How a fluctuating demand forecast works
When Demand forecast by fluctuating values is selected for an item or item‑warehouse combination, Sage Intacct uses the item’s fluctuating demand forecast to determine forecasted demand during each vendor’s lead time, by warehouse.
The examples in this topic show how the entries in a fluctuating demand forecast are used to determine an item's forecasted demand. The forecast is calculated from the As of date specified in the Replenish Inventory page through the supplier lead time. (The suppliers for an item and their lead times are specified in the item.)
All the examples assume that the item, Small Widgets, can be bought from two suppliers in Texas, and can be stocked in warehouses in Dallas, Houston, and San Francisco. The Supplier entries table in the Supplier history tab for Small Widgets has the following supplier information entered:
| Supplier ID | Lead time (days) | Economic order quantity | Supplier minimum order qty | Units of measure |
|---|---|---|---|---|
| Acme Widgets | 4 | 10 | 20 | Each |
| Widget Store | 10 | 20 | 60 | Each |
Example 1
In the example, a fluctuating demand forecast was created for Small Widgets with the needed quantities forecasted daily. Sales from the Dallas and Houston warehouses are about the same, but sales from the San Francisco warehouse are brisker. So, two entries were created for each day—one with no warehouse specified and one with the San Francisco warehouse specified. This is because the quantity needed per day is greater for the San Francisco warehouse from which more of the item is sold.
Portion of the fluctuating demand forecast for Small Widgets with daily forecast quantities
| Effective date | Forecast quantity | Warehouse |
|---|---|---|
| June 11 | 2 | |
| June 11 | 5 | San Francisco |
| June 10 | 2 | |
| June 10 | 8 | San Francisco |
| June 9 | 4 | |
| June 9 | 8 | San Francisco |
| June 8 | 5 | |
| June 8 | 10 | San Francisco |
| June 7 | 10 | |
| June 7 | 20 | San Francisco |
| June 6 | 10 | |
| June 6 | 20 | San Francisco |
| June 5 | 8 | |
| June 5 | 17 | San Francisco |
| June 4 | 8 | |
| June 4 | 17 | San Francisco |
| June 3 | 8 | |
| June 3 | 17 | San Francisco |
| June 2 | 7 | |
| June 2 | 12 | San Francisco |
| June 1 | 5 | |
| June 1 | 15 | San Francisco |
If the As of date in the Replenish Inventory page is June 1, Intacct calculates the demand forecast as shown in the following table. Intacct runs a query against the fluctuating demand forecast for Small Widgets. This is done to find the forecast quantity entered for each day for each warehouse during the demand forecast period (As of date + supplier lead time). By adding up the daily forecast quantities, Intacct arrives at the total demand forecast.
| Supplier ID | Lead time | Demand forecast period* | Demand forecast | Warehouse |
|---|---|---|---|---|
| Acme Widgets | 4 | June 1 to June 4 | 5 + 7 + 8 + 8 = 28 | Dallas |
| 5 + 7 + 8 + 8 = 28 | Houston | |||
| 15 +12 + 17 + 17 = 61 | San Francisco | |||
| Widget Store | 10 | June 1 to June 10 | 5 +7 + 8 + 8 + 8 + 10 + 10 + 5 + 4 + 2 = 67 | Dallas |
| 5 +7 + 8 + 8 + 8 + 10 + 10 + 5 + 4 + 2 = 67 | Houston | |||
| 15 + 12 +17 + 17 + 17 + 20 + 20 + 10 + 8 + 8 = 144 | San Francisco | |||
| *Note: Demand forecast period is As of date + supplier Lead time (days) | ||||
Example 2
The first example showed a fluctuating demand forecast with daily forecasted quantities. Your organization might forecast on a weekly or monthly basis. In this example, entries are entered by week. Like Example 1, sales from the Dallas and Houston warehouses are similar, but sales from the San Francisco warehouse are brisker. So, two entries were created for each week—one without an associated warehouse and one associated with San Francisco.
Portion of the fluctuating demand forecast for Small Widgets with weekly forecast quantities
| Effective date | Forecast quantity | Warehouse |
|---|---|---|
| June 29 | 20 | |
| June 29 | 50 | San Francisco |
| June 22 | 20 | |
| June 22 | 60 | San Francisco |
| June 15 | 30 | |
| June 15 | 70 | San Francisco |
| June 8 | 40 | |
| June 8 | 80 | San Francisco |
| June 1 | 25 | |
| June 1 | 65 | San Francisco |
If the As of date in the Replenish Inventory page is June 7, Intacct calculates the demand forecast as shown in the following table. Intacct runs a query against the entries and uses the full forecast for each week. It includes only weeks with dates on or after the As of Date and within the demand forecast period to calculate the total demand forecast.
| Supplier ID | Lead time | Demand forecast period* | Demand forecast during lead time | Warehouse |
|---|---|---|---|---|
| Acme Widgets | 4 | June 7 to June 10 | Week of June 8 is used. 40 | Dallas |
| Week of June 8 is used. 40 | Houston | |||
| Week of June 8 is used. 80 | San Francisco | |||
| Widget Store | 10 | June 7 to June 16 | Week of June 8 and 15 are used. 40 + 30 = 70 |
Dallas |
| Week of June 8 and 15 are used. 40 + 30 = 70 |
Houston | |||
| Week of June 8 and 15 are used. 80 + 70 = 150 |
San Francisco | |||
| *Note: Demand forecast period is As of date + Lead time (days) | ||||
