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A sales representative at a large company is responsible for forecasting. She creates a periodic forecast by selecting a predefined forecast series. The application automatically creates her forecast by applying the forecast search rules, or a query to the account, opportunity, and partner-related revenue that she is managing. The sales representative analyzes the forecast data, viewing the anticipated revenues by product line and then by account. She then adds a revenue item and modifies an existing revenue item before submitting the forecast to her manager.
After the sales team members have submitted their forecasts, the sales manager runs the same forecast series, which aggregates the teams' submissions. In this way, the sales organization can poll its members for their projected results for the period. The manager modifies the results of the forecast by adjusting one of the individual forecasts submitted. This change to a forecast will not carry over to any corresponding revenue records. To keep his data accurate, the sales manager updates the corresponding live revenue records with the changes he made to the forecast.
The sales manager then remembers that the last time he created this same forecast, he made changes to it as well. He selects auto-adjust to automatically apply the changes made in the most recent forecast to this forecast. This makes sure that any adjustments that were made in the last forecast (the most recent forecast date available) are automatically added to the current forecast. Finally, he analyzes the forecast using charts and reports, and when he is satisfied with it, he submits the forecast to his manager.
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