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Think nationally, act locally: How to use data to close equity gaps

People protest while standing with doctors, nurses, medical professionals, and state lawmakers in support of health equity in New York state as communities recover from COVID-19 during a “EQUITY” art installation at the state Capitol, Friday, April 8, 2022, in Albany, N.Y. (AP Photo/Hans Pennink)

Racial and ethnic inequities are a global issue: No geography can say it has resolved them. But the way these problems manifest themselves — in areas such as education, food security, internet access and housing — is intensely local. 

Recently, McKinsey compared national data to that of eight U.S. cities with large Black and Hispanic populations. One finding was that there can be stark differences not only from state to state and city to city, but even neighborhood to neighborhood. And that led to a conclusion: All of this local data must be included as a source of insight to deliver change that improves people’s lives.

Sorting through the data can be difficult. Local leaders may be tempted to choose whatever topic is in the news, or worse, to rely solely on their intuition. How to make sense of it all? And where to start?

Here are three steps that can help.  

Determine where the equity gaps are. Numbers are a way to paint a picture — and the more numbers, the richer and more precise that picture will be. That means collecting not just the usual data, such as high school graduation rates or median household income, but less obvious indicators, such as access to transportation, technology and fresh groceries. And to uncover underlying trends, it’s important to understand not only racial and other demographic differences, but how the metrics are changing over time, and how they interact and often reinforce each other.

For example, data from U.S. Census American Community Surveys show that while the overall poverty rate fell in Washington, D.C. between 2014 and 2019, that of Black residents (26 percent) remained more than four times higher than for non-Hispanic white residents (6 percent). The disparity is even greater when it comes to households with children: a 32 percent poverty rate for Black households, compared to just 1 percent for non-Hispanic white households. This suggests that, in terms of defining future action, there needs to be a better understanding of the relationship between children in the household and poverty.

Understand conditions at the neighborhood level. Neighborhood-level data can help pinpoint where the most acute challenges are. In Houston, tech access is a challenge overall, but taking a city-level view misses stark disparities. For example, the Bellaire and Gulfton neighborhoods are side by side. But in Bellaire, which is majority white, there is almost universal broadband access and almost no children in poverty. In Gulfton, which is nearly 90 percent Black and Hispanic, more than half of the children are growing up in poverty, and almost as many households lack broadband. A city or regional effort to improve tech access, then, could be directed at places like Gulfton.

It’s also important to remember that when a neighborhood is struggling on one metric, it is likely struggling across others as well. Understanding a neighborhood at a high degree of detail can reveal incremental insights on where to focus.

Compare performance to peer cities. Understanding how a city compares to peers on a given topic can lead to useful insights and ideas for action. For example, Dallas has better overall food security performance compared with other cities but has greater food inequities, with Black residents three times more vulnerable than white residents. Philadelphia, on the other hand, has worse overall food security performance compared to peers, but the inequities are smaller, with Black residents twice as vulnerable. The two cities might therefore want to take different approaches, with Philadelphia choosing to make citywide interventions on food security and Dallas focusing more on Black residents.

Racial and ethnic inequities are not new problems, and it is heartening that in the past three years, a number of communities have promised to do more to address them. But good intentions are not enough. Collecting the right data, historical context and robust resident perspective is crucial. Further, knowing the historical context — why specific problems have emerged — is critical. And so is listening to people’s local experiences, as inequity is not an academic issue, but one that affects people from birth through old age, with a compounding impact. And all of this knowledge needs to be put to work, whether that is focusing on a specific problem, such as reducing evictions or trying to move the needle in a broader domain, such as health care.

By understanding where their most urgent equity gaps are, local leaders can do a better job of setting priorities — and delivering real change.

Darius Bates is a partner in McKinsey & Company’s Atlanta office.

Tags Income inequality in the United States Politics of the United States Poverty in the United States Racial inequality in the United States

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