Abstract: A method for selecting forecasting models for generating timeseries workload forecasts for a contact center covering varying timeseries granularities and operating horizons. The method includes selecting, via a first selection process, a first select forecasting model from first candidate forecasting models for forecasting a workload level in accordance with a lower-granularity timeseries.

Abstract: A method for determining a select forecasting model from among candidate forecasting models for improving workload forecasts generated by a single forecasting model that cover both longterm and shorterm operating horizons. The method may include: receiving a timeseries dataset having values associated with operational metrics of a contact center; receiving the candidate forecasting models, each of the candidate forecasting models configured to receive values of the input operational metrics and calculate therefrom a forecasted value for a value of a target operational metric; using the timeseries dataset to test each of the candidate forecasting models in accordance with a cross-validation process; and selecting the select forecasting model from among the candidate forecasting models based on comparing accuracy scores calculated for the candidate forecasting models as part of the cross-validation process.

Abstract: A method for selecting forecasting models for generating timeseries workload forecasts for a contact center covering varying timeseries granularities and operating horizons. The method includes selecting, via a first selection process, a first select forecasting model from first candidate forecasting models for forecasting a workload level in accordance with a lower-granularity timeseries.