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Here is an example of my customer's forecast. After they create and run the week and publish schedules the below data appear. There seems to be an imbalance each week on the data that the forecast is providing. They typically have to make major adjustments to get the AHT to their standard numbers which in turn drives Service levels higher than they should be.
Before Manipulation: Forecast not touched.
Forecast after adjusting to previous historical data:
After Manipulation: Volume and AHT significantly
I would recommend opening a support case so it can be properly looked into.
If they create a forecast via weighted-historical index method, then the quality of the forecast relies on the quality of their historical day selections and weighting. If they are not using automatic best method forecast generation, I would first suggest using that method. They could even create a forecast for a period in the past and check actuals versus forecast, forecast error, and forecast accuracy in the forecast viewer/editor.
AHT and offered variances are specifically due to historical trends, patterns, etc. If those differ wildly either because historically they did and/or because of changing configuration or assumptions week-to-week, then obviously predicted service performance (e.g., SL, ASA, ABD) and staffing requirements will differ significantly.
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