Access this on-demand session for a practical introduction to time series forecasting and how it can be applied across public and commercial sectors. Time series methods have long been used to anticipate demand, plan resources and respond to external changes, with applications ranging from forecasting passenger volumes to estimating call centre activity or predicting visitor numbers using weather data.

This session explains the core principles of time series forecasting and demonstrates how to explore and visualise time-based data, define periodicity and apply exponential smoothing techniques. You will learn how to assess model fit, incorporate additional predictor fields to improve accuracy and generate clear, actionable forecasts from your data.

Designed for anyone interested in forecasting future outcomes using the data they already have, this on-demand session provides an accessible overview. Some familiarity with analytical concepts may help, but no formal statistical background is required.

Forecasting with time series analysis has been used in both the public and commercial sectors for decades.  Example applications include:

• Forecasting passenger numbers at ferry and airport terminals
• Estimating inbound call volumes to contact centres
• Predicting the load on information networks based on shift patterns and external events
• Using weather data to estimate visitor numbers at key attractions

In just one hour we will cover:-

• The principles of time series forecasting
• Visualising time series
• Defining periodicity
• Using exponential smoothing methods
• Interpreting model fit
• Incorporating predictor fields to improve forecasting accuracy
• Generating forecasts