Demand Forecasting applications enable business managers to accurately predict the future distribution of services by geography and time. Demand Forecasting typically feeds the Territory Planning, Resource Planning, Multi-day Planning and Appointment Scheduling processes.

Demand Forecasting applications use historical job data to forecast future service demand. As time progresses, work history data is continuously fed back into the forecasting engine to increase forecast accuracy and improve operational performance.

Precision equals Power

Accurate forecasting can dramatically improve the quality of a wide range of operational decisions – from locating new service centers to setting customer appointments. Short-term forecasting is particularly critical for optimizing service delivery performance. Leveraging technologies that are used to predict power demand across 20% of the US electricity supply grid, Pointserve creates detailed forecasts of service demand based on the following key attributes:

	Geographic distribution – predicts where the service work is likely to be performed. For example: more work is likely to be needed in a central business district than in a rural area.
	Service type – predicts what service work is likely to be needed. For example: 100 installations, 75 repairs and 25 disconnects are likely required tomorrow.
	Service volume – predicts how much service work is likely to be needed. For example: Service volume may fluctuate according to weekly factors and seasonal trends.