October 30, 2020 – By Sara Soka

Millions of Americans rely on the social safety net to provide basic economic, food, and housing support when experiencing hardship. When COVID-19 killed millions of jobs and drove benefit demand to unprecedented levels, the often-difficult steps to receiving benefits — submitting documents about your income and household at a government office or by mail, waiting for a decision on your application, and needing to recertify your eligibility often if your situation doesn’t improve quickly — got even harder. Applicants have been dogged by outdated, manual systems for years, and they can be especially tough for people in precarious situations to maneuver. In March, Simon Tung told Reuters his attempts to get unemployment payments were a struggle.

“He called hundreds of times. When he did get through, sometimes he would get a message saying the system was overwhelmed and to call back. On April 2, he received his first direct deposit from New York state – for $0.”

cover of social safety net benefits report
Read the Full Report

The good news is that there are successful examples of government bringing social safety net benefit delivery up to contemporary standards. In the last decade, a small but growing number of local, state, and federal government agencies have worked with nonprofits and public benefit corporations to make many steps in the benefit application process easier. The Beeck Center’s latest report, Technology, Data, and Design-Enabled Approaches for a More Responsive, Effective Social Safety Net examines tools and methods that are working, presenting opportunities for scale to reach more Americans in need. Government executives, policymakers, and philanthropic organizations can use the examples and case studies to leverage the renewed interest in improving the functionality of these systems in the wake of COVID-19. With the likely passage of new stimulus legislation after the 2020 general election, this is an opportunity for a large federal investment to improve the social safety net, and the chance to learn from the people who have been working in this field for years.

For instance, the nonprofit design studio Civilla worked with benefit applicants and the Michigan Department of Health and Human Services to combine five benefit applications into one. The new application is 80% shorter and takes half the time to process. It’s also available in a mobile-friendly online format allowing users to manage changes to their benefits, upload documents and photos, and receive text notifications.

We started working on this project in February 2020, just prior to the onset of the pandemic. The report’s recommendations are overarching and tactical, drawn from case studies and white papers from leading organizations in this field including Code for America, Benefits Data Trust, and Nava, interviews with practitioners, and news reports. The report focuses on needs with particular resonance now, when the pandemic has tried the capacity of existing benefit systems and racial justice continues to be a primary concern for the nation. Reports like this are only as useful as they are actionable, and this one offers the chance to apply the hard-earned insights of leaders in the field, who we’ll continue to partner with to implement the lessons we’ve uncovered and scale what works, making these systems work better for everyone.

August 10, 2020 – By Katya Abazajian + Tyler Kleykamp

Since the onset of the COVID-19 pandemic, state governments have used data to respond to real-time needs for critical information. Every day, governors review data and visualizations to react to the evolving challenges of the pandemic. As we learned from state Chief Data Officers in May, CDOs are working overtime to create the dashboards that governors use and share with the public, map food distribution sites, and integrate testing and hospitalization data across disparate sources. 

While state governments must react to immediate, shifting conditions on a daily basis, they’re left with little time to plan for economic recovery from the fallout. As of June, over 30 million Americans had filed jobless claims. Early reports of economic impacts outline tough times for small businesses, renters, working parents seeking childcare, food insecure households, and others in vulnerable situations. To account for these staggering shifts, states’ recovery efforts must be sustainable, infrastructural, and forward-looking. 

cover of leveraging data for economic recovery: A roadmap for statesREAD THE FULL REPORT

Policy makers need to decide how to respond to each new wave of the virus over the coming years. They’ll need to understand how separate social programs interact with one another, when cutting support to one system may overburden another. States should lean heavily on data to make these difficult decisions on the path toward economic recovery.

cover of Social Safety Net Benefits report
Beeck Center report on Social Safety Net benefits

States that have begun long-term recovery planning are doing so under a framework that was created after Hurricane Katrina nearly 15 years ago and predates the existence of state CDOs along with other modern data and digital service approaches. While we know that the pandemic has disproportionately affected poor communities and communities of color, we still don’t know what the long-term effects will be on these communities. By improving the way they use data, states can go beyond restoring the pre-pandemic conditions that enabled these disproportionate impacts to an environment that supports equity and mobility from poverty.

