We are now seeing an ever-increasing trend towards data governance where the relationship between humans and data combine.

What companies are realizing more and more, and being highlighted more so through this pandemic, is that when you can’t have your customers walk in and interact with your business face to face, the only way you can communicate is through your data so data governance is really on the forefront right now. With Data Governance we are taking human implemented concepts, procedures and principals, etc. around compliance policies and trying to apply it towards things and elements that are digital. With the increased presence of data governance policies, companies are now looking at setting up data governance policies systematically where you can attach the policies to the data, and therefore free up bandwidth to focus on using your data to drive business and allowing your business applications to run solely on analytics.

So where to start? A business needs to define what they’re trying to build, the tools needed to build it, ensuring business and tech departments align, and lastly, the crucial piece to a successful implementation, is change management. Implementing a new technology is only half the battle. Changing the mindset of those using it within your organization, and communicating how it will impact their work, is the crucial element in ensuring its success.

Prior to implementation it’s important to look at the company culture. Is change management embedded in the culture, and if not, what needs to change? How do you plan on changing it, what messaging approach will you take? Defining the goal and purpose of what the business is doing when implementing data governance and coming up with a communication plan to properly prepare people for the change, along with how they will be supported throughout the change is a step not rush past. If done right, you will have a successful automation of your data governance resulting in the busines being free to use their data to drive business and having the business applications run on analytics vs. being reactive. If not done well, you risk an implementation where the technology is inconsistently used across the business, if used at all.

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