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8 Top SAP Data Migration Best Practices

Written by Mike McManaman,

Almost every SAP implementation has some form of data migration. Big or small, many data migration projects come in over schedule and over budget. Follow these data migration best practices to ensure your next data migration is a success.

  1. Invest the Time: In my experience, companies don’t spend enough time on two important aspects of implementation: training and data migration. With data migration, resources are not assigned early enough, and data migration activities are started way too late in the game. Don’t let it fall to the backburner. Have dedicated resources assigned, and make sure you don’t wait until late in the project implementation to focus on migration.

  2. Business Involvement Early and Often: Make sure you have a complete and deep understanding of your data. This may seem obvious, but with data reaching back years if not decades, and different people and organizations within your company creating data differently, it can be a nightmare to figure out how legacy information will map properly into SAP. Get the right business experts involved early on so they have ample time to dig into the data. Make sure key business owners give input into how the data is mapped into SAP.

  3. Clean Your Data: With early involvement of business owners, you should have plenty of time to identify bad data and clean it up in the legacy system. Many times, companies assume their data is clean or that someone will clean this data up during the transformation stage, and they won’t put any work in up front. This is a bad idea. Not all bad data can be cleaned up during transformation, and many time-consuming errors will occur during loading and validation. Garbage in, garbage out. Spend the time early in the project to clean your data, so you don’t have to spend more money and energy cleaning it up afterwards.

  4. What’s the Scope: It’s important to understand early on the scope of the data you are migrating. Do you need every piece of legacy data going forward, or can you leave some of it behind? Is it necessary to bring over all change management information, or can you leave the legacy system in a read-only state so select users can go take a look? Avoid scope creep, because moving targets cost delays and money.

  5. Document, Document, Document: Invest the time to document every mapping, every rule, and every decision. Make sure you have an overall data migration scope and strategy document, as well as detailed documentation on how fields from your legacy system map to your SAP system. Don’t do an initial draft of your documentation and fail to update it as you learn more. Make sure you spend the time and resources, so if there’s issues down the road, you understand why.

  6. Validate Every Step of the Way: Have business owners validating both transformation rules and the data loads throughout the data migration process. You should have a non-production system in place to test your transformation and load work. And because you have been documenting everything, business owners should easily be able to understand what has been done to their data. Also, give them plenty of time to validate everything, and not just 30 minutes on a Friday afternoon.

  7. Think About End Users: Provide new users with information about how the legacy data was transformed. You will have power users validating the transformation and load into SAP, but make sure casual users understand what has changed from the legacy system. Provide some documentation so they know where to look for information, and how legacy fields map to the new SAP fields. Give your end users a chance to succeed by empowering them with information.

  8. Have the Right Tools for the Job: SAP has some standard tools you can use to load data. However, they can be difficult to use, and require someone with technical expertise. We’ve had a lot of success using VeloX. It’s a data migration load tool with a drag-and-drop interface that makes data mapping a breeze. It’s flexible and extendable, so if there’s something more complex which does require coding, VeloX can scale.

Some other key features and capabilities of VeloX:

    • Zero-coding approach
    • S/4HANA compatible
    • Cloud support
    • Smart multithreading and balancing for faster performance
    • Embedded Python programming language for advanced users

For more Do’s and Don’t, check out our Data Migration Webinar: Overcoming Challenges, Reducing Costs, Ensuring Success.