Leveraging Data for Economic Recovery: A Roadmap for States is a guide to rebuild the system to be better than it was before. The roadmap is initially focused on four main areas where data can be used in recovery efforts: workforce and education, health and benefits, neighborhood well-being, and budget reallocation. Each of these areas contains a series of use cases where states are uniquely positioned to leverage their data or policy making ability to improve recovery efforts. Some use cases outlined in the report should be feasible and actionable across states, while others require stronger enabling conditions that could shift the landscape of data use for economic recovery. Busting silos and enabling better statewide collaboration remains key to ensuring that public servants across agencies can build on and support each others’ efforts. This report not only points CDOs toward the future of their work, but outlines the powerful assets that CDOs already have at their disposal.

State CDOs play a critical role in advancing on the road to recovery. The role has proven essential to developing multi-agency emergency response functions to COVID-19 and will continue to be crucial in coordinating statewide data-driven plans for economic recovery. CDOs can implement the steps outlined in the roadmap by building more sustainable frameworks for collaboration and consulting on technical issues such as data integration, visualization, or privacy. However, CDOs need support. CDOs need comprehensive data sharing agreements and support in shifting states toward more data-driven culture to run successful data programs. Top-level leaders, including governors, must commit to leveraging data as critical infrastructure for COVID-19 response and recovery. This roadmap provides them with clear steps to take on that path.

Katya Abazajian is a researcher for the State Chief Data Officers Network, and an affiliate of the Berkman Klein Center for Internet & Society. Follow her at @katyaabaz.

Tyler Kleykamp is a Beeck Center Fellow and Director of the State Chief Data Officers Network. Follow him at @tkleykamp.

June 9, 2020 | By Tyler Kleykamp

As the world becomes increasingly digital, what’s become clear for both the public and private sector is that data needs a leader. Since 2010, states have been establishing Chief Data Officer (CDO) roles and most major cities and large federal agencies have them as well. As the number of CDOs has grown to over 25, and the size of their teams have increased, the role has evolved and matured from being primarily focused on open data, to ensuring data is shared and used effectively across their states.

The COVID-19 pandemic and recent protests against police brutality highlight the unique role the state government plays and how it directly impacts people’s lives. Data is already in the spotlight and will play a critical role in how states recover from the pandemic and address systemic racism if leveraged properly. For years, Connecticut has been collecting traffic stop data in an effort to determine whether drivers are being stopped due to racial profiling. A growing number of states are providing COVID-19 case data broken out by race, illuminating the disproportionate toll the virus has taken on communities of color. States must also recognize that years of systemic and structural racism has resulted in overrepresentation of racial and ethnic groups within their data systems. With their ability to engage across agencies and departments, the CDO will be a hub for state governments moving forward.

cover of report: The Evolving Role of the State Chief Data Officer
Read the full report

The goal of the State Chief Data Officers Network is to surface and scale best practices and opportunities for collaboration across states. We also aim to support states in the creation of a CDO role. This means we need to better define what the CDO roles and responsibilities are. While there are case studies and playbooks to support CDOs in various levels of government, most aren’t geared toward the unique challenges states face. City CDOs are often focused on open data and analytics. Federal CDOs roles are generally defined by the Foundations for Evidence Based Policy Act. To help states improve their use of data, the State CDO Network created a core framework to guide them in structuring effective data programs.

Through the insights collected from state CDOs since November, and drawing upon resources from the Pew Charitable Trusts and Results for America, six core elements of a successful state data program have emerged:

  • LEAD – Designate an executive level data leader as the Chief Data Officer
  • PLAN – Create a strategy, governance structure, and inventory of data
  • BUILD – Increase the capacity of stakeholders to effectively use data
  • SHARE – Establish clear and predictable processes for data sharing
  • ANALYZE – Provide mechanisms and platforms to enable data integration and analysis
  • SUSTAIN – Ensure ongoing support exists for data efforts

To implement this framework, we’ve created two tools states can use. The Evolving Role of a State Chief Data Officer will help policymakers and state CDOs alike shape the role and responsibility of a CDO. State Data Policy Options is a guidebook with examples of effective legislation from states that can be used to support efforts to implement this framework. The policy options will grow over time as states continue implementing effective solutions.

States don’t need to implement this framework all at once. Rather, it should be used as a roadmap to help them mature in their use of data over time. Just as the CDO role has evolved since its inception, it’s likely this framework will too. These tools will help get states moving in the right direction.

