Philanthropy has a racism problem. It’s clear from the numbers: Just 7 percent of philanthropic dollars are awarded to groups that specifically serve people of color and others who are part of America’s increasingly diverse population.
The rapid growth of conversations in philanthropy on what diversity, equity, and inclusion really mean is a sign that many of us who work at foundations recognize the problem. But change will only come with concrete action. To guide that action, philanthropy needs to be able to understand the demographics of the organizations that get money and those that don’t, who gets served (and who doesn’t), and which communities get help (and which don’t).
With that data, grant makers can dive into the details and see where disparities are happening. Are organizations led by people of color asking our organization for grants? If they are, are they being funded or do white-led groups get most of the money? If we are funding organizations led by people of color, are the grant sizes comparable to those given to their white counterparts?
There are so many issues to explore, but those questions — which ultimately help grant makers understand how racist, sexist, and otherwise biased their practices might be — can’t be answered if they don’t have data.
Too Little Data
New research conducted by our organization, a coalition of grants managers from foundations nationwide, showed that only about half of philanthropies are collecting demographic data on the leaders of the organizations they support or reject — or on the communities their grantees are working in. In a report we have issued about our findings, we noted that myths abound about the collection of data. Many grant makers thought it was irrelevant or illegal to collect demographic data. Some also reported that their organizations lacked people with the skills to collect, interpret, and manage this information. Others said they were concerned the data was too piecemeal to be useful.
Even among those grant makers that are collecting demographic data, many are not doing so in a standard way, and many don’t use those findings to inform their strategy.
As a result, all too often we have too little information about the grantees working to advance a philanthropy’s mission. Too often we don’t know who is benefiting from philanthropy’s dollars. We don’t know what the beneficiaries look like, where they live, what language they speak. Nor do we know how they worship, whether they have a disability, what their income is, how old they are, or what their gender and sexual identity are. Just as important, we don’t have data that can help us understand whether grant money is doing all it can to advance social change and carry out a grant maker’s mission.
To find the answers to these questions, philanthropy must:
- Build an understanding of why demographics are essential to making philanthropy more effective. It’s not just about achieving equity but also about gaining insight into the impact of our grant making.
- Understand that collecting demographic data should not just be an exercise. Essential parts of the process include careful planning and effective communications about what data will be gathered, how it will be used, and why it is important. Without this data and it’s effective use, advancing diversity, equity, and inclusion is just happenstance, not strategy.
- Embrace the idea that “perfect” should not be the enemy of “good.” Testing tools, terminology, and processes is essential to learning and to contributing to better approaches. We should work toward a shared understanding of the kinds of data it is important to collect and agree on a way to collect and manage that data but acknowledge we won’t get it right from the start.
- Engage with demographic data in a constructive and nonjudgmental way. If people are to voluntarily provide this data in good faith, we must be prepared to support nonprofits in this work. That means paying them for the time and systems they need to adopt to provide useful information to grant makers.
- Avoid overly simplistic categorizations of demographic groups that obscure important differences that affect grant-making approaches. For example, it might be important in figuring out health screenings to note not just that people of color were served but where their parents and grandparents were born. Often the most important information can be found at the intersection of categories, such as looking at the best approaches to aiding transgender Asians or Hispanics with disabilities.
- Recognize that demographics and the identities people associate with them are dynamic. We’ll need to remain open to new identities and nuances as humans continues to evolve. We should capture the current snapshot of our constituencies and be willing to change our definitions and sets of data as those constituencies form new identities.
We can do better. Each one of us can make a difference by seeking more data and then acting on what we learn.
Michelle Greanias is executive director of PEAK Grantmaking, which just published the report “Insight, Impact, and Equity: Collecting Demographic Data.” Melissa Sines is effective-practices program manager at PEAK and helped Michelle write this article. PEAK Grantmaking represents foundation officials focused on improving grant-making practices.
