What We Recommend for Building Better Digital Service Teams, Initiatives, and Results
There is No Unifying Theory of Change
The book Good Strategy/Bad Strategy by Richard P. Rumelt states “Good strategy works by focusing energy and resources on one, or a very few, pivotal objectives whose accomplishment will lead to a cascade of favorable outcomes.”
In every retrospective we hosted, participants bemoaned the lack of a strategy and a longer-term theory of change in their work, or “how”, tied to outcomes. No shared strategy of work and functional purpose across the federal teams – USDS, 18F/TTS, OFCIO, and beyond – led to confusion, competition for limited resources, and a focus on individual team or organizational goals rather than shared agency- or government-wide outcomes. No shared strategy for mission outcomes at the government-wide or agency level meant we heard time and time again during the retros that teams at all levels of government felt like they were missing a chance at making an even greater, deeper impact. In the absence of such shared mission outcomes, digital service teams felt like their participation was the metric for success and their activity was a substitute for long-term progress. This is emblematic of a systemic problem – digital service initiatives operate within silos, compete for limited resources and talent, and often operate at agencies that lack a clear sense of how digital service initiatives contribute to their goals, ultimately diminishing the impact.
The lack of strategy impacted not just the teammates trying to do the work, it also impacted the agencies and stakeholders digital service teams interact with. A strategy defines a set of priorities that is repeatable and accountable, making it easier to partner, delegate, and work fast; it also communicates what you don’t want to work on, transparently outlining priorities. For digital service teams, strategy was absent but should exist at multiple levels. At the highest level, it articulates the theory for how digital services contribute to societal outcomes – how digital and service design improves public health through better access to benefits such as SNAP, or simplified access to healthcare. Strategy also exists at the government-wide level, defining priorities and processes for achieving those outcomes. And at the organizational and functional level, strategy defines the logic model for how diverse teams – including crisis response, modernization, implementation, product building, and operations and maintenance – work together across government.
And now, at a moment of significant technological change and demands on government, the stakes of having no strategy at each of these levels are higher than ever. Without a clear position on AI, government won’t even get their tactics right — they’ll spend all their time debating tools instead of outcomes. A strategy doesn’t require consensus. It is a signal of what you value, and provides the concrete steps to get what you’re trying to achieve, and why — so that people can ignore it, engage with it, challenge it, or build on it.
Moving forward, the digital service community should be a part of articulating an ambitious, outcomes based strategy at each level for what we want to achieve across the country in the next 5-10-20 years; and to look at defining foundational elements that make a strategy effective: building user-centered government and how to reform our institutions to become modern, responsive organizations.
User-centered government. Digital service practitioners have spent a decade hearing firsthand what people actually want and need from government. That knowledge shouldn’t stop at delivery- it should drive the strategy. Digital service teams are uniquely positioned to define those outcomes in concrete, user-centered terms and to hold the strategy accountable to them. No strategy should be set without that perspective at the table.
Institutional (re)design. For a decade, the civic tech community launched good services inside of – and sometimes in spite of – broken institutions. Direct File worked – and yet it didn’t change the IRS. That gap between modern ways of working and working across the organization to support radical change is the opportunity to update and upgrade our government. Digital leaders have the knowledge to go further: to define what a modern agency actually looks like, how it makes decisions, how it procures, how it hires.
Defining an ambitious strategy is an urgent first step: effective strategy is built on clear, user-centered outcomes and institutions that are structured to achieve them. Placing delivery technologists at the top of our organizations to shape both service delivery and how the institutions themselves run is one of the most critical things a political leader must do. The field is navigating AI adoption, budget austerity without a framework for prioritization, and planning for the future with a radically different federal landscape. An ambitious response to this moment is worth examining on its own and we look forward to contributing and seeing what our peers discover.
As is, the Digital Government Field Cannot Scale
Over the course of engaging 100+ individuals through the Digital Services Retros project, one theme that emerged was a shared concern that the individual contributions of any one team, no matter how talented, could not scale to influence how digital services were delivered throughout the rest of an agency. While teams of talented, experienced technical professionals could turn around quality products and evangelize a few allies to their style of working, ultimately teams struggled to turn their hard-won bright spots into scalable models of working across federal agencies.
The government digital services field’s current M.O. is to rely on a relatively small and scrappy pipeline of talent who attempt to sustain their work through oral histories and few resources or tools for which they’ve managed to win temporary exceptions. Scaling quality product development and service delivery across government demands a more mature approach, replacing unpredictable patterns of work with more cohesive processes, a shared vision of quality and strong resources that support the field of civic technology professionals.
