Program Journey

Cities around the world are entering a new era of data and AI. While many have built policies, tools, and governance structures, few have had the chance to test, adapt, and learn how data and AI actually work in real‑world city government. The Bloomberg Philanthropies City Data Alliance (City Data Alliance or CDA) helps cities move beyond planning and into practice.

Led by the Bloomberg Center for Government Excellence at Johns Hopkins University (GovEx), the City Data Alliance equips city teams to apply data and AI responsibly to solve resident problems, manage risk, adapt to change, and scale solutions that work. Since 2022, the City Data Alliance has partnered with over 80 cities in 12 countries, representing 78 million residents, building deep, practice‑based insights into what it takes to use data and AI effectively in city government.

What cities do

Cities enter with a resident‑facing problem that has been difficult to solve. Through structured support, coaching, and practical tools, teams:

Translate a resident-facing problem into a focused project

Refine a known problem into a clear, testable solution with defined users, constraints, and indicators of success.

Prototype to explore and narrow potential solutions

Use low-fidelity tests to explore multiple approaches, surface assumptions, and identify what solution is worthy of further investment.

Design, build, and test a solution

Create and pilot a minimum viable product (MVP) informed by user needs, real constraints, and implementation realities.

Strengthen capacity for sustainability and scale

Deepen skills, judgement, and internal city practices while developing a playbook that enables the city to sustain, adapt, or expand the solution.

Through this work, cities generate real‑world evidence, build confidence in their approach, and leave with a validated, resident‑centered solution and a practical foundation for long‑term impact.




Program Structure and Pathways

All cities begin with a focused scoping phase, then are invited to move into the pathway that best matches their readiness and goals:

Scoping Phase (June–August)

Goal: Translate a resident-facing problem into a clear, feasible project.

City teams focus on:

  • Identifying an actionable, high‑impact problem
  • Stress‑testing solution ideas against constraints and available data
  • Clarifying decision‑makers, ownership, and delivery capacity

Key support provided:

  • A scoping workshop to frame the project and evaluate feasibility
  • Strategic coaching tailored to city priorities and constraints
  • A peer clinic to surface risks, assumptions, and readiness signals

Scoping follows a predictable cadence, with virtual sessions twice per week during the first two months and weekly sessions in the third month as teams consolidate decisions and finalize the project and prototype direction. Between sessions, teams stay connected with CDA coaches and partners through a shared communication channel (WhatsApp, Slack, Teams, etc.) to address issues quickly and maintain momentum. At the conclusion of scoping, GovEx assesses readiness and recommends the next pathway..

Implementation Pathway 

For cities ready to build and test solutions

Cities in this pathway use time‑bound learning loops to iterate solutions in real‑world conditions. Support integrates strategic coaching and technical assistance with strong city ownership, working within existing delivery routines to strengthen lasting internal capacity.

Capacity-Building Pathway 

For cities strengthening foundational skills

Cities in this pathway receive tailored recommendations based on scoping, plus connections to Results for America’s What Works Cities sprints, self‑paced courses, and other resources to accelerate foundational data and performance practices.

Learning Loops

For cities in the Implementation Pathway

Learning Loop 1: Prototype (September–October)

Goal: Generate early evidence about which approaches are most promising.

City team focuses on:

  • Building low‑fidelity prototypes to test competing ideas
  • Gathering feedback from residents and frontline staff
  • Narrowing options based on evidence and feasibility

Key support provided:

  • Strategic coaching to assess findings and refine direction
  • Technical sessions to resolve data and implementation hurdles
  • Curated peer exchanges with cities working on similar problems

Learning Loop 2: Solution Build (November–January)

Goal: Develop a minimum viable solution that works within real operational constraints.

City team focuses on:

  • Translating prototype learnings into a working solution
  • Making explicit trade‑offs on scope, features, and timelines
  • Defining the pilot plan, user groups, and success criteria

Key support provided:

  • Strategic coaching for execution and decision‑making
  • Technical sessions for hands‑on development
  • An MVP workshop to define scope, trade‑offs, and good‑enough criteria

Learning Loop 3: Scale and Launch (February–March)

Goal: Test the solution in practice and prepare for long‑term ownership and growth.

City team focuses on:

  • Piloting the solution with real users in real environments
  • Tracking early outcomes and implementation lessons
  • Establishing governance, ownership, and paths for scale

Key support provided:

  • Strategic coaching and technical sessions
  • A peer clinic focused on lessons learned and sustainability planning
  • A demo day to showcase results and next steps with peer cities



How We Work

Cities often find that investments in data infrastructure alone don’t guarantee meaningful improvements for residents. Even well-designed interventions can fall short without a clear understanding of resident needs or testing in real-world conditions.

The City Data Alliance uses a test-and-learn approach that emphasizes:

  • Action: testing ideas early to understand what works
  • Evidence: generating data to validate assumptions and reduce risk
  • Iteration: adapting solutions based on what is uncovered

Working in learning loops helps cities explore options before committing, strengthen internal capacity, and build confidence in decisions. Structured scoping ensures feasibility, clarifies risks, and sets up delivery.




Participation Expectations

Cities commit to:

  • Completing a What Works Cities Data Snapshot if not already completed
  • Assembling a cross‑functional team with dedicated time, including data specialists and domain experts
  • Engaging in cross‑city learning through workshops, peer clinics, and convenings
  • Hosting an in‑city site visit after scoping for user testing or resident engagement
  • Participating in two progress check‑ins with the mayor and, where applicable, the city manager
  • Keeping momentum between touchpoints by coordinating with the City Data Alliance team through an agreed communication channel
  • Approaching the work with curiosity and a test‑and‑learn mindset



Who This Program is for

Cities best suited for the City Data Alliance typically:

  • Serve 100,000 or more residents
  • Have a mayor with at least two years remaining in office
  • Have a chief data officer or equivalent role
  • Demonstrate strong foundations of data use across services and functions
  • Show leadership commitment to using data and AI to improve resident outcomes
  • Can dedicate a team with decision‑making authority
  • Are open to being challenged in a supportive environment



Key Dates and Events

Welcome & Orientation Call

May 27 · Virtual

City Data Alliance Leads (with optional senior leader participation) meet with program staff to launch the program, establish expectations, and prepare for the scoping phase.

First Coaching Call

Week of June 1 · Virtual

Strategic coaching starts during the scoping phase, providing tailored support as cities clarify their project and readiness to move into testing and delivery.

Site Visits

September 1 - October 16 · In-city

Following the scoping phase, cities in the implementation pathway host a two-day visit with their coach to align city leadership, validate assumptions, and advance prototype testing.

CDA Lead Convening

January 2027 · Baltimore

An immersive gathering for city leads to synthesize learnings, share progress, and strengthen collective capacity across the global network.




What Cities Take Away

Cities leave with more than a single solution. They leave with a validated, resident‑centered solution; evidence of what works in practice; stronger cross‑department coordination and decision‑making; and a practical playbook to sustain, adapt, or scale solutions. Cities also join a durable peer network that extends learning beyond any one project.