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“Because It’s Hard” Is Not an Excuse – Challenges in Collecting and Using Demographic Data for Grantmaking
August 30, 2018

Melissa Sines is the Effective Practices Program Manager at PEAK Grantmaking. In this role, she works with internal teams, external consultants, volunteer advisory groups, and partner organizations to articulate and highlight the best ways to make grants – Effective Practices. A version of this post also appears in the PEAK Grantmaking blog.

MelissaFor philanthropy to advance equity in all communities, especially low-income communities and communities of color, it needs to be able to understand the demographics of the organizations being funded (and declined), the people being served, and the communities impacted. That data should be used to assess practices and drive decision making.

PEAK Grantmaking is working to better understand and build the capacity of grantmakers for collecting and utilizing demographic data as part of their grantmaking. Our work is focused on answering four key questions:

  • What demographic data are grantmakers collecting and why?
  • How are they collecting these demographic data?
  • How is demographic data being used and interpreted?
  • How can funders use demographic data to inform their work?

In the process of undertaking this research, we surfaced a lot of myths and challenges around this topic that prevent our field from reaching the goal of being accountable to our communities and collecting this data for responsible and effective use.

Generally, about half of all grantmakers are collecting demographic data either about the communities they are serving or about the leaders of the nonprofits they have supported. For those who reported that they found the collection and use of this data to be challenging, our researcher dug a little deeper and asked about the challenges they were seeing.

Some of the challenges that were brought to the forefront by our research were:

PEAK Grantmaking reportChallenge 1: Fidelity and Accuracy in Self-Reported Data
Data, and self-reported data in particular, will always be limited in its ability to tell the entire story and to achieve the nuance necessary for understanding. Many nonprofits, especially small grassroots organizations, lack the capability or capacity to collect and track data about their communities. In addition, white-led nonprofits may fear that lack of diversity at the board or senior staff level may be judged harshly by grantmakers.

Challenge 2: Broad Variations in Taxonomy
Detailed and flexible identity data can give a more complete picture of the community, but this flexibility works against data standardization. Varying taxonomies, across sectors or organizations, can make it difficult to compare and contrast data. It can also be a real burden if the nonprofit applying for a grant does not collect demographic data in the categories that a grantmaker is using. This can lead to confusion about how to report this data to a funder.

Challenge 3: Varying Data Needs Across Programs
Even inside a single organization, different programs may be collecting and tracking different data, as program officers respond to needs in their community and directives from senior leadership. Different strategies or approaches to a problem demand different data. For instance, an arts advocacy program may be more concerned with constituent demographics and impact, while an artist’s program will want to know about demographics of individual artists.

Challenge 4: Aggregating Data for Coalitions and Collaborations
This becomes even more complex as coalitions and collaborative efforts that bring together numerous organizations, or programs inside of different organizations, to accomplish a single task. The aforementioned challenges are compounded as more organizations, different databases, and various taxonomies try to aggregate consistent demographic data to track impact on specific populations.

These are all very real challenges, but they are not insurmountable. Philanthropy, if it puts itself to the task, can tackle these challenges.

Some suggestions to get the field started from our report include

  • Don’t let the perfect be the enemy of the good. Pilot systems for data collection, then revisit them to ensure that they are working correctly, meeting the need for good data, and serving the ultimate goal of tracking impact.
  • Fund the capacity of nonprofits to collect good data and to engage in their own diversity, equity, and inclusion efforts.
  • Engage in a conversation – internally and externally – about how this data will be collected and how it will be used. If foundation staff and the nonprofits they work with understand the need for this data, they will more willingly seek and provide this information.
  • For coalitions and collaborative efforts, it may make sense to fund a backbone organization that takes on this task (among other administrative or evaluation efforts) in support of the collective effort.
  • Work with your funding peers – in an issue area or in a community – to approach this challenge in a way that will decrease the burden on nonprofits and utilize experts that may exist at larger grantmaking operations.
  • Support field-wide data aggregators, like GuideStar or the Foundation Center, and work alongside them as they try to collect and disseminate demographic data about the staff and boards at nonprofits and the demographics of communities that are being supported by grantmaking funds.

Grantmakers have the resources and the expertise to begin solving this issue and to share their learning with the entire field. To read more about how grantmakers are collecting and using demographic data, download the full report.

--Melissa Sines

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