We recently reviewed some general considerations for a cloud ERP migration, including moving to a shared environment, the inability to customize, and changes to the reporting structure.
As referenced, in order to navigate these changes, data management needs to become a primary workstream of your digital transformation. Focus and timing are two key components for managing data through your cloud ERP migration:
We mentioned previously that because implementing companies are often not able to bring over their previous custom requirements into a more generic shared cloud application environment, they are facing increasingly complex integrations into ancillary applications and databases to replace their necessary business process customized functionality.
This integration effort will require extra focus on data, meaning you cannot assume data will simply transfer to and work properly in the new system. With each point of integration or each API, you will need to thoroughly test and, in many cases, restructure your data according to the required new data format.
If you wait until you are in the later stages of the project to begin building your RICEFW and tracing the data you are currently using that supports these items, then you will likely run out of time and be forced to skip vital testing, crossing your fingers that you didn’t break anything critical.
Under new accelerated implementation models, System Integrators are no longer gathering extensive requirements and are instead fitting clients into a standard, off-the-shelf functional model. This new focus on retrofitting into pre-programmed processes, rather than building processes from scratch, puts extra stress on data modelers who need to ensure that the data produced by the new system will be congruent with the legacy system’s data outputs.
Many careers have been thwarted by rushed and poorly planned or executed ERP and Digital Transformation projects because the new C-suite reports just don’t line up with the legacy reports that were produced prior to Go-Live.
Referring again to “back in the day”, historically data was a component that would receive attention in the later stages of implementation. Now, with the above-referenced issues, it is no longer an option to delay efforts on data planning, management, and cleansing:
Due to accelerated implementation models and the increased stress on data outlined above, data efforts must begin early to keep the implementation on track. Data cleansing can be a tedious, time-consuming activity that ideally should be tackled prior to implementation kick-off. The benefit here is that you are accessing data owners’ availability while they have capacity during the ramp-up period between system selection and the official start of systems implementation.
During implementation, everyone is stressed to the max. Adding data cleansing duties during implementation will often lead to errors and gaps because people are so distracted with other aspects of the transformation.
Along with completing an assessment prior to implementation, be sure to have dedicated data experts as part of your implementation team. They will need to be part of planning to make sure data is managed properly and will be responsible for the quality of data that goes into the new system.
This is especially important if you are on a rapid or agile implementation track. When pressed to sprint, people will get tired, and mentally drained, and data will become an afterthought.
If you have questions or would like to discuss more on how you can best prepare for a cloud migration, please reach out. We also welcome you to subscribe to our blog and receive current posts on data management, security, and technology transformation best practices.
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