Cause
In the Trigger–Cause–Action model, Cause is the stage where you narrow down which drivers most plausibly explain the change you see. A decision-ready dashboard does not guess the exact cause, but it shortens the list.
What we mean by “Cause”
Cause refers to the factors that materially contribute to a change in your outcome metric. In dashboards, this usually means a small set of driver KPIs or segments whose movement can realistically explain the shift, based on structure and history — not just coincidence.
Why this changes how people read a dashboard
If dashboards do not help people reason about causes, teams fall into familiar traps: blaming the same favourite explanation every time, or drowning in endless lists of possible factors.
- Reviews jump straight from “we are down” to “we need more marketing” without checking which drivers actually moved.
- Or they get stuck generating more hypotheses than the team could ever test.
When you will feel this term in real life
Problems at the Cause stage show up as confusion and circular debate.
- Meetings with data but no decisions — the group cannot converge on a short list of likely drivers.
- Decision fatigue — people leave feeling that “anything could be the cause”, so no action feels justified.
A good dashboard does not prove causality on its own. It reduces the number of sensible bets you need to consider.
See this term in context
Cause sits in the middle of:
Related terms in this glossary
Cause works closely with:
When your dashboard helps the team say “these two or three things can realistically explain the change”, you have already improved the Cause stage.