Global (Multi-stage) Inventory Optimization

Objective

After completing this lesson, you will be able to understand the SAP integrated business planning logic for multi-stage inventory optimization.

Definition of Global Multistage Inventory Optimization Operator

Configuring the Planning Horizon Parameter for Inventory Optimization

Standard planning areas have planning horizons defined. You may want to do the following:

  • Use planning horizons different than the standard planning area planning horizons

  • Apply different planning horizons at the planning unit level

To use different planning horizons than the standard, you can define planning horizon parameters for inventory optimization planning operators. The planning horizon parameter value is equal to calendar weeks. The following operators support the planning horizon parameter:

  • Multistage Inventory Opt

  • Calculate Inventory Components

  • Single-Stage Inventory Opt

The following table details the planning horizon parameter:

ParameterDescription
PLANNING_HORIZONPositive integer value that represents calendar weeks.

Note

For detailed information about configuring inventory optimization operators, see Inventory Optimization (IO) Operator in the model configuration guide.

Operator Running Sequence

For the most accurate calculation results, there is a suggested running sequence for the operators. The sequence is the same for both batch and simulation modes, and is as follows:

  1. Run the Manage Forecast Error Calculations Inventory Optimization app.
  2. Run the Global (multistage) inventory optimization operator.
  3. Run the Calculate Target Inventory Components operator or run the Decomposed (single-stage) inventory optimization operator.

The following figure illustrates the run sequence:

Overview available planning operators in inventory optimization

Note

When you run inventory operators, if output key figure data does not display for certain time periods but displays for others, verify that week level time periods are seven days long. If you’re using a week level time profile, weeks must contain seven days. If you need to break weeks that cross months, use technical week time profile.

Key Figure Dependencies

The unified planning area delivered as sample content has built in logic where one key figure requires the existence of other key figures. These key figure dependencies that can cause some operators to run incorrectly or fail to run.

For the Global (multistage) inventory optimization operator, the dependencies are as follows:

If the key figure SAFETYSTOCKDEMANDVAR exists in the planning area, the following key figures must also exist in the planning area:

  • SAFETYSTOCKSUPPLYVAR

  • SAFETYSTOCKSERVICEVAR

  • SAFETYSTOCKLOTSIZE

  • AVERAGESERVICELEVEL

If the key figure CALCTLEADTIME exists in the planning area, the following key figures must also exist in the planning area:

  • CALCTLEADTIMEVARIABILITY

  • CALCTMINLOTSIZE

  • CALCTINCLOTSIZE

If the key figure CALCPLEADTIME exists in the planning area, the following key figures must also exist in the planning area:

  • CALCPLEADTIMEVARIABILITY

  • CALCPMINLOTSIZE

  • CALCPINCLOTSIZE

    Attributes as Key Figures and Time Period Ranges

    We recommend that you set the time period range for attributes as key figures to be from 0 (zero) to at least 13 weeks.

    You will need to reload data at the frequency you use for the range. That is, if you set the range to 13 weeks, you will need to reload data every 13 weeks.

    The best practice is to set the time period range to 13 weeks (or fewer), but if you choose not to update that frequently, we suggest you update every 26 weeks.

    Global (Multistage) Inventory Optimization Operator

    You use the Global (multistage) inventory optimization operator to recommend safety stock across all products and locations of the supply chain. The optimization minimizes your total safety stock holding cost while ensuring that all customer service level targets are met. The operator performs the following:

    • Optimizes safety stock globally and simultaneously across all products and locations of a supply chain while considering demand uncertainties, supply uncertainties, supply quantity, lead times, costs, and service levels.

    • Propagates forecast and forecast variability to stocking nodes that have customer demand.

    • Propagates forecast and forecast variability to internal (upstream) nodes of a supply chain network.

    • Optimizes internal service levels between internal (upstream) nodes of the supply chain network.

    • Calculates safety stock targets, backorders, and average expedited quantities.

    • Calculates values for the whole supply chain network.

    • Supports subnetwork/planning unit (PLUNITID) filters in batch mode.

    • Supports unit of measure conversion for input and output key figures.

    The Global (multistage) inventory optimization operator considers the aggregated demand and outgoing backlog when recommending safety stock in a time-varying binary sourcing environment (that is when the lead time at one supplier is extensively longer than the lead time of the other supplier).

