Unlearning to Learn: Bringing Rigor and Joy to Conversations about Data

For the last four years, we’ve had the privilege of leading data collaborative sessions for the City of Chicago Department of Family and Support Services (DFSS), working alongside hundreds of agencies implementing youth development programs across our city. Twice annually, we analyze survey data from roughly 10,000 youth participants and 300–400 youth workers, distribute agency-specific data, and then bring program implementers together to make meaning of what we’ve learned. Through this journey, we’ve discovered that: Anyone can enjoy talking about data and evaluation when it’s presented the right way, and you can transform a 3–4 hour conversation about data and evaluation into something that’s useful, fun and social.

The Evolution of Our Data Sessions

Sometimes, you have to unlearn old stuff, make some mistakes, stumble a little, and then combine the old stuff you unlearned with the new stuff to make something good. That’s exactly what happened with our approach to data sessions.

During my time in India, I discovered a deep passion for evaluation and data while working with some of the brightest minds I’ve ever encountered — many former engineers who had turned their talents to education. We conducted weekly data sessions analyzing formative assessments that led to transformative changes in literacy and numeracy rates. These sessions were intense: objective-driven, rigorously analytical, and could stretch for hours. Engagement wasn’t the priority — results were. And they worked. The data-driven approach helped create remarkable improvements in student outcomes.

I naturally tried to replicate this model when I returned to the States. Our first sessions were laser-focused on being objective-driven. I thought the best approach was to be straightforward: have people look at their data, answer reflection questions, and develop action plans. The sessions were structured, formal, and…dry. My brilliant colleague Fausto would leave these sessions frustrated, seeing clearly how people were bored as hell and how the energy would drain from the room. “This isn’t working,” he’d tell me. But I was stubborn. I dismissed his concerns, convinced that this how you are supposed to be “effective and objective driven” with data analysis.

But after another session where you could feel each minute slog by, I decided to go back to basics — the same flow we’d use when leading youth development sessions. Just like with young people, we needed to ensure adults were connecting, moving, creating, and reflecting. We started mixing up activities, getting people into different groups, having them move around the room. We incorporated reflection moments, energizers, art, and music. We gamified data analysis and created healthy competition. Every activity, whether a creative project, a group discussion, or a friendly competition, had to point back to making meaning of our data. But now we kept the energy flowing, just like we would in our youth programs. It was about finding that sweet spot where rigorous analysis meets engaging facilitation.

The Pizza Principle: Making Data Analysis Relatable

Here’s what we’ve learned about meaningful data discussions: start with something relatable and, when possible, add a friendly competition. In Chicago, pizza isn’t just food — it’s a passionate topic that gets everyone engaged. So we begin with a seemingly simple question: “What’s the best pizza in Chicago?”

What follows is a three-round analysis that mirrors how we should look at our youth program data:

Round 1 — Quantitative Data (The What)

• For pizza: Years in business, star ratings, number of locations
• For programs: Survey results showing 80% of youth feel they belong, 92% feel safe.

Round 2 — Qualitative Data (The Why)

• For pizza: Food critic reviews, customer testimonials
• For programs: Youth quotes explaining why they feel connected or what makes them feel safe

Round 3 — Personal Experience (The Context)

• For pizza: First-hand experience eating there
• For programs: Staff observations and daily interactions with youth

Round 4 — Social Marketing (The Pitch)

• For pizza: Groups create different pitches for different audiences — families looking for value, food enthusiasts seeking authenticity, tourists wanting the Chicago experience
• For programs: Teams develop targeted presentations of their data for different stakeholders — youth participants, staff, funders, community supporters
• Everyone votes on the most compelling pitch, creating an energetic finale to the exercise

The beauty of adding this fourth round is that it drives home a crucial point: the same data can and should be presented differently depending on your audience. Just as a pizza place might emphasize its family-friendly atmosphere to parents but its authentic ingredients to food critics, program data needs to be packaged differently for various stakeholders. The friendly competition aspect makes this learning fun — people get creative, even theatrical sometimes, in their pitches. We’ve seen everything from mock TV commercials to spoken word performances, all built around data.

