MP
Migration Proof
Maths, not art

Sample output

See what an Intelligence Report looks like

This is a redacted sample using anonymised data from a real SAP ECC-to-S/4HANA migration assessment. 847 records. 5 object types. Full bijective proof. Every section below appears in the report your own data would generate.

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1. Proof score at a glance

Every record is tested individually. The proof score is a mathematical count, not a statistical estimate.

847Total records
799Proven lossless
48Untransformable
94.3%Proof score

2. Per-field diagnosis

Each untransformable record is diagnosed to the exact field, exact value, and exact remediation. Not "investigate further" — specific, actionable findings.

Finding 1 — Supplier 100456 [Priority 1]

Field
COUNTRY
Value
UK
Issue
Not valid ISO 3166-1 alpha-2. Correct code is GB.
Proof
f⁻¹(f(x)) ≠ x — roundtrip recovers GB, not UK
Remediation
Correct to GB in source system
Cascade
12 POs + 8 GRs + 8 invoices blocked (29 objects)

Finding 2 — Supplier 100891 [Priority 2]

Field
PAY_TERMS
Value
ZCUS
Issue
Custom payment term, no target equivalent
Remediation
Map to ZN60 or create ZCUS in target config
Cascade
3 POs + 2 GRs + 2 invoices blocked (7 objects)

Finding 3 — Material MAT-2281 [Low priority]

Field
BASE_UOM
Value
PCS
Issue
Not recognised ISO unit of measure
Remediation
Map PCS to EA (ISO standard)
Cascade
Self only

3. Cascade impact — fix 2 records, resolve 75%

Root cause failures cascade through the dependency chain. The blast radius analysis shows which fixes unblock the most downstream objects.

36 resolved (fix 2 records) 12 remaining

Fix Supplier 100456 (COUNTRY=UK→GB) and Supplier 100891 (PAY_TERMS=ZCUS→ZN60). Two corrections. 75% of all failures resolved.

4. Bijective proof — the roundtrip

For every proven record, the engine runs: forward transform → inverse transform → field-by-field comparison. Here is what that looks like on a real supplier.

Source (ECC)

LIFNR 0000100234
NAME1 Mueller Ind.
LAND1 DE
BUKRS 1000
ZTERM NET30
AKONT 160000
EKORG 1000
KTOKK KRED

Target (S/4HANA)

BP 100234
Name Mueller Ind.
Ctry DE
CoCd 1710 ⚡
PayT ZN30 ⚡
Recon 160000
POrg 1710 ⚡
Grp KRED

Field-by-field comparison — all 8 fields match

LIFNR0000100234 = 0000100234
NAME1Mueller Ind. = Mueller Ind.
LAND1DE = DE
BUKRS1000 → 1710 → 1000
ZTERMNET30 → ZN30 → NET30
AKONT160000 = 160000
EKORG1000 → 1710 → 1000
KTOKKKRED = KRED

f⁻¹(f(x)) ≡ x — proven lossless

5. Ownership Ledger

Every tested record is logged with a cryptographic hash and timestamp. This is the audit trail that programme boards, auditors, and regulators can independently verify.

LIFNR 0000100234SupplierPROVENa7f3e291b4c8d0e5
LIFNR 0000100567SupplierPROVENc9d2f4a8e6b1c3d7
MATNR MAT-9921MaterialPROVENe1b5d8f2a4c6e9b3
LIFNR 0000100456SupplierFAILED
EBELN 4500017892POCASCADE

Run this on your own data

This is a sample. The real value is seeing your own records — your own untransformables, your own cascade impacts, your own proof scores.

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