A demand forecast gives supply chain managers a prediction, but it may leave them asking how sure the system is. A confidence interval makes uncertainty visible alongside the forecast. One proposed dashboard design shows it as a shaded band around the prediction line, with a nearby percentage range. section 12.1.4
The band is a communication aid, not a promise that the prediction will be right. The proposed percentage label is a design example; it does not establish how an interval is calculated or what coverage a particular forecast achieves. Users need a clear explanation of what the displayed range means before relying on it. section 12.1.4 section 12.3.4
Planning around a forecast
A planner sees a forecast for increased demand. Training pairs the interval with a familiar weather-report analogy: an 80% chance still leaves a 20% chance that the event will not happen. The planner can weigh that uncertainty against knowledge of a possible holiday sales surge, then adjust the plan rather than accept the forecast blindly. The probability analogy helps explain uncertainty; it is not a technical definition of the interval. section 12.3.4
Make the interval useful in the workflow:
- Ask what users need to know about a forecast before choosing how to display uncertainty. section 12.1.4
- Explain that the model can be wrong and let users adjust predictions using their own insights. section 12.2.2 section 12.3.3
- Teach interpretation with everyday scenarios and invite users to report anomalies. section 12.3.4
