[Unilever] had set aside an SAP system specifically for holding a copy of the master data, and assigned responsibility to people to manage the data in that system. They used SAP replication technology to manage all of the other copies that were around the organization.

The skills, principals and techniques that are used to build data warehouses can be used to very good effect in the MDM arena. In actual effect, most data warehouses have at least solved the first part of the problem, which is getting to see what's out there, because you have brought it all into one place.

If you've got lots of different copies of what should be the same information, but it's not the same, then potentially that is a business problem.

It's much easier to take data and push it into a data warehouse than it is to take data and push it into operational systems. This harmonization and consolidation stage has to do with getting sight of what you've actually got and moving it into a better position from a data perspective.

The notion of understanding where your data is stored and managing the potential conflicts that arise when you get copies of that data out of line with one another is what MDM is all about. We have seen some staggering benefits from it and we have seen some things fail.