SAP Migration · 6 min read · September 2025
The hidden data risks that derail S/4HANA migrations, and how to surface them
By Thinklytics Partners, SAP S/4HANA Practice
The risks that derail S/4HANA migrations are rarely on the project plan: duplicate master data, dark data, broken custom code, and reporting that snaps when the data moves.
The risks that derail S/4HANA migrations are rarely on the project plan: duplicate master data, dark data, broken custom code, and reporting that snaps when the data structure changes. Surface them early or meet them at cutover, where they cost many times more.
The four quiet killers of an S/4HANA migration
None of these show up in a sandbox demo. They surface at conversion, reconciliation, or the first close.
- Duplicate master data. Breaks reconciliation and migrates as separate records unless stopped.
- Dark data. Unused historical records that inflate volume, cost, and conversion time for no value.
- Custom code that breaks. ABAP written against the old tables fails on the simplified data model.
- Reporting that goes dark. BW models and downstream dashboards snap when the data structure changes.
Source: Thinklytics SAP data readiness practice, 2026.
The four quiet killers
Duplicate master data that breaks reconciliation. Dark data, the unused historical records that inflate volume and cost. Custom ABAP that fails against the simplified data model. And reporting, the BW models and downstream dashboards that go dark when the data moves.
Why they stay hidden
None of these appear in a sandbox demo. They surface during conversion, reconciliation, or the first close, when the timeline is fixed and fixing them costs many times more. The same defect that is a one-times task in planning is a hundred-times incident in production.
What a data defect costs by the time you find it
The same duplicate, three points in the program. The cost multiplies as you move right.
| When you find it | What it becomes | Relative cost |
|---|---|---|
| During planning | A routine cleanup task | 1x |
| During conversion | A schedule risk and rework | 10x |
| After go-live | A business incident: finance cannot reconcile | 100x |
Source: Thinklytics SAP data readiness practice, 2026.
Surfacing them early
A readiness assessment profiles the data, maps custom-code dependencies, and inventories the reports at risk, then puts it on a Migration Risk Dashboard your leadership can read. Risk you have named and scored is manageable. Risk you have not surfaced is what blows the program. The 30-day Analytics Truth Audit is built to surface it.
Frequently asked questions
What are the biggest hidden risks in an S/4HANA migration?
Duplicate master data, dark data, custom code that breaks on the new model, and reporting that goes dark when the data structure changes. They rarely appear on the project plan.
Why are these risks hidden?
Because none of them show up in a sandbox demo. They surface during conversion, reconciliation, or the first close, when the timeline is fixed and fixing them is expensive.
What is dark data?
Historical SAP data nobody uses and nobody will miss: obsolete customers, dead materials, and stale records. Migrating it inflates cost, volume, and conversion time for no value.
How do we surface these risks early?
Run a readiness assessment that profiles the data, maps custom-code dependencies, and inventories the reports at risk, visualized on a Migration Risk Dashboard.
What is the Migration Risk Dashboard?
A Tableau or Power BI dashboard that shows where your data will fail during conversion, how much is affected, and what it will cost to ignore, in language leadership can read.
Can we fix these after go-live instead?
You can, but it is far more expensive and disruptive in production. Surfacing and fixing them before the move is the cheaper, lower-risk path.
Topics covered
- Migration Risk
- Master Data
- Dark Data
- Custom Code
Frequently asked questions
What are the biggest hidden risks in an S/4HANA migration?
Duplicate master data, dark data, custom code that breaks on the new model, and reporting that goes dark when the data structure changes. They rarely appear on the project plan.
Why are these risks hidden?
Because none of them show up in a sandbox demo. They surface during conversion, reconciliation, or the first close, when the timeline is fixed and fixing them is expensive.
What is dark data?
Historical SAP data nobody uses and nobody will miss: obsolete customers, dead materials, and stale records. Migrating it inflates cost, volume, and conversion time for no value.
How do we surface these risks early?
Run a readiness assessment that profiles the data, maps custom-code dependencies, and inventories the reports at risk, visualized on a Migration Risk Dashboard.
What is the Migration Risk Dashboard?
A Tableau or Power BI dashboard that shows where your data will fail during conversion, how much is affected, and what it will cost to ignore, in language leadership can read.
Can we fix these after go-live instead?
You can, but it is far more expensive and disruptive in production. Surfacing and fixing them before the move is the cheaper, lower-risk path.