These four functions enable you to determine statistical values for use with multilevel scenarios.

In the above graphic example, the figures represent the planned consumption of a product at different levels in the supply chain for one particular period. As well as aggregating the demand from the lower levels the locations also have their own consumption.

The function MULTILEVEL_DEMAND_MEAN forms the sum of these planned demands, in this case 100 + 150 + 130 + 40 + 20 = 440.

The function MULTILEVEL_DEMAND_VAR determines the error variance between the planned and actual values for the whole specified period or if you have not specified a period, the complete past.

(Error variance = where and are the planned and actual values respectively.)

The function MULTILEVEL_LEAD_MEAN calculates the planned lead time for a customer to a receive a product in the period. The system always uses the longest lead time, that is the values from the critical path. The system considers the time from the customer back to the next location that has safety stock. In the above graphic the value would be 6 days.

The function MULTILEVEL_LEAD_VAR determines the error variance between the planned and actual values for the whole specified period or if you have not specified a period, the complete past.

(Error variance = where and are the planned and actual values respectively.)