Preparing HR Data for Migration: Preserving Institutional Insight While Modernizing

By Alicia Rule, Mike Vajda, and Sharon Ginley

If governance is the structure and leadership is the engine, HR data is the institutional memory that fuels decision-making.
The memorandum directs agencies to “prepare HR data for migration.” This seemingly straightforward directive masks complex decisions with long-term consequences.
HR data encodes how an organization understands itself: its workforce composition, talent flows, leadership pipelines, compliance history, and mission capacity.
Data migration is not merely technical. It is strategic institutional preservation.

Why Data Readiness Is High-Risk

HR data is deeply interconnected with:

• Payroll and financial systems
• Workforce analytics and forecasting
• Succession planning and talent pipelines
• Compliance and audit defensibility
• Mission execution capacity

Poorly scoped or rushed migration can break analytic continuity even if the new platform functions as designed.

Step 1: Conduct Data and Systems Discovery

Agencies should establish a factual baseline by:

• Documenting data models and schemas
• Identifying authoritative sources
• Mapping reports and downstream users
• Updating data dictionaries
• Identifying statutory retention requirements

Discovery frequently uncovers undocumented dependencies and shadow systems.

Step 2: Map Integrations and Dependencies

Agencies must inventory all systems that produce, consume, or rely on HR data and document:

• Integration points
• Data flow directionality
• Latency requirements
• Ownership and support models

Operational continuity depends on understanding these relationships before migration begins.

Step 3: Define Migration Scope and Boundaries

Not all data should be migrated. Agencies must decide:

• What is in scope
• What must be retained but not migrated
• What may be archived

Decisions about what not to migrate are often more consequential than what is migrated. Once analytic baselines are disrupted, rebuilding them can take years.

Step 4: Develop a Formal Data Migration Plan

At minimum, agencies should define:

• Scope and boundaries
• ETL methods
• Data quality remediation
• Validation criteria
• Preservation and retrieval strategies
• Risk mitigation and rollback plans

This plan becomes the authoritative reference for OPM coordination and internal accountability.

GKG Example

In support of a federal shared services HR environment, GKG led a comprehensive data discovery and integration mapping effort across HRConnect and agency-specific systems. We identified undocumented data dependencies, reconciled inconsistencies between HR and finance feeds, and developed an enterprise data dictionary to clarify ownership and authoritative sources.

The effort preserved workforce analytics continuity while positioning the agency for future system modernization.

Outcomes:

• Identified and resolved critical data discrepancies prior to system impact
• Preserved multi-year workforce trend baselines for strategic planning
• Reduced audit and reporting risk through clarified data ownership 

Next: Why project management alone is insuffient, and why adaptive change capacity determines success.