Just as participants synthesize these four types of data to make a compelling case for their favorite pizzeria, we encourage them to use the same comprehensive approach when analyzing their youth programs. The numbers tell us what’s happening; the open-ended responses tell us why, their direct experience adds crucial context and nuance, and the marketing exercise teaches how to share these insights effectively with different audiences.

Making Data Come Full Circle: The Art of Reporting Back

Collecting data without sharing what you learned, is like having a conversation where you only listen but never respond. One of the most overlooked aspects of data analysis is what happens after we gain insights — how do we share these learnings back with the people who provided the data in the first place? In our sessions, we dedicate specific time for participants to practice presenting their findings back to different audiences.

We break participants into groups and have them practice three key presentations:

For Youth:

• “You spoke, we listened” sessions where staff share key findings from surveys
• Visual displays showing what’s changing based on youth feedback
• Interactive workshops where youth help design the solutions
• Celebration of wins and honest discussion of challenges
• Clear communication about what specific changes are being made based on their input

For Staff:

• Using youth testimonials in staff appreciation events
• Creating reflection questions and talking points about areas for growth that invite conversation and improvement without anyone getting defensive or hurt
• Designing staff meeting presentations that highlight program successes

For Funders and Stakeholders:

• Crafting compelling narratives that combine numbers with stories
• Creating visually appealing one-pagers that highlight key impacts
• Developing presentation strategies that show both results and responsiveness
• Demonstrating how feedback leads to program improvements
• Sharing success stories alongside statistical achievements

Our Approach in Action

In our recent summer program quality assessment, we created interactive stations where program staff could:

• Compare their agency’s data to city-wide averages
• Analyze youth testimonials from their specific programs
• Share successful strategies that drove their results
• Develop specific plans for addressing areas of growth

What We’ve Learned About Effective Data Collaboration

Working with hundreds of youth-serving organizations has taught us that effective data sessions need to:

Honor the Wisdom in the Room

• Begin with meaningful check-ins that connect to participants’ direct experience
• Create space for program staff to share their stories and insights
• Recognize that everyone brings avaluable perspective to the analysis

Make Data Accessible and Actionable

• Present program information in multiple formats
• Compare results across similar programs to spark discussion
• Provide time for both individual reflection and group meaning-making

Focus on Practical Application

• Move quickly from analysis to action planning
• Create clear connections between survey results and program improvements
• Build in time for agencies to develop concrete next steps

The Rhythm of Reflection

While our citywide collaborative sessions provide valuable insights twice a year, analyzing responses from thousands of youth and hundreds of youth workers, we’ve learned that real program improvement requires a more frequent rhythm of reflection. Organizations need to be examining their data at least every couple of months, combining multiple sources of information:

• Participant surveys (both numbers and narratives)
• Staff observations and daily insights
• Youth assignments and projects
• Daily anecdotes and stories
• Attendance patterns
• Youth and family feedback

This ongoing cycle of reflection and action shouldn’t wait for formal evaluation periods. The most successful programs we work with have built regular data discussions into their organizational culture. They might spend 30 minutes in a staff meeting discussing what they’ve noticed about youth engagement or take an hour to analyze recent participant feedback. These smaller, more frequent touchpoints keep programs agile and responsive to youth needs.

Working Your Data Muscles

The future of our data collaboratives isn’t about more sophisticated analytics—it’s about creating spaces where program implementers can genuinely engage with their data in meaningful and actionable ways. You have to keep doing it and working that muscle until it’s second nature.

For those implementing youth programs, remember:

• Data isn’t just for reports — it’s a tool for program improvement
• Your experience and insights are crucial to interpreting the numbers
• Small, immediate improvements based on data is the way to go. Continuous small improvements add up!

The most powerful moment in any session isn’t when we present the data — it’s when we see program staff leaning in, connecting dots, and walking away with ideas and plans to improve their programs. It’s also fun to see people from different orgs hanging out and socializing. When we get this right, our data sessions become catalysts for positive change, turning information into insight, and insights into impact for the young people we serve.