Background

As a designer stepping into a data manager role, I saw an opportunity to bridge two worlds: the abstract, sometimes alienating realm of organizational data, and the deeply human, day-to-day reality of social service work. I wasn’t just interested in data for compliance or reporting—I wanted it to be useful, understandable, and even motivating for the staff doing the hardest work.

At our organization, I’ve been using design thinking and behavioural design to reframe how we approach performance data. Through workshops, regular trainings, and intentional reframing of our dashboards and language, I’ve worked to build staff buy-in, boost morale through recognition of positive outcomes, and encourage more data-informed decision-making.

Our staff are experienced, committed social workers—often juggling high caseloads and emotionally demanding work. Most don’t have a technical background. And honestly, they don’t need to become data analysts. What they do need is for the data to tell a clear story: something relevant, something that feels connected to their work, and something they can act on.

This quarter, we hosted a staff-facing workshop to review Q2 data and collectively reflect on performance trends. The goal was to make the numbers digestible, reflective, and collaborative—not just something to absorb, but something to talk about.

This wasn’t a typical performance review meeting. It was structured as a conversation, designed to invite reflection, not just passive listening.

We focused on:

• Highlighting simple trends (upward/downward) using visuals that were intuitive, not overwhelming.
• Framing metrics in context, emphasizing outcomes staff care about—like show rates, check-ins, or increases in engagement through webforms.
• Celebrating progress. I made a point to call out small wins, even if targets weren’t fully met. The message was: “Something’s moving here—let’s name it and build on it.”
• Creating space for interpretation. Data doesn’t explain itself. So we asked: Why do you think this happened? What changed on the ground?

The simple worksheet I created (see below) supported this reflection. Staff were split into small teams of three to discuss and respond to four guiding questions:

1. What trends do you notice?
2. What role did you play?
3. What else could we try?
4. How can we support our future goals?

We used this to move beyond passive data sharing into real dialogue—making space for insights from different departments, and for staff to see their own impact reflected in the numbers.

Increased engagement: Staff participation was thoughtful and honest. People shared insights that helped us understand the ‘why’ behind the trends—things we’d never get from a spreadsheet alone.

More ownership: Staff started to make connections between their actions and the results. I heard things like “Oh yeah, we started doing reminder calls in April—that’s probably why show rates improved.”

Reframed mindset: We’re beginning to shift the way people relate to data—from being something that’s “done to them” to something they can work with.

This work isn’t about turning everyone into data scientists. It’s about building confidence, making space for reflection, and giving staff tools to see the story in the data.

I’ve learned that people are much more open to data when:

• It’s connected to their values and work
• It’s framed in language they use
• It creates space for them to contribute, not just receive

Ultimately, we’re not just trying to track what’s happening—we’re trying to build a shared sense of progress.