As COVID-19 made its way through communities across the country this year and last, two things became clear: All communities were not impacted equally, and the health and social sectors didn’t have the right data to predict or measure — let alone respond to — that fact.

The data these organizations would have needed is disaggregated. 

Disaggregated data has become a bit of a buzz term over the past year and a half, but it’s for good reason. So, what does it mean? Any data that’s broken down into subcategories. The kind of disaggregated data a social purpose organization might use to design programs and services or to advocate for its community might include data that’s broken down by race, gender, sexuality, income, education level, and other socioeconomic factors. 

The problem, Future of Good is hearing from changemakers across the country, is that such data just doesn’t exist. And where it does, it’s inaccessible. 

There’s a growing movement to change that — led by frontline and grassroots community organizations. Prime Minister Justin Trudeau even included a line in his government’s 2020 budget about creating a national disaggregated data plan. 

But how exactly would social purposes use disaggregated data to inform their work? How do the organizations who are already using it do it? What are the ways the social sector’s COVID response could have been more equitable if disaggregated data were informing it? And what are the ethical considerations when it comes to collecting this kind of data?

Future of Good writers will dive into all this and more in an upcoming member-exclusive special report — coming early November. 

Join the member community today to make sure you have access to this special report.