Data Migration Scope Statement
This is a practical guide to building a scope statement for a data migration project — a definition of deliverables, boundaries and acceptance criteria, adapted to the realities of moving data from legacy systems into a new platform.
What a Scope Statement is
A scope statement is a definition of deliverables, boundaries and acceptance criteria. For the full concept and how it works in general, see Scope Statement. On a data migration project it plays the same role, tuned to this kind of work.
Why it matters for a Data Migration project
Data Migration projects live or die on moving data from legacy systems into a new platform. A well-built scope statement gives the team a shared, explicit reference for exactly that — reducing ambiguity, aligning stakeholders, and making problems visible early enough to act. Skipping it, or doing it generically, is how data migration projects drift into avoidable delay and cost.
What to include
- Deliverables
- In scope
- Explicitly out of scope
- Acceptance criteria
- Constraints and assumptions
Data Migration-specific considerations
Tailor the scope statement to the risks that most often derail data migration projects:
- Data quality and lineage
- Field mapping errors
- Reconciliation and cutover
Example
On a real data migration project, the scope statement would be shaped by moving data from legacy systems into a new platform. In particular, it should explicitly account for the project’s biggest risks — data quality and lineage, field mapping errors, reconciliation and cutover — rather than treating them as afterthoughts.