Make it as easy to hire technologists as it is to hire lawyers
Current legislation and federal civil service code stops digital service teams from being able to hire the talent they want, build or buy the tools they need, and engage with users in the manner they need to. For this reason, the civic technology field has come to rely on a series of flexibilities and exceptions in lieu of real, streamlined repeatable career pathways.
Reliance on exceptional methods (e.g., term-based hiring, ad hoc programs that get designated salary exceptions) without reforming the system to enable a streamlined and quality process for hiring is an expedient approach, but not a sustainable or scalable one.
Policy leaders, including Congress, need to stop encouraging bandaids: digital service teams were never meant to be their perpetual excuse to avoid reform. Each needs to take concerted action to align the mechanics of the executive branch with modern hiring, workflows, and procurement that force every team to reinvent the wheel.
Make it someone’s job to scale change
Everything – from hiring, to ATO (authorization to operate) processes, to onboarding and everything in between – is a one-off, making lasting change within and across agencies near impossible. Moving forward, agencies and teams need to spend a percentage of time rewiring the agency as the work happens. Service delivery is a great opportunity to model new behaviors, work in an outcomes based manner, and use momentum to make change – this should become the norm and agencies should codify these upgrades alongside delivery work. The best way should be the default way, not the workaround. One strategy to target this need is to create a scale team – a team that shares best practice and is empowered, authorized, and expected to make sure the best ways become the default way. Institutions need to learn to expect change and implement better.
Additionally, there’s no shared definition of what good looks like in government digital delivery, which means digital teams in government are effectively grading their own homework. In contrast, within the private sector, there are industry standards for service-level agreements and user experience. These aren’t necessarily uniform across every enterprise or product, however there is broad alignment of what quality delivery reflects.
Government digital teams need to define their own “industry standards” for service levels and delivery. These definitions should not pigeonhole teams into rigid processes or unnecessary metrics, but rather provide a flexible benchmark that equips teams and leaders to gauge how successful their efforts are and how they compare across government and over time. In concrete terms, this could look like expectations for down time, user satisfaction indicators, and increased uptake of services among eligible populations. These also give agency leaders a way to set expectations and give users a basis for demanding better.
Expand field resources
Even as the field grows, there is still significant work to be done to develop its size and quality through shared vocabulary, resources, training, and methodologies. Organizations like Technologists for Public Good and events like the Code for America conference are promising valuable bright spots, but the potential for building a robust, well-connected field is far from saturated.
Establishing common training and methodologies would not only make the work itself more efficient, but would also create greater worker mobility across organizations. When practitioners share a common foundation, they become more interchangeable in the best sense; technologists are able to move between roles and institutions, which in turn drives more competitive opportunities and raises the quality of the field as a whole.
We Built Digital Teams, Not Services
“Build a digital service team” they said. And they did, oftentimes with great results, change, and service delivery. Over the last 10+ years, digital service teams have added capacity to struggling agencies across the country in order to deliver critical services that may otherwise not reach their intended user. This is a worthy goal. But what was the measurement of success? Was building the team the outcome?
During the Digital Services Retros project a pattern – across all levels of government (federal, state, local) – seemed to emerge: digital service teams were set up to add needed capacity to any number of solutions or as an outcome itself. The early strategy was – land the team, expand to solve new problems.
Somewhere along the way, the digital government field lost sight of what we were solving for. The unit of success was a digital service team; the thinking was that this team of talented individuals could be put against any set of problems or outcomes. And implicitly there was a correlation between the team being the intended outcome – an agency was deemed more “mature” or complete if it housed this team. To a certain degree this worked, and this worked well.
Today, most digital service teams have a similar set of attributes:
- A digital service is typically located centrally, either reporting into the principal or CIO/CTO or COO
- Power and authorities vary greatly; generally power is derived from political capital or occasional legislation that establishes it; they rarely have authorities to hire, fire, or hold teams accountable to outcomes
- The same set of skills were hired, regardless of the intended problem at hand, or outcome
It is assumed that digital services were somewhat plug and play – your handy government Swiss Army knife. Yet, the work itself varies greatly due to the priorities of leadership, the work it is empowered to do, and the depth at which it is allowed to operate. These teams have had great impact – and also, it is time to examine other models, units, and ways of working that can complement the standard digital service team.
