Demographics. What are They Good For? Absolutely Something.

When I think about demographics, my mind jumps to the standard US Census fields: race, ethnicity, gender, household composition, education, etc. Nonprofits can use this data to get a snapshot of their participants in a way that’s meaningful and familiar.

It’s also helpful for nonprofits to think of demographic data more expansively to include things like:

• Religious affiliation

• Military service

• Previously incarcerated

• Lactose Intolerant

Having rich demographic data can help you understand your participant population in ways that help you pursue your mission. For example, if you know that your program works with a lot of people with prior military service, then maybe you can use that to offer specialized resume workshops and job training programs that emphasize these participants’ experiences and strengths.

It’s ideal to collect demographics at the participant level, likely on their profile or on an intake form, so that they can be used for deeper analysis. To get a demographic snapshot of participants in your program, you could simply summarize each demographic field.

It’s less useful, although still useful, for nonprofits to collect demographic data in a way that cannot be directly connected back to the individual participant. For example, you might create an anonymous survey that your participants can complete to gather demographic data. You could still create a snapshot of your participants - which is great! - but it will probably be more difficult to conduct deeper analysis.

How are we supposed to use demographic data?

The easiest place to start is looking at summaries of your demographic data. What percent of our participants are each gender category you collect? What percent fall into the race and ethnicity categories you collect? What percent are single parents, have a special diet, or struggle to pay their rent?

By looking at single field summaries, you get a nice overview for who your program serves. It can also prompt questions like “Why don’t we serve more women in this program?” or “How can we encourage more people without high school diplomas to participate in our workshops?”

Your demographic data gets superpowers when you go beyond summarizing each piece of data by itself. You can use your demographic data to examine your outputs and outcomes.

For example, our Empowerment Program served 10 single parents last year. That statement alone doesn’t tell us much. However, if we say, we served 10 single-parent families and 10 two-parent families, then we start to get a better picture of who our program is serving.

Now we can see that 50% of our families are single-parent and 50% percent are two-parent.

Ok, that’s kind-of interesting, but probably not life changing.

The next question you have to ask is “who are we trying to serve?” If your organization serves a community where 75% of families are single-parent, then you should ask yourself why at least 75% of your families are not single-parent.

By looking deeper into our data, an important question emerges.

What barriers prevent single parent families from accessing my program and how can we address them?

The power of your demographic data increases dramatically when you make comparisons.

• How does the graduation rate differ based on the gender of program participants?

• What percentage of our participants have at least a high-school diploma vs less than a high-school diploma?

• What percent of participants are racial minorities vs. the percent of racial minorities in our target community?

How do we do this fancy schmancy analysis?

Without launching into a training session, here are a few ideas that could work:

• You can create a pivot table in your spreadsheet program (Google Sheets, Excel, etc). Once you get the hang of pivot tables, you have a powerful tool for comparing data across demographic categories.

• If pivot tables are a little too complex, you could filter your data by each category (e.g. Less than an HS diploma, HS diploma or GED, some college, college graduate), and summarize just that data. This approach is tedious and repetitive, but I’ve done it many times and it works.

• Your specialized data collection and reporting software might have some built in reporting tools that do this for you.

So how do we know what to track? Should we just track as much as we can?

It’s tricky knowing what to track and what to ignore. Organizations will widely vary in terms of what they track, but make sure it’s relevant - or probably relevant.

For example, a pet adoption agency likely does not need to know about a person’s citizenship status, but an organization focused on emergency services (e.g. food, clothing, shelter) might benefit from knowing that b/c they could use it to ID services and learn more about the population they are serving.

But what’s the harm in just tracking everything?

Organizations need to strike a balance between collecting rich data and providing high quality services. Both take time and mental energy, so you can't max out both. Asking participants to complete a 70 question bio to get a meal doesn’t help anyone and will likely discourage people from seeking your services.

It’s best to focus on the demographics you need today, and maybe a few exploratory demographic fields that you think could be informative in the near future.

Consider Making Your Data Collection Progressive

The first time someone comes in for a transactional service (e.g. they need baby formula), consider asking them a small number of questions for identification and eligibility screening. Let them know that if they come back again, you’ll ask for more information to see if you can support them in different ways. If they come back in a month asking for more, then that’s a great time to ask for additional information.

The downside of this approach is that there will be lots of missing data for participants who don’t come back for that second visit. If you use this approach, then you’ll have to decide which data is absolutely necessary for funders and program management, and which data is helpful but optional.

So Go Out There and Count Stuff!

Demographics might feel like that junk we need to collect before we can do some good work, but they are so much more than that. They can provide you a window into the quality of your work and the ways you can improve it. Think carefully about the demographics you should collect and analyze them regularly to push your program forward.

Reporting your impact is hard when you’re juggling spreadsheets. countbubble makes it easy so you can focus on your mission.

countbubble is simple, flexible participant management software for human service nonprofits. Learn how we can help your nonprofit track and report participant demographics.

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Ryan Brooks

Founder, CountBubble, LLC

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