challenges of digital cooperation across countries. Specifically, this report details areas of concern and explores some potential resolutions to these challenges.

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Last updated on 01/24/2020

A Fair and Feasible Formula for the Allocation of CARES Act COVID‐19 Relief Funds to American Indian and Alaska Native Tribal Governments

Abstract:

Randall K.Q. Akee, Eric C. Henson, Miriam R. Jorgensen, and Joseph P. Kalt; May 2020 

Title V of the CARES Act requires that the Act’s funds earmarked for tribal governments be released immediately and that they be used for actions taken to respond to the COVID‐19 pandemic. These may include costs incurred by tribal governments to respond directly to the crisis, such as medical or public health expenditures by tribal health departments. Eligible costs may also include burdens associated with what the U.S. Treasury Department calls “second‐order effects,” such as having to provide economic support to those suffering from employment or business interruptions due to pandemic‐driven business closures. Determining eligible costs is problematic.

Title V of the CARES Act instructs that the costs to be covered are those incurred between March 1, 2020 and December 30, 2020. Not only does this create the need for some means of approximating expenditures that are not yet incurred or known, but the Act’s emphasis on the rapid release of funds to tribes also makes it imperative that a fair and feasible formula be devised to allocate the funds across 574 tribes without imposing undue delay and costs on either the federal government or the tribes.

Recognizing the need for reasonable estimation of the burdens of the pandemic on tribes, the authors of this report propose an allocation formula that uses data‐ready drivers of those burdens.  Specifically, they propose a three‐part formula that puts 60% weight on each tribe’s population of enrolled citizens, 20% weight on each tribe’s total of tribal government and tribal enterprise employees, and 20% weight on each tribe’s background rate of coronavirus infections (as predicted by available, peer‐reviewed incidence models for Indian Country).

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Last updated on 06/01/2020

Replicating Urban Analytics Use Cases

Abstract:

Craig Campbell, January 2019

At a 2016 meeting of leading municipal analytics practitioners and experts at the Harvard Kennedy School, Johns Hopkins GovEx’s then-director of advanced analytics, Carter Hewgley, assessed the opportunities for analytics replication: “The good news is that problems and opportunities in U.S. cities are similar, meaning there is unending replication potential,” he said. The bad news was that lack of good protocols for use case discovery, challenges accessing and standardizing data, and uneven investment in data-literate human capital make analytics use cases difficult to generalize and import into different cities. At a time when the value of predictive analytics is widely recognized as a tool for better decision making and “chief data officer” is an increas- ingly common title in municipal government, cities still face the same challenges adopting analytical models into routine operations they have faced for decades.

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Reforming Mobility Management: Rethinking the Regulatory Framework

Abstract:

Stephen Goldsmith, January 2019

More people than ever live in cities, where the dominant mode of transportation continues to be single-occupant personal vehicles. This has created unprecedented burdens on city infrastructure and increased congestion on roads in urban centers. Increased congestion has resulted in greater greenhouse gas emissions, lower reliability of public transit systems, longer commutes, and an overall lower quality of living for citizens.

These challenges have created fertile ground for private-sector innovation within the mobility ecosystem. Thus far, the most significant private sector innovation in urban mobility has been ridesharing. Conventional wisdom attributes the birth of rideshare to the proliferation of smartphones and improvements in wireless connectivity and location data in cities. However, the ridesharing industry also relies on dependability and reliability of free public roads, which were a critical component in the development of the modern car-friendly city. Unfortunately, these same public roads lack the infrastructure to coordinate and interact with digital-first services as effectively as they coordinate the physical movement of people and goods.
 

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Last updated on 08/06/2020

Cooperative Procurement: Today’s Contracting Tool, Tomorrow’s Contracting Strategy

Abstract:

Scott Becker and Stephen Goldsmith, October 2018 

Increasingly, governments across the country are turning to cooperative procurement for greater value. Joining with other entities can significantly reduce administrative costs and leverage the benefits of economies of scale. In recent years, cooperatives have evolved to provide a wider variety of benefits to procurement officials and vendors, offering increasingly complex services adaptable to a growing participant pool. Expansion of offerings and targeted attention to best-in-class contracts have furthered their value proposition. This paper intends to provide insight into today’s cooperative procurement market, evaluate value propositions and challenges, and present strategies for success. 

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Valuing U.S. National Parks and Programs: America’s Best Investment

Valuing U.S. National Parks and Programs: America’s Best Investment

Abstract:

Linda J. Bilmes and John B. Loomis, Routledge, August 2019 

This book provides the first comprehensive economic valuation of US National Parks (including Monuments, Seashores, Lakeshores, Recreation Areas, Historic sites) and National Park Service (NPS) Programs.

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Last updated on 01/24/2020

Public Value: Deepening, Enriching, and Broadening the Theory and Practice

Citation:

Lindgreen, Adam, Nicole Koenig-Lewis, Martin Kitchener, John D. Brewer, Mark H. Moore, and Timo Meynhardt. 2019. Public Value: Deepening, Enriching, and Broadening the Theory and Practice. Routledge.
Public Value: Deepening, Enriching, and Broadening the Theory and Practice

Abstract:

Adam Lindgreen, Nicole Koenig-Lewis, Martin Kitchener, John D. Brewer, Mark H. Moore, and Timo Meynhardt, Routledge, 2019 

Over the last 10 years, the concept of value has emerged in both business and public life as part of an important process of measuring, benchmarking, and assuring the resources we invest and the outcomes we generate from our activities. In the context of public life, value is an important measure on the contribution to business and social good of activities for which strict financial measures are either inappropriate or fundamentally unsound.

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Last updated on 03/16/2020

A New City O/S: The Power of Open, Collaborative, and Distributed Governance

Citation:

Goldsmith, Stephen, and Neil Kleiman. 2017. A New City O/S: The Power of Open, Collaborative, and Distributed Governance. Brookings Institution Press.
A New City O/S: The Power of Open, Collaborative, and Distributed Governance

Abstract:

Stephen Goldsmith and Neil Kleiman, Brookings, November 2017

At a time when trust is dropping precipitously and American government at the national level has fallen into a state of long-term, partisan-based gridlock, local government can still be effective—indeed more effective and even more responsive to the needs of its citizens. Based on decades of direct experience and years studying successful models around the world, the authors of this intriguing book propose a new operating system (O/S) for cities. Former mayor and Harvard professor Stephen Goldsmith and New York University professor Neil Kleiman suggest building on the giant leaps that have been made in technology, social engagement, and big data.

