SAP Integrated Business Planning for Supply Chain ...

ThomasKlemm · ‎10-27-2023

Today, October 27, 2023, SAP Integrated Business Planning for Supply Chain 2311 was generally released as planned.

The new release comes packed with a wide array of highly anticipated features. Notably, the integration of transportation and production receipts as flexible constraints from SAP IBP into SAP S/4HANA Manufacturing for planning and scheduling (PP/DS) marks an important milestone for Synchronized Planning for Production.

Check out what else we have in store for you:

Synchronized Planning for Production

Production Planning Integration Using Flexible Constraints in SAP S/4HANA PP/DS

We now offer the possibility to integrate key figures from SAP IBP into the new flexible constraint framework available in SAP S/4HANA Production Planning and Detailed Scheduling (PP/DS). These constraints represent planning decisions from SAP IBP, giving PP/DS the freedom to do detailed planning and scheduling while respecting the global supply plan from SAP IBP.

To give an example, pre-build decisions you made to cover seasonal demand in your supply plan will now be followed in SAP PP/DS as the new heuristic uses the constraints during supply generation. This means you already build up your stock as defined in the supply plan in SAP IBP to cover the seasonal demand.

Integration of Resource Capacity and Order Delay Information from SAP S/4HANA PP/DS

Information about resource capacity and order delays can now be integrated from the PP/DS plan monitor as key figure information to SAP IBP. The key figures can be displayed in SAP IBP and used in analytics or in calculated key figures.

Planners can access critical resource and order delay information without switching systems. PP/DS key figures can be used in Planner Workspaces, in the SAP IBP, add-in for Microsoft Excel, or in analytics dashboards for SAP IBP.

Demand

Improved Forecast Accuracy with Curve-Based Forecasting

Curve-based forecasting clusters and typifies the historical sales curves of all products and leverages this information for forecasting an individual product. You can, for example, predict the demand for the whole four-year lifecycle of a product that only has a history of three months.

Curve-based forecasting can help to automate the forecasting of non-mature products without the need to maintain reference products (“like-modelling”). It is based on an ML-driven sales curve clustering process and can be used in weekly or higher aggregated time granularities.

Curve-based forecasting can also be used within the best-fit logic and competes against existing forecasting methods.

Inventory

Improved Visibility with Customer Service Level Prediction

Situations may arise in which you want to determine how adjustments to safety stock values will impact service levels, such as when you want to limit your investment in inventory holdings at the end of a fiscal period. The new Service Level Prediction operator enables planners to predict the customer service level by product-location, based on a predefined safety stock plan.

After creating a safety stock plan, planners can analyze predicted customer service levels in the plan’s future periods. Action may then be taken to minimize impact during anticipated periods of inadequate service, thus protecting customer service levels and minimizing revenue impacts.

Planners can run scenarios of potential future conditions and predict the customer service level and revenue impact. Scenario examples include unplanned events that increase lead time or reduces capacity, potential new market demand or unexpected surge in demand, inventory budget constraints directed by the Finance department, and so on.

SAP IBP General

Customized Master Data Validation

With the introduction of the Manage Master Data Checks app, you can extend your master data validation processes in SAP IBP. Administrators can define custom checks for master data correctness with a high level of personalization, catering to both permanent and temporary requirements.

Custom checks run with integration processes, consistency checks, application jobs for master data health checks, and any master data maintenance activities. They can be adapted to changing business requirements and help to improve the quality of master data and planning accuracy.

You can define custom validation criteria, flexibly enable/disable specific custom checks and provide multi-language check messages.

Real-Time Forecast Consumption Calculation

Key figure calculations for forecast consumption can now be done in real time. They help you to manage your inventory and plan your demand more efficiently. When an order is created, planners can use the IBP_CONSUMPTION function to see how the forecast has been consumed. They can set the direction in which the periods are considered for consumption and set the number of forward or backward periods.

With real-time forecast consumption calculation, it’s no longer necessary to schedule jobs and planners always have up-to-date and accurate information on their forecast consumption calculations.

Response & Supply

Optimized Planning Results with Fixed Capacity Consumption

With the introduction of the fixed capacity consumption feature for production sources and production group planning, planners can now incorporate the impact of fixed capacity consumption to optimize planning results.

The feature enables you to optimize the number of products or product groups (for example, color, size, flavor, package) planned on a production resource in a period to reflect and minimize set-ups.

In addition, you can adjust the resource’s available capacity, allowing for a more precise analysis of fixed capacity consumption and changeover impacts which in turn results in more accurate and feasible production plans.

SAP Best Practices

Easy Implementation of Carbon Rollup with New SAP Best Practices Content

The calculation of carbon emissions that we presented to you in SAP IBP 2308 can now be easily implemented with the help of Best Practices content. As announced in the last release, the Network Aggregation Operator calculates the carbon emissions per unit of a product (carbon footprint) at a location and in a period by rolling-up carbon emissions incurred at various places throughout the supply chain, helping you to make sustainable decisions and reduce your carbon footprint.

The SAP Best Practices content contains documentation, technical assets, and modeling to support you in comparing supply plans based on sustainability KPIs and evaluating the effect of changes to your supply chain on the carbon footprint of your products.

The operator transfers carbon emissions of materials from an upstream node to downstream nodes of a supply network using the quantities of material flowing through it.

The content includes a preconfigured Planner Workspace with planning views and charts to allow the planner to gain insights into the current status of the emissions for a given supply plan and to create scenarios.