Learn to Love Your Local Data

Last month at the AAM conference, a speaker said, "we should all be using measures of quality of life  to measure success at our museums."

I got excited. 

"We should identify a few key community health indicators to focus on."

I got tingly.

"And then we should rigorously measure them ourselves."

Ack. She killed the mood.

Many museums (mine included) are fairly new to collecting visitor data. Especially new to collecting data about broad societal outcomes and experiences. Why the heck would we be foolish enough to do it all ourselves?

The "we have to do it ourselves" mantra is one of the most dangerous in the nonprofit world. It promotes perfectionism. Internally-focused thinking. Inability to collaborate and share. Plus, it's expensive. So when we find we can't afford to do it ourselves, we throw up our hands and don't do it at all.

Here are three reasons to find and connect with community-wide sources of data instead of doing it yourself:

The data already exists.

Want to know the demographic spread of your county? Check the census. Want to know how many kids ate fruits and vegetables, or how many teens graduated high school, or how many people are homeless? The data exists. In some communities, it exists in different silos. In others, someone is already aggregating it. 

When we started more robust data collection at our museum, we wanted a community baseline. We thought about collecting it ourselves (stupid idea). Instead, we found the Community Assessment Project--an amazing aggregation of data from all over our County, managed by a wide range of stakeholders from health and human services. Not only do they aggregate existing data, they do a bi-annual phone survey to tackle questions like "have you been discriminated against in the last year?" and "what most contributes to your quality of life?" We got the data, and we got involved in the project. Now, instead of using our meager research resources to collect redundant data, we can springboard off of a strong data collection project that we access for free. 

You may not have a Community Assessment Project in your community, but you have something. Ask the health department. Ask the United Way. Someone is collecting baseline community data. It doesn't have to be you.

We're stronger together.

Imagine a community with 50 different organizations working to reduce childhood obesity. Would you rather see them each pick a measure of success that is idiosyncratic to their program, or join forces to pick a single shared measure of success?

If your museum is working to tackle a broad societal issue, you're not doing it alone. Your program may exist in its own bubble of the museum, but there are likely many organizations tackling the same big issue from different angles.

Each of you is stronger--in front of funders, in front of advocates, in front of clients--if you can work together towards one shared goal. Even if it doesn't map perfectly to your program, it's worth picking a "good enough" measure that everyone can use as opposed to a perfect measure that only works in your bubble.

For example, one of the outcomes in our theory of change that we care about is civic engagement. We want visitors to be inspired by history experiences at the museum to get more involved as changemakers in our community. Our Community Assessment Project already measures indicators of civic engagement like voting, writing to an elected official, and speaking at a public hearing. Are these the indicators we would choose in a bubble? Probably not. But are they more powerful because we have years of good countywide data about them? Absolutely.

Shared data builds shared purpose.

What happens when those 50 different organizations agree on one indicator for success in reducing childhood obesity? They get to know each other. They understand how their individual work fits into a larger picture. They build new partnerships, reduce redundancies in programming, and fill the gaps. They do a better job, individually and collectively, at tackling the big issue at hand.

That's what we should be using measurement to do. I can't wait to hear a story like this at a conference and fall in love with data all over again.

Are you working across your community to share key indicators of success? Share your story, question, or comment below. If you are reading this via email, you can join the conversation here.