In volatile markets, the point forecast is the least useful part of a forecast. What operators actually need is the shape of the uncertainty: how wide the band is, what drives it, and which decisions are sensitive to being wrong.
Useful forecasting systems combine three inputs. Historical signals provide the baseline. Operational context (planned wells, scheduled maintenance, committed orders) adjusts it. And scenarios let planners stress-test decisions against the cases that would hurt most.
The output should be decision-shaped. Not 'demand will be X' but 'under the likely band, this stockout risk is real in week seven; under the downside case it arrives in week four'. That framing turns a forecast into a procurement, inventory, or scheduling decision.
Accuracy targets still matter, so agree them before you build. But measure the system on the decisions it improves, not just the error it reduces.