DeKenipp: Data Management Maturity Model points way to best practicesDate: Dec 18, 2013
When your data management processes aren't up to par, it might be difficult to figure out where the weak points are -- and where to start in order to fix them. But identifying areas of weakness is a must when working to improve data management practices. That's where the Data Management Maturity Model comes in, according to Patrick DeKenipp, senior vice president of business intelligence at Sterling National Bank in Montebello, N.Y.
At TechTarget's BI Leadership Summit in New York last month, DeKenipp gave a presentation about the maturity model, which is called the DMM for short. He further discussed the model in a video interview conducted by Scot Petersen, editorial director of SearchDataManagement and its sister site SearchBusinessAnalytics.
The DMM is being developed by the Enterprise Data Management Council, a group founded by financial services firms, to provide a way for organizations to assess where their data management programs stand on a five-level scale. The EDM council released an initial version of the model to its members in June 2012; updates have been made this year, and the group expects to release the DMM publicly in 2014 along with a self-assessment spreadsheet.
Even a basic assessment could be beneficial to companies looking to step up their data management game, DeKenipp said in the interview. "At a minimum, the organization and the executives become educated around the disciplines of data management that they may not be aware of," he said, adding that the exercise should also provide a baseline for "where your organization is and give you visibility into where you may need to improve."
More detailed assessments can produce an action plan for upgrading various aspects of data management, such as data governance and data quality processes, said DeKenipp, who helped put the DMM into use in a previous job as part of an internal audit group at Citigroup that handled oversight of the company's chief data office. He also is incorporating some of the DMM principles into the business intelligence program at Sterling National, in order to involve his team in the full data management lifecycle on information that will be used for BI purposes. When new applications or data sources are added, DeKenipp said, he wants the BI group to be part of the process up front "so that we understand how the data is going to flow through" the organization and be used.
In the nine-minute interview, DeKenipp further discussed his experiences with the Data Management Maturity Model. Viewers of the video will:
- Learn about the potential benefits of using the DMM to assess their data management practices.
- Hear about DeKenipp's experiences with data management and business intelligence while working at Citigroup and Sterling National Bank.
- Get his thoughts on treating data as an asset and whether a financial value can be placed on corporate information.