Outliers

Outliers are extreme demand points in historical demand that you can't explain using the forecasting process.

The forecasting process uses historical demand data, such as shipments and bookings, to detect outliers and replaces the missing data to minimize forecast errors. In such instances, the forecasting methods can adjust historical demand and smooth out extreme data points. The forecasting process also marks the points that were adjusted.

Understanding where outliers occurred can help in forecast analysis. By using tables and graphs for outlier analysis, you can know the following:

• Percentage of forecast combinations having outliers.

• Number of combinations where outliers are detected and adjusted.

• Average number of outliers found for a combination.

You can use these predefined page layouts for viewing outliers:

• Bookings Forecast Outlier Analysis

• Bookings Forecast Outlier Details

• Shipments Forecast Outlier Analysis

• Shipments Forecast Outlier Details

Also, you can add measures showing outlier values to any table or graph for historical demand to understand how it was adjusted during the forecast.