We recently submitted for a HUD grant, and needed to identify specific areas of potential lead remediation risk in Rhode Island. This type of scoring analysis could have been done over a couple of days with our small research team. Using the 3-Layer Map function on the PolicyMap tool, we were able to identify where the risk level for lead met the grant criteria – in minutes rather than hours or days. Nishi Kumar, Manager of Policy & Government Relations, RIHousing
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Challenge

RIHousing’s policy and research teams needed a way to track impact of their programs and investments against indicators of household income, housing stock, and changing housing costs. Rather than allocating days and expense of researcher time and GIS expertise, they sought a more efficient way to conduct spatial research and apply for grants. They also needed a way to succinctly and plainly communicate impacts of their work to Rhode Island’s state legislators. To advocate for affordable housing opportunity statewide, RIHousing needed to quickly illustrate where residents are feeling pressed by housing cost burdens, where housing stock is aging, and where previous RIHousing investment might be leveraged.

Solution

RIHousing designed a PolicyMap embedded mapping tool for use by both elected officials and community members throughout Rhode Island. Through publicly available maps and data embedded in the RIHousing website, residents can navigate to their neighborhood and explore local housing stock, housing cost, and demographics data. Public access to the PolicyMap maps and data shines light on the state of housing affordability, stock, and quality throughout Rhode Island. Rather than spend hours downloading Census data and developing district-scale maps before meeting with a state representative, RIHousing researchers now use the same tool for internal reporting. Staff clicks on a district of interest, downloads a 2-page report, and comes well-prepared to public meetings and legislative hearings. The RIHousing PolicyMap report is also used to test assumptions around affordable housing. One state representative required an accessible way to generate district-wide data – to argue, ‘yes, we do need affordable housing investment here – there are low-income families, they are cost burdened, and the cost burden has grown over time’. This reporting tool has allowed her to challenge perceptions of affluent communities in her district using the reality of what local data shows. (Find more information of the $8.4 million grant from HUD here.)