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, TShirts 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. Formula is ABS(Plan  Actual) / Actual. 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. The time frame used is MAPE calculation interval. It is calculated as follows:
 Difference for each bucket = (Total  Actual)
 BIAS = number of difference above zero / all nonzero differences
 > 0.5 → OVER (The number of positive buckets are more than half of all buckets. Thus less time the Total Demand Plan was higher than Actual. Thus we are consistently OVER forecasting)
 < 0.5 → UNDER (The number of positive buckets are less than half of all buckets. Thus more often the Total Demand Plan was higher than Actual. Thus we are consistently UNDER forecasting)
 =0.5 → NONE (The number of positive buckets are exactly half of all buckets. Thus there is no bias)
 CoV: Coefficient of Variation over the last 52 weeks period of time calculation. To compute the coefficient of variation, we will only consider the nonzero 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
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