Data Migration Is Won Long Before Cutover

Not all data migration programs are created equal, but they have this in common: successful data migrations are rarely determined by technology. Rather, they are determined by how effectively organizations prioritize work, engage stakeholders, manage risk, and build repeatable delivery processes.

This is especially true in P&C insurance, where reporting logic spans actuarial, finance, underwriting, claims, and regulatory functions. Critical calculations may be embedded in legacy platforms, and infrequently used reports may still carry significant financial, operational, or compliance importance.

Let Usage Data Define the Migration Strategy

Every migration begins with the same question: What actually matters?

The answer is rarely found in project plans or application inventories alone. It begins with usage data.

Usage reports provide the clearest picture of how the business truly operates as data consumers. They identify power users, critical reports, heavily used data assets, and operational dependencies. More importantly, they reveal what is not being used.

However, usage frequency should not determine priority on its own. In P&C insurance, a monthly, quarterly, or annual report may still be essential. Migration decisions should consider:

• Usage frequency

  
  

• Business and regulatory importance

  
  

• Dependency complexity

  
  

• Opportunities to consolidate or retire assets

  
  

In the reporting platform migration, usage data allowed us to eliminate and consolidate reports before development even began. In the data platform migration, usage reports became the foundation for migration sequencing, business engagement planning, and UAT scope definition.

Migration strategy should be driven by evidence, not assumptions. Combined with business context, usage data provides objective insight into business dependency, operational risk, testing scope, and stakeholder impact. Without it, prioritization quickly becomes opinion-based rather than evidence-based.

Build Reusable Foundations Before Scaling Delivery

Not all reports deliver the same value or create the same leverage.

Through a Cognos-to-Power BI reports migration, we discovered that a relatively small set of calculations drove a large percentage of reporting requirements. Metrics such as earned premium, loss ratio, reserves, and IBNR appeared across finance, actuarial, underwriting, and claims reporting.

Rather than treating each report independently, we prioritized building these shared calculations first. Common SQL transformations, reusable DAX measures, and standardized report templates became reusable components that accelerated every subsequent migration wave. By reusing proven logic instead of recreating it for every report, we accelerated delivery, simplified validation, and improved consistency across reporting domains.

The same principle applies to modern cloud architecture. Whether using Snowflake, dbt, semantic models, or governed data products, organizations should build shared business logic once and reuse it wherever possible.

Treat Pilots as Learning Exercises, Not Success Stories

Many organizations view pilot migrations as an opportunity to demonstrate quick wins.

A better approach is to use the first migration wave to uncover problems before they are repeated at scale.

In a legacy-to-Snowflake platform migration, the most valuable pilot was not the simplest business unit. Instead, it was a domain that exposed multiple dependency scenarios, user patterns, source systems, and operational workflows.

The goal was not simply to deliver the smallest usable release. It was to test the migration approach under realistic conditions and expose:

• Integration and dependency issues

  
  

• Testing and governance gaps

  
  

• Stakeholder and workflow concerns

  
  

• Weaknesses in the delivery process

Those lessons should shape every migration wave that follows.

Stakeholder Engagement Should Begin Long Before

UAT 

Technical readiness and business readiness rarely progress at the same pace.

Many migration delays occur because business users are engaged too late in the process. By the time testing begins, teams are often still working through UAT access, environment provisioning, competing business priorities, and operational constraints such as month-end reporting activities. Engaging stakeholders (business and IT) early helps identify and resolve these issues before they impact delivery timelines.

Successful migration programs engage stakeholders months before formal testing begins. The earlier stakeholders understand the objectives, timeline, and expectations, the more effectively they can contribute to testing, adoption, and change management efforts.

Business readiness activities should reflect the type of migration:

• Reporting migrations require preparation around metric consistency, navigation, functionality, and user workflows.

  
  

• Data platform migrations require preparation around reconciliation, lineage, downstream dependencies, and data validation.

In both cases, stakeholders should enter UAT focused on validating business outcomes, not learning how to use the platform for the first time.

Build a Migration Framework That Scales

As migration programs scale, consistency becomes more valuable than speed.

The goal should not be to solve every business unit’s migration differently. Organizations should establish a repeatable operating model that remains flexible enough to accommodate unique business requirements.

This model should encompass migration sequencing, testing strategy, stakeholder communications, governance checkpoints, deployment processes, and change management. Standardizing these components reduces execution risk, improves predictability, and allows teams to focus their energy on solving new problems rather than reinventing proven processes.

The most scalable migration programs repeat their approach across business units, data domains, and migration waves. When a migration framework becomes repeatable, organizations gain the ability to accelerate delivery while maintaining quality and stakeholder confidence.

Successful Data Migrations Are Built on Decisions, Not Technology

Whether modernizing a reporting platform or migrating the underlying data environment, the principles for leading successful migrations remain remarkably consistent. The most successful programs use data to drive decisions, establish foundational capabilities early, engage stakeholders before they become blockers, and build repeatable delivery models that scale.

The technology stack may change from one migration to the next, but successful programs consistently rely on the same fundamentals: making informed decisions, reducing uncertainty as early as possible, and building stakeholder confidence from planning through production.