We say it all the time: Data governance should be driven by the business. But let’s face it: IT knows the technology and most of the technology requires heavy IT involvement.
So what does that even mean when you’re talking about something as technology-focused as master data management? And how can CIOs convince the business that data governance is its responsibility?
You may know that White focuses on master data at IT research firm Gartner, but what is less well-known is that White is a supply chain management expert, as well. And like everything else in the world, supply chains are becoming more data-driven. That’s putting pressure on supply chain leaders to deal with their data problems, White explains in the article.
He’s writing for a supply chain audience, but as an interesting side effect, he succinctly identifies what CIOs need to change to ensure that MDM and data governance are business driven.
Here’s what White says are the dos and don’ts that will lead to MDM and information governance success:
Don’t start the project within IT, even if the data is a mess and clearly needs MDM. There are two simple reasons for this: First, the business won’t do it anyway unless it sees the benefit. Second, governance will end up being about IT control rather business value.
“…information governance should only be undertaken when a business has both a desire to first, govern data for the express purpose of realizing business value, and second, a willingness to change its business processes that create, enrich, approve, or otherwise use data, so that it can extract that value,” White suggests.
Do think and talk about governance differently. Part of the problem is that governance is a tainted word for business users, who regularly tell Gartner that governance means “security, access, control, rigidity, limited flexibility, IT managers or ‘Big Brother’ watching, extra work, ‘something focused on data that IT needs to work with,’ ‘something we are doing wrong (apparently), and ‘not related to what we do in the business,’” writes White.
Instead, use words like stewardship and custodianship to better express the relationship between business users and data.
Don’t set up rules that stop the business user from doing his or her job. White gives a great theoretical example of how Fred bypasses governance efforts by deliberately entering the wrong code to get around the system. His reason: It’s taking too long and stopping him from being effective for no clear benefit. Don’t be that IT department.
Do let business outcomes set the parameters for data quality and data governance. Too often, data quality is done because it’s obvious to CIOs that organizations need better data quality. But that isn’t working out so well, which is why business outcomes need to come first, writes White.
One way to put business outcomes first is through the metrics you use, he explains. For instance, instead of measuring the “number of de-duplicated records per month,” measure MDM by “net new revenue per first six weeks of new product introduction,” he suggests. Just using the word revenue will ensure that it’s relevant to the business user, he adds.
For example, business users who had previously been reluctant to participate in the governance of customer data would be willing to do so if it would help them achieve their own, measured objectives.
Don’t make data stewardship a full job. “If it is, then the organization is focusing on the wrong things,” writes White.
If IT can’t solve the problem, it must at least ensure that business users can address the problem quickly.
“How many minutes may differ for each organization—it might be 15 minutes, or 20, or 10,” White writes. “The number is not the point; the point is that this responsibility should take up a very small amount of time compared to the rest of a business user's work.”
If the governance effort outweighs the business value, you’re likely to see more Freds and fewer results.
Do think about the financial value of your information. Information can have financial value in two ways: The information itself can be turned into a financial asset or the information supports business goals. By considering the financial value of data, you can better prioritize information management projects.