    The operator also considers smoothing for continuous binary sourcing. Spikes and dips in supply are detected based on the sum of the incoming supply ratios offset by their respective lead times. A spike in a period is removed using the maximum arc’s recommended safety stock for that period. A dip is removed using the average of the recommended safety stock before and after that period. Binary sourcing input data must exist in each period of the planning area’s planning horizon configuration for smoothing to work.

    The operator uses the following push logic for non-stocking nodes: for the relationship Stocking Node A → Non-Stocking Node B → Stocking Node C, Lead Time and Lead Time Variability between Stocking Node A and Non-Stocking Node B is pushed to Stocking Node C. The higher the Lead Time or Lead Time Variability, the higher the Recommended Safety Stock at Stocking Node C. The Recommended Safety Stock at Stocking Node C is aligned with pure push logic (that is, cumulative lead time is considered).

    Note

    Stocking Node A can be an internal or external (vendor) node, and supports BOM in non-stocking components. If the non-stocking node is multi-sourced or multiple components in a bill of material, then the lead time is not pushed.

    The Global (multistage) inventory optimization operator rounds the fractional exposure period up to a multiple of weeks in the calculation of the recommended safety stock due to service variability. For example, if periods between replenishment (PBR) = 1 day and lead time = 1 week, the exposure period of 1.14 is rounded up to 2 weeks. The recommended safety stock due to service variability is then calculated based on the demand over the past two weeks.

    The following figure shows the stages of the Global (multistage) inventory optimization operator and what inputs are used:

    The figure describes the Global (Multistage) Inventory Optimization: Inputs attributes and key figures.

    The following table lists the policy parameter inputs to the Global (multistage) inventory optimization operator:

    InputsType
    PBRAttribute as key figure
    PLUNITIDMaster data type attribute
    MININTERNALSERVICELEVELAttribute as key figure
    MAXINTERNALSERVICELEVELAttribute as key figure
    INVENTORYHOLDINGCOSTRATEKey figure
    MAXINVENTORYVIOLATIONCOSTRATEKey figure
    IOMAXINVENTORYKey figure
    SERVICELEVELTYPEMaster data type attribute
    SAFETYSTOCKPOLICYMaster data type attribute
    STOCKINGNODETYPEMaster data type attribute
    SOURCETYPEMaster data type attribute
    TDELIVERYTYPEMaster data type attribute
    PDELIVERYTYPEMaster data type attribute
    DISTRIBUTIONTYPEMaster data type attribute
    UOMCONVERSIONFACTORAttribute as key figure
    PLOTSIZECOVERAGEAttribute as key figure
    TLOTSIZECOVERAGEAttribute as key figure
    IOCFROZENWINDOWAttribute as key figure
    IOTFROZENWINDOWAttribute as key figure
    IOPFROZENWINDOWAttribute as key figure

    The following table lists the demand inputs to the Global (multistage) inventory optimization operator:

    InputsType
    IOFORECASTKey figure
    IOFORECASTERRORCVKey figure
    IOLAGFORECASTERRORCVKey figure
    IOLAGFORECASTERRORCVTYPEKey figure
    TARGETSERVICELEVELAttribute as key figure

    The following table lists the lot size and lead time inputs to the Global (multistage) inventory optimization operator:

    InputsType
    TLEADTIMEAttribute as key figure
    TMINLOTSIZEAttribute as key figure

    TINCLOTSIZE

    or

    TROUNDING

    Attribute as key figure

    or

    Master data type attribute

    PLEADTIMEAttribute as key figure
    PMINLOTSIZEAttribute as key figure

    PINCLOTSIZE

    or

    PROUNDING

    Attribute as key figure

    or

    Master data type attribute

    TLEADTIMEVARIABILITYAttribute as key figure
    PLEADTIMEVARIABILITYAttribute as key figure

    The following table lists the sourcing quotas and BOM inputs to the Global (multistage) inventory optimization operator:

    InputsType
    RATIOTSMaster data type attribute
    PRATIOTSMaster data type attribute
    OUTPUTCOEFFICIENTTTSMaster data type attribute
    COMPONENTCOEFFICIENTTSMaster data type attribute

    LOCATIONRATIO

    or

    TRATIO

    Key figure

    or

    Attribute as key figure

    PRODUCTIONRATIO

    or

    PRATIO

    Key figure

    or

    Attribute as key figure

    OUTPUTCOEFFICIENTKey figure
    COMPONENTCOEFFICIENTKey figure

    The following figure shows the stages of the Global (multistage) inventory optimization operator and what outputs result:

    The figure describes the Global (Multistage) Inventory Optimization: Outputs attributes and key figures.