Tyler Kleykamp is a Beeck Center Fellow and Director of the State Chief Data Officers Network. Follow him at @tkleykamp.

January 30, 2020 | By Natalie Evans Harris

Society uses data for just about everything. Every day we hear about different ways organizations collect data about us for marketing purposes, insurance decisions, and improved delivery of social services including housing, education, and mental health. We also hear about data being used to deny home loans, set outsized bail, and often exacerbate existing biases within our social systems. It’s no question that, good or bad, data drives decisions by large organizations, small nonprofits, government officials, and everyone in-between. 

Through this expansive approach to using data, many government agencies are also experiencing the pains of governing how that data is shared, resulting in practices that are unsustainable, ineffective, and not forward-thinking. There is a fundamental need to evolve these practices into a governance approach that balances the need to protect people’s data with the need to uncover opportunities to better serve communities through data. 

As we head into 2020, it is already clear that a shift in how we make decisions with data is underway. The Federal Data Strategy Action Plan makes data governance processes a top priority. The California Consumer Privacy Act went into effect Jan 1, 2020, requiring entities to fundamentally change how they handle data with data governance standards as a main focus. And Congress continues to work on national privacy legislation that influences data governance standards, including nearly 10 bills under consideration for regulating the collection and use of personal data, individual consent, and even defining what constitutes personal data. Simply put, new data governance strategies are being developed and policy improvements are driving this conversation.

At the Beeck Center, I spent the past year leading a research effort to gather best practices and lessons learned on data sharing. In partnership with The Rockefeller Foundation, I hosted collaborative discussions with multiple stakeholders and practitioners, conducted independent research with dozens of organizations, companies, and government teams, and drew on my nearly 20 years leading data practices. We are excited today to launch a new resource based on that research: Sharing Data for Social Impact: a Guidebook to Establishing Responsible Governance Practices.

cover of Sharing Data for Social Impact report

Thankfully, we aren’t starting from scratch as many government agencies have well-established use cases for sharing data in pursuit of improved social service delivery in areas such as K–12 education, public transportation, and healthcare. For example: 

  • In 2017, Florida’s Broward County saw the number of children moving into their Kinship Care Program — where kids live with grandparents or other non-parental relatives — had increased significantly. To improve services for these kinship providers, the county took data from a variety of sources — the public schools, Department of Children and Families, Department of Juvenile Justice, and others — and worked with the community to analyze the information, then put it into practice. This engagement of stakeholders and participants created community feedback loops on shared data between families and agencies, strengthening family outcomes through a decision making process that emphasizes collaboration, transparency, and shared interest in positive results.  
  • On the other side of the country, Los Angeles County wanted to study the effectiveness of a number of social service programs for people experiencing homelessness. While the data was available, it was trapped in individual agencies, making it difficult to understand if an individual used services outside a single agency. As a way to combat this siloing of data and link social service organizations, researchers created an integrated data system. This system, launched in 2015, “provided agencies with a comprehensive picture of the [homeless population] and their needs and helped these agencies consider different models for service delivery… The project was relatively easy to execute with the [integrated] data, but would have been impossible without it.” By not only linking data from several agencies but also outlining data-use practices and procedures for each agency, Los Angeles County is ensuring the delivery of vital services to a vulnerable population.

Another recent trend is private companies, governments, and nonprofits forming cross-sector data-sharing collaboratives in support of the social good, but these can be hampered by organizational rules restricting the availability of data to external actors. In an environment where data are only used for making funding decisions or to narrowly evaluate programs, this model can work well. But in pursuit of innovation or improved social service delivery, this model is less encouraging. I discussed the need to shift to a more equitable and sustainable governance process in a previous blog. 

As the amount of data and methods for collecting it increase, so have opportunities for drawing insights about society. Bringing together diverse data sources is crucial to ensuring that insights promote equitable growth. And as promising as data sharing is for improving societal outcomes, the analysis of integrated data (especially through predictive analytics) can easily repeat inequities learned from past service delivery. Contextualizing data analysis with methods used by social sciences and ongoing community engagement is crucial to ensuring data analytics do not replicate or worsen inequitable outcomes.

Through our research, we found three key phases critical to establishing equitable and sustainable data sharing governance practices for social impact. Our guidebook helps individuals and teams seeking a primer to better understand the key legal, technical, and cultural components to data sharing governance. The guidebook provides a holistic process detailing each phase and extensive resources to aid stakeholders.