The needs are so disparate and each context they work in so unique, we need a wider set of models from which to draw upon on purpose, not happenstance. Agencies and leaders at all levels need to have the right model that fits their constituents’ or agency’s or legislative need, as well as their agency’s maturity.
In its current evolutionary phase, most digital service teams are stand-alone teams assigned to deliver a specific task, often embedded in the CIO or agency head’s office. It is true that top cover and leadership capital is critical for success; however, we would like to challenge this new model in an attempt to create more enduring, transformative change for end users and for agencies.
The key ingredient: organizing the work around the shared outcome of a service, rather than a functional or organizational boundary. This orientation focuses the team on the outcome and be held accountable to its delivery. Such teams are more likely to be enduring, as the services that they deliver are either embedded in statute or have a permanency. Furthermore, the funding is allocated to outcomes that are aligned to the strategic goals (and budget) of the organization, leading to more enduring change.
The Service Team
The target state: a service. Established by the UK’s Government Digital Service and developed further by practitioners like Kate Tarling, a service team is organized around a service as experienced by an external user, i.e. “file my taxes,” “apply for college financial aid,” “enroll in benefits.” It’s not a project, nor an app, nor a vendor run system – a service is a thing a person needs to do.
A service, as Tarling defines it is described from the user’s point of view; encompasses every step between the user and the outcome; crosses organizational silos; and ties directly to the institution’s goals. This is similar to the “product operating model” seen in the private sector.
Where government services depart from a typical product team are the unique constraints faced by the public sector. A private sector product team is usually a mix of engineers, designers, and a product manager sitting in a product silo. A government service team needs that, plus program and policy staff, and often lawyers who have to navigate the policy requirements alongside the technical ones. Crucially, the user of government services also usually can’t “opt out” for a competitor product; if a benefits application breaks, the user has no other option.
These differences in the staffing and user experience are significant, however the underlying logic of a persistent, empowered ownership team remains the same. The product operating model gives government the operating mechanics: how a team should be funded, staffed, and run day to day. The service model outlines the unit that the team should be organized around: the user’s full journey, rather than an IT system, or office, or budget line. Government needs both the discipline of the product operating model, applied to the full weight of what an end-to-end government service actually requires.
A few items stand out here. First, a service is an end-to-end journey. In most agencies a service team by this definition would span across multiple teams and silos in an organization. A service also completes the user’s task (and it does so confidently, securely, and accurately). And a service team crosses organizational boundaries and is fully empowered to deliver this complete, end-to-end task. Restructuring delivery around an end-to-end service, either collapsing or working across silos, allows digital to truly shape the work that matters most to users.
That last part is what makes this model sticky. A service team organized around “Renew My Passport” is less likely to be disbanded when leadership turns over, because the service doesn’t go away. Funding is allocated to an outcome, year after year. The work survives because it’s embedded in something tangible.
We don’t have to look to the UK for proof of concept. An independent assessment of the IRS conducted in 2024 described Direct File as already ‘functionally operating as an isolated service-oriented organization.’ The model worked well and was proving itself across the organization for two prominent reasons. First, the most important decision the Direct File team made was to appoint a single accountable owner empowered to make day-to-day decisions. This leadership and governance model allowed the team to work in an empowered manner, at pace. Second, the service team joined up customer support and product teams.
What we heard in the retros was the flip side of that: projects that stalled because of indecision, too many stakeholders, being dropped into ambiguous situations without clear ownership, among other reasons. Building end-to-end service teams is not for the faint of heart – achieving this model of embedded technical and program teams, working collaboratively on an end-to-end journey, fully empowered to update processes and ways of working as they go is the mature end of the digital government spectrum. But it is included here as it not only achieves better results for the end user, it also helps the agency and staff transform as they work in a new, fully digital, collaborative manner.
Different Models for Different Problems
Not every new challenge in government requires the same organizational response. During our retros, participants bemoaned how USDS and 18F didn’t often build the right team for the problem they were trying to solve. This was often due to multiple reasons, top among them scarcity of talent. Below are models and purposes that emerged from our retros, each with distinct purposes, skill requirements, and conditions for success. These aren’t mutually exclusive; a mature digital organization will likely need more than one at once. The service team is the north star, the most mature model. The others are legitimate and necessary, but they should be chosen deliberately and not defaulted into.
