Twenty-two days on the showcase estate
How a first load into IBP runs for an estate with two SAP systems, an Oracle unit and a 3PL. Figures are from the showcase estate.
connect
keys
levels
time profile
first load
write-back
hand-over
IBP stores planning numbers as key figures at a planning level — product by location by customer by week, say — inside a planning area whose master data must exist first. Where the whole estate is one S/4HANA system, SAP's own integration covers the core. Where it includes ECC, a second ERP, warehouse and 3PL systems or external forecasts, Lima Backbone conforms them to IBP's keys, builds the key figures at their level with the sums checked, loads them on the planning cycle, and returns approved plans to the ERP with every write acknowledged.
Everything in IBP hangs on the planning level: a key figure is stored against a set of attributes (product, location, customer, week), and the combinations behind those attributes must already exist as master data. That ordering, and the time profile, decide whether a load lands.
| Object | What it holds, in plain words | Why the plan needs it | SAP source | Oracle source |
|---|---|---|---|---|
| Master data types | Products, locations, customers, resources, sources of supply, each with attributes | The building blocks of every planning level | MARA · T001W · KNA1 · CRHD · EORD · MKAL | Items · organizations · customers · resources · sourcing rules |
| Compound master data | Valid combinations: product at location, product for customer | A key figure row for a missing combination is rejected | MARC (product-plant); product-customer derived from sales history | Item-org assignment; item-customer derived |
| Key figures | Time series such as actuals, consensus demand, projected stock, capacity, each at a planning level | The numbers the plan is built from | VBRP · LIPS · MARD · KAKO | OE lines · WSH · MTL_ONHAND · resources |
| Time profile | Days rolling into fiscal weeks, months and quarters | Every key figure lives in a bucket | T009 · T009B | GL_PERIODS |
| Versions and scenarios | The baseline plan and named scenarios | Keeps a scenario from overwriting the baseline | Tagged by Lima on load | Tagged by Lima on load |
| Attributes | ABC class, planner, lifecycle status, unit — the fields planning levels are made of | A missing attribute means the row cannot be stored at its level | MARC-MAABC · MARC-DISPO · MARA-MSTAE | Item attributes |
| Order-based data | Orders and stock for response and supply planning, near real time | Order-level planning | EKPO · VBAP · PLAF · MARD | PO · OE · WIP · MTL_ONHAND (via Lima) |
| Non-SAP and second-ERP sources | Oracle, warehouse and 3PL stock, external forecasts, point-of-sale | The inputs SAP's own integration leaves out | — | Conformed by Lima to IBP's keys |
A single S/4HANA system feeding IBP with standard master data and key figures is what SAP's own integration is built for, and it can stay. Lima adds the layer for ECC as a source, a second ERP, warehouse and 3PL systems, external forecasts, planning master data governed outside the ERP, reconciliation reports per load, and write-back to non-SAP systems.
Two of these are IBP's own strictness — planning levels and compound master data — and the rest come from feeding IBP from more than one system.
Consumer-products estates bring customer-level demand review and promotions, so the product-customer combinations matter most. Life sciences brings batches and expiry that feed projected stock. Industrial estates bring resources and capacity key figures from work centres. Estates moving from ECC to S/4HANA bring two SAP systems feeding one planning area for a year or more. Each has a check in Step 4.
The figure shows daily invoice rows becoming one weekly key figure at its planning level, with the compound check before the load. The table maps all six problems.
| Problem | What Lima does | The capability behind it | What you see |
|---|---|---|---|
| 1 · Planning-level completeness | Requires every attribute of the key figure's level on every row; rows with a missing attribute are held with an owner, so they never land at an aggregate | Rules in plain language per key figure; exception routing | Held rows per key figure with the missing attribute named |
| 2 · Compound master data | Derives product-customer and product-location combinations from history and orders, maintains them as customers appear, and loads them before key figures with the owner's approval for new ones | Derived master data with owner review; dependency-ordered loads | A combination register: existing, new this cycle, approved |
| 3 · Time profile | Builds each key figure at its bucket from the daily rows using IBP's fiscal calendar and checks weekly and monthly sums against the daily rows | Grain builder with a configurable calendar; sum-of-parts checks | Per-key-figure reconciliation: daily total, weekly total, difference |
| 4 · Stored versus calculated | Keeps a catalogue of the planning area's key figures that accept loads, and refuses a load into a calculated one before it starts | Target-model catalogue for IBP | The key-figure catalogue with load status per key figure |
| 5 · Versions | Tags every load with its version and blocks a scenario load that names the baseline without a second-person approval | Version tagging; second-person approval | Loads listed by version with who approved them |
| 6 · One key set | Conforms products, locations and customers across ECC, S/4HANA, Oracle, WMS and 3PL sources into one key set before any load, with the mapping versioned | Consolidation with name resolution; versioned mappings | One key with its source codes listed underneath, per system |
Every check is a rule with an owner. A failed row is held with the rule and the row; the load continues with the rest and the report says what was held. Examples from the showcase estate:
| Check | Kind | Example | When it fails |
|---|---|---|---|
| Every key figure row carries every attribute of its planning level | Completeness | 9,120 sales rows with no customer at PRDLOCCUST level | Held; exception to the sales-data owner |
| Every product-location and product-customer combination exists before the key figure loads | Completeness | 212 new product-customer combinations this cycle | Proposed; owner approves; then loaded |
| Weekly and monthly totals equal the daily totals they were built from | Consistency | Week 37 actuals vs VBRP rows for plant 1000 | Load stays open until they match |
| The target key figure is stored (accepts loads) | Quality | A load aimed at a calculated key figure | Refused before it starts |
| Every load carries a version; baseline loads are approved | Consistency | An upside scenario without a version tag | Held for the planner |
| Units converted to the IBP base unit; currency key figures converted at the rate type and date | Quality | Revenue in local currency without a rate for the period | Exception to finance |
| Keys identical across ECC, S/4HANA and Oracle sources | Consistency | Customer C-88 in S/4HANA and CUST88 in Oracle | Consolidated; owner confirms |
| Time profile covers the planning horizon with no missing buckets | Completeness | Fiscal 2027 buckets still undefined | Exception to the calendar owner |
| Record counts and control totals per key figure match the source | Completeness | Every key figure, every load | Load report stays open until they match |
Integration suites such as Informatica sell data integration, data quality, the catalog and lineage as separate services on one consumption meter, and a team stitches the four together for each load. Lima runs the four as one surface. The screen above is the same for every load into SAP IBP: each step from the ERP invoice table to the IBP key figure row shows its row count; the rule that stopped a row shows the row and the person who owns the fix; the fix is applied where the row stopped and the replay starts from that step. Column-level lineage is recorded from the run itself, so the trace from a number in SAP IBP back to the ERP table is current every morning without a scanning project.
