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This is a blog on the optimizers available within the Response & Supply application of SAP IBP, including the Time-Series (TS) and Order Based Planning (OBP) optimizer.

Please note that for the TS optimizer both R&S and S&O license are required. For the OBP optimizer the R&S license is sufficient. See also SAP Help for Applications and Features.

Expert help for Optimization in IBP (SAP Consulting):

  • Note 2427153 - IBP Supply Optimization Consulting
  • Note 3030891 - IBP Optimizer Reporting Service. More details of this service on this Infopage

Blogs on TS Optimizer

Webinars

  • Meet the Expert: IBP Supply Optimization - the do's and don'ts, Nov 2022: PDF , Recording
  • Meet the Expert: Time Series Supply Planning Capabilities (Dec 2021) PDF | Recording
  • Overview of SAP IBP Supply Planning Algorithms (Webinar in Sept 2020) PDF | Recording
  • IBP Product Webinar Series, R&S - Tactical & Operational Supply Planning: Recording & Presentation
  • SAP IBP Operational Supply Planning - Overview and Capabilities (May (2020) PDF | Recording
  • SAP IBP Operational Supply Planning - Deployment Planning (Oct 2020): PDF | Recording
  • IBP OBP optimizer webinar (Nov 2020): PDF | Recording

Useful links to SAP IBP Help, specific for R&S (TS = Time-Series, OBP = Order Based Planning):

SAP Notes with useful information for R&S:

IBP Training

IBP optimizer scenario guide, including runtime benchmark data 

The SAP IBP Supply Optimizer Scenario Guide is a document that helps you to classify scenarios for Supply Optimization in SAP IBP.

Very often there are questions like “can supply optimization handle such a volume?”, or “what will be the runtime to solve a specific scenario?”
An answer to such questions is very difficult. The final behaviour of the optimizer depends on a lot of details. For example, a very large scenario
can be solved very fast, if the constraints are easy to satisfy. But if we have very challenging constraints, a smaller scenario could need much
more runtime. 

As these details often are not known at the beginning of a project, no one can answer questions like above upfront in an exact
manner. Estimations which are too conservative (leaving a large buffer for example for the runtime) are also not very helpful. And setting up
prototypes is either inaccurate or causes too much effort.
The best and most convincing alternative is to compare the current project with already realized projects in IBP. On this level you don’t need to
investigate all details, but you get very soon an impression about the planning of your scenarios, if you look into some similar scenarios. This is
the approach we want to establish with this document.
The scenarios and numbers in this document are based on the experiences we made with different customers, partners, and projects.

Fundamentals of classifying optimizer scenarios: 

  • Details vs. Runtime: Details meaning granularity of time buckets and length of time horizon, number of products, lot sizes, etc.
  • Runtime vs. Quality: If runtime is critical define maximal runtime with a solution gap that is acceptable for the business
  • Global planning vs. decomposed planning: Can you split the model into sub-problems, or do you need to solve it in one global planning run?

Drivers of complexity: 

  • Scenario Size: Horizons & Planning Periods; number of products, customers, locations; faire share feature 
  • Lot-Sizes: keep the horizon to consider lot sizes as short as possible
  • Type of algorithm: For example Dual Simplex or Barrier method 
  • Numeric: In most cases it is sufficient to follow the warnings and instructions in the log of the optimization run, that is, to switch on the recommended additional
    features to transform your supply chain in numerically more robust optimization model

You can get a sense of the complexity of your optimizer model by looking at the number of the variables on the "Optimizer Run Details" screen in your IBP system and compare it to the numbers in the scenario guide: 

 

IBP Supply optimizer safeguarding engagement

SAP IBP Supply Optimizer Safeguarding Engagement

The check is meant to be as support for partner led supply optimizer implementations to give optimizer modeling and performance recommendations in an early stage.

The check will be performed at two distinct points of time:

  1. Begin of implementation: Design Evaluation
  2. Before volume test: Performance Optimization

The length of the engagement is 3-5 days for each of the two checkpoints and depends on the complexity of the optimizer model.

