3 Pearls of Data Governance Wisdom

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Max Just (a presenter at the AI Data and Democratization event this April 27-28) and his team are looking to build a data governance framework that not only protects data and ensures data quality, but serves as an enabler of business strategy. With this in mind, we asked him to share 3 pearls of wisdom for building an agile, innovation-first data governance approach. Here’s what he told us.

#1 Narrow your focus to what really matters

As he puts it, “[organizations that are successful with data governance] don't try to boil the ocean. They focus on the use cases that are going to move the needle for the business. They start with the objectives of the business and then build necessary governance activities around the data sets that drive those use cases.”

By delivering the necessary data quality for a few initial use cases, stakeholders can immediately start linking governance with value. 


#2 Cultivate a non-invasive approach to data governance

At Coca Cola, Mr. Just and his team have developed “a non-invasive approach to data governance, so that it doesn't come across as something that needs to get done out of fear. it's not about adding more things, it's about modifying our behaviors so that we treat data as a strategic asset.”

Fear-based DG strategies are rarely successful. Instead the goal should be to integrate DG-related activities into everyday workflows so the stakeholder doesn’t even have to think about compliance, it just comes naturally. 


#3 Embrace tech-enabled governance 

As the strategic importance of data governance has increased, so have the number of solutions available to help streamline and strengthen these processes. According to Mr. Just, organizations are increasingly adopting new DG tools as well as reconfiguring existing solutions to better support DG objectives. As a result, “now “you don't have to rely so much on manual processes. A lot of that is changing, quite a bit to my surprise. When I got into this role, I thought DG was all about compliance, creating standards, policing the data quality of every system out there, and the more I get my feet underneath my desk and my hands dirty, the more I realize that it is not so much about that.”


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