Calling their approach “distributed governance,” Goldsmith and Kleiman offer a model that allows public officials to mobilize new resources, surface ideas from unconventional sources, and arm employees with the information they need to become pre-emptive problem solvers. This book highlights lessons from the many innovations taking place in today’s cities to show how a new O/S can create systemic transformation.

 

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Last updated on 10/18/2021

Public Health Preparedness: Case Studies in Policy and Management

Citation:

Howitt, Arnold M., Herman B. "Dutch" Leonard, and David W. Giles. 2017. Public Health Preparedness: Case Studies in Policy and Management. American Public Health Association.
Public Health Preparedness: Case Studies in Policy and Management

Abstract:

Arnold M. Howitt, Herman B. "Dutch" Leonard, and David W. Giles, American Public Health Association, February 2017

Containing 15 Harvard Kennedy School case studies on public health emergency preparedness and response, this book provides detailed accounts of a range of natural disasters, infectious diseases, and bio-terrorism. With chapters on Superstorm Sandy, the 2009 H1N1 pandemic, the 2001 anthrax attacks, and evacuations from Gulf Coast hurricanes, the book covers major areas in public health preparedness, portraying the varied and complex challenges the public health community faces when confronting disaster.

Publisher's Version

Last updated on 03/01/2020

Dealing with Dysfunction: Innovative Problem Solving in the Public Sector

Dealing with Dysfunction: Innovative Problem Solving in the Public Sector

Abstract:

Jorrit de Jong, Brookings Institution Press, 2016

How can we intervene in the systemic bureaucratic dysfunction that beleaguers the public sector? De Jong examines the roots of this dysfunction and presents a novel approach  to solving it. Drawing from academic literature on bureaucracy and problem solving in the public sector, and the clinical work of the Kafka Brigade — a social enterprise based in the Netherlands dedicated to diagnosing and remedying bureaucratic dysfunction in practice, this study reveals the shortcomings of conventional approaches to bureaucratic reform. The usual methods have failed to diagnose problems, distinguish symptoms, or identify root causes in a comprehensive or satisfactory way. They have also failed to engage clients, professionals, and midlevel managers in understanding and addressing the dysfunction that plagues them. This book offers conceptual frameworks, theoretical insights, and practical lessons for dealing with the problem. It sets a course for rigorous public problem solving to create governments that can be more effective, efficient, equitable, and responsive to social concerns.

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Last updated on 01/24/2020

Economics of the Public Sector

Citation:

Stiglitz, Joseph E, and Jay Rosengard. 2015. Economics of the Public Sector. W.W. Norton & Company.
Economics of the Public Sector

Abstract:

What should be the role of government in society? How should it design its programs? How should tax systems be designed to promote both efficiency and fairness? Nobel Laureate Joseph Stiglitz and new co-author Jay Rosengard use their first-hand policy-advising experience to address these key issues of public-sector economics in this modern and accessible Fourth Edition.
 

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The Responsive City: Engaging Communities Through Data-Smart Governance

The Responsive City: Engaging Communities Through Data-Smart Governance

Abstract:

Stephen Goldsmith and Susan Crawford, Wiley, 2014

The Responsive City is a compelling guide to civic engagement and governance in the digital age that will help municipal leaders link important breakthroughs in technology and data analytics with age-old lessons of small-group community input to create more agile, competitive, and economically resilient cities. The book is co-authored by Professor Stephen Goldsmith, director of Data-Smart City Solutions at Harvard Kennedy School, and Professor Susan Crawford, co-director of Harvard's Berkman Center for Internet and Society.

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Last updated on 01/26/2021

The Persistence of Innovation in Government

The Persistence of Innovation in Government

Abstract:

Sandford Borins, Brookings, 2014

In The Persistence of Innovation in Government, Sandford Borins maps the changing landscape of American public sector innovation in the twenty-first century, largely addressing three key questions: Who innovates? When, why, and how do they do it? What are the persistent obstacles and the proven methods for overcoming them? Probing both the process and the content of innovation in the public sector, Borins identifies major shifts and important continuities. His examination of public innovation combines several elements: his analysis of the Harvard Kennedy School's Innovations in American Government Awards program; significant new research on government performance; and a fresh look at the findings of his earlier, highly praised book Innovating with Integrity: How Local Heros Are Transforming American Government.

Recognizing Public Value

Citation:

Moore, Mark H. 2013. Recognizing Public Value. Harvard University Press.
Recognizing Public Value

Abstract:

Mark H. Moore, Harvard University Press, 2013

Mark H. Moore's now classic Creating Public Value offered advice to public managers about how to create public value. But that book left a key question unresolved: how could one recognize (in an accounting sense) when public value had been created? Here, Moore closes the gap by setting forth a philosophy of performance measurement that will help public managers name, observe, and sometimes count the value they produce, whether in education, public health, safety, crime prevention, housing, or other areas. Blending case studies with theory, he argues that private sector models built on customer satisfaction and the bottom line cannot be transferred to government agencies.

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Agents of Change: Strategy and Tactics for Social Innovation

Citation:

Cels, Sanderijn, Jorrit de Jong, and Frans Nauta. 2012. Agents of Change: Strategy and Tactics for Social Innovation. Brookings Institution Press.
Agents of Change: Strategy and Tactics for Social Innovation

Abstract:

Sanderijn Cels, Jorrit De Jong, Frans Nauta, Brookings Institution Press, 2012

Agents of Change describes imaginative, cross-boundary thinking and transformative change and explains exactly how innovators pull it off. While governments around the world struggle to maintain service levels amid fiscal crises, social innovators are improving social outcomes for citizens by changing the system from within. In Agents of Change, three cutting-edge thinkers and entrepreneurs present case studies of social innovation that have led to significant social change. Drawing on original empirical research in the United States, Canada, Japan, Germany, Denmark, and the Netherlands, they examine how ordinary people accomplished extraordinary results.

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Ports in a Storm: Public Management in a Turbulent World

Ports in a Storm: Public Management in a Turbulent World

Abstract:

The 9-11 attacks resulted in heightened security efforts in American ports. Any attack on a seaport would be far more disruptive to the day-to-day functions of the country than even airport closures. Much of the responsibility for increasing port security fell to the U.S. Coast Guard. In this book, Harvard Kennedy School authors focus diverse conceptual lenses on a single high-stakes management challenge – enhancing U.S. port security. The aims are two: to understand how that complex challenge might plausibly be met and to explore the similarities, differences, and complementarities of their alternative approaches to public management.

