04/08/2026
๐๐๐ญ๐ ๐ฆ๐ข๐ ๐ซ๐๐ญ๐ข๐จ๐ง ๐๐๐ข๐ฅ๐ฎ๐ซ๐๐ฌ ๐ก๐๐ฏ๐ ๐ค๐ข๐ฅ๐ฅ๐๐ ๐ฆ๐จ๐ซ๐ ๐๐๐ ๐ฉ๐ซ๐จ๐ฃ๐๐๐ญ๐ฌ ๐ญ๐ก๐๐ง ๐๐๐ ๐๐จ๐ง๐๐ข๐ ๐ฎ๐ซ๐๐ญ๐ข๐จ๐ง ๐๐ฏ๐๐ซ ๐ฐ๐ข๐ฅ๐ฅ.
After working through S/4HANA migrations across Saudi Arabia and India, the pattern is almost always the same: companies underestimate their data, rush the cleansing phase, and then spend the first six months post-go-live firefighting.
Here is what actually goes wrong โ and how to stop it before it starts.
๐๐ก๐ ๐ซ๐๐๐ฅ ๐๐ฎ๐ฅ๐ฉ๐ซ๐ข๐ญ๐ฌ:
- Duplicate vendor and customer master records that nobody audited in years
- Legacy data mapped to the wrong S/4HANA structures
- No data governance owner assigned before migration begins
- Testing done on a 10% data sample, then surprise at full-load failures
๐๐ก๐๐ญ ๐๐ข๐ฌ๐๐ข๐ฉ๐ฅ๐ข๐ง๐๐ ๐ญ๐๐๐ฆ๐ฌ ๐๐จ ๐๐ข๐๐๐๐ซ๐๐ง๐ญ๐ฅ๐ฒ:
They start data profiling on Day 1 of the project โ not Week 10.
They assign a Data Migration Lead with authority, not just a title.
They run at least three full mock loads before cutover.
They define "good data" in writing, with sign-off from Finance and Operations.
Migration is not a technical exercise. It is a business discipline.
The companies that treat it that way go live clean. The ones that treat it as an IT task spend the next year correcting it.
๐พ๐๐๐ ๐๐๐ ๐๐๐๐ ๐๐๐ ๐๐๐๐
๐๐๐ ๐๐๐๐ ๐๐ ๐
๐๐๐ ๐๐๐๐
๐๐๐๐๐ ๐๐ ๐๐๐๐ ๐บ๐จ๐ท ๐๐๐๐๐๐๐ โ ๐๐๐ ๐๐๐๐๐๐๐, ๐๐๐ ๐๐๐๐๐๐, ๐๐ ๐๐๐ ๐๐๐๐๐๐๐๐ ๐๐๐๐๐๐
๐๐?
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