Every S/4HANA project starts the same way — until someone asks for clean master data
Every ECC → S/4HANA migration begins the same way. There’s a chosen implementation partner, a project plan, milestones, a go-live date. Then, somewhere between the first and second workshop, a single sentence lands:
“We need clean master data from you.”
And that is where the part of the project nobody scoped begins — the part that can eat more time and budget than the entire partner-side implementation. The conversion of Customer and Vendor records into the Business Partner model is rarely on anyone’s deliverables list, yet it lands squarely on your team.
Let’s count what it costs if you do it yourself
Take a realistic, mid-sized case: around 100,000 Customer and Vendor records, two or three company codes, converted to the Business Partner model. Here is what your team has to do by hand — and how long each step typically takes.
Spread across your master-data, IT and business teams. At a conservative €50–80 per specialist hour, that’s €40,000–80,000 in internal time alone. Hand part of it to external consultants (€120–150/h) and the bill runs into the hundreds of thousands.
And those are only the costs you can put a number on. The harder ones are hidden:
Business pulled off its real work
Finance, procurement and sales sit in spreadsheets instead of doing what you actually pay them for.
Trial and error under pressure
Errors surface weeks before cutover, at the worst possible moment, with no slack left in the plan.
Risk of a slipped go-live
The most expensive scenario of all — and the one data problems are most likely to cause.
And after those 1,000 hours, you have one-off clean data — no repeatable standard, and no tool to hold that quality for the next partner you onboard tomorrow.
How we do it — at a fixed price
We have run exactly this work for more than 16 years. Proven templates, tested algorithms and our own tooling — vise DMW — mean we don’t reinvent the wheel on every project. That is precisely why we can offer it at a fixed, predictable price, instead of an open-ended “however long it takes.”
Each step is a gate that filters out a class of error before it reaches the next stage — so problems surface at the source, not inside the cutover window.
Step 01 · Extraction
Pull only what truly goes to S/4
We define the criteria together — active partners, open items, transactions from an agreed period — rather than dragging the entire legacy database along for the ride.
Step 02 · Profiling
A real picture of your data
Completeness, empty fields, inconsistent value lists and the genuinely problematic records — visible up front, not discovered at load time.
Step 03 · Deduplication
By agreed algorithms, not magic
Duplicates removed against rules we settle on together — transparent and reviewable, so you can see exactly why two records were treated as one.
Step 04 · Mapping & harmonization
FieldMap AI + vise LoV Map
FieldMap AI maps Customer and Vendor data to the BP structure and surfaces errors that would take weeks to find by hand. Dictionary and value harmonization across companies runs on vise LoV Map — multi-OpCo, consistent.
Step 05 · Validation rules — not just SAP’s
SAP standard will check formats and mandatory fields. But the expensive errors live in the business logic SAP simply doesn’t hold — because it comes from your business. For example: that a given account must be tied to a specific reconciliation group, but only for a selected customer account group.
You write those rules however suits you — Word, Excel, PDF, whatever is convenient — and we implement them as validations in the process. You define what “correct data” means for you; we make sure every record meets it.
Load simulation: prove the data will pass — before you load anything
This is the moment that turns a project from “we hope it works” into “we know it works.” We run a full load simulation into your chosen target — Quality or any other system — without writing a single record. You see in black and white that the data will pass, and you catch errors before they touch anything in production.
And the simulation can run far earlier than the real load. You don’t have to wait for cutover: push the data through today, clear the errors calmly, then repeat the same process for every target system you need to load — as many times as it takes.
What you get at the end — and what we commit to
How the data lands is your call. Either way, the scope is fixed and agreed up front — because these are the things we commit to deliver.
Loaded for you
The validated data is loaded directly into S/4HANA by our tooling — the same engine that ran every simulation, now writing for real.
Or handed over, ready
Prefer to load it yourself? We deliver in SAP Migration Cockpit format, ready for your team or your implementation partner to run.
And the whole thing leaves you with more than one-off clean data: a standard and a tool you can use to hold that quality for the new partners that appear tomorrow, next month and next year. It isn’t a one-time clean-up — it’s a repeatable way of working, delivered as a fixed-price service.
Compare it for yourself
Do it yourself
800–1,000+ hours of your own people’s time, trial and error under go-live pressure, and the standing risk of slipping the date — for data that is clean exactly once.
With Visehub
A predictable, fixed price and a team that has run this Customer-and-Vendor-to-Business-Partner conversion dozens of times — leaving you a standard you keep.
We know this from practice — including a long-standing partnership with a global FMCG company operating across dozens of subsidiaries in multiple markets.
Planning a move to S/4HANA?
If a migration to S/4HANA is ahead of you and “who prepares the data?” is still hanging in the air, let’s sort that part out before it becomes your bottleneck. We offer a free 30-minute data-readiness assessment, no strings attached.
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