A rule such as "confirmed date is on or after order date" is written in words, previewed on live rows, versioned, and owned by a named person.
A row that fails a rule becomes an exception with the row, the rule, an owner and a deadline. The load carries on with the valid rows and says what it held.
Every step records what it read and wrote at column level, so the trace from a planning number back to the ERP field is captured as a by-product of running.
Values the ERP never held — hierarchies, changeover matrices, demand-stream rules — live in Lima with an owner and an effective date.
Results return to the ERP as transactions the ERP confirms; the confirmation is stored and reconciled against what was sent.
Each load carries its window and deadline; a tripped rule pauses the run and the clock, and the run resumes from its checkpoint after the fix.
IBP is loaded on its cycle through the channel you use; every load ends with a reconciliation report; approved plans return to ECC, S/4HANA and non-SAP systems as transactions they confirm.
Actuals and attributes at their planning level before the demand review, with compound checks and sum checks.
Stock, open orders and capacity as net-change, in dependency order, for supply and response planning.
Scenario versions loaded and tagged; the baseline is written only with a second-person approval.
| Result | SAP transaction | Oracle interface | How it is confirmed |
|---|---|---|---|
| Approved supply plan | BAPI_PLANNEDORDER_CREATE · BAPI_PR_CREATE into ECC or S/4HANA | WIP job interface · PO_REQUISITIONS_INTERFACE_ALL | Order numbers stored; failures re-queued with reason |
| Consensus demand to the ERP | Planned independent requirements: BAPI_REQUIREMENTS_CREATE | MRP_FORECAST_INTERFACE | Counts acknowledged and reconciled per product-plant |
| Safety-stock and parameter updates | BAPI_MATERIAL_SAVEDATA | Item interface | Second-person approval in Lima, then the acknowledged write |
| Results to non-SAP systems | — | Oracle, WMS and 3PL through their APIs | Acknowledged and reconciled the same way |
How a first load into IBP runs for an estate with two SAP systems, an Oracle unit and a 3PL. Figures are from the showcase estate.
| Program | What it gives you | Status |
|---|---|---|
| SAP PartnerEdge · listing | An SAP Store listing and, depending on tier, a certification badge | Tier decision · Q4 2026 |
| Systems integrator delivery | Delivery by your SI or ours on the same fixed-scope offer | Available |
One engine underneath every page in this family. It reads from any source and writes to any target, runs batch loads or change-data streams, handles a nightly delta or a multi-terabyte migration, and is licensed by capacity, so the bill stays the same however many rows move. Lima's fabric answers questions on data in place; Lima Backbone moves, transforms and returns data on a deadline. When to federate and when to pipeline · The Backbone hub.
Through the integration channel your planning area uses — batch time-series integration, real-time order integration or the APIs — in IBP's planning-level format, on the cycle you set, with counts proved per load. Your IBP team keeps its planning areas and key-figure definitions.
Yes. Lima reads ECC and S/4HANA with the same methods, both can feed IBP during the transition, and the IBP feeds built on ECC continue after cut-over.
They are held with the others for that product and location, listed for the sales-data owner with the missing attribute named, and loaded once fixed. The load carries on with the rest.
Where SAP's own integration already carries the S/4HANA core, it can stay. Lima carries the rest — the second ERP, the non-SAP sources, the planning master data — and the reconciliation.
Approved supply plans as planned orders and requisitions, consensus demand as planned independent requirements, and approved parameter changes, into ECC, S/4HANA or a non-SAP system — each write acknowledged and reconciled.
Yes. They are sources on the same pipeline, conformed to IBP's keys and aligned to its time profile and units before the load.
One planning dataset, four weeks, fixed price, with the checks above run on your own data and a reconciliation report at the end.