Additional models for teams that could be applied to different problems, include:
A Forward Looking Agenda for Digital Service Delivery
This is the moment for ambitious change. The digital government field has an opportunity to build a more responsive and resilient government by pushing into expanded frontiers, with new tools, approaches, and even organizations that don’t exist yet. While the pace of change can be overwhelming, there is something clarifying about a moment when people are questioning the value of institutions themselves. This is the time for radical experimentation, delivery, and exploration.
So what’s next? The recommendations we’ve laid out – building a coherent strategy, matching the right team for the right problem, and scaling what works to stabilize and reposition the field can be read through multiple future-looking lenses. First institutional: what does building ambitious and capable government institutions look like, and how do you build it? Another is contextual:, trends like artificial intelligence and austerity are both going to reshape what’s possible and not in directions we can easily predict.
The following options and ideas exist on a spectrum, and are part of a suite of reform ideas that can help build government with the ambition and capacity to deliver. We welcome challenge, debate, and more ideas to this dialogue – love or hate it? Great! Tell us! Like an idea? Great! Steal it and go deeper!
Federal Digital Service Delivery
Building ambitious and capable government institutions – Federal edition
Federal capacity, or “The Department of Digital”
Federal digital and delivery capacity will continue to be a necessary piece of a strong, delivery oriented government. The question is – now that the US Digital Service has become DOGE and 18F is dismantled, what should the future model be?
The federal government needs a strong, centralized digital capacity responsible for three distinct purposes: capacity to deliver on presidential priorities, setting standards for better delivery, and building and managing shared platforms that can be used across government to save both government and external users time and money. For inspiration on what this centralized structure could be in a federal system, we look to Germany and the UK.
Germany’s recently established Ministry for Digital Transformation and Government Modernisation is delivering a portfolio of services, holding agencies across the government accountable for excellent, modern services, and ensuring that all software that is developed is interoperable across agencies and to devolved jurisdictions. It is a priority of the German government to build software that can be reused not just across the central government, but to states as well. Embedded in the ministry is a 250+ strong digital service team, responsible for excellent user experiences and digitizing the key interactions with government.
Germany is also taking the software it uses seriously and, in an effort to ensure national sovereignty over their own technology, is setting out to build their own full stack office software, across document management, presentations, collaboration suites, and other essential office software for use by civil servants across the country. It has become a national priority to not get locked into any single vendor or be reliant on any single country to provide software or cloud services; building resiliency across the tech stack is a strategic national necessity, not an afterthought.
The UK’s Government Digital Service (GDS) established a central team that builds platforms that can be used across government and sets standards that all new services must meet before they launch. These standards ensure consistent design and interaction patterns, end-to-end transaction completion, and more. The central team also builds shared platforms – GOV.UK Login, Pay, Notify, NDX Cloud, and Design System. More recently, they began developing shared open source frameworks to support local governments across the country. These platforms have become an essential foundational layer for the modernization of the UK’s government; the central team has many tools and templates that are easy to use, replicate, and apply to launching new services.
In the U.S., a central digital department could truly hold agencies accountable and help drive the momentum for change across the federal government, as well as support, build, and launch critical government platforms. Additionally, identifying and setting shared standards that not only establish a baseline for experiences, but also come with muscular authorities to enforce and hold teams accountable to those standards. What does accountability look like in practice? Agencies having their services assessed and getting approval before launching a new service experience, as the UK does now.
Recommended additions to the U.S. toolkit
Example standards. Standards that define what good looks like and come with the authority to enforce it could include:
- AI in practice – guidance for application and usage
- Service standards – design, interaction, call center, and service completion standards
- Budget controls – oversight over digital and tech procurements
- Service performance standards – transparency into service performance across government
Example platforms. Platforms any agency or jurisdiction can plug into, rather than procuring their own version from scratch. These could include:
- Login.gov
- A payment platform
- Income verification platform
- AI LLMs for civil servants that are compliant with federal and state laws (for example, Berlin’s BarGPT for Berlin city government employees and is GDPR compliant)
- Open Source office software (for example, France’s Lasuite) and code (for example, U.S. Web Design System (USWDS))
- Identifying projects similar in nature and scope to Ukraine’s Diia
Federal agencies – models for services and more
At the agency level, there are multiple models to support service delivery and leaders should support the model that meets their needs. However, almost universally we recommend that agencies should explore the service model for their key services. This model organizes teams and the work around the shared outcome of a service, rather than a functional or organizational boundary. Working across silos, in multidisciplinary teams leads to better outcomes for users and helps transform the organization into a more modern, responsive one along the way.