Last updated on 01/30/2020

The Power of Social Innovation: How Civic Entrepreneurs Ignite Community Networks for Good

Citation:

Goldsmith, Stephen, Gigi Georges, and Tim Glynn Burke. 2010. The Power of Social Innovation: How Civic Entrepreneurs Ignite Community Networks for Good. Jossey-Bass.

Abstract:

Stephen Goldsmith with Gigi Georges and Tim Glynn Burke, Jossey-Bass, 2010

Civic leaders across the U.S. and throughout the world are discovering creative ways to overcome the obstacles that seal the doors of opportunity for too many. These inspiring individuals believe that within our communities lies the entrepreneurial spirit, compassion, and resources to make progress in such critical areas as education, housing, and economic self-reliance. Real progress requires that we take bold action and leverage our strengths for the greater good. The Power of Social Innovation offers public officials, social entrepreneurs, philanthropists, and individual citizens the insights and skills to create healthier communities and promote innovative solutions to public and social problems. This seminal work is based on Stephen Goldsmith's decades of experience, extensive ongoing research, and interviews with 100+ top leaders from a wide variety of sectors. Goldsmith shows that everyday citizens can themselves produce extraordinary social change.

Read the first chapter of the book 

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Last updated on 04/13/2021

From the Ground Up: Improving Government Performance with Independent Monitoring Organizations

Citation:

Griffin, Charles, Stephen Kosack, and Courtney Tolmie. 2010. From the Ground Up: Improving Government Performance with Independent Monitoring Organizations. Brookings Institution Press.
From the Ground Up: Improving Government Performance with Independent Monitoring Organizations

Abstract:

Charles Griffin, Stephen Kosack, and Courtney Tolmie, Brookings Institution Press, 2010

From the Ground Up proposes that the international community's efforts to improve public expenditure and budget execution decisions would be more effective if done in collaboration with local independent monitoring organizations. The authors track the work of 16 independent monitoring organizations from across the developing world, demonstrating how these relatively small groups of local researchers produce both thoughtful analysis and workable solutions. They achieve these results because their vantage point allows them to more effectively discern problems with governance and to communicate with their fellow citizens about the ideals and methods of good governance.

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The State of Access: Success and Failure of Democracies to Create Equal Opportunities

Citation:

de Jong, Jorrit, and Gowher Rizvi, ed. 2009. The State of Access: Success and Failure of Democracies to Create Equal Opportunities. Brookings Institution Press.

Abstract:

Jorrit de Jong and Gowher Rizvi, editors, Brookings Institution Press, 2009

The State of Access documents a worrisome gap between principles and practice in democratic governance. This book is a comparative, cross-disciplinary exploration of the ways in which democratic institutions fail or succeed to create the equal opportunities that they have promised to deliver to the people they serve. In theory, rules and regulations may formally guarantee access to democratic processes, public services, and justice. But reality routinely disappoints, for a number of reasons – exclusionary policymaking, insufficient attention to minorities, underfunded institutions, inflexible bureaucracies. The State of Access helps close the gap between the potential and performance in democratic governance.

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Managing Crises: Responses to Large-Scale Emergencies

Citation:

Howitt, Arnold M., Herman B. Leonard, and David W. Giles, ed. 2009. Managing Crises: Responses to Large-Scale Emergencies. CQ Press.
Managing Crises: Responses to Large-Scale Emergencies

Abstract:

Arnold M. Howitt, Herman B. Leonard, and David W. Giles, editors, CQ Press, 2009

From floods to fires, tornadoes to terrorist attacks, governments must respond to a variety of crises and meet reasonable standards of performance. What accounts for governments’ effective responses to unfolding disasters? How should they organize and plan for significant emergencies? With twelve adapted Kennedy School cases, readers experience first-hand a series of large-scale emergencies and come away with a clear sense of the different types of disaster situations governments confront, with each type requiring different planning, resourcing, skill-building, leadership, and execution.

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Unlocking the Power of Networks: Keys to High Performance Government

Citation:

Goldsmith, Stephen, and Donald Kettl, ed. 2009. Unlocking the Power of Networks: Keys to High Performance Government. Brookings Institution Press.
Unlocking the Power of Networks: Keys to High Performance Government

Abstract:

Stephen Goldsmith and Donald Kettl, editors, Brookings Institution Press, 2009

The era of textbook top-down, stovepiped public management in America is over, and the traditional dichotomy between public ownership and privatization is an outdated notion. Public executives have shifted their focus from managing workers and directly providing services to orchestrating networks of public, private, and nonprofit organizations to deliver those services. In this new book, Stephen Goldsmith and Donald Kettl head a stellar cast of policy practitioners and scholars exploring the potential, strategies, and best practices of high-performance networks while identifying next-generation issues in public sector network management. Unlocking the Power of Networks employs sector-specific analyses to reveal how networked governance achieves previously unthinkable policy goals.

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The Public Innovator's Playbook: Nurturing Bold Ideas in Government

Citation:

Eggers, William D., and Shalabh Kumar Singh. 2009. The Public Innovator's Playbook: Nurturing Bold Ideas in Government. Deloitte Research.
The Public Innovator's Playbook: Nurturing Bold Ideas in Government

Abstract:

William D. Eggers & Shalabh Kumar Singh, Deloitte Research, 2009

The Public Innovator’s Playbook, published by Deloitte Research in the U.S. with the Harvard Kennedy School’s Ash Center, describes how governments have the opportunity to help improve the economic environment, create jobs, and more efficiently manage costs. According to the book, governments currently innovate. Moreover, some creative approaches in the private sector come from the public sector. However, few governments take an integrated view of the process or treat it as a discipline – which includes methodical processes, reward systems, and a mission linked to the process and organizational structure.

