We resolve the MasterData_BP blocker (Customer/Vendor → Business Partner) in your ECC-to-S/4HANA conversion the way enterprise master data demands: consistency-first, secure by design, and human-in-the-loop — an AI resolver does the diagnosis, your people approve every change, and your data never leaves your landscape.
The S/4HANA Readiness Check turns your conversion into a wall of Simplification Items. Most go green with config. A few don't — and MasterData_BP is the one that turns a technical upgrade into a master-data project. It fails for two very different reasons, and telling them apart is where projects lose weeks.
An SP level too low to generate CVI proxy objects, half-failed proxies, missing customizing. Nothing can be created until it's fixed — and it's easy to misdiagnose as a data problem.
Unmappable industry keys, placeholder countries, missing tax categories, bad characters in names, customers that are also vendors. At scale, thousands of records each fail their own way.
The check only verifies a link row exists — an orphaned link passes the gate while the Business Partner behind it was never created. We report both numbers, honestly.
We don't ask for broad system access on day one. We start read-only, prove the picture, and only escalate to changes when you've seen the plan and approved it. Each step is a deliberate grant — the safe default never changes on its own.
A read-only readiness assessment against your system (or a copy). Volumes, overlap, data-quality percentages, SP gate, config readiness — turned into a report you can act on.
We read the post-processing errors, resolve every message to its root cause, and hand you a prioritized fix list mapped to SAP Notes and config — before touching anything.
We apply the config and data fixes and run the CVI load — dry-run first, batch by batch, each with your explicit approval. At scale, a self-resuming loader that survives restarts.
Re-run the Readiness Check to RC0, clear every orphan link, and hand over a complete audit record of what changed and why — your evidence trail for cutover.
Governance is built in, not bolted on. The tooling runs inside your landscape, returns aggregates rather than records, masks any personal data before it's ever inspected, and refuses production by default. See the architecture & data-governance model →
We don't ask you to trust a black box. Here is exactly how the tooling is built and where the data goes. The engine is an AI skill (the methodology) plus a Python MCP (the hands) that reaches your system only through a governance kernel and a swappable adapter — never a raw connection, never a hosted service.
Anyone can force a check green. The hard part of a master-data conversion is doing it so the data is consistent, the process is secure, and the result is verifiably right — with people, not a black box, accountable for every change. That is where we spend the effort.
"RC green" can hide un-created Business Partners — the check only wants a link row. We reconcile links against the actual BP records, harmonize customers that are also vendors into one partner, and handle the match-code and buffer traps that silently corrupt names. Green means real, consistent BPs.
The AI does the diagnosis; humans own the decisions. Every write is dry-run first and approved batch by batch. We sample and verify converted records against source — a statistically meaningful check per account group — so accuracy is measured, not assumed. Nothing writes autonomously.
The engine runs in your landscape and returns aggregates, not records; personal data is masked before anyone — or any model — sees it; production is refused by default; access stays least-privilege. Data residency and minimization aligned with PDPA & GDPR.
An immutable log captures who changed what, where, and when; each fix is mapped to a SAP Note or a named config change; the same read gives the same numbers. That is the evidence trail your auditors and your cutover board expect.
Field-tested, method-first. Proven on real ECC→S/4HANA conversions — from an SP-gated framework rebuild to multi-country data harmonization — the method is built to hold as the data volume grows, because it's the governance and verification that scale, not luck.
An AI resolver drives the repetitive diagnosis; a human approves every change. One shop runs the SP upgrade, drives the load, and signs off the check.
The SI-Resolver is built, owned, and warranted by adamOne Services. If you run S/4HANA conversions — as a systems integrator, a Basis practice, or an SAP partner — you can deliver MasterData_BP readiness under your own badge, powered by our engine and backed by our support.
One engine, warranted at the source. However it's delivered — directly or through a partner — the tool is developed and maintained by adamOne Services, so the methodology, the governance model, and the fixes stay consistent and supported.
Start with a read-only readiness assessment. We'll show you your BP-conversion exposure — volumes, overlap, data-quality, and blockers — and scope the work from there. Reach out for a conversation and pricing.