ServiceNow Data Migration and Import Sets: Roles, Responsibilities and RACI

Understanding Data Migration Responsibilities

Data migration from legacy systems to ServiceNow involves multiple teams with different expertise and accountability. The Data Architect designs the migration strategy and maps source fields to target tables. The Source System Owner maintains the legacy system and extracts data. The Target System Owner (ServiceNow Platform Owner) validates that migrated data works correctly in the new system. Quality Assurance verifies data completeness and accuracy. Business Data Stewards confirm that migrated data represents real business situations correctly. Without clear responsibility, data issues get blamed on the tool or the migration approach when the real problem is unclear ownership of data quality.

Role Model for Data Migration

Data Architect: Designs the migration approach, creates field mapping from source to target, writes transformation rules, and oversees technical execution. Reports to IT leadership. Decides whether to use import sets, direct API calls, or batch jobs. Source System Owner: Provides access to the legacy system, extracts the required data, and confirms data completeness. Ensures source data is available and accurate. Does not make decisions about how data will be used in the target system. ServiceNow Platform Owner: Validates that migrated data matches ServiceNow table structures and rules. Confirms that integrations expect correctly formatted data. Makes decisions about data validation rules, defaults, and error handling in ServiceNow. Business Data Steward: Confirms that migrated data represents actual business entities and transactions. For example, verifies that customer records, contracts, and transaction histories are complete and accurate. Data Quality Analyst: Compares source and target data counts and spot-checks records for accuracy. Runs test queries to identify missing or incorrect data. Escalates data issues for root-cause investigation and correction.

RACI Matrix for Migration Phases

Escalation Paths for Data Issues

When Data Quality Analyst finds a discrepancy (for example, 50,000 records in source but 49,800 in target), escalate to Data Architect promptly. Data Architect investigates the transformation logic and the source data. If the issue is in transformation logic, Data Architect fixes it and re-runs the migration. If the issue is in source data (for example, malformed values), escalate to Source System Owner to correct the source. If records are correctly migrated but business interpretation is wrong (for example, a status code means something different than expected), escalate to Business Data Steward to confirm correct interpretation. Do not re-run production migrations without explicit approval from Platform Owner.

Handling Data Ownership Post-Migration

After migration, data ownership transfers to the departments that use the data. Finance owns financial transaction data, HR owns employee records, Operations owns service records. Each owner is responsible for data ongoing accuracy and maintenance. Establish governance so that data stewards understand their responsibilities post-migration: how to update records, what validations apply, and how to report data quality issues. Retain migration documentation so that future enhancements or corrections can reference the original migration approach.

Managing Incremental Migrations and Cutover

Large migrations often happen in phases (for example, migrate customer data first, then orders, then history). Each phase should follow the same RACI: define scope, map fields, test, validate quality, and gain approval before production. Cutover (when legacy system is decommissioned and ServiceNow becomes the source of truth) requires explicit authorization from leadership. Plan for a period where both systems run in parallel so users can verify that migrated data is working correctly. Document data for the parallel period (changes made to legacy system that need to be migrated to ServiceNow) and re-run migrations if needed.

Who owns the exception queue after a row fails

Role definitions tell you who is accountable for the migration as a whole. They often leave out who picks up a single failed row at eleven in the morning on a working day. That gap is where migration programs often lose momentum. The reject queue fills, each person assumes someone else is looking at it, and the rows wait until the next load overwrites them or until a user finds the problem first. Assigning exception ownership by category, rather than leaving it to the migration team as a whole, closes that gap.

Each category of exception should have a triage owner who decides what the row is, a fix owner who changes the thing that is wrong, and an approver who signs off the correction. In a small program one person may hold two of these, but the three roles should still be named on paper so that nobody has to guess.

How responsibility changes at each stage of the program

The same person can be accountable for the design and then only consulted during the load. The table of roles should therefore show how responsibility moves across the program, not only what each role is called. Before the load, the data architect and the source owner carry most of the work. During rehearsal and cutover, the platform owner and the data quality analyst take over the operational weight. After acceptance, the business owners and the data stewards hold the data, and the platform owner’s role shrinks to keeping the platform sound.

1. During design, the data architect owns the mapping and the source owner confirms the extract covers the agreed scope.
2. During rehearsal, the platform owner owns the load outcome and the data quality analyst owns the reconciliation.
3. During cutover, one named operator runs the load and the platform owner is the only person who can approve a rerun.
4. After acceptance, each dataset passes to the business owner, with the data steward taking the day-to-day corrections.

Why a role model fails without a rule for tie-breaks

Many disputes in a migration are not about who is responsible but about which of two sensible answers is correct. The source owner says the value is right in the legacy system, the platform owner says it fails the target rule, and the business says neither is the meaning they expected. The role model should include a tie-break rule that decides who holds the question. A practical rule is that the business owner decides the meaning, the platform owner decides whether the platform can hold it, and the data architect decides how the map represents it. Without that rule, each owner is correct within their own area and the row remains unresolved.

Handing data to stewards and keeping the record

When a dataset is accepted, its operational ownership moves to the business. Stewards need the mapping document, the list of accepted exceptions and the contact for the migration team, but they do not need the load logs. Give them a short handover note that says which fields were derived, which were defaulted and which were left blank because the source had nothing. A steward who knows that a blank field is intentional will not spend a week trying to fill it.

Questions teams raise about these roles

Can one person be the triage owner and the approver for the same exception?

It is better not to. The person who decides what a row means should not also be the only person who approves its correction, because the approval then checks nothing. In a small team, have the approver be a peer who did not triage the row.

What if the source system owner has left the organization?

Assign the role to whoever now holds the legacy system, and record the handover in the role register. The extract cannot be treated as complete until someone accepts responsibility for it, so an unassigned source role is a blocking gap for the next load.

Should contractors hold any of these roles?

They can hold fix or triage roles while the work lasts, but approval and final acceptance should rest with permanent staff who will be present after the contract ends. Record the handover each time a contractor’s role moves to someone else.

Next step

Role assignments are only as strong as the governance that backs them.

Related guides: ServiceNow Platform Operating Model and Governance and ServiceNow Data Migration and Import Sets Governance Model.