History used for forecasting statistics is based on "Forecast history length (months)" and "Forecast history based on" defined in System Settings. The bucket type used for calculations is the Forecast bucket type.
Parent Node is the current level in which the forecast is being viewed. Child Node are the entities within the context of the Parent Node.
All calculations are based on approved plans that populate the waterfall.
Algorithm: The selected forecast algorithm. Available only on the forecasting level(s).
Revenue: Sum of last 52 weeks of revenue
Percentage: The percentage contribution within the sum of the revenue of all listed nodes in the grid (which are within one parent).
Cumm Percentage: The cumulative percentage is the cumulative sum of all Percentage values for this node
For example, T-Shirts which are Red, Yellow, Blue and Green, and their revenue is Red - 40%, Yellow - 30%, Blue - 20% and Green - 10%. Thus their cumulative percentage will be Red - 40%, Yellow - 70%, Blue - 90% and Green - 100%.
MAPE: Mean Absolute Percent Error. Calculated by taking the average absolute percent error of each month's or week's (if weekly buckets are used) total demand plan value against actual during a set number of periods as defined by MAPE calculation interval
Naive: The Mean Absolute Percent Error of the statistical forecast. Calculated by taking the average absolute error of each month's statistical forecast value against actual for each month or week. The goal is to have your total demand plan MAPE (Level MAPE) value be less than the statistical forecast MAPE value (Naive). The time frame used is MAPE calculation interval in system settings.
Bias: Is the measure to determine if the total demand plan is consistently over or under the actual value. If the value is Over it means the total demand plan is consistently greater than actual. If under, it is consistently less than actual. If None then the total demand plan is following the plan on average. The time frame used is MAPE calculation interval.
CoV: Coefficient of Variation over the last 52 weeks period of time calculation. To compute the coefficient of variation, we will only consider the non-zero values of the forecasting history.
ADI: Average Demand Interval measures the regularity of a demand in time by computing the average interval between two demands.
Forecast Profile: This is based on ADI & CoV, defining the type of demand as Smooth, Intermittent, Erratic or Lumpy.
Stability Index: A measure of how much the total demand deviates from the recent past. Stability Index is Average of Last 3 months forecasting history vs Average of Current + Next 2 months total demand plan