Moving to a new software system? It's like moving to a new house but for your data. First, take inventory of everything you have and make sure it's clean and organized. Create a map to show how your data will move from the old house to the new one. Test everything before you move, and back up your data just in case. Communicate the plan to everyone involved and be ready to help people adjust to the new system.

Within the project plan, the biggest chunk of time from my experience should be spent on Testing. Planning is important, but I find companies spending too much time on analysis and then they often tend to miss the boat. Methodology I prefer here is Agile (waterfall is okay, but agile is better). Product that you choose should allow rapid prototyping and fast return to last known good stage.

Understand well data migration requirements and decide purpose-fit migration approach, e.g. big bang, incremental, CDC; Improve data quality to avoid rubbish in and rubbish out; Test performance of migration program with representative data volume; Design for fault-tolerance Sufficient data reconciliation in place to validate source and target;

I would say...account sufficiently for unknowns you would discover progressively... you need talent available who has depth of both of the systems... the FROM system and the TO system... to map the data properly... after all end users who consume it at the end are key to be fulfilled... Prioritize which functions need to be served first... get their department buy in for availability and active engagement... schedule it accordingly...

In my experience, backward planning is essential and key for successful data migration. Identify a cutoff date, migrate data from old systems to new, while old systems are still running, test new systems and fix if there are any issues. Set log shipping daily so that on the D-day with minimum data migration the new systems are good to go. Planning and validation is essential.

Choosing the right data migration tools was a game-changer for our recent SAP S/4HANA transition. We carefully selected tools that were compatible with both our legacy SAP systems and the new S/4HANA environment. Key features like data integrity checks, real-time monitoring, and rollback capabilities were crucial for us. For example, we used SAP’s Data Migration Server, which allowed us to track the migration progress and quickly address any issues. Investing in these reliable tools minimized risks and ensured a smooth and accurate data transfer. This approach not only safeguarded our data but also helped us transition seamlessly, setting the stage for a successful implementation of our new SAP system.

One if the biggest challenges I faced numerous times was data migration. The cleanup, the classifications, the error handling, exception handling. On more than one occasion we chose to run two systems until we could close out the old one. On one occasion the issues were so daunting that using a tool was too expensive and too risky and i hired a team of people offshore to rekey data for millions of records ... much cheaper, much faster ... much better.

There are many ai assisted tools. It is very time consuming & costly to find out which one is the right fit for our data. But this is must be done. Try a small set of data for ETL transform & for migration. Once, the right AI assisted tool is found, your life is much easier.

Find a partner that either has or can create migration tools for add-on programs that will ease the implementation & shorten the timeline

Testing isn’t just about checking if the data made it to the new system. It's about verifying that everything is accurate, complete, and functioning as expected. Start with data integrity testing, this ensures the data migrated correctly without corruption. From there, move to application-level testing, which checks if the data performs as expected within the new system. Also, use the data reconciliation technique, which compares data in the old and new systems to verify accuracy. And don’t forget to involve your key stakeholders. They should be involved in testing to validate that the data makes sense from both a business and an operational perspective.

A company, eager to migrate customer data to a new platform, skipped thorough testing, assuming the process would be smooth. Post-migration, they found missing records and altered data, causing major disruptions. Realizing their mistake, they reverted to a backup and took a different approach. This time, they performed a pilot migration on a small dataset, rigorously testing every step—extraction, transformation, and loading (ETL). The testing uncovered issues that were fixed before the full migration, which then went flawlessly. This experience reinforced that testing is non-negotiable in ensuring a seamless data migration.

Testing was crucial for our SAP data migration project. We started with a pilot migration using a small data set to uncover potential issues early. Our thorough testing covered every aspect of the process—data extraction, transformation, and loading (ETL). For instance, we validated the accuracy and completeness of the migrated data by comparing it against our original datasets. This meticulous approach revealed critical insights and ensured nothing was lost or altered. By addressing these issues before the full-scale migration, we gained confidence that our strategy was solid. This step was vital for a smooth transition, ensuring that our SAP S/4HANA implementation went off without a hitch and met all our accuracy requirements.

Take this sample data & run it parallel to the entry in the legacy system to confirm accuracy and determine if the process for each department processes is optimized

Preparing our staff for the SAP S/4HANA transition was a top priority. We provided extensive training covering both the migration process and the new system. Our sessions included detailed instructions on managing data before, during, and after the migration, as well as hands-on training with SAP S/4HANA’s features. For example, we organized workshops where team members practiced data handling scenarios and explored new functionalities. This comprehensive approach not only equipped our staff with the necessary skills but also built their confidence in navigating the new system. By ensuring everyone understood their roles and responsibilities, we minimized the risk of human error and paved the way for a smoother, more successful transition.

Train the trainer for the internal project champions help build confidence in the rest of the team. They already know the champions and are confident in their internal knowledge of company processes

Ahh Training. Unlike AI that will retain training results forever, human tends to forget unused skill. And training for a skill used only once in a lifetime is expensive. Companies don't migrate data every day. Thus, if a bonafide migration professionals are available with reasonable cost then non it focus company with non sensitive data, can explore.

For me it is showing appreciation of people and their responsibilities. When switching to a new software system, I always make sure to involve people from different teams early on. It’s not just an IT job. You need to bring in those who use the data every day. Their input can help catch problems before they become big issues and everyone feels being part of the team.