A critical understanding of data, or data literacy, is essential for working in the field of early childhood policy because of the complex factors that play a role in a child’s development. Data must be interrogated for bias, representation, and potential conflicts of interest to allow for more accurate interpretation and use of imperfect data. Data literacy is not optional, it is required for ensuring that equitable, effective policy has a solid foundation.
My experiences of looking critically at data began during my time at Building Bight Futures when trying to understand various data that showed up when I was conducting research for potential Policy Recommendations. I was looking at different data, trying to interpret the data, and trying to make informed recommendations, but I kept getting stuck on why things weren’t lining up. Fortunately, I had the privilege to work with Dora Levinson, the Research and Data Director at Building Bright Futures, with whom I had one-on-one weekly meetings. She was able to provide personalized training to help me understand how to interpret different kinds of data, elevate it, and use it to drive policy. Many people do not have this opportunity, and I wanted to help make data literacy more accessible for others.
Questions to Ask When Looking at Data
- Who collected the data?
Consider the source. Are they credible? Do they have any potential biases or interests that might shape what’s being presented? - What exactly is being measured?
Look closely at how key terms are defined. Are important parts of the issue missing or left out? What might the data not be showing? - Who is included—and who isn’t?
Think about representation. Does the data reflect the full picture or only a subset of people or experiences? Is it a sample or a complete count? Are there potential inequities across demographic or identity groups that might be hidden by the average? - How has the data been presented or manipulated?
Check for context. Are only certain years or comparisons shown? Does the y-axis start at zero? Do the labels or categories match common understanding, or do they use narrower or broader definitions? - What can this data tell us—and how can it guide action?
Reflect on how the information might inform decision-making, planning, or policy. What kinds of changes or solutions could this data support?
The Importance of Including Qualitative Data
Being data-literate is not just about reading numbers on a page, it is about asking the right questions, uncovering what those numbers mean, and ensuring that the lived experience of children and families is not lost in translation. Numbers can point to patterns, but without stories and lived experiences, we could miss the truth. Qualitative data helps fill in those gaps, giving us the ‘’why’’ behind the numbers and making sure policies reflect real family needs. Policymakers can move beyond surface-level statistics to craft policies that are equitable, responsive, and grounded in families’ experiences.
When we combine stories and numbers, or qualitative and quantitative data, we create stronger, fairer policies, and opportunities for equitable growth and development. When we listen to families, we see a more complete picture.
Families regularly share their struggles to navigate early childhood systems. But because we don’t capture these stories in a consistent way, they’re often dismissed as “anecdotal.” Yet this data, however informal, is crucial for policymaking. Anecdotal evidence reveals patterns, exposes flaws, and brings urgency to issues that numbers alone can’t fully explain. We need to treat family voice as a valid and necessary part of the evidence base, not as optional.
