1. Incomplete critical fields
Required business attributes may be missing, inconsistent, or populated differently across legacy sources. This can affect downstream processing and validation.
2. Duplicates and inconsistent identities
Customers, suppliers, materials, and other entities may exist in multiple forms. Duplicate or conflicting identities can complicate migration and business adoption.
3. Invalid or obsolete values
Legacy values may no longer align with target-state structures, classifications, or business rules. These require explicit transformation decisions.
4. Weak reference-data alignment
Codes, units, categories, organizational structures, and other reference values can require mapping and harmonization before migration.
5. Inconsistent business definitions
Different teams may interpret the same field or object differently. Transformation exposes those differences and forces decisions.
6. Poor historical relevance
Large volumes of old data can increase migration effort without delivering equivalent business value.
7. Unclear ownership
Issues without accountable owners tend to remain unresolved and reappear during later cycles.
Axiums perspective
The value of early assessment is not simply finding defects. It is identifying which patterns can affect the transformation and creating a controlled path to resolution.
- Profile critical objects early.
- Prioritize issues by process and business impact.
- Resolve mappings and definitions before repeated test cycles.
- Make ownership part of the remediation plan.