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Last updated on 02/05/2020

The Right to Vote: The Contested History of Democracy in the United States

The Right to Vote: The Contested History of Democracy in the United States

Abstract:

Alexander Keyssar, Basic Books, 2009

Most Americans take for granted their right to vote, whether they choose to exercise it or not. But the history of suffrage in the U.S. is, in fact, the story of a struggle to achieve this right by our society's marginalized groups. In The Right to Vote, HKS historian Alexander Keyssar explores the evolution of suffrage over the course of the nation's history. Examining the many features of the history of the right to vote in the U.S. – class, ethnicity, race, gender, religion, and age – the book explores the conditions under which American democracy has expanded and contracted over the years. Keyssar presents convincing evidence that the history of the right to vote has not been one of a steady history of expansion and increasing inclusion, noting that voting rights contracted substantially in the U.S. between 1850 and 1920. Keyssar also presents a controversial thesis: that the primary factor promoting the expansion of the suffrage has been war and the primary factors promoting contraction or delaying expansion have been class tension and class conflict. The June 2009 edition includes a new chapter on voting rights since 2000.

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If We Can Put a Man on the Moon: Getting Big Things Done in Government

Citation:

Eggers, William, and John O'Leary. 2009. If We Can Put a Man on the Moon: Getting Big Things Done in Government. Harvard Business School Press.

Abstract:

William Eggers and John O'Leary, Harvard Business School Press, 2009

The American people are frustrated with their government — dismayed by a series of high-profile failures (Iraq, Katrina, the financial meltdown). Yet our nation has a proud history of great achievements: victory in World War II, our national highway system, welfare reform, the moon landing. The truth is, we need more successes like these to reclaim government's legacy of competence. In the book If We Can Put a Man on the Moon, William Eggers and John O'Leary explain how to do it. The key? Understand — and avoid — the common pitfalls that trip up public-sector leaders during the journey from idea to results.

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The Right to Vote: The Contested History of Democracy in the United States

The Right to Vote: The Contested History of Democracy in the United States

Abstract:

Alexander Keyssar, Basic Books, 2009

Most Americans take for granted their right to vote, whether they choose to exercise it or not. But the history of suffrage in the U.S. is, in fact, the story of a struggle to achieve this right by our society's marginalized groups. In The Right to Vote, HKS historian Alexander Keyssar explores the evolution of suffrage over the course of the nation's history. Examining the many features of the history of the right to vote in the U.S.—class, ethnicity, race, gender, religion, and age—the book explores the conditions under which American democracy has expanded and contracted over the years. Keyssar presents convincing evidence that the history of the right to vote has not been one of a steady history of expansion and increasing inclusion, noting that voting rights contracted substantially in the U.S. between 1850 and 1920. Keyssar also presents a controversial thesis: that the primary factor promoting the expansion of the suffrage has been war and the primary factors promoting contraction or delaying expansion have been class tension and class conflict. The June 2009 edition includes a new chapter on voting rights since 2000.

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Improving the Local Landscape for Innovation Part 3: Assessment and Implementation

Abstract:

Gigi Georges, Tim Glynn-Burke, and Andrea McGrath, June 2013. 

This paper is the third in a miniseries that explores emerging strategies to strengthen the civic, institutional, and political building blocks that are critical to developing novel solutions to public problems — what the authors call the “innovation landscape.” The miniseries builds on past research addressing social innovation and on The Power of Social Innovation (2010) by HKS Professor Stephen Goldsmith.

In this paper the authors focus on implementation of their framework’s strategies, primarily through the introduction of a unique assessment tool that includes key objectives and suggested indicators for each component of the framework. This final paper also includes a brief case study on New York City’s Center for Economic Opportunity, an award-winning government innovation team, to demonstrate and test the validity of the assessment tool and framework. The paper addresses some likely challenges to implementation and concludes with an invitation to readers to help further refine the framework and to launch a conversation among cities that will help improve their local landscapes for innovation.

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Last updated on 10/28/2021

Improving the Local Landscape for Innovation Part 1: Mechanics, Partners, and Clusters

Abstract:

Gigi Georges, Tim Glynn-Burke, and Andrea McGrath, June 2013 

This paper is the first in a miniseries that explores emerging strategies to strengthen the civic, institutional, and political building blocks that are critical to developing novel solutions to public problems — what the authors call the “innovation landscape.” The miniseries builds on past research addressing social innovation and on The Power of Social Innovation (2010) by HKS Professor Stephen Goldsmith.

In this first paper, the authors introduce readers to the nature of the work by highlighting current efforts to drive innovation in Boston, Denver, and New York City. They also orient the miniseries within the robust discourse on government innovation.

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Last updated on 10/22/2021

Improving the Local Landscape for Innovation Part 2: Framework for an Innovative Jurisdiction

Abstract:

Gigi Georges, Tim Glynn-Burke, and Andrea McGrath, June 2013 

This paper is the second in a miniseries that explores emerging strategies to strengthen the civic, institutional, and political building blocks that are critical to developing novel solutions to public problems — what the authors call the “innovation landscape.” The miniseries builds on past research addressing social innovation and on The Power of Social Innovation (2010) by HKS Professor Stephen Goldsmith.

In this second paper, the authors introduce a framework for driving local innovation, which includes a set of strategies and practices developed from the Ash Center’s recent work on social innovation, new first-person accounts, in-depth interviews, practitioner surveys, and relevant literature. The authors explore the roots and composition of the core strategies within their framework and provide evidence of its relevance and utility.

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Last updated on 10/28/2021

Innovation as Narrative

Sandford Borins, February 2010 

This paper begins by outlining a number of key narratological concepts, such as the distinction between narrative – the events represented – and one or more narrators' presentations of the events, implied author and implied reader, and structural analysis of narrative genres. It then applies these concepts to the three narrations of the 31 finalists of the 2008 and 2009 Innovations in American Government Awards. The paper concludes with suggestions for how public management scholars could incorporate narratological insights into their analysis, how innovation awards could ask applicants to develop more explicit narratives, and how innovators could make more effective use of narrative in communicating their achievements.

Leading Civic Engagement: Three Cases

Citation:

Husock, Howard, Inessa Lurye, Gaylen Moore, Archon Fung, and Jorrit de Jong. 2020. “Leading Civic Engagement: Three Cases”.

