You want to get cost under control. Maybe even save. You need to ensure compliance. You need to satisfy the auditors. You want to know the risks you face. And the risks you could face. All laudable goals, but all goals that are unobtainable without … you guessed it … data.

More specifically, clean, rich, up-to-date, relatively complete data … which, likely, resides in multiple systems, duplicated across each. This makes data centralization, which is necessary for any of these initiatives, complicated, and often difficult. It’s not just the last update record date, especially since some systems do the last update at the record level, and not the data element level.

Plus, how do you know which parts of which records can be combined? Especially when they conflict or don’t line up. Without an appropriate master data management strategy, and a system that can handle master data management across multiple, loosely related, supply management and enterprise, it can be downright impossible for any initiative that spans more than a few dozen providers or categories. And even that is an effort.

But MDM is not easy to define, and even less easy to implement. First of all, which systems do you use for master data when there is an argument for multiple systems that store a record, such as a supplier, to be a master data system. Secondly, when you do identify the master system, how do you manage, and approve, updates … and how do you insure they get synched to the right systems at the right time? Third, how do you integrate all the data into a single, even if only virtual, record so that you can run a spend report. A compliance report. A risk report. An audit report?

The point is that it’s not just as easy as selecting a system, proclaiming it your MDM, and believing the implementor that your MDM problems will be solved in a few months. Some companies, that aren’t heavily focussed on, and involved with, the initiative take years to integrate systems and arrive at a nearly clean set of master data.

So before you march forward on your next, data intensive initiative, maybe you should step back, ask yourself where you are on your data management journey, and give an honest answer.