Classify your material master to ECLASS during your S/4HANA migration
Manufacturing and industrial companies moving to S/4HANA are sometimes asked, by a parent company, client or engineering stakeholder, to classify their material master to ECLASS (formerly written eCl@ss) rather than, or alongside, a spend category standard. Doing this during the migration itself, rather than after go-live, means the classified data is ready for the same test runs the rest of your migration goes through.
What this means for your data
Manufacturing and industrial companies moving to S/4HANA are sometimes asked, by a parent company, client or engineering stakeholder, to classify their material master to ECLASS (formerly written eCl@ss) rather than, or alongside, a spend category standard. Doing this during the migration itself, rather than after go-live, means the classified data is ready for the same test runs the rest of your migration goes through.
What it costs to leave it
Bad data doesn't stay behind when you migrate. It gets carried into the new system, where it causes extra test runs, a delayed go-live, and spend reports nobody trusts once the dust settles.
How classification to ECLASS works
Assess the material master
Pearstop checks your material master data alongside the rest of your migration assessment, so ECLASS classification isn't a separate, later project.
Classify with AI and a person reviewing uncertain lines
AI classification handles the clear cases, and a person reviews anything uncertain, so the ECLASS labels going into S/4HANA are ones you can trust.
Map to S/4HANA's fields
Classified data is mapped to the material master fields S/4HANA expects, in the format your implementation partner's import tools need.
Where ECLASS classification matters
- The material master, which is where ECLASS attributes are recorded, alongside the rest of the S/4HANA data cleanup.
- Whether ECLASS needs to sit alongside a spend category standard such as UNSPSC, since most manufacturing groups need both.
- Timing: classifying the material master during the assessment phase, not after the first failed test run.
What good data looks like
- One record per supplier, with no duplicates across entities.
- Every spend line labelled to one standard (UNSPSC or your own).
- Item and material descriptions written the same way.
- Units of measure consistent.
- Inactive suppliers and items flagged, not migrated.
- Every field mapped to the new system and documented.
- Material master records carrying ECLASS attributes wherever a stakeholder requires them.
- ECLASS and any spend category standard both mapped to S/4HANA's fields, documented, not left as a manual side project.
How Pearstop handles it
The data doesn't need to be clean first. AI classification handles the clear cases, and a person reviews anything uncertain. ECLASS labels are mapped to S/4HANA's fields, in the format your migration needs. New invoices stay classified after go-live, so reporting doesn't slip back into the same mess.
Work with your partner
Most migrations run through an implementation partner. We work alongside them, or directly with you. Your partner sets up the new system; we give them clean, classified data in the format their import tools need. Nobody's scope changes, and your partner's team can spend their time on the new system instead of fixing records.
Why start early
Bring us in when you assess the data, not after the first test run fails. You find duplicates, free-text lines and missing categories while there is still time to fix them, nothing has to be cleaned twice, and the test runs go faster because the data goes in cleanly. Some problems only show up once you look closely at how the data behaves, which is why it pays to work with someone who handles this data every day.
Frequently asked questions
Can we classify our material master to ECLASS during an S/4HANA migration?
Yes. It fits naturally alongside the rest of the material master cleanup an S/4HANA migration already requires, and doing it during the assessment phase means the classified data is ready for the same test runs as everything else.
Related reading
Send us 200 lines
We'll classify a sample of your purchase data and send it back so you can see what good data looks like before you commit to cleaning the rest.
