Ten articles on why migration assessments measure the wrong thing — and what to measure instead. The mathematics is universal. The examples are from SAP. Start anywhere.
Start here: If you read one article, read The 98% Problem. If you want the mathematics, read Bijective Proof. If you want to understand the engine, read Five AI Personas.
Your programme dashboard is green. Your data hasn't been tested. Here's what that means.
Every system migration transforms data. Almost none prove the transformation is correct.
A record that loads successfully is not the same as a record that works.
What if the mapping kernel already knew the rules?
Mapping coverage is a progress metric, not a safety metric.
If the assessment is mathematical — not manual — what does that do to the cost equation?
Failures are the most valuable output — each one is a diagnosed, remediable finding.
What if the engine that proved your migration could guard your data permanently?
Catastrophe theory explains why big-bang migrations are structurally fragile.
What if every record was proven correct before it entered the target system?