The migration was a success. Yet something doesn't feel right.
SAP is live. But operations, procurement and logistics are still working around what the system tells them — because nobody fully trusts it.
SAP Data & Master Data Specialists · Since 2011
The ERP did not create the problem.
It only made it visible.
Bad data does not stay in the system. It shows up in the P&L.
→ Let's talk ERP dataDoes any of this sound familiar?
Finance has one number. Operations have another. IT says both are correct.
Reconciling data that should already match has become a weekly ritual. Nobody is sure where the discrepancy starts. So the source of the problem stays untouched.
Nobody really knows who owns which data. Until something breaks.
Legacy structures, inherited rules, processes that changed years ago. The system still accepts it. The business still uses it. Just not confidently.
The source is rarely obvious. But it can be found.
Data does not exist in isolation.
What Procurement considers correct may be incomplete for Logistics. What Production needs to see may not be what Finance needs to report. Before recommending anything, we look at the full operational chain — how the data moves, who uses it, which decisions depend on it.
That is usually where the real issue appears.
From there, the work is straightforward. Three steps, in that order, no shortcuts.
Assess
We map the real state of your data across systems and identify the operational impact of its quality issues. No assumptions. A clear picture of where the problems actually start.
Deliverable: Prioritised findings report. Typical timeline: 2–4 weeks.
Prioritise
Not every issue needs to be fixed immediately. Some create operational risk. Others are mainly noise. We define what to address first based on business impact, not on what is technically easiest to clean.
Deliverable: Prioritised action plan with effort and impact mapped.
Cleanse
We find, quantify and fix the issues that matter. Cleanup is paired with governance — owners, validation rules, change control — so the data stays clean. Not just temporarily.
Deliverable: Clean datasets + governance baseline.
The assessment finds it. The priorities focus it. The cleansing fixes it. After that, you decide what comes next.
What we found. What changed.
Procter & Gamble
A data migration methodology that became the EMEA standard — and still is.
In 2017, we designed an end-to-end data migration methodology for one of the world's largest FMCG companies. Eight years later, it is still the reference across EMEA. Not because nobody reviewed it. Because it still works.
Petit Forestier
A data model that survived two new business lines and an international expansion.
When we arrived, the material master reflected years of historical decisions. The business had changed. The data model had not. We rebuilt it around operational logic instead of technical legacy. Two years later, the company still runs on the same model — without redesign. It supports 3 lines of business across 23 countries and more than 350 sites, integrating operations from purchase to sales of services and the maintenance of their assets — ultimately supporting a P&L view by asset.
Bridgestone
80+ data issues. Some spanning 100,000+ material records. Zero operational incidents at cutover.
The product catalogue had grown without structure. Different teams, different definitions, no governance. We assessed the impact across sales, production and logistics, identified what was critical versus noise, and ran the cleanup in parallel with a new governance structure. Eighteen months later, planning, logistics and procurement work from the same material structure. Same reference. Same description. Same rules. And end-to-end supply chain visibility.
Large enough to handle complexity. Small enough to stay involved.
Large consulting firms have scale. They also have layers. The senior person who sells the project is rarely the person doing the work.
Freelancers bring expertise. But they are a single point of failure.
XFlowdata works differently. Two partners, a delivery team, and fifteen years of the same problems solved in different contexts. Direct communication. No inflated delivery model.
The people who assess your data are the same people accountable for solving it.
Real ERP experience
SAP, Salesforce, ServiceNow. Complex, multi-system environments across EMEA. We have seen most of the problems before.
Operational perspective
We evaluate how data issues affect planning, reporting, procurement and operations — not just how they look inside the system.
Clarity instead of dependency
The goal is to give you back control over your own data. Not to create an ongoing engagement.
That is what fifteen years inside ERP environments looks like in practice.
FAQs
How long does an assessment take?
Typically two to four weeks from the moment we start. We work with a limited number of clients at a time — each assessment requires full attention to be useful. That is why we always begin with a short conversation: to understand the situation and make sure we can give it what it needs.
Do you only work with SAP?
SAP is where most of our work happens, and where we have the deepest experience. We also work in Salesforce and ServiceNow environments. If you are not sure whether your setup is in scope, the 30-minute call is the right place to find out.
What happens after the assessment? Are we locked in?
No. The assessment ends with a prioritised findings report — yours to keep and act on however you choose. If it makes sense to continue with the cleansing work, we discuss it then. There is no automatic next step and no ongoing contract implied.
What tools do you use?
Syniti ADM, insightsoftware Process Runner and SAP Migration Cockpit, depending on the environment and the scope of the work. We recommend the right tool for the situation — we are not tied to any single vendor.
30 minutes is usually enough to know whether we can help.
If it makes sense to work together, you will know by the end of the call.
→ Let's talk ERP data