5 Best Practices for Equitable and Inclusive Data Collection

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How our organizations collect demographic data speaks to our values and has a real impact on the communities we serve. The way we collect demographic data can either perpetuate harmful inequity and bias, or foster a healthy culture of equity and inclusion.   

Many of our partners share a genuine desire to reflect a commitment to diversity, equity and inclusion through their data collection, such as alumni surveys and program evaluations. But they end up coming up against the same barrier: a lack of uniform, comprehensive best practices they can turn to.

That’s why we created More Than Numbers: A Guide Toward Diversity, Equity and Inclusion (DEI) in Data Collection, a tool that lays out clear practices for crafting demographic inquiry that helps organizations make informed decisions about their work while appropriately representing marginalized communities. Importantly, this guide provides more than just conceptual advice—it is packed with clear guidelines, sample templates and quick tips to help organizations improve their data collection both thoughtfully and efficiently.

Beginning the process of improving your data collection is easier than you think. Check out five best practices from our guide that you can start implementing at your organization right now:

1. Explain why you are asking for demographic information.
Respondents can perceive demographic questions as sensitive and private, and providing demographic information may make them identifiable. With these considerations in mind, let respondents know how your organization will use their data, how it benefits them and how you will protect their information. This should include:

  • Language explicitly requesting consent;
  • An explanation of how your organization will use the data to support underserved communities; and
  • A reinforcement of the survey’s confidentiality.

Here is one example you are welcome to use as a template:

“The following demographic questions are intended to assess how members of various communities are participating in our programming. The responses, which will be kept fully confidential, will help us make decisions about our outreach, engagement and programming efforts to ensure we are effectively serving our diverse membership.”

2. Provide multi-select checkboxes or open-ended questions.
Identity is complex, so the best approach for inclusive data collection is to avoid making respondents feel like you are “boxing them in” with only one possible answer. Give respondents the freedom to express the diversity of their identity for a given trait by allowing them to select multiple answers or self-identify.

3. Assess the order of response choices.
The order of response choices can reinforce implicit biases—like putting “United States” as the first response to a question asking about country of origin, or “white” as the first response to race and ethnicity questions. Best practices for avoiding these biases include randomizing response choices, ordering them alphabetically or manually arranging the choices to support an inclusive survey experience.

4. Give respondents the option to opt-out.
Identity is personal, and if you require respondents to answer demographic questions, they might not complete the survey or form. Instead, include “Prefer Not To Answer” options to track how often respondents select that response choice and explore why individuals may be opting out of responding. In addition, we suggest replacing “Other” options with “Prefer to Describe” or “Prefer to Self-Describe” to avoid alienating respondents that do not see their identity represented.

5. Solicit feedback from the communities responding.
Actively seek input from individuals representing your populations of interest about what demographic data will be most helpful, relevant and inclusive. Soliciting and incorporating feedback from your organization’s membership or constituents about how they choose to express or define their identities is a good practice to integrate into your organizational culture. And remember—always compensate anyone who provides input.

Of course, while we intend for these best practices to promote a thoughtful approach to inclusive and equitable data collection, they do not necessarily serve as a cut-and-paste formula for each specific organization. And that is okay—best practices are always a starting place, rather than a one-size-fits-all solution. Our hope is that this guide is a useful tool to jumpstart a review or refresh of your organization’s data collection, however that looks for you.

Get the full set of our best practices for equitable and inclusive data collection here.

Rella Kaplowitz is the Senior Program Officer for Evaluation and Learning at the Charles and Lynn Schusterman Family Foundation.
Jasmine Laroche is a Program Associate for Evaluation and Learning at the Charles and Lynn Schusterman Family Foundation.


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