In this episode, we’re exploring why Sprockler puts such emphasis on stories and how that’s reflected in the language we use. So let’s dive in. Why are stories so central to how Sprockler works?
Because stories bring depth. Standard data collection methods often flatten complexity; they ask for answers without exploring the context. A story gives you sequence, emotion, decisions, and consequences. It shows you not just what happened, but how someone experienced it and how they made sense of it.

So Sprockler is both qualitative and quantitative?
Yes. A person tells their story in their own words, and then they interpret it themselves by answering structured questions using bipoles, tripoles, or image-based prompts. We call this process self-signification where every story creates data, without stripping away its richness.

And what do you call this whole process of gathering stories and responses?
We call it an inquiry. That’s deliberate. In other contexts, people might use the word “survey,” but we chose “inquiry” because it reflects what we’re really doing: inviting people into a process of meaning-making. It’s not about ticking boxes or completing a form. It’s about being curious, being open, and listening deeply. As one of our co-founders said, the word “inquire” carries a feeling, a posture of interest and respect that matches what Sprockler is all about.

That reframing makes a big difference.
It does. And it shows up in the examples too. One came from a healthcare project. A woman shared a story about trying to access services for her child. After the story, she placed it on a slider between “rules and processes” and “emotions and relationships.” That gave us not just her story, but her perspective on what shaped it. When you have hundreds of these, you begin to see patterns not just about the system, but about how people experience that system.

So you’re seeing patterns emerge from interpretation, not just responses?
Correct. Another example was in a community development setting. People shared stories about whether they felt their voices were heard in a local planning process. Then they placed those stories on a triangle between “trust,” “power,” and “resources.” What we saw were clusters: in some neighborhoods, trust was high but power was low. In others, the reverse. And every dot on that map was a story told and interpreted by the person who lived it.

So you’re generating insights without losing the people behind them.
Yes. That’s why we say: don’t just count things, understand them. An inquiry is not just about data. It’s an invitation to reflect. Stories help us listen in complex systems. They make meaning visible. And that opens the door to better action.