Variant Configuration in SAP: Description of complex products that are manufactured in many variants (for example, cars).
All variants are defined as one variant product
The variant product has a super BOM (Bill of Material), containing all the components that can be used in the product, and a super task list, containing all the operations that can be used to manufacture the product.
By assigning the variant product to a class, you assign characteristics to the variant product
You use these characteristics to describe an individual variant
Object dependencies ensure that the correct components are selected from the super BOM and the correct operations are selected from the super task list.
When Product is configured the following Master Data is accessed.
Material Master and BOM Data for Configurable Materials
Basic Data – Tick Material is configurable indicator
Sales View – It category group
0002 or 0004
MRP View — Strategy group for ex. 25
— Availability check 02
— MRP type PD ( MRP)
— Lot Size EX(Lot for lot order Qty)
Classification View – Class type 300
BOM usage – 3 Universal.
Variant Configuration in SAP
The list below various Transactions in Variant Configuration as below
1. Create Class with Variant Material Name:
Menu Path :Logistics>Central Functions>Classification>Master Data>Classes.
Transaction code: CL02
2.Assign Header ( Variant) Material Object to the class.
Menu Path: Logistics>Central Functions>Classification>Assign Objects to Class.
Transaction code: CL20N.
In this step – also create characteristics and assign values to the characteristics.
3.Create Configuration Profile:
Menu Path Logistics>Central Functions>Variant configuration>Configuration profile>Create
Transaction Code: CU41.
Here you assign specific value of each characteristics to the profile.
Menu Path Logistics>Central Functions>Variant configuration>Dependency>
Transaction code: CU01
You can use the configuration simulation to check your configuration model. In the configuration simulation, you can test whether you have created the objects correctly and whether your dependencies work.
The BOM for the configuration result is selected according to the BOM application in the configuration profile.
Menu Path : Logistics>Central Functions>Variant configuration>Environment>
Transaction ode: CU50
To Working with Configurable BOMs
You work with configurable BOMs if you manufacture a product with many variants. You produce the product especially for your customers, who specify how the product should look. In doing this, you use variant configuration.
Process Flow for super BOM
You create a super BOM Apart from the components that are relevant to all variants, this bill of material also contains selectable components. You maintain the bill of material for a configurable material as you would a normal material BOM.
You define in, for instance, object dependencies, the conditions according to which the selectable components should be selected during configuration.
You perform configuration, for instance, when entering a sales order.
The system selects the desired and suitable components from those that are selectable.
Also See: How to Change the Type of Price Control in SAP?
A forecasting method is a category (or specific group) of algorithms. A forecasting technique is a specific type of algorithm used to address a certain data condition. A a forecasting model is the final application of the technique.
Each model and application of the technique can be different based on the situation, purpose, and/or data configuration.
Based on existing plan or actual data, new plan data is generated for a certain time period. Various forecast strategies or models are supported such as moving average, 2nd order exponential smoothing, and seasonal models. The models and forecast parameters are maintained in forecast profiles. Using a forecast profile, you can forecast plan values for several combinations of characteristics and key figures.
A forecast profile consists of a strategy and a grouping of parameters, according to which, you can project existing plan or actual data into the future.
The profile allows you to execute the forecast repeatedly without having to make the forecast settings each time.
Each profile has a forecast strategy. This defines the forecast model, for example constant, trend, seasonal model, together with the desired parameters.
When a series of consumption values is analyzed, it normally reveals a pattern or patterns. These patterns can then be matched up with one of the forecast models listed below:
Constant -consumption values vary very little from a stable mean value
Trend – consumption values fall or rise constantly over a long period of time with only occasional deviations
Seasonal -periodically recurring peak or low values differ significantly from a stable mean value
Seasonal trend -continual increase or decrease in the mean value.
Forecast Parameters: Independent of the Forecast Model
You can/must maintain the following parameters independent of the method you use for model selection and which model you choose.
Period indicator:The period indicator determines the time interval the system is to use to store consumption or forecast values.
Fiscal year variant: You must maintain the fiscal year variant if you want a flexible period length for the material equal to that of the accounting period.
Historical values:You specify how many historical values the system should take into account for the forecast by filling in this field. The default value in this case is the maximum number possible (60).
Initialization periods : You specify the number of periods the system is to use for model initialization here.
Forecast periods: Via the number of forecast periods, you specify for how many periods the system determines forecast values.
Fixed periods via the number of fixed periods, you determine how many periods are fixed in the future and are no longer automatically changed by the next forecast run.
Correction factors If you fill in this field, historical values and forecast values are weighted with the appropriate period factors which you determined via customizing.
Forecast Parameters: Dependent on the Forecast Model
Alpha factor The system uses the alpha factor for smoothing the basic value. If you do not specify an alpha factor, the system will automatically use the alpha factor 0.2.
Beta factor The system uses the beta factor for smoothing the trend value. If you do not specify a beta factor, the system will autimatically use the beta factor
Gamma factor The system uses the gamma factor for smoothing the seasonal index. If you do not specify a gamma factor, the system will automatically use the gamma factor 0.3.
Delta factor The system uses the delta factor for smoothing the mean absolute deviation and the error total. If you do not specify a delta factor, the system will automatically use the delta factor 0.3.
Also See: What is SAP Advanced Planning and Optimizer (SAP APO)
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