Master data management (MDM) is kind of low these days — it’s down in the trough of disillusionment, you might say. Reality is a sad situation for MDM advocates: So much promise, so little actual delivery.
“The sad part to this story is that many organizations are actually getting budget for MDM investment; they actually implement a technology, and then sit back and wait to see the magic happen,” writes Gartner MDM and analytics guru, Andrew White. “Then of course it doesn’t.”
Is this a case of expecting technology to magically work? Surprisingly, no. White says the problem is that organizations find that “the work of MDM is too oriented on data quality, as if it alone will make things in the business work better.”
Data quality is important, White writes, but on its own it is inadequate. MDM needs to deliver business value, which means focusing on the data quality that matters to the end user and the business, he explains.
Instead, IT is focused on measuring data quality as if it were some inherently valuable KPI, when, in fact, it should be focused on the business priorities.
White’s piece doesn’t really try to fill in the gaps on what that means or how you can fix it. In fact, he calls this his “2014 theme,” so I suspect he’ll more fully explain or be developing more.
In the meantime, Rob Karel’s recent Wired column may help us fill in some gaps. Karel previously worked as Forrester’s MDM specialist, but now he’s the vice president of product strategy at Informatica. Still, what he writes applies no matter which solution you have or plan to deploy.
Karel hits a similar theme as White when he warns that data management professionals should “stop talking about the data!”
“Accept the fact that the ultimate objective for MDM, data quality and data governance, is actually not to achieve a single, trusted and secure view of your data,” he continues. “It’s only the means.”
Instead, you should be focused on those business processes, decisions and interactions that matter to business executives and managers. Look at how MDM and other data management projects can:
Oh, and you might want to look at a little something businesses call “strategic differentiation,” too.
The problem, Karel writes, is that data management projects are often planned backwards by starting with data consumers and working their way up to business sponsors to help fund the project.
That might seem like a smart approach. Start with the end user problems and work up. But Karel says a smarter approach for MDM is to reverse that: Look at the business imperatives defined by your CEO and board of directors. Often, there will be no more than three to five major objectives.
Karel identifies five steps in all, in which you end by surveying business users about their confidence in the data. From there, you can develop a use case that reflects the organization’s real business priorities.