December 7, 2025 • 5 Min Read

That’s why it’s so important to start with a solid plan. Before you dive into implementation, take a good look at the state of your data. Is it clean? Consistent? Reliable?

The good news? Cloud ERP systems like Oracle, SAP and Workday have simplified the data migration process with standard tools and templates putting more power in the hands of business users by reducing dependency on IT. In addition to this, the ETL tools like Alteryx offer native advanced AI capabilities that help with data clean up and transformation. The best practice is to avoid relying on excel spreadsheets to transform data. ETL tools can eliminate duplicate data with fuzzy logic and help to maintain audit trail as data like chart of accounts is refined throughout the implementation lifecycle.

With cloud ERP migrations accelerating, as a result of AI, there’s no better time to get your data in order.

Before anything else, take a good, honest look at your current data. The best time to do this? In the planning phase before ERP implementation kicks off.

If your organization has been using the same legacy system for years, chances are there are outdated records, duplicates, inconsistencies, and so on. This applies to both master data (like customer and supplier info) and transactional data (like invoices and purchase orders).

Don’t wait until you’re halfway into the project to realize your data needs a deep clean.

ERP systems connect everything; from finance, HR, supply chain, to operations, so data ownership needs to be shared across teams. That’s why it’s crucial to form a dedicated data governance team for the transformation.

Make sure your functional teams understand how their data decisions affect other areas. For example, a mistake in supplier setup can ripple into procurement, accounts payable, and reporting. Encourage collaboration, not silos.

As you design your new ERP system, identify where each type of master data will live as your “single source of truth.”

Let’s say Salesforce is your go-to system for customer data. That means updates to customer info shouldn’t happen in your ERP system—they should happen in Salesforce.

This clarity helps set up the right roles, access controls, and governance processes. If you’re using Oracle Cloud, consider a tool like Enterprise Data Management (EDM) to manage your master data centrally. It can automatically sync updates across ERP and EPM systems, so everything stays in sync.

A well-documented data migration strategy keeps everyone on the same page.Here’s what to include:

• List of source systems and how data will be extracted from each
• Approach for each data type, like only migrating open invoices (not fully paid ones) or mapping legacy sales order numbers
• Data cleansing plans by phase (Simulation 1, CRP, UAT, etc.)
• Tools and methods for extracting, transforming, and validating data

Migrating data is one thing, validating it post-migration is another. You’ll need a reconciliation plan to ensure that what went into your new ERP matches what came out of your legacy system.

Set up standard and custom reports, define clear validation criteria, and build in time for spot checks. Don’t assume everything came over correctly, you need to verify it.

What’s a data handbook? Think of it as your ERP playbook. A data handbook should document all your master data rules, naming conventions, approval workflows, and handoffs between business and IT teams.

Why bother? Because when everyone follows the same rules, you avoid errors, duplicates, inconsistent data, and confusion. It’s especially helpful for onboarding new team members or working with external partners.

Let’s Talk About Getting Your ERP Data Right

With cloud ERP adoption accelerating and timelines tighter than ever, taking the time to plan and govern your data upfront can save headaches, reduce costs, and turn your migration into a real business advantage.

Not sure how to assess the health of your data or your readiness for ERP transformation? RGP’s Streamline 360™ ERP Assessment provides a clear, objective view of your data gaps, priorities, and risks, before you commit millions to a migration timeline.