Stages of Data Sharing Governance

Build the collective

Get everyone on board. Start with the policy problem. Identify stakeholders. Take stock of capacity, motivations, barriers, and potential data solutions. Demonstrate value and reduce uncertainty to generate buy-in. Establish a minimum viable coalition and enshrine your shared vision in a charter. 

Data Sharing - Build the Collective graphic

Define the operations

Get everyone in line. Create the governance framework tied to the charter. Design a feedback loop and integrate it into the governance framework. Formalize those two elements into a data-sharing agreement. Launch the operations of the minimum viable coalition.

Drive impact

Get everyone to improve and share. Re-evaluate assumptions, approach, and metrics. Survey impacted communities and stakeholders. Use feedback loops to enact iterative improvements to the governance structure. Repeat this process until feedback becomes minimal. Scale up. 

We recognize that many different actors will be involved in this process and that each one faces unique challenges, goals, motivations, and opportunities. This guidebook is for people looking to leverage data and data sharing towards evidence-based policy making. Moreover, it can be used by policy makers and organizations interested in giving agency to individuals over their data along with organizations interested in ethically and responsibly sharing data. 

Data Sharing Driving Impact graphic

While data use can sometimes lead to harmful outcomes, what will never change is that data can, should, and will be used for good. Because data plays such a large role in society, it is imperative that organizations and governments use and share it responsibly. While there are resources out there to do this, our Guidebook delivers the perfect framework with resources, advice and practical examples for tackling the complexities of data sharing going forward. We look forward to supporting organizations as they activate the lessons we captured and will continue recording and sharing good practices through that process.

Natalie Evans Harris is a Beeck Center Fellow and a sought-after thought leader on the ethical and responsible use of data after nearly 20 years advancing the public sector’s strategic use of data. Follow her on Twitter @QuietStormNat


The digital transformation of government is a powerful idea. It has sparked great enthusiasm and speculation about how technology and data might revolutionize government efficiency, policy-making and service delivery. But despite significant investments and innovations, these promises have not yet delivered at scale.

To better understand the limits and potential of digital technologies in American government, the Digital Service Collaborative (DSC) at Georgetown University’s Beeck Center for Social Impact + Innovation1The Digital Service Collaborative (DSC) is a program designed to develop research around government digital services, create tangible resources for practitioners, cultivate the community of digital service leaders in governments to share and scale efforts, and explore policy considerations including ethics and privacy. The DSC team is based out of the Beeck Center at Georgetown University, supporting public and private sector efforts to responsibly share and use data to address some of society’s most challenging issues and to support civic engagement with public institutions. See https://beeckcenter.georgetown.edu/project/digital-service-collaborative-building-capacity-for-digital-transformation-in-government/, accessed 21 October 2019. spent five months talking with people working at the frontlines of digital transformation in US cities, counties, states, and federal agencies.

A full description of background, methods and findings from this research are presented in the 37-page report: Setting the Stage for Transformation: Frontline Reflections on Technology in American Government.

Key findings and recommendations are presented here, including the following recommendations:

table of 14 recommendations

A summary of these recommendations and the research on which they are based is presented below in three sections. 

  • The first section describes how people working on the frontlines of American government experience the limits and potential of technology more generally. 
  • The second section describes the above recommendations in greater detail. 
  • The final section provides a brief description of the research methodology and context in which this should be considered. 

Understanding Transformation

18F defines digital transformation according to three characteristics of a transformed government institution: the connectedness of staff to an agency’s mission, the application of technology toward that mission, and agency commitment to continued improvement.2Pandel et al., “Best Practices in Government Digital Transformation: Preliminary Report.” Responses to this research supported that view, but also described digital transformation as more of a journey than a destination. This is best summarized in the following three arguments: 

  1. Digital transformation is an iterative and evolutionary process, in which new tools and strategies are applied and demonstrate value incrementally, opening space and interest for additional tools. No single tool or strategy ever immediately transforms an institution.
  2. Digital technologies are an instrument for improving government and not an end in themselves. The objective behind implementing any digital tool, product or associated process is and should always be providing better government and better government services to the public. 
  3. Digital technology is embedded in contemporary governance; it cannot be avoided, nor should it be fetishized. As a descriptive term, “digital government” makes as little sense as “paper government.” To effectively adapt to the new technological context in which they necessarily operate requires government institutions to acknowledge that using digital tools is the new normal. 

