Data in the Quest for Equity
Some fear that as cities increasingly tap into the power of data to improve services, they risk dehumanizing the work and leaving vulnerable residents behind. But in fact, well-managed cities across the country are actually proactively pairing data with a resident-centered focus to understand gaps and drive more opportunity and access. Simone Brody is the Executive Director of What Works Cities, a Bloomberg Philanthropies initiative helping US cities improve residents’ lives by using data and evidence effectively. At this year’s Code for America Summit, Simone took the stage to speak about how data can—and is—being used to address inequities and reach our most vulnerable populations.
“Data didn’t always illuminate answers. Sometimes it just illuminated the right place to start a conversation. It identified the problem and it gave us quality, nuanced information with which to chart a path forward.”
Before joining What Works Cities, Simone worked at New York City’s Department of Education during the Bloomberg administration. She spoke at length about the many ways they used data to unearth and examine painful disparities in a school system that educates 1.1 million children every year. Disaggregated data helped dispel some false but widely held beliefs about their schools, and helped educators and school leaders make better decisions by enhancing judgments that can be clouded by inherent biases. And the data- and evidence-driven approach wasn’t restricted to the Department of Education—similar strategies were improving outcomes all across the city.
“We need to be really honest about what the data tells us. Sometimes it reveals failure, and we have to use what we learn from those shortcomings to change course and iterate until we get it right.”
After Mayor Bloomberg left office, they received a huge amount of interest from cities that wanted to adapt a data-driven approach to all of their service delivery, in education, in blight, in public safety and even in climate change. That’s the mission of What Works Cities: they empower and enable cities to use evidence and data to deepen their understanding of the needs of their communities, to use that understanding to design and deliver services more equitably, and then to track their progress so that they can direct precious resources most efficiently. And not just major metropolises, but cities of all sizes in all corners of the country.
“Data and technology just are not enough… [They] can, however, be an indispensable tool to inform robust conversations and a deep understanding of the real needs of residents and to create a foundation for innovative policies and programs.”
To hear more about the kinds of initiatives that Simone’s team is working on, watch the video or read the transcript below.
Great. Good afternoon. Hi, everybody. I’m Simone Brody, Executive Director of What Works Cities, and I’m thrilled to be here today to talk with all of you about data, the stories it tells and the way it can really drive change to improve people’s lives.
This isn’t a crowd that needs a lesson in the power of data. I think the agenda for this conference really reads like a wishlist for data junkies and good government geeks like myself. So, I thought I would use the time to talk about how data can and really is being used to reach our most vulnerable populations and really address equity.
And I want to really push back on a criticism that we hear a lot, which is that being data-driven is somehow the opposite of being human-centered. I think the reality is the best use of data really contributes to more meaningful engagements. It sparks conversation, it spurs innovation, and it really enables us to talk about this work in a more meaningful way.
And so, here, I think among the true believers, we really understand how digital technology can transform the way we provide services in government. We understand how data can help us really meaningfully understand the needs and the people of our communities, and we understand it because we see it every single day. I know that I really do.
Before I joined What Works Cities, I worked in the New York City Department of Education during the Bloomberg administration. Mayor Bloomberg took office in 2001, if not at quite the dawn of the digital age, then very early in the morning. We were just beginning, in City Hall, to really understand the power of the internet and data to address our challenges.
But Mike Bloomberg had already started, really, a data revolution in the financial sector, and he was determined to translate that into how New York City could approach its problems very differently. And in a city as big and diverse and, frankly, unequal as New York, addressing education was one of our biggest challenges.
There isn’t much that’s more important to the future of a city than the 1.1 million children that are its future. Yes. In New York City, we educate 1.1 million children every year.
So, we launched a massive change operation to improve low performing schools, to empower accountable educators and to engage students and families. And it was such an exciting time.
We were working to dramatically improve outcomes in New York, and we were seeing real progress. More kids were on track in elementary school, more kids were graduating from high school and more kids were enrolling in college.
What we did not see enough of was equity. We were making progress, generally, across the city, but somehow we were still missing some of the hardest to reach and most vulnerable kids. Achievement gaps between students of different races, different levels of privilege, were not closing quickly enough, and we really didn’t understand why.
So, to find out, we turned to data, of course not for the first time, but in a very different way. For the most part, we had been looking at data across the city by race and sometimes by district. So, we saw test scores, we saw graduation rates, we saw the broad strokes, but we didn’t really understand the nuanced picture of what was happening in specific communities.