Abstract:

Howard Husock, Inessa Lurye, Gaylen Moore, Archon Fung, and Jorrit de Jong; July 2020 

These three short cases are stories of city officials leading civic engagement and public participation in pursuit of public goals. From a variety of different positions in city government, the protagonists in each case departed from typical bureaucratic processes to reach out directly to the public, using unexpected methods to solicit input, raise awareness, and effect behavioral change in their communities. In the first case, the new director of the Seattle Solid Waste Utility, Diana Gale, implemented sweeping changes to the City’s solid waste collection practices. To secure compliance with new rules and regulations and tolerance for inevitable stumbles along the way, she developed a public relations capacity, became the public face of her agency, and embraced an ethos of humility and accountability. In the second case, Antanas Mockus, the eccentric mayor of Bogotá, sought to improve public safety—focusing particularly on the unregulated and lethal use of fireworks around the Christmas holiday. He tried at first to effect change through persuasion, offering citizens alternatives to fireworks and engaging vendors in the effort to reduce fireworks-related injuries and deaths. When a child suffered severe burns, however, Mockus followed through on a threat to ban firework sales and use in the City. In the third case, David Boesch, city manager of Menlo Park, California, decided to engage residents in setting priorities around cost reduction as a major budget shortfall loomed for the coming fiscal year. He hired a local firm to plan and execute a comprehensive participatory budgeting process. In a city with a sharp divide between haves and have-nots, Boesch and his partners had to take special care to ensure that everyone’s interests were heard and represented in budgetary decision-making.

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Last updated on 01/11/2021

Growing Pains: How A Dutch Cross-agency Team Took On Illegal Marijuana Production In Residential Areas

Citation:

de Jong, Jorrit, Sanderijn Cels, Martijn Groenleer, and Eric Weinberger. 2020. “Growing Pains: How A Dutch Cross-agency Team Took On Illegal Marijuana Production In Residential Areas”.

Abstract:

Sanderijn Cels, Jorrit de Jong, Marijn Groenleer, and Erica Weinberger; July 2020 

In June 2015, a task force convened in the Netherlands to consider cross-sectoral approaches to fighting organized crime in the south of the country, particularly in the homegrown marijuana industry. From that larger group, five professional managers and officials were tasked with devising an approach to target and break up criminal drug gangs that paid or coerced residents in beleaguered neighborhoods to grow pot in back rooms or attics; activities which put a huge strain on the power supply and greatly increased the risk of fire.

The five men did not know each other and came from different organizations or professional backgrounds with their own training and ideas: the police, the regional utility company, the national tax bureau, the mayor’s office in nearby Breda, and the public prosecutor’s office. A policeman would not see the problem, or the solution, in the same way as a utility company manager. How would the five manage to work together—not just devise an approach, but return to their organizations and convince their bosses and colleagues this could work? Not all of the team were based in the City of Breda, but Breda, under the auspices of Mayor Paul Depla, would serve as the first trial ground to identify a neighborhood and carry out an operation to see if the new cross-sectoral approach could work.

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Last updated on 01/11/2021

Design Decisions for Cross-Sector Collaboration: Mini-Case Modules

Citation:

Rivkin, Jan, Susie Ma, and Michael Norris. 2020. “Design Decisions for Cross-Sector Collaboration: Mini-Case Modules”.

Abstract:

Jan Rivkin, Susie Ma, and Michael Norris; June 2020

These five short cases aim to help city leaders explore whether working with sectors outside their own government organizations is the right path forward, and how to be effective if/when they choose to engage in cross-sector collaboration. The cases especially highlight key design decisions that every cross-sector collaboration must make, to help students reflect on design decisions of their own collaborative efforts.

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Last updated on 01/11/2021

The “Bilbao Effect” The Collaborative Architecture that Powered Bilbao’s Urban Revival

Abstract:

Fernando Monge, Jorrit de Jong, and Linda Bilmes; June 2020  

In 2018, Bilbao was presented with the Best European City award, adding the prize to a long list the Spanish city had collected since the mid-2000s. The success was often attributed to the Guggenheim museum, giving name to the "Guggenheim effect." This was based on a fairly shallow assessment of the City's transformation. In fact, the building blocks of Bilbao's transformation are to be found in the collaborative efforts established by government entities during the 1990s, in the context of a deep economic, political, and social crisis.

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Last updated on 01/11/2021

Driving Change in São Paulo

Citation:

de Jong, Jorrit, Carlos Paiva, Carin-Isabel Knoop, and Rawi Abdelal. 2020. “Driving Change in São Paulo”.

Abstract:

Jorrit de Jong, Carlos Paiva, Carin-Isabel Knoop, and Rawi Abdelal; May 2020 

In 2016, after many months of negotiation, the City of São Paulo approved a new ordinance regulating Transportation Network Companies (TNC). The new regulation allowed citizens to take advantage of innovative services and it enabled city leaders to manage the fleet with significant savings as well as unprecedented transparency and data. São Paulo, the first Brazilian city to adopt this model, faced internal responses ranging from vehement opposition to overwhelming support.

The case chronicles the road to implementation, including lessons learned from the TNC ordinance process and the previous pilots. It examines the efforts of key players—including Administration Secretary Paulo Spencer Uebel—to fulfill Mayor João Doria’s public commitment to fix the transportation model, consider public opinion, and minimize disruption during Doria’s first year in office. The case also explores strategies for implementing innovative practices in government as well as dealing with resistance to change in organizations, especially in the public sector.

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Last updated on 01/11/2021

The “Garbage Lady” Cleans Up Kampala: Turning Quick Wins Into Lasting Change

Abstract:

Lisa Cox and Jorrit de Jong, May 2020 

In 2011, at the newly formed Kampala Capital City Authority (KCCA), Judith Tumusiime, an impassioned technocrat who prided herself on operating outside of politics, was charged with transforming a “filthy city” to a clean, habitable, and healthy one. Early in her tenure, she was able to vastly improve Kampala’s solid waste management (SWM) system by creating efficiencies, increasing accountability, and bringing her technical know-how to a team that held little expertise. But by 2015, after several years of strong momentum, Tumusiime felt that her progress was stalling, and she faced political challenges around creating a sustainable SWM system.

More specifically, her team was grossly overextended and needed to assign some of its SWM responsibilities to private contractors through an innovative public-private partnership (PPP). To ensure that the PPP was viable, Tumusiime strongly believed that all residents, no matter their income, needed to pay fees for garbage collection. However, the federal and local elections were approaching in February 2016, and politicians had told their constituents that they would not allow garbage collection fees, leaving Tumusiime with little support for her long-term vision. She was faced with a challenge: she could either dive into a political world that she had never wanted anything to do with to see if she could achieve radical change, or she could continue to make tweaks that might achieve short-term, small improvements at a slow—and even halting—pace.

