Your City Has Better Metrics Than Ever. So Why Is Nothing Getting Fixed?

I recently started listening to the All In podcast, which leans toward a certain tech-libertarian center-right sensibility. Not my usual media diet. A recent episode featured Matt Mahan, the mayor of San Jose who is running for California Governor. He seemed grounded and non-ideological. His pragmatism seemed genuine. He talked about homelessness, housing, and public safety.

To be clear: this piece is not a political statement, and I am not taking sides on his candidacy. What his episode stirred in me is a question that has nothing to do with Mahan specifically — and everything to do with how we think about leadership, policy, and change.

Dashboard For Accountability?

Mahan kept talking about accountability. One of his signature accomplishments as mayor is a set of public-facing dashboards: one tracking homelessness spending and outcomes, one covering public safety and city services, and a performance-based budgeting system tying departmental funding to results. He partnered with Bloomberg Philanthropies to expand this into a citywide data strategy.

This seems good governance. In a political culture where public money disappears into programs that are never evaluated, a mayor who publishes the results deserves credit.

But here are what such dashboards cannot tell you:

—> why the number is what it is, whether you are measuring the right thing, how long to wait before concluding something is not working, or which trade-off to make when two numbers pull in opposite directions.

A dashboard is a window. But you also need to understand the landscape you are looking at.

Jane Jacobs Was Building a Different Kind of Dashboard

In the 1950s and 60s, American cities were being remade with great confidence. Urban renewal was the policy of the era. That about clearing the slums, building highways, and erecting towers. The metrics looked pretty good. Units demolished, roads built, federal dollars spent.

Jane Jacobs watched this from her street in Greenwich Village and understood something that planners, designers and politicians did not: the metrics were measuring the wrong things.

The planners were tracking outputs. She was watching what cities actually needed to live: mixed uses, short blocks, density that generates safety through human presence, the informal interactions that make neighborhoods economically vibrant. She published The Death and Life of Great American Cities in 1961. The people destroying those cities had not read it. And, now our leaders (whether they’ve read the book or not) are dealing with the consequences.

The result was not a data failure. It was a failure of understanding how cities actually work. The accountability infrastructure of the era was capable of reporting that the highway got built. It had no mechanism for asking whether building the highway was the right intervention — because that question requires understanding how cities function, how communities hold together, who is left off, and how economic life organizes itself.

The Same Problem, A New Era

I have sat in rooms (policy conversations, funding committees, planning sessions) where we decided how to allocate $100 million dollars of public funding. And I can tell you honestly: we often did it without a clear picture of how the thing we were funding actually works. Not because we lacked data. Because we had not asked the harder question underneath the data:

—> What is the mechanism that connects this investment to the outcome we want?

Think of it like a doctor prescribing medication. Data tells you a patient's symptoms and lab results. But treatment requires understanding how the body works. Like what causes the condition, how the drug interacts with the system, what the side effects of each choice will be. Without that, you are not practicing medicine. You are guessing with a stethoscope.

That is what I mean by understanding how things work. But, yes, understanding the theory. But, don’t see it as a pure academic thing. It’s about: why housing costs what it does, how regional labor markets shape where people can actually afford to live, how energy grids fail and recover, how homelessness is produced and resolved. This kind of knowledge does not live in our dashboards. It lives in the hard-won lessons of what has been tried, where it worked, and where it collapsed. And, many of them are mentioned in the history and theory books that we don’t read anymore.

Jeffrey Pressman and Aaron Wildavsky, in their foundational study of a federal jobs program in Oakland, found that policy failures were almost never about bad intentions or missing data. They were about a failure to understand the chain of dependencies connecting the intervention to the intended outcome. Every handoff, every assumption, every actor whose cooperation you needed but did not have. When you do not understand that chain, you cannot navigate when things go sideways. You can only watch the dashboard and wonder why the numbers are not moving.

The Trade-Off No Dashboard Can Make

There is a moment every serious practitioner recognizes. You have done everything right. Set goals, built accountability systems, removed barriers. And then reality arrives: a labor shortage, a legal challenge, a community that experiences your intervention differently than you intended. You are standing at a fork with no clear signal from your data.

In that moment, what you need is not a better dashboard. You need to understand the system well enough to reason about the fork, and the confidence to make a trade-off and own it. Housing or energy or homelessness policy always involves choices: speed versus targeting, regional coordination versus local control, short-term cost versus long-term resilience. Those choices cannot be made well without understanding what drives the outcomes you are chasing. The data shows you the fork in the road. Understanding how the system works (the theory behind things) tells you what is likely to be around each corner.

Knowledge is Power. And, Is More Accessible Now.

Here is the genuinely new thing: that knowledge has never been more accessible. And, we all can (and must) use it to push for better policies. To push back on half-baked ideas that result in allocating millions of dollars to public funds on things that don’t work.

For most of policy-making history, the gap between hard-won expertise and political practice was partially (not fully) because of access to knowledge. The books were long, the research dense, the translation from insight to action required years of specialized training. That barrier has fallen dramatically. AI has not replaced deep expertise, but it has lowered the cost of (and time for) accessing its core insights enormously. A policy director preparing a housing proposal can now surface the key debates, understand the historical precedents, and identify the mechanism questions that need answering in a fraction of the time it once required.

There is less excuse than ever for making consequential decisions without grasping how the thing you are trying to change actually works.

What We Should Ask

We should not expect a governor to be a housing policy nerd, an urban economist, or an energy systems theorist. That is not the job. But we should expect that governors, their advisors, and our legislators build policy from a foundation of understanding and knowledge. Not just what to measure, but why the intervention should work, what trade-offs it requires, and what kind of enabling environment will let implementation succeed over the years and decades that real results require.

Mahan's dashboards make the invisible visible. That matters. But Jacobs also created the foundation for a different kind of dashboard: one that tracked what actually makes cities live or die, not just what governments do to them. The planners of her era had their metrics. What they lacked was her map.

The goal is to have both.

ONE BIG IDEA

A dashboard shows you what is happening. Understanding how things work tells you what to do when the numbers stop moving. Without the second (i.e. theory), the first is just a well-documented guess.

ONE THING TO SIT WITH

Bad policy often does not come from bad intentions. It comes from unexamined assumptions about how things work, and, lack of incentives to go deeper. Policies sometimes go unchallenged because no one in the room knows enough to push back.

ONE PRACTICAL ACTOIN

Next time you encounter a plan or policy proposal, before it gains momentum, ask one question: What exactly has to happen, in what sequence, for this to produce the outcome we want? If no one can answer it clearly, that is your pushback.

Last week, I released this self-assessment tool to help you deisgn more effective programs, plans, and policies. To help you Strategize, Learn, and Measure for Community Impact.

Answer honestly and you will walk away with a personalized snapshot of where your program stands: what is working, where the gaps are, and a practical set of next steps tailored to your context and stage.

No login required. No email needed to see your results. Takes about 5 minutes.

See your readiness profile and personalized plan here.

Think of it as a starting point not a diagnosis. I hope it helps you reflect, understand where you are, and figure out where to focus next when designing or implementing your program.

Looking for ways to measure your community impact?

Nader Afzalan, Ph.D.

Founder and CEO, The Triangle

Program Director, Sustainable Environmental Design, UC Berkeley