Forecasting, Anomaly Detection and Early Warning Systems
Addresses the design of early warning systems that forecast demand and operational load through time series forecasting and anomaly detection, while taking the cost of false alarms into account.
Training content
- Time series approach
- Anomaly detection
- Threshold setting
- Cost of false alarms
- Capacity planning and early warning dashboard design
At the end of this training, participants
- Will be able to grasp the basic logic of demand and operational workload forecasting models based on past trends.
- Will be able to define an anomaly approach suited to the processes to detect sudden spikes and deviations.
- Will be able to assess the risks of false alarms and misses from a cost perspective when setting early warning thresholds.
- Will be able to design how forecast outputs are linked to capacity and resource planning.
- Will be able to apply KPI and alarm design principles for early warning dashboards.
In this way, management will gain the operational visibility to intervene before problems grow.