DRP - Forecast Method FAQ

Available to Promise

Character

Standard

This determines the logic to be used for the available to promise calculation. For more information, see DRP - Available to Promise FAQ.

• Standard - The standard Available to Promise window is displayed.

• Option 1 - Certain companies want to protect availability for forecasted sales in the future (based on the Available To Promise Days parameter).

Available To Promise Days

Integer

0

This is the available to promise days. This is used in conjunction with the Available to Promise parameter. For more information, see DRP - Available to Promise FAQ.

Exclude Promotional Sales

Logical

No

Select one of the following options:

• Yes - Exclude promotional sales from the Adjusted Net Sales row in Product DRP Management.

• No - Include promotional sales in the Adjusted Net Sales row in Product DRP Management.

Forecast Direct Ship

Logical

No

Select one of the following options:

• Yes - Displays and enables the Direct Ship check box in Product DRP Management, so that actual and forecasted direct/drop ship sales are displayed by forecast group.

• No - Does not display or enable the Direct Ship check box in Product DRP Management.

Forecast Frozen Periods

Integer

0

Select one of the following values for the number of forecast frozen periods (periods for which automatic reforecasting is not changed):

• 0 - No frozen periods are used.

• 1 - The current time bucket is frozen.

• 2 (or more) - The specified number of time buckets are frozen, including the current time bucket.

Note Forecasts can still be manually changed for forecast frozen periods.

Forecast Hold

Character

Standard

This determines the logic used for putting sales orders on forecast hold. For more information, see DRP - Forecast Hold FAQ. Select one of the following values:

• Standard - Forecast hold is not enabled.

• Customer Forecast - When an order is entered or updated, each line is evaluated to determine whether the customer forecast by forecast group has been exceeded.

• Actual Forecast - When an order is entered or updated, each line is evaluated to determine whether the actual forecast by forecast group has been exceeded.

Forecast Hold % Overage

Integer

0

Enter the percentage overage that you will tolerate. If a order line is for a percentage that is greater than this percentage, the order is placed on forecast hold.

Forecast Hold Shipment Quantity

Character

Standard

Select one of the following to determine allocation for orders on forecast hold:

• Forecast Allocation - Allocate up to the remaining forecast amount. The forecast amount is based on the Forecast Hold parameter.

• No Allocation - Do not allocate any quantity to order lines on forecast hold.

• Standard - Fully allocate order lines even if an order is on forecast hold.

Forecast Logic

Character

Standard

Select one of the following to configure how the Actual Forecast row is calculated in Product DRP Management:

• Standard - The Actual Forecast is set equal to the manual override forecast if it is available. If it is not available, the Actual Forecast is set to the Customer Forecast if it is available. If the Customer Forecast is not available, the Actual Forecast is set to the System Forecast.

• Customer - The Actual Forecast is set to the Customer Forecast, even if it is zero or blank. The All Other forecast group uses the system forecast because it does not have a customer forecast.

• System - The Actual Forecast is set to the System Forecast, even if it is zero or blank.

• Highest - The Actual Forecast is set to either the Customer Forecast or the System Forecast, whichever is a higher value.

• Lowest - The Actual Forecast is set to either the Customer Forecast or the System Forecast, whichever is a lower value.

Forecast View

Character

Standard

This determines how the Manage Product Forecasts tab in Product DRP Management is displayed. Select one of the following options:

• Standard - Standard format

• Customer Forecast - Customer Forecast format.

Note This can be overridden for specific users in User Extended Options.

History Data

Character

Default

This determines whether point of sale amounts are used for sales history data. Select one of the following options:

• Default - Calculate forecasts using shipment data for sales history.

• POS - Calculate forecasts using point of sale data for sales history.

Promotional Forecast Logic

Character

Include

This determines whether the Promotional Forecast row quantities are included in the Actual Forecast row and the remaining forecast in Product DRP Management. Select one of the following options:

• Include - Include any quantity in the Promotional Forecast row in the Actual Forecast row and the remaining forecast.

• Exclude - Exclude any quantity in the Promotional Forecast row from the Actual Forecast row and the remaining forecast.

Remainder Forecast

Character

Total

This determines how the Remaining Sales Forecast row is calculated on the DRP Schedule Management tab in Product DRP Management. Select one of the following:

• Total - All forecast groups consolidated

• Forecast Group - Forecast groups individually evaluated

For an example of using both options, see below.

Time Bucket

Character

Month

This determines the time period columns used for calculations and for display in Product DRP Management. Month, Week, and Day are valid options.

Note If you change this to Month or Week, rebuild customer forecasts in Forecast Create.

Time Horizon Forward

Integer

6

This indicates how many time buckets into the future to forecast.

Average
(methfcave.p)

This method is used for products expected to have a relatively steady sales pattern where there may be some slight seasonality, but no radical seasonality. It uses a pure moving average based on the prior sales history time bucket of calendar days, weeks, or months.

Time Horizon Past

Integer

6

This indicates how many time buckets into the past to use to calculate the average.

Average-RAD Season
(methfcavrs.p)

This method is used for products with radical seasonality (for example, snow shovels). It uses the prior year as a starting point, then calculates the average moving forward (instead of moving backwards) and a percentage +/- change to calculate forecast.

Time Horizon Past

Integer

2

This indicates how many time buckets to go forward from the previous year’s starting point to use to calculate the average.

