Best Practices to ConsiderBy Jill Dyché | Posted 2011-07-28 Print
Guidelines for defining data governance and formalizing it as a sustainable set of practices.
Best Practices to Consider
The good news is that companies embarking on data governance for the first time are learning from those that have gone before them. Here’s a list of best practices to consider before launching a data governance initiative:
Find the need, pain or problem. Sure it sounds trite, but if data governance isn’t addressing an acknowledged business problem (such as fines for noncompliance or duplicate customer records eroding marketing ROI), it won’t stick.
Know your road map. If you know your problem, you can scope your project. And that leads to definable measures that can prove the value of data governance.
Get an executive sponsor—if you need one. Companies—often large ones with consensus-driven cultures—require executive buy-in before launching cross-functional initiatives such as data governance. Others, however, need to show value quickly before enlisting senior-level support.
“We enlisted our CIO as the sponsor at the very beginning of data governance,” says Karen O’Dell, director of business systems for Station Casinos, based in Las Vegas. “He was a champion on behalf of corporate information and kept saying, ‘We really need to do this.’ Involving him ultimately got everyone else on board pretty quickly.”
Start small. You can build a data governance charter and craft some guiding principles. Indeed, these are great mechanisms to support data governance. But make sure these apply to an actual project that addresses an identified business problem.
And ensure that the project solves at least a portion of the business problem, while at the same time introducing new processes and job roles. This is the proof of concept that will give data governance the visibility it needs to have staying power.
Proselytize your success. A successful project is the platform on which you’ll make the data governance pitch to a broader audience of business constituents and executives. Show how implement-ing data policies, cleaning up a subset of data, and deploying it to support a business process helped lower costs or drive new revenues. People will be lining up to be next.
Think transformation. Data governance involves more than buying a data-quality tool or hiring a data steward. Clear policies for the definition, access and use of corporate information raise the probability that data can be leveraged to streamline business processes, generate new revenue and even drive innovation.
When data governance works, it not only meets one or more business needs, it also cultivates an awareness of specialized skills, processes and tools needed to define, maintain and provision data across the enterprise. It removes needless manual rework by businesspeople who have day jobs, and it reduces the overreliance on human relationships that many businesspeople still fall back on.
Good data governance ensures consistent and meaningful information to support strategy and streamline operations. In short, it’s what the “data-driven organization” is all about.
Jill Dyché, partner and co-founder of Baseline Consulting, is the author of several books on the business value of IT, the latest of which is Customer Data Integration: Reaching a Single Version of the Truth (Wiley).
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