And so, we needed to go deeper. And to do so, we really needed to disaggregate the data, to break down this very large system into individual students and small groups of students to understand what was happening. And that made people, frankly, very nervous.
On the one hand, people were worried that looking deeply into the data would contradict some of the great claims of progress that we were making. And our answer to that was that any lack of progress, anybody we were leaving behind, was not enough, and we needed to understand what that looked like.
And on the other hand, some people were really worried that poor performance among disadvantaged students would perpetuate an idea that these students couldn’t keep up. We knew that was false and we knew that we could prove that was false.
So, we started digging deeper into the data. And sure enough, we saw really painful and real disparities. We could see pockets of exclusion that were leading to poor performance. We could see which kids were falling behind and when, and we could even begin to understand why they were falling behind.
I’m going to give you one example. As we began to look at city-wide test scores broken down by where children lived, we saw that students in temporary housing, and that is one in 10 students in New York City, 100,000 students, were half as likely as other students to be on-track in elementary school.
It’s obviously a really sad statistic in and of itself, but to make it worse, you have to understand that students living in temporary housing move more often than other students, and often they move much more often than other students. And what we saw when we went deeper was that vital information about what these students needed to succeed was not getting passed on to their additional schools as they moved.
Sometimes it was academic information and sometimes it was information about what they needed to feel safe and come to school really ready to learn. That could be a meal, it could be an adult they could trust or it could be somebody to communicate with their parents about what their schoolwork was.
And even schools that were tracking information to help students succeed often weren’t passing that information on to other schools. And especially for vulnerable kids, that means a lot, because a child who falls behind in a core subject like math or reading might never catch up.
And so, it should come as no surprise that fewer than one in two of these students were graduating from high school. And that’s how vulnerable kids fall through the cracks. It’s how futures are lost and it’s how these intergenerational cycles of poverty are perpetuated.
And so, imagine, and we imagined, how different outcomes could be if crucial information was part of the enrollment data that every school must collect and connect to that student as they’re moving schools. What we saw in our work was that data didn’t always illuminate answers. Sometimes it just illuminated the right place to start a conversation. It identified the problem and it gave us quality, nuanced information with which to chart a path forward.
Disaggregated data also gave us information with which to approach educators and school leaders, many of whom were not even aware of the widely disparate outcomes of different groups of students, and who often used mostly intuition in their decision-making. To be clear, data are never a substitute for the powerful judgment of educators based on experience, but they are vital information to enhancing that judgment, especially when we do know that often that judgment can be clouded unknowingly by the inherent biases of our systems.
By the same token, data also helped us dispel some false and really harmful beliefs, for example, that the challenges schools faced in disadvantaged communities were just too entrenched for them to tackle. Better data helped us see and learn from schools that were dispelling and defying that narrative. It helped us prove that, of course, schools with predominantly disadvantaged kids could and were, all across the city, excelling, and it enabled us to share what those schools were doing to help other schools learn.
I’m very behind on my slides. It showed us that smaller schools produce dramatically better results than the massive schools that previously dominated low-income communities, that school choice had the potential to change the terrifying reality that zip code could determine a student’s outcome, but that school choice alone was not the answer.
It showed us that small class sizes weren’t the magic bullet that many people believed they would be, but that maybe teacher quality was. And lessons like these informed our work and work across the entire school system. We identified risk factors for dropping out of high school or not applying to college and we used them as flags across the city so that teachers could immediately work with students at risk before they were disengaged.
The data- and evidence-driven approach wasn’t restricted to the Department of Education. Similar strategies were improving outcomes all across the city. And when Mayor Bloomberg left office, we saw so much interest from cities that wanted to adapt a data-driven approach to all of their service delivery, in education, in blight, in public safety and even in climate change. And not just big cities, all cities.
And that is the mission of What Works Cities. We empower and enable cities to use evidence and data to deepen their understanding of the needs of their communities, to use that understanding to design and deliver services more equitably, and then to track their progress so that they can direct precious resources most efficiently. And it’s happening in cities all over the country, not just in big cities like L.A. or Boston, but in cities like Fayetteville, North Carolina, Bellevue, Washington, and Arlington, Texas.
Let me give you two examples of the kinds of programs I’m talking about. Consider 911 and ambulance response times. EMS personnel respond to roughly 37,000,000 911 calls across the country every year.
And nationally, patients wait an average of seven to eight minutes for an ambulance after a 911 call is placed. But that is just the average. Recent studies show that ambulance response times in low-income communities can be nearly four minutes longer than in high-income communities.