The check is performed by SAP optimizer experts and is a paid engagement. The SAP service account team can find out what the rate is in a specific country.

For customers who have a Premium Engagement contract, like MaxAttention, the engagement days are usually covered by the that contract.

Contact:  Please contact your assigned SAP Digital Supply Chain Customer Success Partner (CSP) if you are interested in the engagement. If you do not know the CSP, please contact SAP via the email address engage-ibp@sap.com.

Please fill out the IBP optimizer questionnaire when requesting the safeguarding check.

IBP Supply Optimizer Questionnaire

The set of questions asked in the questionnaire will help you to evaluate the complexity of the optimizer model. The questionnaire is ideally filled out by the end of Busines Blueprint.

The list of criteria on the first page will give you an idea of the complexity of your optimizer model. 

To answer the questionnaire, please download the Word document and respond direclty in the local file from page 2 on.

SAP IBP Supply Optimizer Questionnaire (Word format for download)

SAP IBP Supply Optimizer Questionnaire (PDF version to read)

IBP Supply Optimizer - Do´s and Don´ts Document

SAP IBP Supply Optimizer - Do´s and Don´ts Document

The document answers questions on the following topics:

  • How to address complexity in optimization
  • Optimizer Expert Parameters
  • Explanation of optimizer runs
  • Runtime and complexity
  • How to reduce complexity
  • How to deal with Numerical Problemas

How to address complexity in Supply Optimization:

  • General advisory: Keep unnecessary complexity out of the model!
    • Remember, it’s mid-term planning in most of the cases.
  • Careful use of discretization (lot sizes, fixed cost, setup):
    • Use discretization only in short-term horizon.
    • Use minimum lot sizes instead of integral lot sizes (rounding values) where possible.
    • Avoid using integral lot sizes on several levels (e.g. production and transportation).
    • If multi-level lot sizing cannot be avoided, make sure lot sizes are aligned.
  • Reduce model scope:
    • Use shorter and/or time aggregation.
    • Only plan relevant location levels in network. Consider propagating demand using heuristic for certain network levels.
    • Only plan relevant SKUs. Components/Raw materials may not be required.
  • Split Optimization scope into separate runs:
    • Plan by product group.
    • Identify bottleneck resources – non-bottleneck resources can be part of multiple runs.
    • This also improves planner experience / usability / fail safeness!
  • Take care modeling alternative sourcing:
    • Avoid using ‘exception only’ alternatives in automated planning. Handle exceptions via alerts and manual planning.
    • Avoid modeling ‘don’t care’ options (identical cost for alternative sources). Use ‘virtual’ priorities if necessary, to avoid strong fluctuations in optimizer results.
    • Consider restricting multi-sourcing to selected products (e.g. fast movers).
  • Shift part of complexity to short-term distribution and/or production planning
    • Distribution planning – use of Deployment (optimization)
      • Plan part of the distribution network in deployment only
      • Consider transport lot sizing only in deployment
      • Planning in daily periods only in deployment
      • Allows consideration of additional constraints (e.g. storage, handling)
      • Fair-share considerations (location/region level) may only be considered in deployment
    • Production planning
      • Use PP/DS for detailed production planning
      • Alternative: Use ‚production-only‘Supply Optimizer model in short term
      • Consider production lot sizes etc. only in short-term planning
      • Consider raw materials/component only in short-term planning
  • Do not consider Optimizer as a black box! Build understanding of working principles of optimizer:
    • It’s not rocket science…
    • Build a ‘formal’ tool translating business rules into an optimizer cost model
    • Especially useful if there are complex business requirements
    • Involve (power) users in design of optimizer cost model
  • Set up ‘How-to’ guides for analyzing / addressing frequent issues
    • In most scenarios, the same issues come up again and again
    • Document approach for new issues as they occur
    • Document resolutions provided by the experts in a way that non-experts can understand


IBP Best Practices

IBP Best Practices Explorer, processes specific for R&S in screenshot below







1 Comment

  1. Mukesh Singh

    Informative documents, thanks 👍