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Last updated on 01/11/2021

In the Green: Negotiating Rail Expansion in Somerville, MA

Citation:

Norgaard, Stefan, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian. 2020. “In the Green: Negotiating Rail Expansion in Somerville, MA”.

Abstract:

Stegan Norgaard, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian; May 2020

Successful litigation against the Commonwealth of Massachusetts made an original, legal, and moral case for building alternative transportation in Somerville: the Green Line Extension (GLX). Having campaigned on extending the Green Line—first as alderman, then as mayor—Joe Curtatone took office as mayor in 2005. His first victory was creating a MBTA “T” stop for the Orange Line at Assembly Station. Working with the same coalition of nonprofits, he pursued a participatory visioning process (“SomerVision”) that brought together over sixty organizations from different sectors in Somerville, that had a common vision for the GLX. Curtatone overcame hiccups surrounding industrial parcels and successfully kept the project eligible for a federal NewStarts grant; using an economic-development narrative, he acquired the problematic parcels through eminent domain. By 2014-2015, though, the project was running over budget and it was uncertain whether the Commonwealth would support the GLX.

Curtatone negotiated with the State of Massachusetts and agreed on simplifications to the original GLX, including a shorter route that would no longer directly benefit neighboring regional communities. He also negotiated project funding by the Cities of Cambridge and Somerville and the Boston Regional Metropolitan Planning Organization board (BRMPO). But then, the Commonwealth announced a shortfall of roughly $200 million, that Curtatone resolved through an agreement: Somerville paid $50M, Cambridge $25M, and the BRMPO diverted funding for the rest. The narrower GLX project was approved and construction began in May 2018. This case is designed as the capstone case in a series of negotiation cases developed by the Bloomberg Harvard City Leadership Initiative. 

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Last updated on 01/11/2021

Making a Statement: Mayor Libby Schaaf and the Sanctuary City of Oakland, CA

Citation:

Moore, Gaylen, Chistopher Robichaud, Jorrit de Jong, and Anna Burgess. 2020. “Making a Statement: Mayor Libby Schaaf and the Sanctuary City of Oakland, CA”.

Abstract:

Gaylen Moore, Christopher Robichaud, Jorrit de Jong, and Anna Burgess; May 2020 

In February 2018, Oakland Mayor Libby Schaaf learned through unofficial sources that Immigration and Customs Enforcement (ICE) was planning to arrest a large number of undocumented immigrants in her City. Oakland had been a “sanctuary city” since 1986, and more than one in ten residents were undocumented. Mayor Schaaf believed that the ICE action was the Trump administration’s political retaliation against California’s sanctuary cities. She feared that law-abiding immigrants in her community—who she saw as scapegoats for a broken federal immigration system—would be swept up in the raid and subject to deportation. Faced with very little time and potentially significant legal implications, Mayor Schaaf had to decide whether and how to alert the community to a threat she took to be highly credible.

The case is designed to help mayors, city leaders, and other public executives think through adaptive leadership challenges with highly sensitive moral dimensions.

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Last updated on 09/15/2020

Beyond the Table: Infrastructure Development in Kampala, Uganda

Citation:

Vo, Hung, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian. 2020. “Beyond the Table: Infrastructure Development in Kampala, Uganda”.

Abstract:

Hung Vo, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian; May 2020 

Uganda’s development relied heavily on the economic growth and management of its capital city, Kampala. The World Bank had been active in Uganda’s urban sector since the 1980s and, in 2007, awarded Kampala a $33 million loan for institutional reforms and infrastructure development. Yet by the project’s 2010 deadline, only 30 percent of the project had been completed. Given the delays and its skepticism of a new, inexperienced administration, the World Bank threatened to withdraw funding. Nonetheless, Judith Tumusiime—first as a technical consultant and then as deputy executive director of the newly established Kampala Capital City Authority (KCCA)—managed to turn the project around within two years, an almost miraculous transformation. Beyond revitalizing and completing the project’s first phase, could Tumusiime convince the World Bank to invest even more in the second phase?

The case explores Tumusiime’s work to regain trust with the World Bank and persuade it to not only fund a second phase of the project, but to also significantly increase its funding commitment to the City. It examines how Tumusiime navigated her team, the World Bank, other local officials, and national level government actors. Moreover, it unpacks the misguided notion that a negotiation is a solely interpersonal activity that occurs at the table; a broader understanding of process—specifically scope and sequence—can impact the outcome (1). Drawing from David Lax and James Sebenius’ 3-D negotiation framework, the case demonstrates how Tumusiime built a strategy to effectively sequence actions in her negotiation with the World Bank. Her strategic vision and interpersonal strengths enabled her to make dynamic setup moves, improving her ability to negotiate at the table and craft a better deal with the World Bank.

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Last updated on 01/11/2021

“Pressing the Right Buttons” Jennifer Musisi for New City Leadership

Abstract:

Jorrit de Jong and Eric Weinberger, May 2020 

Jennifer Musisi, a career civil servant most recently with the Uganda Revenue Authority, was appointed by President Museveni as executive director (equivalent to city manager) of a new governing body for Uganda’s capital, the Kampala Capital City Authority (KCCA). Previously, power in Kampala had been held by an elected body, the Kampala City Council (KCC), dominated by opposition politicians and notorious for corruption, poor service delivery, and inadequate tax and revenue collections.

As head of the new KCCA, a quasi-corporate authority now under central government, Musisi’s job was to change all that, and quickly, by fighting corruption and modernizing (thereby increasing) tax and revenue collections. She had to decide which municipal fees or taxes would recoup the greatest revenues for maximum impact on her city-improvement agenda of better roads, clean streets and markets, modern drainage and lighting, and more.

Musisi also needed to find ways to remove longtime private tax agents who took, supposedly, a 10 percent commission from the City but in fact withheld most of their receipts, sometimes extorting additional, unofficial sums. Property tax—as it is throughout the world—was potentially Kampala’s most lucrative revenue source, but here Musisi’s effectiveness was limited without national legislative reform and government support. Thus, her most difficult challenges were transit and trading, on which thousands of poor people depended for their living while being vulnerable to private revenue collectors, middlemen, local bosses, and law enforcement.

