I have encountered quite a few companies that are now anticipating the move of as many of their source systems as possible into SAP.  I think this is probably a good decision for quite a few of these organizations.  However, in doing so, we must keep or create data management guidelines and principles that take into consideration data governance, integration and data quality.

For example, I have seen the "afteraffects" of moving to a new system without paying attention to data quality issues.  If you have read some of my earlier posts, you will encounter many stories about incorrect codes in the data warehouse environment that originate in source systems like SAP.  These issues are usually NOT the product's fault, but these errors occur due to the actions of those who create the data.  If you find suspect data in any source system(s), you may want to consider the following:

1. Profile the data for each table created in the source system(s)
2. Assess any interfaces that take data from the source system(s) and propagate it into another system (like the data warehouse)
3. Consider creating business rules and processes to keep the data clean, and try NOT to "MacGyver" a view or process to overlook the suspect data – JUST DEAL WITH IT!  Otherwise, it will come back for you to address in a later phase or another project.  I believe that fixing the data issues now will save more time later.

While addressing your data issues now by finding ‘suspect’ data and assessing that data may not be part of your "current" SAP or new source system project plan, it should be part of the enterprise plan for information management.