Synthesizing data for equitable access to small business resources
Helping the Small Business Administration use data science and visual analytics techniques across several sources of cross-agency data to better serve the needs of underserved small business owners.
The U.S. Small Business Administration helps power the American dream of business ownership. As the only go-to resource and voice for small businesses backed by the strength of the federal government, the SBA empowers entrepreneurs and small business owners with the resources and support they need to start, grow, expand their businesses, or recover from a declared disaster. It delivers services through an extensive network of SBA field offices and partnerships with public and private organizations.
How can SBA identify and connect with entrepreneurs and business owners in greatest need – tapping into their community networks to help people keep their businesses going during the pandemic?
To help entrepreneurs and business owners recover quickly from the pandemic, the Small Business Administration’s (SBA) Office of Entrepreneurial Development sought to get information and grants in the hands of those who needed it most. To accomplish this, the SBA needed to drive awareness of available aid, especially in traditionally underserved communities.
Working with a data scientist from TTS’ Presidential Innovation Fellows (PIF) Program, SBA was able to identify the distribution of underserved entrepreneurial people participating in the Community Navigator Program and compare them with historical data to demonstrate the outcome and impact of this program. The Community Navigator Program provides services including financial assistance, access to capital, training and other resources to help stabilize or expand small businesses owned by veterans, women, and socially and economically disadvantaged individuals. Using data science and visual analytics techniques for quantitative and qualitative data across several sources of cross-agency data, the PIF developed a framework to analyze geographic and demographic data at a more granular level by incorporating additional datasets from other SBA programs and agency sources. This work also identified the frequently used languages used in small businesses served by this program and the need of multi-lingual service. The PIF partnered with other offices of SBA as well to map SBA eco-system and analyze and detect service opportunities in rural and urban areas.
This framework enabled SBA to set goals around equity, strategically partner with local organizations to conduct outreach in underserved communities, and improve access to the Community Navigator Program.
Making data work for people, serving the “underserved of the underserved”
Bringing in a PIF data science lead, the SBA was able to identify entrepreneurs in underserved communities and partner with local organizations to get people the resources they need. For example, thanks to targeted outreach of the program, a business owner in Salt Lake City, UT, received language assistance to help complete his Paycheck Protection Loan application.
Source: American Rescue Plan (ARP) Yearly Report. ARP Success Story: Using data to help small business owners recover from the pandemic