SAP IBP 2611 Release Sneak Peek: Highlights

With the SAP IBP 2611 release, arriving in November 2026, SAP introduces new capabilities for supply planning, scenario analysis and inventory management. To give you a head start, here are McCoy's top picks from the 2611 release.

Time-Series-Based Supply Planning

Nested Subcontracting and Subcontracting for Multiple Plants

Subcontracting in time-series-based supply planning, introduced in 2608, gets two new scenarios. This makes it possible to plan scenarios where subcontracting takes place across multiple levels, and where one subcontractor supplies several plants:

Nested subcontracting: a first subcontractor processes components and ships the semi-finished goods directly to a second subcontractor, who makes the finished good and delivers it to your plant.

Multiple plants: one subcontractor works for several of your plants. Each plant keeps its own subcontractor location, transportation lane and production data structure, so component supply and finished-good planning stay separate per plant.

Quality Inspection Lots

Quality inspection lots can now be taken into account in time-series-based supply planning. What this means in practice: stock that is still under quality inspection is not treated as available right away, but it is not ignored either. SAP IBP treats it as supply that becomes available on the inspection lot's end date, as integrated from SAP S/4HANA or SAP ECC.

Order-Based Planning

Excess Stock Netting Phase

Today, the finite heuristic aims to meet every demand on time. If existing fixed supply would cover a demand only a few days late, the engine creates new supply to be on time, and the existing supply ends up as excess stock.

With 2611 you can switch on an extra netting phase that runs before the main planning run. In this phase, the engine first uses existing fixed supply, even if that means delivering a little late. Only the demand that is still open after that gets new supply in the main phase. You decide how much lateness is acceptable (for example, a maximum of 10 days), and you can exclude specific transportation lanes when they need to stay just-in-time.

Example: A demand of 100 pieces is due on day 10, and a fixed receipt of 100 pieces arrives on day 14. Today, the heuristic plans a new order of 100 to be on time, which leaves 100 pieces of excess stock. With the netting phase and a maximum lateness of 7 days, the demand is covered by the existing receipt four days late, and no new supply is created.

Data Integration

SAP Business Network Planning Collaboration

SAP IBP and SAP Business Network Planning Collaboration can now exchange key figures in both directions, which closes the loop with your suppliers:

1. Share: SAP IBP sends your demand forecast (for example, your unconstrained forecast) to the supplier.

2. Respond: the supplier answers with a committed forecast (confirmed quantities), manufacturing visibility (their own production plan) and inventory visibility (their on-hand stock). This is written back to key figures in your planning area.

3. Plan: you run constrained planning based on what your supplier actually confirmed, not on assumptions.

The data is exchanged through SAP Cloud Integration, with no additional middleware needed, and the mapping between key figures and message fields is fully configurable.

AI & Inventory

AI-Assisted Inventory Analysis: Lot Size Source

AI-assisted inventory analysis now shows which lot size source is influencing a safety stock recommendation: a transportation lot size, a production lot size, and the type (minimum, incremental or coverage duration). This helps planners understand the factors behind inventory recommendations and interpret the calculated safety stock levels.

Planner Workspaces

Enhancements to Scorecards

Comparing scenarios on several KPIs at once is hard: one scenario has the highest revenue, another the lowest cost. With 2611, you can give each KPI in a scorecard a target and a weight. SAP IBP then gives each KPI a score from 0 to 100, adds the scores up using the weights into one scenario score, and recommends the scenario with the best score. Bullet charts show at a glance whether each KPI meets its target, and a new spiderweb view compares the scenarios visually.

Example: three scenarios are scored on revenue (weight 50%, target 10M), capacity utilization (30%, target 80–95%) and cost (20%, lower is better). Scenario A is the cheapest, but it misses the revenue target. Scenario C has the highest revenue but overloads capacity and is the most expensive. Scenario B meets both the revenue and capacity targets and comes out on top with a score of 90.

Curious what SAP IBP 2611 means for your planning landscape? Get in touch with McCoy, and we'll be happy to go through it with you.