State and Local Digital Service Delivery
Building ambitious and capable government institutions: Working across federal and state/local
Federalism, what is it good for?
Federalism is great for ensuring power doesn’t get too centralized when managing a huge and hugely diverse country. However, federalism is rarely good for the end-user experience or for delivery efficiency. A review found that federal legislation meant to quickly build infrastructure, support cities and states during COVID, and pave a path towards a greener country was slow to get out the door and make tangible. The matrixed delivery of federal -> state -> city/local doesn’t always support efficient implementation, and it also doesn’t have to be this complicated.
An ambitious federal digital strategy should include consideration of the complete delivery cycle – inclusive of legislation, the disbursement of funds, tracking all the way down to the front line and ultimately the intended end users. There are two potential areas to explore for better outcomes – a ‘middle layer’ of shared open, public infrastructure that helps budget-strapped state/local governments deliver on key services and the inclusion of state/local digital capacity to support implementation of any legislation that requires a user experience.
A menu of tools: open source platforms, shared infrastructure, and public options
There are countless examples of large IT vendors building the same product, poorly, for 50 states. This model can and should be reimagined – moving towards a vision where governments can opt-in to a shared public infrastructure. It is time to look at options that tie federal outcomes to delivery intent: We need shared public infrastructure around key legislation and universal platforms. These could support both internal government efficiency and end-user experience.
Shared open source platforms and digital infrastructure can provide government teams across the country with additional options for delivery at a national scale. This ‘middle layer’ would look at services that are required in multiple jurisdictions or infrastructure necessary to implement new legislation. Such platforms could exist as a public option – government-provided services that coexist with one or more private options.
Governments shouldn’t have to build from scratch: Modern income verification infrastructure really only needs to be built once and made available to jurisdictions that opt-in and could be used in a countless number of ways, from federal scholarship applications to SNAP. Governments at all levels lose money to payment processing fees. A public option payment platform would cut costs and add a new competitor to the market, saving taxpayers money. Universal moments, such as birth and death registry, could be built centrally and deployed locally. Even when state and local governments build their own services, government registries and digital services could be built using a government-managed open-source low-code platform, like is being done in Ukraine with Diia.Engine.
To date, these delivery challenges have been too onerous to tackle. States are often reluctant to share data and platforms. Some jurisdictions have begun planning shared procurement strategies, but radically different, outcomes-based delivery will take reimagined governance and significant political will.
State and Local delivery capacity
State and city governments are the source of many peoples’ daily experiences with public services and infrastructure. Yet most lack the resources and capacity needed to deliver the efficient, seamless, and intuitive digital experience that the public has come to expect in the private sector. This gap is not a reflection of ambition or effort at the state level, but the result of long-standing structural constraints on funding, talent, and technical support.
Existing federal funding mechanisms and technical assistance programs are insufficient to close this gap. While federal dollars often support state IT projects, they rarely come with embedded technical capacity, hands-on delivery support, or durable mechanisms for knowledge transfer. Today, states face persistent challenges recruiting and retaining digital talent due to rigid hiring systems, compensation constraints, and limited professional development pathways.
From this, we propose a couple of options to close the capacity experience gap between the end user and state and local institutions.
- Include implementation or service teams as part of legislation to ensure that delivery intent is actually possible and is critical to the success of any legislation. Building that capacity in-house, in the institution that is responsible for the end-user interaction, is a critical step towards a successful implementation.
- Centrally funded technical assistance – in this model, a dedicated central office in the federal government – should be established to provide consultative and technical assistance to state governments at scale. This office would form interdisciplinary teams that consist of state government employees and technologists who work on high impact issues of service delivery, ranging from social safety net access, to environmental permitting, to shared digital infrastructure modernization.
Artificial Intelligence Risks and Rewards in Digital Service Delivery
AI was not a major topic during the retros, largely because many practitioners view AI as one of many commercially available technologies that can be deployed to solve problems. However, interest in AI is growing as governments increasingly experiment with and deploy AI in their operations and service delivery.
AI, when deployed responsibly and with a clear purpose in mind, has the potential to assist in streamlining benefits, reaching citizens with timely information, and automating certain tasks. However, AI does not exist in a social, economic, or political vacuum and carries significant risk to governments and the general public through cybersecurity vulnerabilities, data privacy risks, entrenched bias, intellectual property infringement, and more. These risks highlight the need for a well informed government workforce, and additional in-house technical experts within government to support users and make decisions that advance progress with a robust understanding of the implications.
