In aviation supply chains, forecasting errors are not just about dollars. They cascade into grounded aircraft, strained contracts, and damaged trust. A model does not eliminate uncertainty, but it ensures you anticipate it rather than react to it.

Think about a recent inventory or procurement decision in your organization, or this course's case study scenario. How were forecasts developed, and what assumptions were left unchallenged? If a hybrid statistical-ML framework had been applied, what blind spots might have been revealed?