This blog was created by Kevin Rak, Strengthening Chicago’s Youth Data Specialist.
How do you know if you have a fever? You use a thermometer to take your temperature.
How do you know if you’re going the speed limit? You look at the speedometer on your dashboard and compare it with the sign on the side of the road.
You use data all the time, even if you don’t think about it as using data. Whether in these simple examples, or a team of scientists conducting a clinical trial trying to develop a vaccine, the basic idea is the same: gathering information to help you answer a question.
Data can help you get lots of valuable insights, including in the struggle for social change. It can give you a sense of the scale of a problem. Take mental health, for example. About one in five adults have some kind of mental illness, yet just 42% of those receive treatment, whether counseling or medication.1 Data can also illustrate patterns that may not be obvious. For example, Black Americans are more likely to be unarmed than White Americans when killed by police officers.2 These data points illustrate the need for significant, large-scale change.
If you’ve never worked with data for social change before, you may be wondering where to start. Fortunately, for a huge range of topics, a lot of the work is already done. SCY has curated many of them into the Violence Data Landscape, but I wanted to highlight two here that go well beyond violence data. The Chicago Data Portal has datasets on topics from the city budget to crime to poverty and education. The Chicago Health Atlas goes into great detail about health indicators, including access to care, behavioral health, community safety, injury & violence, and socio-economic factors. Many of these are available for the whole city and broken down by community area (the technical term the city uses for neighborhoods).
If you work in a social services organization, chances are you already collect lots of data that gets reported out. Do you ever look at the data yourself, beyond what is needed for your regular reporting? This can help you learn more about what is going on in your program. When I worked at Enlace, I sat down with program staff and reviewed the answers their youth were giving to some surveys. It was a great conversation because they learned what their youth were saying, which helped them adjust their programming. Plus, I learned we had to alter some of the questions because they were confusing to the youth.
The Importance of a Research Question
It’s easy to get overwhelmed when delving into data. There is so much information out there, and every piece of information you discover can lead to three more questions. Having a research question, a statement that captures what you are trying to learn, is a valuable way to guide your investigation. It doesn’t have to be anything complicated. It can be something like, “Are there disparities in access to mental health services in Chicago?” or “How well did our program do in meeting its outcomes last year?” These questions narrow your focus into something that is specific enough that you can realistically come up with an answer.
Having a research question also helps provide context for whatever data you uncover. Data, by itself, doesn’t mean much. Let’s go back to the driving example. If you’re going 45 miles an hour, what does that mean? It all depends on the context. If the speed limit is also 45, you’re fine. If it’s 30 because you’re driving by a Chicago park in the middle of the day, get ready to pay a fine.
It’s the same idea with your program data. If 70% of program participants showed improvement at the end of the program, that’s not enough to know if your program met its outcome objectives. Was your goal to have 60% show improvement? Then great! It surpassed expectations. Was the goal 80%? Then you have some work to do. Or, if you didn’t have a specific goal, you can try to do some other comparisons. How did youth in the program do the year before? If this kind of program is delivered elsewhere, how have youth done in those other settings?
The research question can also guide you to different types of data. This may be review for you, but generally speaking, data can be numbers (quantitative) or descriptions (qualitative). The thing is, it’s usually a good idea to have both. Numbers give you a good sense of overall scale and trends that may not be obvious, but descriptions like interviews and open-ended questions give a richness that numbers just can’t get.
When working with data, it’s helpful to have at least one person you can bounce questions off of. This person can be a manager, a colleague, a formally identified mentor, etc. At the same time, the data doesn’t tell the whole story. It’s important to check in with others to see if what you’re uncovering seems reasonable and realistic. As much as possible, it’s a good idea to have conversations with the people who are closest to the data. These can be clients, residents, program staff, or some combination of the above. They can provide valuable insights that the numbers themselves won’t show you.
I hope this has been helpful for you. If you have any feedback about the article, or if you have a question about using data, please feel free to reach out to me! I can’t do your project for you, but I can probably point you in the right direction.
1: National Institute of Mental Health. (2019 February). Mental Illness. https://www.nimh.nih.gov/health/statistics/mental-illness.shtml
2: DeGue, S., Fowler, K. A., & Calkins, C. (2016). Deaths Due to Use of Lethal Force by Law Enforcement: Findings From the National Violent Death Reporting System, 17 U.S. States, 2009-2012. American journal of preventive medicine, 51(5 Suppl 3), S173 – S187. https://doi.org/10.1016/j.amepre.2016.08.027