Operational risk.

Utility Grid Risk → Capital deferral decisions are made as if the grid is static.

Load is shifting, mix is shifting, and the controls available now will look different in five years. A static reliability model assumes the deferred asset will be needed for the same job; the causal model represents what happens when the job changes.

Asset Reliability → The control that prevented the problem you can’t see.

Three unplanned outages looks like a failure. The causal model asked how many would have occurred without the program. The KPI was wrong because the intervention was working.

Supply Chain Risk → The risk you didn’t know was there.

Three suppliers in three countries. The scorecard called it diversification. The causal model found one fabricator with three labels — $23M in concentration risk scored as managed.

Quality & Defect Attribution → The defect rate is 2.3%. Which line, which material, which operator?

A predictive model can tell you defects are correlated with night shift on line 4. A causal model tells you whether changing the line, the shift, or the supplier reduces the rate — and by how much.

Training Effectiveness → The training completion rate is 94%. The performance metric was unmeasured.

Completion was answerable from existing systems; the actual reason the program existed was not. The cheaper metric won by default. A causal model is what isolates the training effect from everything else that affects performance.