[Webinar Recap] Data-driven Decision-making
It all begins with city leaders leveraging better mobility data to make informed policy decisions.
That was the general consensus during a recent virtual panel discussion moderated by Mayor Stephen Goldsmith, advisor to Passport and professor of Government at the Harvard Kennedy School of Public Policy. He was joined by industry experts to discuss how cities should be using mobility data to create more livable communities.
- Marla Westervelt, Director of Policy, Coalition for Reimagined Mobility
- Emily Eros, Product Manager, Streetlight Data
- Lillian Coral, Director of National Strategy and Tech Innovation, The Knight Foundation
Here are some key takeaways from the session:
Equity and Access
In most urban areas, curbspace is often managed in an ineffective manner, leading to inconsistent pricing for things like parking and citations.
Maria Westervelt explained that it is important to first understand how assets are currently being used, and then determine a more optimized distribution of curbspace across populations based on needs. This results in pricing being aimed at specific outcomes.
Emily Eros echoed the sentiment, stating that proper asset allocation ensures policy goals are also being matched. For example, in cities like San Francisco and Seattle where they consistently monitor inventory, location-based data and how people are moving throughout the city are matched with equity goals.
Rethinking Transportation Data
People already provide a ton of data via their phones. But for cities, it is important to understand that data and to utilize it in a way that is attuned to privacy.
“It’s also about pushing information that is useful to people in real time,” Lillian Coral said. “Give them a better sense of how to move around their city.”
One of the ways this is made possible is by centralizing all data across the multiple platforms and systems cities use so they can compare their data with others, eliminating information silos.
Data Drives Policy and Technology
Eros explained how her company created a dashboard to help policy makers understand where they would install electric vehicle chargers based on different policy goals.
“Our concern was that if we keep putting them where intuitively we think chargers should go, or where the utilization will be high,” she said, “then you end up with a ton of chargers where more affluent people end up shopping or going.”
Instead, Eros’ company has built a tool that uses movement data coupled with demographics, air quality, electric vehicle ownership and existing charger locations to help determine how to proceed with installing chargers.
“This tool doesn’t take a position on where these chargers should go, but it depends on your policy goals,” she added. “If we can show you six different maps of where you might put them based on what you care about, it gets policy makers thinking about [their] goals and how to shape their policy based on what their equity goals are.”
Harnessing the Power of Big Data
City officials struggle with the amount of data that is handed to them, so it is important to organize and validate it by extracting insight.
“We get a large volume of data, and have to aggregate it up to the street level so that we are not focusing on individuals,” Eros said. “But if we have a small sample size, how do we extrapolate this into volume for a particular roadway? That’s where a data science team comes in to continually do validations and characterizations.”
Insights are needed from both private and public sectors to figure out how people are moving around our cities, and how we in turn, provide better services for them. One way is to aggregate the data that is collected to help shift policy.
Watch the on-demand webinar.