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A
Appendix: Forecast Approval Exceptions
This appendix provides the details on approval and navigation exceptions defined for the GA version of IPOCS-Demand Forecasting.
The exception management framework available in RPASCE works on several levels. First, the users refines the approval and navigation rules in the Business Rule Engine.
The forecast approval method is one of the following options:
- Manual
The system-generated forecast is not automatically approved. Forecast values must be manually approved by accessing and possibly amending values in the Forecast Review workspace.
- Automatic
The system-generated forecast is automatically approved as is.
- By exception
This list contains the exceptions that were configured for use in the forecast approval process. They should match the dashboard exceptions and workspace alerts.
The unapproved Product/Locations are then assigned in order of priority to one of the following buckets:
-
Urgent
-
Required
-
Optional
-
Informational
Both the approval and navigation features can be configured to fit retailers’ needs.
Then, the batch is run and the approval and navigation exceptions are worked out. Now it is time to review them and take actions. First there is the dashboard. You can review the approval exception tiles and see which business rules had a larger impact. The navigation exception profile displays how many production/locations are in each of the navigation buckets. This helps you plan your work when reviewing forecasts in order of priorities, assigned using business rules. From here you can open the Forecast Review workspace. Once in the workspace, you can decide how to review the forecasts. Every dashboard exception can have a workspace alert counterpart. You can navigate to Product/Locations that are flagged as exceptions, or you can use the workspace exceptions, that point you to cells where the business rules have been violated. This is possible because the workspace alerts have the time dimension while dashboard exceptions are at the production/location intersection, pointing you to the time series that needs attention.
The following details the GA approval alerts calculations.
Forecast versus Recent Sales
Usually it is not expected that demand values differ very much period to period. This also implies that the forecast magnitude generally is in line with the magnitude of the most recent
May 15, 2026 Appendix A-1 of A-4
yiloday +alert window length adjusted baseline (t) rote > threshold1 alert window length l| View window length baseline demand LY (t) TTTalert window length > thresholdmeso && Diode +alert window length adjusted baseline (t) — 1) > threshold2 dtodaytoday+alert window length baseline. demand LY(t)
Adjusted Peak > Max Sales History * Causal Peak Factor
Appendix A Promo Peaks
Where the Causal Peak Factor is an adjustable parameter.
The business case this addresses is to alert you when the peaks in the forecast region are larger than any observed sales in the past. There may be valid justification for this, for instance, several events are active in the same time period, thus creating a huge spike in demand. You can review the alert and take action.
Enabling GA Approval Alerts
The process around enabling GA approval alerts is as follows:
1. GA alerts to be used in the approval process are configured in the IPO-DF plug-in
2. Only alerts enabled in the plug-in can be selected for the approval method in the Forecast Setup workspace.
3. The Forecast Approval process is limited to only the alerts selected in the Forecast Setup workbook. It calculates all of the enabled alerts for the unapproved Item/store combinations.
4. The dashboard then displays all of the enabled alerts for the unapproved Item/stor. However, the approval process is limited to only whatever was selected as the approval method.
5. Forecast vs. Last Year Sales Batch Alert is the same as Forecast versus Last Year Sales .
May 15, 2026 Appendix A-4 of A-4