Decomposed (Single-stage) Inventory Optimization

Objective

After completing this lesson, you will be able to understand the usage of the decomposed (single-stage) inventory optimization algorithm.

Definiton of Single-stage Inventory Optimization Operator

You use the Decomposed (single-stage) inventory optimization operator to calculate recommended safety stock and target inventory position values locally for each product-location combination.

Because some of the inputs to the Decomposed (single-stage) inventory optimization operator are outputs of the Global (multi-stage) inventory optimization operator, you must run Global (multi-stage) inventory optimization before running Decomposed (single-stage) inventory optimization.

The operator is used to do the following:

Run simulations when you want to determine the impact on recommended safety stock for local changes to input key figures.
Produce missing data when you have an individual node of the supply chain with incomplete inventory data.
Calculate values for a scope defined by the planning filters or Microsoft Excel view filters.
Supports unit of measure conversion for input and output key figures.

The following figure shows the Decomposed (single-stage) inventory optimization operator, what inputs are used and what outputs result:

The figure describes the Local (Single-stage) Inventory Optimization.

The following table lists the demand inputs to the Decomposed (single-stage) inventory optimization operator:

Inputs	Type
IOFORECAST	Key figure
IOFORECASTERRORCV	Key figure
DEPENDENTLOCATIONDEMANDMEAN	Key figure
DEPENDENTLOCATIONDEMANDSTDDEV	Key figure
DEPENDENTLOCTOPRDDEMANDMEAN	Key figure
DEPENDENTLOCTOPRDDEMANDSTDDEV	Key figure
DEPENDENTSRCTOLOCDEMANDMEAN	Key figure
DEPENDENTSRCTOLOCDEMANDSTDDEV	Key figure
AVAILABLEINFULL	Key figure
INTERNALAVAILABLEINFULL	Key figure
INTERNALLOCTOPRDAIF	Key figure

The following table lists the policy parameter inputs to the Decomposed (single-stage) inventory optimization operator:

Inputs	Type
PBR	Attribute as key figure
PLUNITID	Master data type attribute
SAFETYSTOCKPOLICY	Master data type attribute
STOCKINGNODETYPE	Master data type attribute
SOURCETYPE	Master data type attribute
TDELIVERYTYPE	Master data type attribute
PDELIVERYTYPE	Master data type attribute
UOMCONVERSIONFACTOR	Attribute as key figure
IOCFROZENWINDOW	Attribute as key figure
IOTFROZENWINDOW	Attribute as key figure
IOPFROZENWINDOW	Attribute as key figure

The following table lists the lot size and lead time inputs to the Decomposed (single-stage) inventory optimization operator:

Inputs	Type
TLEADTIME or CALCTLEADTIME	Attribute as key figure or Key figure
TMINLOTSIZE or CALCTMINLOTSIZE	Attribute as key figure or Key figure
TINCLOTSIZE or TROUNDING or CALCTINCLOTSIZE	Attribute as key figure or Attribute as key figure or Key figure
PLEADTIME or CALCPLEADTIME	Attribute as key figure or Key figure
PMINLOTSIZE or CALCPMINLOTSIZE	Attribute as key figure or Key figure
PINCLOTSIZE or PROUNDING or CALCPINCLOTSIZE	Attribute as key figure or Attribute as key figure or Key figure
TLEADTIMEVARIABILITY or CALCTLEADTIMEVARIABILITY	Attribute as key figure or Key figure
PLEADTIMEVARIABILITY or CALCPLEADTIMEVARIABILITY	Attribute as key figure or Key figure

Inputs

Type

TLEADTIME

CALCTLEADTIME

Attribute as key figure

Key figure

TMINLOTSIZE

CALCTMINLOTSIZE

Attribute as key figure

Key figure

TINCLOTSIZE

TROUNDING

CALCTINCLOTSIZE

Attribute as key figure

Key figure

PLEADTIME

CALCPLEADTIME

Attribute as key figure

Key figure

PMINLOTSIZE

CALCPMINLOTSIZE

Attribute as key figure

Key figure

PINCLOTSIZE

PROUNDING

CALCPINCLOTSIZE

Attribute as key figure

Key figure

TLEADTIMEVARIABILITY

CALCTLEADTIMEVARIABILITY

Attribute as key figure

Key figure

PLEADTIMEVARIABILITY

CALCPLEADTIMEVARIABILITY

Attribute as key figure

Key figure

The following table lists the sourcing quotas and BOM inputs to the Decomposed (single-stage) inventory optimization operator:

