What is Decision Intelligence?

Decision Intelligence, as Gartner frames it, is the discipline that treats decisions as something to engineer, not just to inform. It is not enough to put the right numbers in front of a person: you explicitly map the path from data to decision to action, choose the models supporting it, and close the loop by measuring what happened afterward, to correct the next cycle. The difference from traditional reporting sits entirely in that last step: a dashboard showing a sales dip informs, but does not say what to do nor check whether the action taken changed the outcome. Decision Intelligence treats every recurring decision, say how much stock to reorder, where to open the next store (the typical ground of Location Intelligence) or who gets a priority ticket, as a small system with an input, a model recommending an action and a measured outcome, so the next cycle starts from data on what actually worked, not from intuition.

Beyond Business Intelligence

Business Intelligence answers "what happened": reports, dashboards, historical KPIs someone reads and interprets. Decision Intelligence starts there and goes further, asking "what should we do now, and how do we know if it worked". It does not replace BI, it completes it: BI informs the person, Decision Intelligence operationalizes the next step, often automating parts of the decision or its execution.

How it is built

In practice this means connecting three layers that often live separately in a company: a reliable data foundation with a semantic layer giving metrics a shared meaning, predictive or causal models translating data into recommendations, and a mechanism that closes the loop by measuring the outcome of every decision made. Without that third piece, the feedback loop, what you have is still sophisticated reporting, not Decision Intelligence.