Businesses spend hundreds of billions of dollars a year to gather and analyze data about us as individuals — our heart rates, our credit-card spending, you name it. But there’s not nearly that level of understanding of us as a collective. The data is out there, yet city planners know almost nothing about us at the community level. So our mission is to improve the tools that are available to make better decisions with data about how to invest in our neighborhoods.

In many cities, there’s a team of trained GIS experts who understand mapping and geospatial data, but there’s often not a lot of healthcare or education or other experts who know how to make use of the data to understand the particular forces at play in those domains. When those experts do try to find data, they often have to go through the GIS folks who may not get back to them for weeks, often not with the information they need. So mySidewalk has created a data warehouse that draws on 65 sources including the Bureau of Labor Statistics, the CDC and the Census Bureau, and created tools that help non-technical people see trends in the data that had previously been invisible.

Many of our customers use our platform to help them compete for federal grants. Dayton, Ohio, for example, won $138 million dollars in competitive grants last year. They used our data to make sure they understood their areas of greatest need, and then used our storytelling tools to state their case in an objective, powerful way that many communities weren’t able to. This is important, because grants often go to the communities that can afford to have grant writers on staff. So those with more resources are better able to get federal dollars, which just increases their advantages over places that might need the help more.

A revolution in economic development started after the sweepstakes over Amazon’s second headquarters a few years ago, when there was one winner and a whole bunch of disappointed city leaders. Clearly, there had to be a better way. Then the pandemic accelerated the move to new ways of working, including more people starting microbusinesses. But cities had no way of knowing what was actually happening with microbusinesses in their communities. The Chamber of Commerce didn’t know, nobody knew. With the Venture Forward data, cities can see where these entrepreneurs live, their education levels, their biggest challenges and opportunities. All of a sudden, they have the information to design programs to serve these peoples’ needs.

For example, many of our suburban communities suddenly have a daytime population that’s a lot higher than before because people are working from home, but they are amenity deserts. That has major implications for how you think about zoning, about how you get these home-based businesses everything they need within a 15-minute drive. That’s a much better approach than just trying to lure businesses from another city.

We have officials who use it, such as fire chiefs who use our fire prevention analysis tool to understand which parts of their community are most ripe for interventions to prevent fires, like understanding which neighborhoods take the longest time to reach from a fire station. Then there are the analysts across different fields and sectors who tend to do the most interesting research with our data. Healthcare is one sector I’m particularly excited about, to support a growing interest in using place-based data to learn more about patients. And our report generation tool lets government agencies, like Public Health, turn the data into stories for the general public, in a way that’s understandable to the layperson.

We’ve been through a decade when cities were just posting all their data onto open portals, which is admirable, but where insights can be hard to find. There were no schemas, no common way of looking at the data. But schemas and structure matter. We’re working with partners like the National League of Cities and the National Fire Protection Association and other national advocacy organizations to standardize the way we collect various kinds of data. It’s a data maturity thing, as much as anything.

One of our employees posted an article on our Slack channel, and it caught my eye for two reasons. One, it sounded like a unique dataset. And two, it was clear to me that there was a team of people there that cared about the same things we care about. So while I don’t usually do a lot of our prospecting for new sources of data, I reached out to the Venture Forward team and it was immediately clear that this could be cool – that we had an audience that would be really interested in their data and could put it to good use.