And as we know, when every minute counts, this can literally be the matter of life or death. In fact, studies cite the gap in response times as a potential driver of income mortality disparities across the country.
Virtually every city in the country struggles with this challenge of reducing response times without incurring unsustainable expense. How do you do it without buying more emergency response vehicles or increasing the number of first responders? And a deeper look at the data is helping some cities change their approach to this problem. Memphis, Tennessee is one such city.
As the city started examining how it could improve ambulance response times, it began to see evidence that too many ambulances were being called in non-emergency situations. And as staff dug deeper, they began to understand that many residents simply lacked information about how to solve their pressing challenges, but they did know how to reach 911. So calls were placed and ambulances were dispatched when what callers really needed was somebody to drive them to the doctor or to have a nurse tell them how to handle a situation at home.
As one city official put it, these callers were not abusing the system, they just didn’t know where else to turn. As a result, up to 20% of ambulance calls could have been solved in another less resource-intensive way. Armed with this data, the city of Memphis piloted a new program to dispatch a paramedic in a cherry red SUV to conduct an onsite medical exam in non-emergency cases instead of sending a costly ambulance and a full response team to every call.
Tracking data shows that this program is working. Response times in Memphis are down, people are getting the right level of care no matter where in the city they live and costs are not going up. It’s a great example of how data can help define a problem and innovation can help design a solution that works for everyone. Virtually all cities struggle with this question of how to make services more accessible and more affordable, and the idea that data and innovation can help is really catching on.
Tulsa, Oklahoma is another great example. In 2008, the city’s mayor commissioned an Equalities Indicator report to begin what he called a community-centered conversation to make services and outcomes more equitably grounded in standardized data.
One of the most glaring examples of inequity was an 11-year disparity in the average lifespan of residents in the wealthiest and poorest zip codes in Tulsa. As the city dug deeper into the numbers, they began to wonder whether improving housing options for residents might help close this outrageous gap.
So, equipped with its own disaggregated data and other studies, the city began to rethink the way it allocated Community Development Block Grant funding, CDBG funding, for local housing initiatives. Many cities struggle with the best use of this limited discretionary funding to really advance stable housing in their communities.
Tulsa decided to shift from an equal approach to funding, where funding was going to all of the neighborhoods regardless of need, to an equitable approach, with funding really going to the neighborhoods with the greatest need and the highest levels of poverty. Now the city is working to establish a partnership with community organizations to help evaluate the effect of this increased funding on mortality rates in their poorest communities.
And this is how progress reaches everyone. The cities we work with, and the partners who support our work, share our conviction that we cannot solve our biggest problems unless we understand the underlying causes of those problems and the people whose lives are affected by them.
And contrary to the common belief that data dehumanizes this deeply human work, it actually does the opposite. It enables us to see into the real lives of individuals, so many of whom are overlooked or obscured by looking at the big picture. It enables us to make our efforts laser-focused, right-sized and truly able to meet the needs of the people we intend to serve. If you start with a big question and use information to engage your community and drill down to the core of it, and then test and measure potential answers to that question, hand-in-hand with your community, data is the most powerful and efficient tool we have to solve some of our nation’s biggest challenges.
So, what do I want you to take away from all of this? I think, first, that this is such an incredibly exciting time for all of us in this room. New tools and ways of using data are actually changing the way we dissect and take bold action on problems in cities and communities across the country.
But second, that data alone really isn’t enough, as so many folks talked about this morning as well. Data and technology just are not enough. They neither should be ever used to distance government from residents or to replace the invaluable role of listening to people. It can, however, be an indispensable tool to inform robust conversations and a deep understanding of the real needs of residents and to create a foundation for innovative policies and programs.
And third, we need to be really honest about what the data tells us. Sometimes it reveals failure, and we have to use what we learn from those shortcomings to change course and iterate until we get it right.
And so, what can all of you do to help? City leaders, so many of you are doing this already, working so hard to use data and tech to address inequity in your community. If you’re already part of What Works Cities great, and hi. And if you’re not, let’s talk. I know there is great work we can do together and we have a range of free expert supports to help you improve how data can drive results in your community.
And tech community, as you know, government is the scale play here. It’s worth repeating. The best opportunity for your tools and strategies to reach those most in need is by truly collaborating with local government in the communities where you work. They are the front lines of solving these problems and you have a huge role to play in accelerating their efforts. Leverage your expertise to help cities better do their job. Share your data and go one step further. Help them to understand and use that data to meaningfully address these complex issues.
Where you lead, others will follow, and the future of our cities and of our country is riding on it. Thank you.