Inputs	Type
RATIOTS	Master data type attribute
PRATIOTS	Master data type attribute
LOCATIONRATIO or TRATIO	Key figure or Master data type attribute
PRODUCTIONRATIO or PRATIO	Key figure or Master data type attribute

The following table lists the multi-echelon internal service level impact inputs to the Decomposed (single-stage) inventory optimization operator:

Inputs	Type
OUTGOINGBACKLOGMEAN	Key figure
OUTGOINGBACKLOGSTDDEV	Key figure
OUTGOINGSRCTOLOCBACKLOGMEAN	Key figure
OUTGOINGSRCTOLOCBACKLOGSTDDEV	Key figure

The following table lists the key figure outputs for the Decomposed (single-stage) inventory optimization operator:

Outputs	Base Planning Level
RECOMMENDEDSAFETYSTOCK	WKPRODLOC
TARGETINVENTORYPOSITION	WKPRODLOC
PROPAGATEDDEMANDMEAN	WKPRODLOC
PROPAGATEDDEMANDSTDDEV	WKPRODLOC

Run a Decomposed (Single-stage) Inventory Optimization

ExerciseStart Exercise

Business Example

As inventory planner you would like to run a decomposed (single stage) inventory optimization to compare results. To do that we will work during this exercise with the connection ZIOUNIFIED within the Planning Area ZIOUNIFIED.

Prerequisites

Planning View: IO210 Input Data Review ##, IO220 Planning Result ## and IO 240 InvComp Review ##.
All previous exercises are prerequisites for this exercise.
For this exercise we will work with FG1##.
Use the filters within the planning view based on Macros to activate the Graphs.

Note

Manual inputs are only feasible in the current and in the future period. Calculations will not affect the past in the planning horizon. Keep the planning views open as it is a suitable way to identify changes.

Steps

Go to the Application Jobs group to run the decomposed inventory optimization algorithm
1. Under Inventory Planning (advanced), click on Run.
2. Select Decomposed (single-stage) inventory optimization as Function under Inventory Planning Profile_SAP.
3. Select all planning units which correspond to your group number ## e.g. Planning Units: Brasil##, Europe##, India##, US## and Venezuela##.
4. Select Scenarios: Baseline, Versions: Base Version.
5. Use the filter you have created to show FG1##. Click on Next.
6. Select as Reason Code: Inventory and add a comment Running the single stage algorithm.
7. Click on Run and click on OK to confirm that you have scheduled a job.
8. Watch the progress in the dialog box. When the run is finished, choose Navigate to Status to view the list of logs. Close to return to planning view.
9. When the status is Finished close the window Inventory Optimization - Status.
10. Refresh all three planning views: IO210 Input Data Review ##; IO220 Planning Results ##; and, IIO 240 InvComp Review ##.
Note
Because the GIO Operator was already activated, we can see results under Recommended Safety Stock in the current and in the future periods as well
Go to the IO210 Input Data Review ## favorite to verify that there are no changes within the inputs tab by tab, for instance: IOCV, Demand Input, Production Input, Transportation Input and Cost Input.
1. Open your favorite IO210 Input Data Review ##. Filter by your group number ## to display your planning objects.
2. Verify that there are no changes within the inputs tab by tab.
Go to the IO220 Planning Result ## to identify changes.
1. Open your favorite IO220 Planning Result ##. Filter by your group number ## to display your planning objects.
2. Click on Refresh to update all key figures.
3. Verify on the tab HighLevel Results that there are changes within all combinations.
Go to the IO 240 InvComp Review ## to update the sheets.
1. Open your favorite IO 240 InvComp Review ##. Filter by your group number ## to display your planning objects.
2. Verify on the tab InvComp(Avg), InvComp(Target) and Plnd on Hand vs. Proj. Stock whether there are changes or not. What is your guess? Why?

Result

Results

After this exercise, you have seen how you can activate the decomposed single stage inventory optimization after having activated the global inventory optimization and the target inventory components calculation.

Note

During these exercises we have not saved previous results. The Single-stage Inventory Optimization algorithm overwrites the results from Global multi-stage Inventory Optimization algorithm. Observe that Propagated Demand Mean was calculated.

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