3 Data Governance Challenges Today’s Companies Face

Data governance policies are full of holes that can become expensive pitfalls. We explain some of the stumbling blocks.

Some organizations have mastered data governance, but they are in the minority. As data volumes continue to grow, most businesses are finding it hard to keep up. 

“You’re going to do this one way or another,” said Shannon Fuller, director of data governance at  Carolinas Healthcare System. “You can do it in a controlled, methodical manner or you can do it when your hair’s on fire.”

Poor data governance can result in lawsuits, regulatory fines, security breaches and other data-related risks that can be expensive and damaging to a company‘s reputation. “We don’t have regulation about data lineage and reporting and all that, but it’s going to come,” said Fuller. “Do you want to prepare for that now or do you want to be like Bank of America and spend billions of dollars complying with the law?  Most healthcare organizations don’t have that kind of cash lying around.”

Another problem is legal discovery. Without proper data governance, companies end up handing over information that is not relevant to the case.  Some of that information may be sensitive.

There are valid reasons why companies are struggling with data governance.  Following are three of them.

1. It’s considered a technology problem. Effective data governance requires the use of good tools; however, the use of good tools does not guarantee effective data governance.  Some companies find this out the hard way when they invest in technology but fail to make the necessary adjustments to their culture and business processes.

“The common wisdom is you need an executive sponsor and the support of the C-suite and roll that down. It helps, but there are things you can do from a data governance perspective without having that buy-in,” said Fuller in a recent interview. “It has to be tied to your business processes. In healthcare, that’s one of the biggest stumbling blocks.”

2. Old approaches are applied to new requirements. Data governance policies and procedures require updating as more data flows into and out of organizations.