Last week I attended the MDM Summit in New York, ably hosted by Aaron Zornes. I sat on a panel discussing master data management business and technology strategies for the IT executive. It was a eclectic panel; me, Elaine Bradshaw, SVP at Marsh in charge of data management, Nachi Desai, VP of enterprise architecture and BI at 1-800-flowers.com, and Sandeep Manchanda, Head of Information & Technology Management, General Insurance at Zurich Financial Services.
What was fascinating to me was that each of these very accomplished executives was taking a different approach to implementing MDM in their enterprise, but each in their own way understands the critical need for business end-user and executive involvement.
Elaine offered an interesting organizational twist; while she is responsible for data management, she reports to the COO. Marsh very much views data as a business issue, not an IT issue. Nachi very cleverly “lured” the business into getting more involved by showing them the fundamental compliance issues with bad data, and Sandeep was taking a more structured, 5 year plan approach, complete with blueprints, committees, and a “rolling thunder” approach.
Listening to their challenges, I couldn’t help but wonder how a similar problem can be solved in so many different ways, but then I realized it’s for the very same reasons I’ve been talking about; that data governance is as much if not more a cultural and behavioral issue than a technology infrastructure problem. Many companies have approached data governance by forming committees that are designed to set standards. These are often cross-functional task forces that consist of representatives from across the business. While having input from multiple “owners” is a good start, most of these committees do not focus on the hard part; how to monitor and maintain compliance to standards. Without these essential elements, standards decay and are eventually discarded by the business in favor of driving short-term results.
So what are the key elements for business involvement in data governance? For me, it comes down to three key areas:
- First and foremost, the business must understand the difference between accountability and ownership of data. Accountability means owning the definitions of the data, the rules on how it is used and the policies that govern its use over time. It does NOT mean they are responsible for how it is created, stored or archived; that is IT’s responsibility.
- Second, business users must actively engage in monitoring and maintaining important reference and master data. If they do, data quality and integrity will improve and they will benefit as a result.
- Finally, business users must demand that IT give them easy to use tools to play their role in the process. It is too much to expect the business to become technologists. This must be “iPhone simple” for the business to adopt it in any meaningful way.
Good data governance programs spend as much time educating and involving the business as implementing technology. The crucial step is getting the business to understand the role of data governance in improving business results, not getting them to understand the technology. Over time, the business will take on more responsibility for data and will begin to play a proactive role in how data is governed across their enterprise.
This post originally ran on CIO.com