RAD Seas-% chg last year

Decimal

3%

Custom
(methfccustom.p)

This method is used if you have created a program that contains custom forecast logic.

Custom Forecast Logic

Character

This is the file name of the .p that contains your custom forecast logic.

ExpSmooth
(Methfcexph.p)

This exponential smoothing method weighs the most current sales history heavier than the least current sales history.

This forecast method should not be used for radically seasonal products because it will result in invalid forecasts.

Alpha

Decimal

0.3

This is a smoothing factor that controls the weight of sales history. If you increase the value of the Alpha parameter, you increase the affect of the current month's sales history on the calculated forecast. For more information on how this parameter affects forecast calculations, see the example below.

Time Horizon Forward

Integer

1

This indicates how many time buckets into the future to forecast.

Time Horizon Past

Integer

12

This indicates how many time buckets into the past to use for the calculations.

MildSeasonalAvg
(methfcmsea.p)

This forecast method uses a seasonal index along with a moving average. The moving average first is de-seasonalized (either period by period, or by a group of periods), then re-seasonalized for the forecast periods. This moving average detects whether there is stronger or slower demand for each season.

This forecast method should not be used for radically seasonal products because it will result in inappropriate forecasts.

Group by Deseasonalization

Logical

No

Select one of the following options:

• Yes - Deseasonalize with the grouping of periods entered for the Periods to Deseasonalize parameter.

• No - Deseasonalize each period by itself.

Periods to Deseasonalize

Integer

4

This is the number of periods to group together if you enter Yes for the Group by Deseasonalization parameter.

Time Horizon Past

Integer

12

This indicates how many time buckets into the past to use for the calculations.

RAD Season
(methfcrad.p)

This method is used for products with radical seasonality (for example, snow shovels). It uses the prior year actual results and a percentage +/- change to calculate this year’s forecast.

Only use this forecast method for radically seasonal products.

RAD Seas-% chg last year

Decimal

-.10

This is the radical seasonality percentage change compared to the actual prior year's sales.

Weighted Average
(methfcavwa.p)

This method is used for products for which future order demand and previous sales cannot be directly correlated. It uses a weighted moving average based on the prior sales history and/or prior order history across two separate time buckets of calendar days, weeks, or months.

Order History Date

Character

Order

This is the type of date used for order history (either Order or Required).

Time Horizon Order History 1

Integer

6

This is the first number of past time buckets (based on the value of the Time Bucket parameter) to use for order history.

Time Horizon Order History 2

Integer

2

This is the second number of past time buckets (based on the value of the Time Bucket parameter) to use for order history.

Time Horizon Order History Weight 1

Decimal

.25

This is the weight of the order history for the first range of history. The sum of the Time Horizon Order History Weight 1, Time Horizon Order History Weight 2, Time Horizon Sales History Weight 1, and Time Horizon Sales History Weight 2 parameters must equal 1.

Time Horizon Order History Weight 2

Decimal

.25

This is the weight of the order history for the second range of history. The sum of the Time Horizon Order History Weight 1, Time Horizon Order History Weight 2, Time Horizon Sales History Weight 1, and Time Horizon Sales History Weight 2 parameters must equal 1.

Time Horizon Past

Integer

6

This parameter is not used for this forecast method.

Time Horizon Sales History 1

Integer

6

This is the first number of past time buckets (based on the value of the Time Bucket parameter) to use for sales history.

Time Horizon Sales History 2

Integer

2

This is the second number of past time buckets (based on the value of the Time Bucket parameter) to use for order history.

Time Horizon Sales History Weight 1

Decimal

.25

This is the weight of the sales history for the first range of history. The sum of the Time Horizon Order History Weight 1, Time Horizon Order History Weight 2, Time Horizon Sales History Weight 1, and Time Horizon Sales History Weight 2 parameters must equal 1.

Time Horizon Sales History Weight 2

Decimal

.25

This is the weight of the sales history for the second range of history. The sum of the Time Horizon Order History Weight 1, Time Horizon Order History Weight 2, Time Horizon Sales History Weight 1, and Time Horizon Sales History Weight 2 parameters must equal 1.

Yr over Yr Seasonality
(methfcyoys.p)

This forecast method calculates a seasonal year to year rate of change (growth or decline), which is used for forecast calculations.

NOTE You must use monthly time buckets for this forecast method.

# of Months - Max Forecast

Integer

0

This is the number of months to go back from the current month to search for the highest adjusted net sales.

EXAMPLE If the current month is February 2020 and this is set to 12, the system will seek the highest sales from February 2019 to January 2020.

The forecast going forward cannot exceed this value. If 0 is entered, this logic is ignored.

# of Months - Change Factor

Integer

0

This is the number of months to go back from the current month. This is used for the change factor calculation.

EXAMPLE If this value is 4, and the current month is February 2020, then it will add the four months preceding (October 2019, November 2019, December 2019, and January 2020 = 150) and this will be the numerator, and then add the same four preceding months from a year ago (October 2018, November 2018, December 2018 and Jan 2019 = 100) and this will be the denominator. So, the change factor will be 1.5.

Change Factor Option

Character

Current Month

Select one of the following options:

• Current Month - The system calculates the rate for the current month and uses the rate for all forecast months.

• Rolling Month - The system calculates the rate for each forecast month.

Time Horizon Past

Integer

24

This indicates how many time buckets into the past to use for the calculations.