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One foundation’s quest for better demographic data

Two women sitting at a computer analyzing data and looking at charts together

We are in the midst of a timely and important discussion in philanthropy about increasing support to organizations led by people of color and women. However, many grantmakers like the Charles Stewart Mott Foundation have lacked access to the empirical data on race, gender, and other characteristics of leadership in the organizations we seek to fund. Far from a check-box approach of counting heads, Mott and many other funders want deep and meaningful information that can lead to specific actions to do better in terms of diversity and equity.

Over the last six months, we have worked with Candid to implement several of its tools to achieve our goal at the Mott Foundation to be more data driven in our diversity, equity, and inclusion efforts. Rather than create yet another custom reporting requirement for applicants and grant recipients, Mott is helping to lead a growing movement of grantmakers who use the ready-made and scalable demographic profile reporting within Candid’s GuideStar tool. Through GuideStar, Candid possesses the single most cost-effective and scalable solution for philanthropy to understand the demographic characteristics of grantee organizations.

GuideStar provides a platform where all U.S.-based 501c3 organizations can “claim” their profile. The basic profile already exists on the portal using IRS reporting. By claiming their profile, nonprofit organizations can self-identify the demographic characteristics of their board, management, and staff.

Rather than maintain a static database of individual organizations’ information, Candid has created developer tools to allow the data to be exported so that others can aggregate, analyze, and incorporate the information. With the API/developer tools, Candid has created a pathway for GuideStar data to be scalable and to help promote transparency and reduced burden on nonprofits. Now, for instance, grantmakers can easily incorporate full integration of the demographic data from GuideStar into grants management software used by many funders.

Beginning earlier this year, Mott Foundation requested that all grant seekers and grant recipients who are U.S-based 501c3 organizations update the race and gender data in their GuideStar profile. This simple, one-time action by the grant seeker reduces burden and increases scalability because updating the profile allows the data to be used by all funders, donors, researchers, advocates, and anyone else who views it on GuideStar.

To make the data useful to Mott staff and leadership, however, required some effort. Our team worked to migrate the data into Fluxx, our grants management software, and to PowerBI to aggregate and visualize the data. Candid’s API, for a reasonable fee, allowed us to build real-time and automatic integration of the data into the workflow tools for all program staff and management. We can now see, along with other critical grantmaking information, whether an applicant or grant recipient has entered their demographic data in GuideStar. We can also see what that data tells us about the race, ethnicity, and gender of the organization’s staff, management, and board. Lastly, we can now roll that data up and use visualization tools to see the aggregate profile of who we support.

Using the API/developer tools from Candid, we finally have the ability to know with certainty how well we do in supporting Black-led, minority-led, and women-led nonprofit organizations. We can also feel good that we are not increasing the burden on individual nonprofits to provide yet another custom form for all funders. Nonprofit organizations claiming their GuideStar profile, and funders like Mott using the API/developer tools, creates an easy, cost-effective, less-burdensome, and scalable solution to be more data driven around diversity, equity, and inclusion.

Click here for more information on Candid’s APIs and its newly-launched portal for developers. Candid has prepared user guides to help foundations standardize demographic data collection.


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