Calculate aggregate forecast
Optimize forecasting at more aggregated levels by grouping sales historical data taking advantage of a larger dataset.
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With this functionality you will leverage the aggregation of historical sales data to improve the forecast at more aggregated levels, benefiting from a broader data set.
By aggregating data at higher levels, random and seasonal variations are smoothed out, improving forecast accuracy by removing noise and highlighting underlying trends. Lower-level apportionments are made from historical weights detected on a month-by-month basis.
Technical sheet
| Version: | 1.0 |
|---|---|
| Last update: | 1/3/2024 |
| Tags: |
Integrate the plugin and go one step further in optimising your tool.
Data aggregation
Combines individual sales of similar products within the same family to get an overview of demand.
Trend identification
Identifies general patterns and trends in product family demand, helping to predict future behavior.
Last level apportionment
Distributes by historical weights of demand at product level and sales dimension.
Calculate aggregate forecast
Optimize forecasting at more aggregated levels by grouping sales historical data taking advantage of a larger dataset.
50€/mes
Request a free demo