In keeping with these arguments, respondents viewed digital transformation as something that could and should be managed by people working in government, in order to improve government and the services it provides. In particular, respondents described multiple benefits and contributions that the smart use of technology and data could provide to (a) civic interaction and service delivery; (b) data, evidence and analytics; and (c) efficiency and resources.  Respondents also described numerous specific obstacles and barriers posed by (a) insufficient capacities or resources, (b) formal rules and institutional structures, and (c) institutional cultures and preconceptions. 

Respondents described an interaction between short term benefits of using technology, and the long-term changes to institutional practice and culture that would enable more scaled and widespread use of technology to improve outcomes. This interaction is how respondents described processes of digital transformation in government institutions. 

When describing what enables such processes, respondents described three broad institutional conditions:

  1. Explicit support for cross-functional technical expertise
  2. Deliberate professionalization of technical expertise, and 
  3. Open and engaged institutions. 

In order to facilitate these conditions, and set the stage for meaningful digital transformation in government institutions, this analysis makes fourteen recommendations to policy-makers, implementers, and external stakeholders.


Recommendations for policy makers 

  1. Lead with curiosity. There is often an esoteric quality to the types of tools and strategies referenced in this report. This makes them easy to dismiss, underestimate, or in some cases, it can inflate expectations. Leaders in government should take time to explore and understand the roles, skills and ways of working that are associated with the strategies described here, and the value that they can add to policy and service delivery. Doing so helps to maximize their value, and to signal that value across institutions, while also strengthening coherence across teams and setting realistic expectations.
  2. Initiate an explicit institutional discussion. This might take any number of forms, including an audit of existing practices, setting up a task force to review opportunities, or simply asking technical staff to begin holding brown bag lunches. The important thing is to create a space in which new ideas and approaches can be suggested and considered, with a real potential for implementation. The context of this discussion could also vary widely. A good checklist can be drawn from the “seven lenses of transformation” proposed for defining and benchmarking transformation by the 7 UK Government Digital Service.3Vickerstaff and Cunnington, “How to Set up Transformation Projects That Could Shape Our Future.”
  3. Budget creatively. The cost of technology can be inhibitive. Engage technical staff to identify ways in which implementing digital can cut costs elsewhere. What processes could be automated to free human resources? What paper processes can be digitized to eliminate printing and transporting costs?
  4. Build cross-functional teams. Identify ways to avoid responsive silos of technical expertise by integrating technical and non-technical expertise in teams and processes. Create opportunities for technical and policy experts to collaborate across project cycles, from planning to evaluation, even in projects where technology or data play a minor role. When possible, aim to establish cross-functional and co-located teams in order to strengthen learning and cross-pollination between technical and policy expertise.
  5. Demystify technology and cultivate tech-normal institutional cultures. Identify opportunities for trainings, hosting events, or inviting speakers that can communicate the nuts and bolts of relevant data and technology. Cultivate an institutional environment that values frank conversations about technology and its limits, and that does not fetishize technical expertise at the expense of other expertise. 
  6. Avoid exploitative procurement. One of the most profound ways to limit the cost of technology programs is to avoid overpaying on technology procurement. Contacting peer institutions that have made comparable investments and conducting more thorough market research can help.4Brethauer, “Announcing OASIS Discovery: Making Market Research Easier.” It may also be possible to pursue cooperative procurement,5See, for example https://www.nigp.org/home/find-procurement-resources/directories/cooperative-purchasing-programs, accessed 21 October 2019. modular contracting,6Jaquith, “Prerequisites for Modular Contracting.” or to piggyback on existing contracts with other government agencies or institutions.7See https://www.coprocure.us/about.html, accessed 21 October 2019. 
  7. Foster environments for responsible experimentation. Attention to the novel risks that accompany technology and data often focus on challenges to privacy and consent, but also involve more subtle ethical risks, such as poorly informed policy or the opportunity cost of wasted technology budgets and processes. Explicit institutional processes and attention during planning and analysis phases can help to identify and mitigate these risks, and can be integrated into several of the other recommendations presented here.8For a detailed description of a process-based approach to managing risks associated with government data, see Wilson, 2018. For a collection of applied tools, see the Responsible Research and Innovation Toolkit at  https://www.rri-tools.eu/about-rri, accessed 21 October 2019. 

