The system offers two different methods for forecasting product demand. The default is Standard. You can select one of the following forecasting methods:
Standard for products with larger demand histories.
Median for products with smaller demand histories.
The system identifies and eliminates from demand forecasting any sales exceeding the back order tolerance quantity (BTQ) during the forecast period.
After eliminating sales exceeding the BTQ, the system eliminates from demand forecasting any sale exceeding the exceptional sale percent during the forecast period.
The system adds the remaining sales quantities together and divides the sum by the number of days in the forecast period.
This demand per day is then multiplied by 30 to produce a monthly demand. The system rounds up to the nearest unit.
For example, Product A sells ten times in a forecast period of 365 days in the following quantities: 200, 100, 9, 8, 7, 6, 5, 4, 3, and 2. The sale of 200 is exceptional and eliminated from demand forecasting. The system adds the remaining quantities together (100+9+8+7+6+5+4+3+2=144) and divides the sum by the days in the demand period (144/365=.394). The system then multiplies the daily demand by 30 days (one month) to produce a monthly demand of 12 units (.394*30=11.82).
Consider that if Product A had a BTQ set to 100, the sale of 200 would be eliminated and the sale of 100, being 50% more than the second largest sale of 9, would be considered an exception and eliminated from demand forecasting. Adding the remaining quantities together (9+8+7+6+5+4+3+2=44), dividing by the days in the demand period (44/365=0.12), and multiplying by 30 days would produce a monthly demand of only 4 units (0.12*30=3.61).
The system identifies and eliminates from demand forecasting, any sales exceeding the BTQ and the exceptional sale percent during the forecast period.
The system identifies the median quantity of the remaining sales and multiplies this quantity by the number of hits counted in the forecast period.
This daily demand is multiplied by 30 days to produce a monthly demand. The system rounds up to the nearest unit.
For example:
Product A does not have a BTQ set. The exceptional sales percent equals 50%. Product A sells ten times in a forecast period of 365 days in the following quantities: 200, 100, 9, 8, 7, 6, 5, 4, 3, and 2. The sale of 200 is proven to be exceptional and eliminated from demand forecasting. The median of the remaining quantities (100, 9, 8, 7, 6, 5, 4, 3, 2) is 6. The system multiplies the median quantity by the number of hits counted (6*9=54) and divided by the days in the forecast period (54/365=.148). The system then multiplies the daily demand by 30 days to produce a monthly demand of 5 units (.148 x 30=4.4).
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