The case describes an extremely difficult, often dangerous situation in a fast-growing African capital, and an individual determined to make Kampala the model city she believed it could be. How did Musisi even begin? What was the best strategy for raising own-source revenue (OSR), and how did she navigate the politics—both ways, that is, with opposition city politicians who cultivate the poor, but also with President Museveni and his governing NRM (National Resistance Movement)? In recent history African capitals have depended on central government transfers for their budgets and that is still the case in Kampala. But with little expectation that she would get more support from central government, Musisi had to collect enormous sums for the improvements needed for Kampala’s infrastructure, health services, schools, and general business environment.

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Last updated on 01/11/2021

The Queen City’s Collective and Compassionate Approach: Fighting Opioids and Homelessness in the Granite State

Citation:

Roberts, Brady, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian. 2020. “The Queen City’s Collective and Compassionate Approach: Fighting Opioids and Homelessness in the Granite State”.

Abstract:

Brady Roberts, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian; May 2020 

Elected at the height of the opioid epidemic, Mayor Joyce Craig came to represent the City of Manchester, New Hampshire as it grappled with the dual tragedies of substance abuse and chronic homelessness. An idealist in a state that valued personal responsibility and financial restraint, Craig had successfully expanded her City’s services to those seeking treatment for opioid use disorder and shelter. But these were hard-fought victories at every stage, and there was still work to be done. With just a few months remaining in her first two-year term, the mayor found herself on the eve of another difficult negotiation. She had recently established a diverse Task Force on Homelessness and set her sights on permanently solving Manchester’s homelessness and opioid crises. Next, Craig had to convince her counterparts at the state and local level to dedicate equitable funding to solving these intractable, moral challenges. (See Teaching Case Appendix 1 for a timeline of events in the case.)

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Last updated on 01/11/2021

Shanties in the Skyline: Addressing Unauthorized Building Works in Hong Kong

Citation:

de Jong, Jorrit, Gaylen Moore, and Howard Husock. 2020. “Shanties in the Skyline: Addressing Unauthorized Building Works in Hong Kong”.

Abstract:

Howard Husock, Gaylen Moore, and Jorrit de Jong, May 2020 

Throughout the 1980s and 1990s, high atop a great many of the older, concrete-block buildings in lower-income areas of central Hong Kong and the neighborhoods of the Kowloon peninsula, informal metal-framed wooden structures housed thousands of families in austere, inexpensive quarters. These rooftop dwellings created a sort of shantytown in the air and, though built illegally, were nonetheless bought, sold, and rented on the open market. These structures were just one example of the larger phenomenon of so-called unauthorized building works (UBWs) in Hong Kong. These included balconies added to windows—sometimes used for beds—as well as hundreds of thousands of storefront street signs and canopy extensions on buildings in commercial districts, used to create rental space below for stores and restaurants on the ground floor. By 1999, the total number of UBWs was estimated at 800,000. By one assessment, if authorities continued enforcing the laws in the manner they had been, it would take more than 130 years to remove all such structures—assuming that new ones were not built in their place.

This case raises questions about how to respond effectively to a complex problem that has arisen as a solution to other problems.

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Last updated on 01/11/2021

“You Have One Hundred Days”: Accelerating Government Performance in the UAE

Abstract:

Fernando Monge, Jorrit de Jong, and Warren Dent; May 2020 

In the fall of 2016, the state government of the United Arab Emirates decided to take a new approach to spur floundering projects toward faster results.

Frustrated with slow progress on key issues like public health and traffic safety, the state launched a new program to accelerate change and enhance performance across government agencies. The innovative program, called Government Accelerators, ran 100-day challenges—intense periods of action where “acceleration” teams of frontline staff worked across agency boundaries to tackle pressing problems. This case illustrates how three teams were chosen to participate in the program, and how, in the 100-day timeframe, they worked toward clear and ambitious goals that would impact citizens’ lives.

The case aims to raise discussion about different types of public sector innovation, to explain the approach and methodology of the Government Accelerators, and to analyze the conditions under which a similar tool might work in other cities.

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Last updated on 01/11/2021

Fortaleza: Keeping An Electoral Promise

Citation:

Knoop, Carin-Isabel, Carlos Paiva, Jorrit de Jong, and Rawi Abdelal. 2020. “Fortaleza: Keeping An Electoral Promise”.

Abstract:

Carin-Isabel Knoop, Carlos Paiva, Jorrit de Jong, and Rawi Abdelal; May 2020 

During his re-election campaign in 2016, Mayor Roberto Cláudio faced recurring complaints from voters concerning the availability of essential medicines at their health clinics. Limited access to medicine frustrated patients and health care providers, raised the cost of treating chronic conditions, and increased the risk of infectious diseases. It also placed the City in violation of Brazil’s constitution that guaranteed access to essential medicines to patients of the public health system, most of whom were low income. In Cláudio’s first term, Fortaleza’s public health network went through significant advances, renovating the majority of its health clinics and improving access to medical personnel. The team’s considerable progress nonetheless fell short of a comprehensive solution for the lack of access to medicine. This became one of Cláudio’s main campaign promises, and a priority for his second term. The case chronicles how he approached a persistent problem, changed tactics and teams, and pushed for the necessary improvements and innovations to fulfill his promise.

The case raises questions around how to deliver on a campaign promise when your organization seems to have hit a ceiling in performance improvement: When do you push harder for better execution and advancement of current systems? When do you invest in something new to achieve optimal performance? What is the role of mayoral leadership in ensuring that goals are achieved?

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Last updated on 01/11/2021

In the Weeds: Securing a Grass-Mowing Contract in Stockton, CA

Citation:

Norgaard, Stefan, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian. 2020. “In the Weeds: Securing a Grass-Mowing Contract in Stockton, CA”.

Abstract:

Stegan Norgaard, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian; May 2020

Kurt Wilson, the City Manager of Stockton, CA, joined the city government ten months after the City declared bankruptcy. After successfully steering Stockton out of bankruptcy, Wilson committed to implementing a set of permanent financial control measures to ensure that the City remained fiscally solvent well into the future. He had an extensive background in both the private and nonprofit sectors and had served as city manager in four other California cities.

Stockton’s Long-Range Financial Plan (L-RFP) indicated that the City could spend, at most, approximately $1.3M in 2019 fiscal year (FY19) on a contract to mow grass on city medians. The City had spent $1.2M the previous year. Wilson believed shortages of tradespeople in the Bay Area—caused in part by demand for construction after California wildfires—would affect price points. At worst, he thought he could justify spending $1.6M on the contract. Wilson cared about the fiscal health of Stockton, but he also wanted to ensure high-quality public services.