    The following table lists the key figure outputs for the Global (multistage) inventory optimization operator:

    OutputsBase Planning Level
    RECOMMENDEDSAFETYSTOCKWKPRODLOC
    SAFETYSTOCKDEMANDVARWKPRODLOC
    SAFETYSTOCKSUPPLYVARWKPRODLOC
    SAFETYSTOCKSERVICEVARWKPRODLOC
    SAFETYSTOCKLOTSIZEWKPRODLOC
    IOMERCHANDISINGSTOCKWKPRODLOC
    PROPAGATEDDEMANDSTDDEVWKPRODLOC
    AVERAGESERVICELEVELWKPRODLOC
    DEMANDRAMPDOWNINDWKPRODLOC
    DEMANDPHASEOUTINDWKPRODLOC
    DEPENDENTSRCTOLOCDEMANDMEANWKPRODLOCSRC
    DEPENDENTSRCTOLOCDEMANDSTDDEVWKPRODLOCSRC
    OUTGOINGSRCTOLOCBACKLOGMEANWKPRODLOCSRC
    OUTGOINGSRCTOLOCBACKLOGSTDDEVWKPRODLOCSRC
    CALCPLEADTIMEWKPRODLOCSRC
    CALCPLEADTIMEVARIABILITYWKPRODLOCSRC
    CALCPMINLOTSIZEWKPRODLOCSRC
    CALCPINCLOTSIZEWKPRODLOCSRC
    INTERNALLOCTOPRDAIFWKPRODLOCCOMPSRC
    DEPENDENTLOCTOPRDDEMANDMEANWKPRODLOCCOMPSRC
    DEPENDENTLOCTOPRDDEMANDSTDDEVWKPRODLOCCOMPSRC
    AVAILABLEINFULLWKPRODLOCCUSTGROUP
    DEPENDENTCUSTOMERDEMANDMEANWKPRODLOCCUSTGROUP
    DEPENDENTCUSTOMERDEMANDSTDDEVWKPRODLOCCUSTGROUP
    LOSTCUSTOMERDEMANDMEANWKPRODLOCCUSTGROUP
    DEPENDENTLOCATIONDEMANDMEANWKPRODLOCLOCFR
    DEPENDENTLOCATIONDEMANDSTDDEVWKPRODLOCLOCFR
    INTERNALAVAILABLEINFULLWKPRODLOCLOCFR
    OUTGOINGBACKLOGMEANWKPRODLOCLOCFR
    OUTGOINGBACKLOGSTDDEVWKPRODLOCLOCFR
    CALCTLEADTIMEWKPRODLOCLOCFR
    CALCTLEADTIMEVARIABILITYWKPRODLOCLOCFR
    CALCTMINLOTSIZEWKPRODLOCLOCFR
    CALCTINCLOTSIZEWKPRODLOCLOCFR
    INTERNALLOCTOPRDAIFWKPRODLOCCOMPSRC
    DEPENDENTLOCTOPRDDEMANDMEANWKPRODLOCCOMPSRC
    DEPENDENTLOCTOPRDDEMANDSTDDEVWKPRODLOCCOMPSRC

    The following table lists the Location Product master data type attribute outputs for the Global (multistage) inventory optimization operator:

    Mater Data Type Attribute
    NETWORKID
    IOECHELONID

Note

To run the inventory operators, specific technical IDs defined by SAP must be used for the relevant master data types, attributes, and key figures. If these technical IDs are not used, the inventory operators will fail.

Series or Tandem Supply Chain

The tandem or series supply chain has the following features:

  • Simplest model

  • Node versus stocking point

  • Single versus multi-stage (echelon)

  • Upstream versus downstream

  • Pull and demand propagation

  • Calculation (single-stage)

  • Optimization (multi-stage)

The figure describes the Series Supply Chain.

Process and Distribution Supply Chains

Compare the two supply chain concepts depicted in the following figure to get an impression of what the different supply chains look like.

The figure describes the Supply Chains.

Supply Chain Network Representation

The following figure is the representation of the actual facilities and distribution options. It is a traditional modeling approach.

The figure describes the Supply Chain.

Here is how to represent the actual facilities in an accurate inventory model, using the appropriate symbols.

The figure describes the Inventory Model.

Multi-stage Dilemma

The following figure shows a customer-facing (CF) node satisfying external demand with the following features:

  • Service Level is 95% (NSP)

  • Forecasts are moderately good

The figure describes the Multi-stage dilemma.

