Thinklytics

SAP Migration · 8 min read · July 2025

Why SAP S/4HANA migrations really fail, and it is not the software

By Thinklytics Partners, SAP S/4HANA Practice

Ask why an S/4HANA migration failed and people blame the software. They are almost always wrong. The platform works. What breaks is the data underneath it.

Topics covered

  • S/4HANA
  • Data Migration
  • Master Data
  • Migration Risk

Frequently asked questions

Why do S/4HANA migrations fail?

They fail on data, not on SAP. The platform and the tooling are mature. Programs stall on ungoverned master data, duplicates, dark data, custom ABAP that breaks against the simplified data model, and reporting that goes dark when the data moves. About 30 percent of migration projects run late or over budget, and the cause traces back to data nearly every time.

Is the SAP software the problem?

Rarely. What varies between programs is the condition of the data going in and the reporting that depends on it. The technical conversion is the most predictable part of the move.

What does the data actually look like after years on ECC?

Ungoverned. The same vendor entered five times, materials under three part numbers, units of measure that do not match, missing fields, broken classifications, and custom code nobody fully maps anymore. An in-memory system exposes all of it at cutover.

How much of a migration is data work?

Plan 25 to 30 percent of total effort for data preparation, and expect discovery and cleansing to consume about 40 percent of the timeline. Pre-move cleansing cuts post-migration defects by about 60 percent.

Why does the data work get missed?

It is tedious and low-margin, so it is the first thing cut when a program runs hot, and it usually lands on the most junior people. Meanwhile the date and budget get set before anyone measured the data.

How do we avoid a failed migration?

Measure readiness before you commit to a date, clean the data before you move it rather than in production, keep the data workstream senior, and plan reporting continuity as part of the migration instead of after it.

When does ECC support end?

Mainstream maintenance ends December 2027, extendable to 2030 at a premium. Starting early lets you choose your path instead of the calendar choosing for you.

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Thinklytics

Data and AI consulting for Fortune 500s, health systems, and growth-stage companies. Clean data, governed metrics, analytics ready for AI.

Austin, TX · United States

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