Artificial Intelligence in the age of austerity
During periods of financial uncertainty or recessions it can be challenging to make the case for AI adoption when it weighs against more urgent needs. Additionally, nationwide, states, counties, and cities are facing tighter budgets due to existing deficits and a change in federal funding. Resource- and capacity-constrained institutions are turning to AI to help fill that gap and deliver for their constituents. But to ensure that AI adoption is fair and transparent, governments need AI strategies and strong, technical talent embedded to deliver on this new technology.
This moment demands confronting a reality that is complex, rapidly evolving, and where just about every decision will have a profound impact on the lives of those the government is meant to serve and the institutions themselves. If the government and the civic tech community are not intentional about how we design, procure, use, and govern this new technology, it has the risk of making capacity issues worse and undermining trust in institutions that are already fragile.
Artificial Intelligence, practically
In this moment, our recommendations – have a strategy tied to outcomes, build embedded multidisciplinary teams, make it easy to build and sustain this capacity – are more important than ever, as AI becomes a critical tool that governments across the country are rapidly adopting. AI can help improve service delivery when applied to specific problem-driven use cases and deployed in ways that promote fair, user-centric, and transparent application.
Where we would deploy AI towards service delivery:
- Embedding in the practices of front line employees, to understand where processes can be automated, notes transcribed, and the right approach to using LLMs that allow employees to save time on notes, searching and applying different policies, etc, ultimately allowing them to spend more time with clients.
- Prototyping new experiences, forms, and interactions – normally these are interactions that require lengthy procurement processes, now governments have the opportunity to use new AI tools to perform exploratory work.
- Other problem-driven uses that focus on solving specific challenges rather than adopting technology for its own sake.
- With content support across translation, transcription, simplification.
Principles:
- Build with, not for – build systems that complement the lived experience of the government employee and meaningfully include end-users in the design and testing of AI platforms.
- Be transparent around how and when AI is used, especially in decisionmaking processes or in the provision of benefits.
- Best practices include: public use-case inventories, and consumer notification/disclosure of AI use (and where)
- De-bias, wherever possible – Understand how LLMs have certain biases and how, as government employees, there are frameworks around those biases to mitigate potential risk or harm.
- Being aware of existing applicable laws, and of increased compliance risk with AI tools that have limited interpretability or control over data inputs (such as adverse action notices that are required under FCRA/ECOA)
- Pre-deployment planning: Before you deploy, understanding how it is best used, and situations in which in can actually make things work less well (i.e., when you need factual information)
- Preventing buyers remorse: Clear procurement guardrails that include sunset provisions, and auditability/interpretability (to prevent accidental bias).
- California is a great example. The state piloted multiple programs to improve service delivery and killed the ones that didn’t work or were too costly.
- Preventing buyers remorse: Clear procurement guardrails that include sunset provisions, and auditability/interpretability (to prevent accidental bias).
- Consistent quality control: As agencies independently acquire a growing number of services, maintaining consistent quality control and oversight becomes increasingly difficult. A centralized review and governance function should evaluate and monitor the tools and services being adopted across agencies. (i.e., a FEDRAMP process for AI)
- Centralized vetting of AI models and products ensures consistent standards and is more effective than fragmented (and often more expensive) agency-level procurement.
The platforms and models that we choose matter. Again, there is inspiration to be found abroad. The Swiss Euria GPT is fully powered by renewable energy, and all heat produced by the platform’s data centers is fed back into Geneva’s heating network; furthermore, it does not collect or train its models from any user data and is fully compliant with Swiss data and privacy laws.
While the future holds seemingly unlimited uncertainty, there is a lot of opportunity to learn from what’s come before and to radically redesign the future of digital government.
The digital government field has an opportunity to build a more responsive and resilient government by pushing into new frontiers, with new tools, approaches, and even organizations that don’t exist yet. This is the time for radical experimentation, delivery, and exploration.
There is no question this is a Big Deal. If you are a university or research lab, or aspire to work in one, or are simply an enthusiast of federally-funded research, what’s next will matter.
The emerging federal metascience community is asking fascinating questions that are equally vital for democratic legitimacy: beyond “did this program work” to “how does the federal R&D enterprise itself work, and how could it work better?”
Get it right, and pooled hiring becomes a model for how the federal government decides what to do together and what to do apart. That’s a bigger prize than faster hiring. It’s a more functional government.