Assume that for the internal warehouse (WH) staging inventory, holding cost is half as expensive as customer-facing (CF).

How should we allocate safety stock buffers across the stages?

  • As much as possible to WH?

  • Shared, more to WH?

  • Shared, more to CF?

  • As much as possible to CF?

  • Half and half?

Different stages should optimally share the risk to:

  • Propagate demand from downstream to upstream

  • Model the impact of the Internal Service Level (ISL) decision of the upstream stage at the downstream stage

Capturing Interactions Between Stages

In multi-stage supply chains, stages are linked together. Orders placed by the customer-facing node create demand for product upstream. The upstream service level has an impact on the ability to meet the service level downstream.

The figure describes the Interactions Between Stages.

Optimal Internal Service Levels Versus Holding Costs

The table in the following figure gives an overview of the optimal internal fill rates as a dependency of different holding costs.

The figure describes the Service Levels and Holding Costs.

Multi-stage Logic for Complex Supply Chains

Simple supply chains can be optimized easily by simple search. For the more complex supply chains that we usually find in practice, sophisticated multi-stage logic is required to efficiently determine optimal solutions. SAP tools provide the appropriate optimization techniques.

The figure describes the Complex Supply Chain.

Safety Stock Buffers for All Forms of Uncertainty in the Supply Chain

Summing up, the following figure provides an overview of the different safety stock buffers for the different kinds of uncertainty that we find in a supply chain.

The figure describes the Safety Stock Buffers for All Forms of Uncertainty in the Supply Chain.

Run a Global (Multistage) Inventory Optimization Operator

Business Example

As inventory planner you would like to run the global (multistage) inventory optimization operator. To do that we will work during this exercise with the connection ZIOUNIFIED within the Planning Area ZIOUNIFIED.

Prerequisites

Prerequisities

  • Planning View used for this exercise: IO 220 Planning Result ##
  • All previous exercises are prerequisites
  • For this exercise we will work with the planning filter 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 periods. Calculations will not affect the past in the planning horizon

Steps

  1. Verify in the first tab Demand Input that results of the Forecast Error Calculation exist. With this step we are verifying as well that IO Demand Forecast, IO Demand Forecast Error CV and Target Service Level contain input values.

    1. Log on into the SAP IBP, add-in for Microsoft Excel.

    2. Open your favorite IO 220 Planning Result ##.

    3. In the first tab Demand Input, filter by your group number ## to display your products.

    4. Verify that IO Demand Forecast, IO Demand Forecast Error CV and Target Service Level contain input values. Remark: IO Demand Forecast Error CV only contains values in the current period.

  2. Go to the HighLevel Results tab to verify that there are no values in this sheet

    1. In the second tab HighLevel Results, filter by your group number ## to display your products.

    2. Verify that Propagated Demand Mean, Recommended Safety Stock (LPA), Final Safety Stock (from IO) (LPA), Safety Stock Delta (LPA) Recommended Safety Stock Value (LPA), Final Safety Stock Value (from IO) (LPA), Safety Stock Delta Value (LPA), Alert for Recommended Safety Stock and Alert for Safety Stock Delta do not contain input values.

  3. Go to the Application Jobs group to run the algorithm

    1. Under Inventory Planning (Advanced), click on Run.

    2. Select Global (multistage) inventory optimization as Function under Inventory Planning Profile_SAP.

    3. Select all planning units which correspond to your group number ## e.g. Trainee00 with Planning Units: Brasil00, Europe00, India00, US00 and Venezuela00.

    4. Select Scenarios: Baseline, Versions: Base Version.

    5. A filter is not needed. Click on Next.

    6. Select as Reason Code: Inventory and add a comment Running the global multistage inventory optimization operator if a reason code is requested.

    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 and refresh the planning view.

    10. Go to the current period.

    11. Verify that Recommended Safety Stock (LPA), Final Safety Stock (from IO) (LPA), Safety Stock Delta (LPA) Recommended Safety Stock Value (LPA), Final Safety Stock Value (from IO) (LPA), Safety Stock Delta Value (LPA), Alert for Recommended Safety Stock and Alert for Safety Stock Delta now do contain results. If the Standard Unit Cost key figure appears blank, ask the instructor to reload the exchange rate.

    12. Compare the different results from one Location to the other one.

    13. Observe that Propagated Demand Mean do not provide values yet.

Result

Results

Now you have seen how you can activate the Global multistage Inventory Optimization operator and you have analyzed the effects of the inputs over the results.