Travel retail presents unique forecasting challenges: extreme seasonality, dependency on flight schedules, economic shocks, and sudden policy changes. Traditional point forecasts fail to capture the inherent uncertainty in this volatile sector.
Point forecasts provide a single "best guess" but offer no insight into uncertainty. Probabilistic forecasting generates entire probability distributions, enabling:
- Risk-aware decisions: Understanding downside scenarios - Inventory optimization: Balancing stockouts vs. overstock - Scenario planning: Preparing for multiple futures - Confidence intervals: Quantifying forecast reliability
In travel retail, the difference between 50th and 95th percentile forecasts often exceeds 300%, making uncertainty quantification critical for operational planning.
À propos de l'auteur
Cyril Noirot
Lead Data Scientist
Data scientist freelance. Je conçois et déploie des systèmes de décision — prévision, pricing, marketing measurement, optimisation.