2018 Impact Summit

Data disaggregation, in this context, is the process of breaking out large racial and ethnic groups like the five main groups used by the U.S. Census Bureau (American Indian, Black or African American, Asian, Latinx, and White) into smaller, more nuanced cultural, national, regional, or other sub-groups. Data disaggregation can help to inform questions about who has (or doesn’t have) access to various social services or amenities, how different groups of people experience a certain intervention or event, and/or how program outcomes or impacts vary by subgroup. Often, we need disaggregated data to help us understand complex social issues, because large race/ethnic categories just don’t give us enough information.
The purpose of this presentation is to illustrate how organizations use disaggregated data to inform their policies and programs, using real examples.