Decision Design: Connecting Insight to Action in Real Time

Integration isn’t about getting tools to talk to each other. It’s about ensuring insight lands where a decision gets made — and that it lands in time to shape it. HBR calls this the difference between information and influence. Most AI systems still miss that mark. They produce information. They visualise patterns. But they don’t connect cleanly to action. There’s a lag. A handoff. A hesitation. And that’s where value decays.

This is the missing layer: decision design. A deliberate effort to map how, where, and by whom decisions are taken — and how AI needs to slot into that moment without friction. The system doesn’t just need to be accurate. It needs to be actionable. And that means surfacing the right signal, to the right person, in the right format, at the point of use. MIT Sloan researchers argue that when organisations design backwards from the decision, adoption accelerates and impact compounds.

Without this, integration is performative. Dashboards proliferate. Reports are generated. But behaviour stays the same. Teams revert to instinct, or stall while seeking clarity. Not because they doubt the model — but because the output wasn’t embedded in the rhythm of the decision.

The organisations getting this right treat decision points as design objects. They reverse-engineer how AI needs to appear inside a workflow. They ask: what context does this person have? What pressure are they under? What trigger should elevate this insight into view? That’s why we focus on decision enablement at MadeWithData — because performance isn’t about more dashboards, it’s about sharper decisions.

Integration only drives performance when it collapses the gap between intelligence and action. And decision design is how that gap gets closed — not with more tooling, but with tighter alignment between system behaviour and human judgement.

This is what integration looks like at the sharp end. Not data flowing. Decisions shifting.