An operator needed to identify emerging cell-site congestion before it began affecting subscriber experience. We use DPI analytics and machine-learning models to analyse traffic patterns and relevant contextual data, forecasting congestion up to 48 hours in advance. Automated load-balancing recommendations and actions help the operator prevent 30% of congestion-related service degradations before they occur.