MDM keeps enterprises from poisoning themselves with their own data.
We usually think of the brain and the heart as being our most vital organs. But kidneys also play a literally vital role in the proper functioning of the human body. Without them keeping our blood clean and chemically balanced, we would eventually die.
Those whose kidneys have failed use dialysis to imitate their function. The patients’ blood is pumped through the dialysis machine* to cleanse it and then circulated back into their bodies. It isn’t a perfect solution, but it does keep renal patients alive when their own kidneys don’t work sufficiently.
In the enterprise, some people (either business or IT) might think it’s more trouble and expense than it’s worth to develop the processes and deploy the technologies for a master data management initiative, to ensure that data in their ERP and other enterprise systems is kept clean, current, and correct.
After all, they might reason, the data is already there in the ERP system; why take it out of the system (even virtually, in registry-style MDM) to be managed in an MDM hub, which is only going to serve the data back to the system?
They might think that a better solution is to emphasize best practices for data governance among the users of the ERP system – that best practices alone are sufficient to ensure the ERP data stays accurate and up-to-date, and is maintained according to the organization’s standards.
But in many cases that isn’t realistic. Most ERP systems are notoriously inadequate at the technical functions that help support sound data governance. And, honestly, most people (being human) are notoriously inadequate at the human side of data governance. Both the systems and the people need tools to help them with these vital tasks.
An MDM platform serves that role, similar to the function of a dialysis machine. It takes raw “impure” data from the system, ensures that it’s clean, current, and correct, and then circulates it back to the originating system for use in the enterprise.
Beyond just ensuring data quality, MDM also integrates and manages data from a variety of sources, uses a flexible data model to create associations among complementary data, and makes the master data available for all requirements and applications across the enterprise, such as business intelligence, multichannel publishing, partner feeds, and others.
(To push this hematological simile even further, it’s almost like a combination of dialysis and blood transfusion; you take data from a variety of donors, cleanse it and make it available for other life-giving enterprise processes, then make sure it goes back to the original donors.)
I’m sure that renal patients would rather not go through the expense, discomfort, and inconvenience of dialysis therapy. But it’s better than poisoning themselves with their own blood. In the same way, enterprises that rely on ERP and other enterprise systems need to go through the effort of MDM and sound data governance to ensure they don’t poison their critical processes and operations with their own data.
*From Wikipedia: “Dr. Willem Kolff, a Dutch physician, constructed the first working dialyzer in 1943 during the Nazi occupation of the Netherlands. Due to the scarcity of available resources, Kolff had to improvise and build the initial machine using sausage casings, beverage cans, a washing machine and various other items which were available at the time.” Extraordinary.