Recommendations for implementers and doers

  1. Document and share digital and data-driven projects and processes. The demand for storytelling and experience sharing is widespread and consistent across the front lines of digital transformation. Conferences and events provide a much-needed forum for inspiration and “therapy” — as well as learning and education — but there remains a need for technical documentation for the types of projects that are implemented in multiple jurisdictions. Make a point of documenting technical specifications, steps taken, challenges and processes along the way. Share this. 
  2. Don’t reinvent the wheel, the interface, or the database. There is a significant degree of replication in government technology. Conduct market research to determine what similar platforms and products have been created by others.9The Federal Source Code Policy supports reuse and public access to custom-developed Federal source code, which is published at https://code.gov/about/overview/introduction. Organizations like 18F and Code for America also often publish detailed documentation and descriptions of digital tools (see https://18f.gsa.gov/2016/04/06/take-our-code-18f-projects-you-can-reuse/ and https://www.codeforamerica.org/news, accessed 21 October 2019.). International resources, like the International Development Bank’s repository of off-the-shelf technology solutions may also be useful (see https://code.iadb.org/en, accessed 21 October 2019). Modify and adapt open source solutions when appropriate. Produce and share open source solutions whenever possible. 
  3. Create feedback loops between the public and government. Most digital services imply an opportunity to solicit feedback from users. Leverage this to collect input for continually improving those services. Ensure that users can see how their input is received and that they feel heard. Look for opportunities to publicly respond to feedback, building confidence and trust in government. 
  4. Several of the above recommendations for policy makers can also be relevant, especially regarding procurement, creative budgeting, demystification, and responsible experimentation. 

Recommendations for external stakeholders

  1. Fund the “boring stuff“. Grants and resources tend to flow toward what seem to be the most novel and exciting projects, like blockchain and machine learning products, which are often untested, unproven and not what government leaders will say they need most urgently. Often, the kinds of digital and data-driven innovations with the greatest potential to transform government and government services can sound a lot less exciting, and struggle to find support. Developing common data identifiers across agencies or moving data from servers in a closet into a secure cloud environment are examples of work with revolutionary potential, but for which it is difficult to secure funding. 
  2. Support everyday superheroes. Several respondents pointed out that the most important and transformative work isn’t always being done by the usual suspects on the civic technology conference circuit. Some of the most impactful support may involve doing research to discover who is already naturally advancing digital transformation in state and local government, without recognition, and what kind of support they need to scale their successes. In the words of one respondent, discussing the limits of support to CIOs, CTOs, and CDOs, “C-suite only gets you so far. You need to focus on the people in the field.”
  3. Build an ecosystem for social support. Dedicated support to specific projects is important, but much of the work to enable digital transformation involves more sharing and learning across institutions. To the degree that this is already happening, it is happening organically. Gatherings such as the annual Code for America Summit10See https://www.codeforamerica.org/events/summit, accessed 21 October 2019. provide prominent fora for digital service professionals to gather and share, as do internationally focused events and communities, like those surrounding the Open Government Partnership11See https://www.opengovpartnership.org/ accessed 21 October 2019. and the international open data community.12Christopher Wilson, “Open Data Stakeholders: Civil Society.” The movement of experienced digital service experts through the agencies and institutions they support is also seen as an important, if limited, mechanism for building community and spreading awareness. The digital service delivery community should create more opportunities and modalities for government champions to engage with and learn from their peers, both in person and online. 

About this research

This research was designed based on the conviction that the individuals doing hands-on work to bring technology into government best understand technology’s potential and limitations. These individuals do the hard work transforming government. Their work isn’t always the most exciting or shareable, i. It sometimes results in compromise and failure. But it is from this perspective that we can best understand what technology can do to improve government, and how to manage the risks and challenges along the way. 

To better understand the perspectives, the DSC team collected data and conducted interviews between November 2018 and March 2019. This included a desk review of more than 80 articles, reports, and policy briefs, semi-structured interviews with more than 70 individuals, and informal consultation and planning conversations with more than a dozen professionals and organizations. The data collected from this process was reviewed during a three-day synthesis workshop in March 2019. A detailed description of the methodology is provided in the full report: Setting the Stage for Transformation: Frontline Reflections on Technology in American Government.

