Siebel Forecasting Guide > Common High-Level Forecast Usage Examples >
Opportunity Product Forecasting
A company might need to forecast both opportunity and product revenues related to opportunities, but only want to see forecast details by opportunity.
The forecast must incorporate both opportunity and product revenues related to opportunities.
Administrator Usage Example
The administrator defines an opportunity product forecast series. The Auto Forecast Search Spec is set as follows:
[Product] IS NOT NULL and [Calculated Primary Flag] = 'N'.
This search specification pulls product revenue line items that have the product indicated into the forecast.
End User Revenue Example
The end user:
- Creates a new opportunity.
- Associates and creates product revenue line items using the New Record command, revenue scripts, or revenue plans.
- Uses the Revenues list or spreadsheet views to edit and maintain product revenues (add quantity, cost, margin, price, and product line).
- Uses revenue charts and reports to graphically display data and to perform ad hoc analysis. For example, the end user can create charts and reports with the parameters revenue by opportunity or quantity by opportunity.
End User Forecast Example
The end user:
- Creates an opportunity product forecast.
- In the Details view, uses the spreadsheet and chart views to evaluate and adjust product revenues.
- Uses charts and reports to view product revenues by opportunity and to see aggregates of product quantity and revenue by opportunity.
- Uses queries to view live forecast details by opportunity.
Preconfigured, these queries are set up to query by product.
- Adjusts and submits forecasts.
NOTE: To roll up total quantity, the administrator needs to expose the quantity rollup in the total forecast. This is a simple configuration procedure. Also, to use the forecast queries to filter opportunities, the administrator needs to configure this.
About Forecasting Opportunity Products
The Expected Delivery Date field in the Opportunities screen > Products view determines the column (month) into which that product falls in the forecasting views. For example, several opportunity products can be combined into one product forecast record. The value that is seen for January for product x might be an aggregation of several opportunity product records. If the date on one of those records is changed, thereby knocking it out of the forecast, other records might still remain with slightly lower quantities or a slightly different average price.