About
A diagnostic, not a ranking.
Public sector innovation in the United States does not fail for lack of ambition or talent. It fails because government’s operating model — how it procures, hires, organizes, and coordinates — was designed for industrial-era stability and cannot meet modernity’s demands. This tool exists to make that structural diagnosis legible: it maps the institutional terrain a government operates within, surfaces structural peers, and points at the highest-leverage next moves — for practitioners and innovators inside and outside government.
01 · The diagnosis
What we observe
77% → 17%
Federal trust collapse (1964 → 2025)
47.2 yrs
Avg federal civilian age — 30% retirement-eligible within 5 years
94 / 36 days
Federal vs private IT hiring — operating-model mismatch
65% / 3%
Investment at Parameters (lowest leverage) vs Intent (highest)
American government operates on an industrial-era model — hierarchical agencies, classification-based civil service, milestone-based procurement, jurisdictional silos. That model worked when problems were stable, predictable, and bounded. Modernity’s problems are none of those. The visible failure surface — collapsing IT projects, aging workforces, stalled programs, eroding public trust — reflects that structural mismatch, not separate dysfunctions. And yet the redesign ecosystem is unusually robust: state digital service teams, regulatory sandboxes, benefits-delivery infrastructure at national scale, and the first philanthropic capital dedicated to civil-service and procurement modernization. These are early prototypes of the next operating model — built in pockets, not yet systematized.
The operating-model inversion
Where public-sector innovation investment actually flows
Using Donella Meadows’ leverage-depth framework: 65% of investment lands at the lowest-leverage Parameter level while the highest-leverage Design and Intent levels sit systematically under-resourced. Until those layers are addressed, additional Parameter-level investment compounds the mismatch rather than resolving it.
Funding levels, salary adjustments, class-size mandates
Quality reporting, FAFSA simplification, school ratings
Procurement architecture, civil-service redesign, coordination infrastructure
Operating-model paradigm, government-as-platform, redefining institutional purpose
Investment pattern across US public-sector innovation, mapped to Meadows’ twelve leverage points and condensed into four depth categories. The full field-level view lives in the systems map.
02 · The causal logic
What we believe
Public sector innovation fails because we treat structural problems as performance problems.
A city that can't adopt an open data policy isn't slow or unsophisticated. It may be a Dillon's Rule city without legislative authorization. Naming the structure is the first move; without it, every recommendation lands as either obvious or impossible.
Higher-leverage moves require structural diagnosis first.
Pathway recommendations untethered from binding constraints produce churn, not change. Knowing the leverage depth of an intervention — Parameter vs. Feedback vs. Design vs. Intent — is as important as the intervention itself.
Cities don't need rankings. They need to know which other cities share their binding constraint.
Comparison along structural lines surfaces transferable practice. Comparison along population, region, or political color surfaces noise. Detroit and Gary share more with each other than either does with the demographically similar suburbs surrounding them.
Practice transfers across structural peers. It does not transfer across superficial similarity.
Two mid-size Sun-Belt cities with different home-rule status, different state preemption regimes, and different revenue structures are not actually peers — no matter how similar their populations look on a map.
Naming a binding constraint is itself an intervention.
Most city governments do not have a single shared answer to: what is the one thing most shaping what we can do next? The tool's first contribution is to manufacture that answer and put it in front of the team.
03 · The tool’s role
What the tool does — and is not
Cities are characterized by the structural conditions that shape what is possible, not graded on outcomes. Two cities with identical structural profiles can be on wildly different trajectories — culture, leadership, timing, and politics matter at least as much as anything captured here. The tool surfaces what is available in an operating environment. What actually happens depends on who shows up.
What the tool does
- Compress 40+ hours of structural desk research into a 5-minute read
- Surface structural peers and learning partners — not "similar-sized cities" or "regional peers"
- Align pathway recommendations to the city's binding constraint and to Meadows leverage depth
- Generate a starter Ambitious Impactful Mission template tied to actual operating context
- Make all six institutional dimensions and twelve community context categories legible at a glance
What the tool does not do
- Score city performance
- Publish a rank
- Predict innovation outcomes
- Substitute for practitioner judgment
04 · The framework · Layer 1
Six institutional capacity dimensions
What the city government itself can do. Captures the formal and statutory constraints on what kinds of moves are even possible.
04 · The framework · Layer 2
Twelve community context categories
The conditions the city is operating in — demographic, economic, civic, historical — that shape which institutional capacities matter most. Currently populated for the founding-cohort 26 cities; backfill for the top 50 US cities is in progress.
04 · The framework · Categorization
City clusters
Each cluster names the type of work the cities in it most need to do next — not what kind of city they are or how they rank. The four categories are descriptive, not evaluative; the assignment is structural.
05 · Downstream outcomes
What changes if this works
Practitioners spend less time diagnosing and more time delivering.
Hours of desk research become five-minute reads. Innovation team capacity gets redirected from "figuring out what's possible" to "executing the next move."
Cross-city learning routes around superficial peer-matching.
Detroit learns from Camden, not just from Cleveland. The peer logic is structural, so the transfer is structural — what actually works in one binding-constraint context tends to work in another.
Philanthropy and technical assistance providers target binding constraints, not familiar cities.
Capital and capacity flow to the structural problem, not to the network's address book. Cities outside the canonical philanthropic portfolio get matched into peer learning by their conditions, not their connections.
Pathway investment shifts toward higher-leverage Meadows depths.
Initiatives that change Design (procurement reform, civil-service redesign, citizens' assemblies) get visibility alongside the Parameter-level moves that currently dominate the conversation.
Practitioners can articulate what they need from outside their walls.
A city manager can name their binding constraint in a single sentence — and the specific partners required to address it. The tool produces vocabulary, not just analysis.
If even one of these shifts happens at scale, it justifies the tool. None of them happens without structural diagnosis as a precondition.
06 · Provenance
Data sources & methodology
Seven primary sources feed the diagnostic. Bloomberg City Leadership Initiative supplies the AIM template structure; Census, GFOA, and ALICE supply quantitative ground truth; Compass research and live web research fill the remaining gaps.
07 · Limitations
What this tool doesn’t capture
The diagnostic reflects what is legible in public records and structured data. Several important things sit outside that frame.
08 · The ecosystem
Key resources & partners
The tool plugs into a larger ecosystem of methodology, certification, peer learning, and civic-tech infrastructure. This list is non-exhaustive; the public-sector innovation field is large and growing.
Funders
Funders operating in this space (non-exhaustive) include Knight Foundation, Bloomberg Philanthropies, MacArthur Foundation, Ford Foundation, Rockefeller Foundation, Robert Wood Johnson Foundation, Schmidt Futures, Emerson Collective, and a growing network of community foundations that anchor local civic infrastructure on a per-city basis.
Want to shape the tool itself? Start with the five-minute feedback prompt.