A note on the research context for digital government transformation

This research builds directly on the foundational efforts of New American Foundation’s work on Public Interest Technology and government innovation,13Schank and Hudson, “Getting the Work Done : What Government Innovation Really Looks Like”; Muñoz et al., “Public Interest Technology: Closing out Year One and Looking Forward to Year Two.” by focusing specifically on the experiences of front-line civil servants and policy makers. It makes an effort to deepen that work by attending to the role of individuals at multiple levels of government and in multiple policy areas. 

In doing so, this analysis departs most research on the digital transformation of government, which adopts a global perspective and emphasizes the work of national level digital service teams.14Bracken and Greenway, “How to Achieve Sustain Gov. Digit. Transform.”; Eaves and McGuire, “2018 State of Digital Transformation.” Much of that work is also relevant to this analysis, however, and should be considered in future research transformation processes in American institutions. In particular, recent work by Ines Mergel and colleagues has suggested a conceptual model for linking the drivers, objects, processes, and outcomes of digital transformation,15Mergel, Edelmann, and Haug, “Defining Digital Transformation: Results from Expert Interviews.” and four propositions regarding the sustainability and impact of digital service teams.16Mergel, “Digital Service Teams in Government,” 10–11. A summary of the four propositions suggests that the effectiveness of digital service teams is related to their centralization of decision authority, that the duplication of practice across teams increases the likelihood of adoption elsewhere, that increased formalization of teams increases their capacity to scale and likelihood of standardization of practice, and that the acceleration of organizational change increases the likelihood of standardized and successful innovation practice. These may provide useful frameworks for designing and evaluating specific applications of technology to institutional processes in future research.








December 9, 2019 | By Christopher Wilson

Digital tools and strategies have a tremendous potential to transform government: improving services, boosting efficiency, and strengthening ties to the public. The last decade has seen several important milestones as data and technology have been leveraged to solve specific challenges across the vast scope of government in the United States. 

But despite the best efforts of technologists, visionaries, and institutional champions, the full potential of these tools has been slow to materialize at scale.  

To better understand why, the Beeck Center spent several months in early 2019 conducting research and interviewing experts working in and around tech in government. We spoke to people on the front lines of digital transformation, doing the hard work of making technology useful for government, and making government better. More than 70 people leading or supporting the novel use of technology or data in federal, state, and local government in the United States told us about how these tools could best add value to government, what was obstructing their work, and what they needed to do their work better. 

Their stories confirmed that there are a lot of hopes and concerns surrounding government technology, and that there are big differences in how the opportunities and challenges play out across different policy areas and levels of government. But there are also common threads, and one message was clear: 

Technology and data are the new normal, and governments have no choice but to address how they impact the core work of government. This has tremendous potential to improve government and government services. But technology is no magic bullet, and never catalyzes government transformation on its own.

People working at the front lines of government technology and innovation rather describe digital transformation as an iterative and evolutionary process. They describe a variety of ways in which it can be supported, challenged, and leveraged to facilitate lasting transformation. 

cover of Setting the Stage for Transformation report
Download the Report

Drawing on those perspectives, the Beeck Center is rolling out a new report documenting the perspectives and needs from the frontlines of digital transformation.

Setting the Stage for Transformation: Frontline Reflections on Technology in Government reviews what we learned, and suggests that there are three broad institutional conditions that facilitate digital transformation by using technology-related tools and strategies to add value to specific programs and processes. 

  1. Explicit support for cross-functional technical expertise
  2. Deliberate professionalization of technical expertise, and 
  3. Open and engaged institutions. 

In considering how to establish those conditions and set the stage for digital transformation in government institutions, the report also makes specific recommendations to policy-makers, implementers, and external stakeholders. 

table of 14 recommendations
To review the full results of this research, you can download the full report, including detailed methodologies, findings and analysis, or read the report highlights that presents the main findings and conclusions.

This analysis builds directly on foundational work done by researchers from the Public Interest Technology team at New America and the digital HKS project at Harvard University, as well as practitioners currently and formerly on government teams. We hope that it advances both research and practice in the field, and enables more of the good work already being done to improve government through the use of new tools, technologies, and approaches.

Christopher Wilson is a fellow at the Beeck Center for Social Impact + Innovation.  His research focuses on open government, citizen participation, and the influence of international norms on government practice. He is based out of Oslo, Norway. He blogs about research and methods for assessing civic technology at https://methodicalsnark.org.