When the City issued its RFP, bids started at $2.26M, well above what Stockton could afford. After considering his options, Wilson issued a new RFP that included a lower “base” scope of services with modular components that the City could accept or decline depending on cost. Stockton ended up spending $1.91M for a year of service, but even as costs increased, tall grasses remained on city medians. Wilson wondered whether there might have been a better way for the City to have anticipated the higher prices.

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Last updated on 01/11/2021

You Get What You Pay for: Reforming Procurement in Naperville, Illinois

Citation:

Norgaard, Stefan, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian. 2020. “You Get What You Pay for: Reforming Procurement in Naperville, Illinois”.

Abstract:

Stegan Norgaard, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian; May 2020

Naperville, Illinois is a suburb of approximately 150,000 people in the Chicago metropolitan area. Traditionally, the City focused on price for all procurement negotiations, but it often had few vendors applying for key contracts and struggled to negotiate on both price and quality.

Naperville’s original procurement process was called Quality-Adjusted Cost (QAC). This process sought to simplify a myriad of concerns and variables (including price, quality, timeline, and scope, among others) into a single metric, so that the City could easily and objectively evaluate bids. Although QAC attempted to incorporate quality into the evaluation, there were instances when it seemed the best vendor was not selected.

In an effort to improve the quality of City services, Naperville adopted a new procurement approach called “Cost as a Component.” This revamped process allowed the City to negotiate with vendors on more than just price for technology upgrades and aimed to ensure long-term partnerships with relevant firms, creating value for both vendors and the City. This case illustrates the trade-offs between QAC and “Cost as a Component” for Naperville and prompts participants to apply negotiation concepts to the broader process of city procurement.

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Last updated on 01/11/2021

Many Ways to Get There: Securing Public Investments in Richmond, VA

Citation:

Vo, Hung, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian. 2020. “Many Ways to Get There: Securing Public Investments in Richmond, VA”.

Abstract:

Hung Vo, Elizabeth Patton, Monica Giannone, Brian Mandell, Jorrit de Jong, and Guhan Subramanian; May 2020 

The City of Richmond elected Levar Stoney as its youngest mayor in 2016. Mayor Stoney campaigned for better-funded public schools, government accountability, and crime prevention. One of the mayor’s main responsibilities was to propose biannual budgets to a nine-member city council, which could approve the budget as proposed or pass it with amendments. This case illustrates Stoney’s efforts to increase Richmond’s real estate tax from $1.20 to $1.29 per $100 of assessed value. This tax increase was quickly rejected by a majority of city council members. Disagreements climaxed when the mayor’s administration walked out of a city council budget hearing, prompting council members to respond by voting to pursue legal action against Stoney.

This case focuses on how positional bargaining prevents creative deal-making when negotiators fail to understand the interests of other parties. By exploring Stoney’s relationship with city council, the case emphasizes the downsides of positional bargaining and the opportunities for better outcomes with an interest-based approach to negotiation. This case also introduces the four negotiation concepts of interests, options, criteria, and alternatives, and examines their relevance to city-level negotiations.

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Last updated on 01/11/2021

1904.0 Taking a Therapeutic Approach to Juvenile Offenders: The “Missouri Model”

Abstract:

Division of Youth Services: Missouri – 2008 Innovations Winner

In the early 1970s, the Missouri Division of Youth Services (DYS) took its first steps toward radically changing the way it dealt with youthful offenders remanded to its custody. For years, like most states, it had incarcerated juveniles convicted of felony or misdemeanor offenses in large quasi-penal facilities called “training schools.” Instead, DYS began establishing smaller “cottage-style” residential programs that emphasized rehabilitation over punishment and applied a therapeutic approach to its troubled young charges. Over the next three decades, DYS expanded this approach to encompass its entire juvenile offender population. By the mid-2000s, the “Missouri model,” as it became known, was perhaps the most admired – and, many considered, most effective – juvenile corrections system in the U.S.

This case describes the Missouri model – including the population it serves, the educational and therapeutic programs it offers, and the frontline staff of “youth specialists” it employs to work closely with young offenders. The case also provides an overview of Missouri’s impressively low recidivism figures and a brief discussion of the complexities of comparing such figures among states. It concludes with a discussion of the challenges the Missouri DYS has faced in sustaining its highly regarded, but demanding, approach over many years. The case can be used in classes on child welfare policy and criminal justice.

1243.0 Mountaineer Habitat for Humanity and the West Virginia Housing Development Fund: The Prospect of Partnership

Abstract:

Low-Income Assisted Mortgage Program: West Virginia – 1993 Innovations Winner

When a local chapter of the Habitat for Humanity organization learns that a state-chartered development fund might be able to provide it with financial help, the non-profit organization faces a decision. Should it accept funds from a public agency? Would doing so jeopardize its independence and push the organization in directions it might not want to go? So, too, does the Development Fund face decisions as it contemplates aiding the non-profit, which builds small homes for the near-poor, in part through the use of volunteer labor. Should Habitat’s religious affiliation bar the Fund from helping it? Should Habitat be allowed to retain control over who gets to purchase the homes it builds? This case focuses on the intersection of the public and non-profit sectors and raises questions about when they should or shouldn't overlap.

1193.0 Fighting Graffiti in Philadelphia (B)

Abstract:

Philadelphia Anti-Graffiti Network: Philadelphia, PA – 1991 Innovations Winner

When Wilson Goode becomes the first African-American mayor of Philadelphia, he must find ways to fulfill a particularly visible campaign pledge: elimination of the graffiti which mar public buildings throughout poorer sections of the city and particularly in the North Philadelphia black wards crucial to Goode’s victory. This tells the story of a series of quite different compliance strategies pursued by a new city agency specifically created to curtail graffiti and housed within the mayor’s office. The anti-graffiti effort first conceives the problem in social terms and initiates a series of efforts to deal with the ”roots” of the graffiti problem, specifically the alienation and joblessness which may affect graffiti writers. Public pressure builds, however, for the city to adopt a more aggressive enforcement posture, viewing graffiti as a criminal act which must be swiftly punished. The case allows for discussion of the nature of public compliance and how it is achieved.

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