Data Governance as We Enter a New Decade

More and more marketers are beginning to understand not only what data governance is, but also why it’s important. This understanding, and the subsequent implementation of new data governance processes, allows data governance to become an integral part of the day-to-day business operations within an organization. But as marketers opt to operationalize these processes, they’re finding more technology options, more quality measures, and more privacy regulations with which to contend. That may lead some to realize that while data governance decisions are led by the business, they must also be supported by IT.

As new data governance processes are implemented, and new challenges arise, it’s crucial to consider the following:

1. Digital Innovation of Automated Processes – with the increased demand for data governance, many are turning towards the advances offered by leveraging new technologies like artificial intelligence (AI) and machine learning (ML) or the Internet of Things (IoT) – all three are buzzwords you’ve probably encountered at conferences, in industry webinars, or during the sales process as you purchase new products for your tech stack. These technologies are becoming required capabilities worth investment as we look to capitalize on our online presence with the ability to personalize, react to engagement in real-time and operationalize the vast amounts of data being captured.
2. Data Quality Measures of Process Digitization & Auditing Needs – as technologies like AI and ML make their entrance in helping govern data, there is also going to be an increase in effort to maintain data quality. Automated processes are only going to be as good as the inputs they’re being given, so while these agents may accelerate data processing speeds and increase data processing power, they also can be limited in their effectiveness without audits to ensure quality results. Since better data quality overall is one of the main goals of implanting a data governance strategy this manual/human oversight will be key in running effective digitized processes as a part of data governance.
3. Roles & Responsibilities – with radical shifts in the digital landscape, and as more organizations implement good data governance practices, there will be a cultural shift from a campaign-centric approach to a data-centric one. With that change in business function, it’s fair to expect a change in roles and responsibilities as well. Organizations with more mature data governance and data management approaches may begin to make room for Chief Data Officer (CDO) roles, which are becoming more common as companies look to the future of a data-driven world.

Moving beyond an initial implementation of basic data clean up into a more mature and overarching governance policy will push organizations forward and potentially shape their internal dynamic as new technologies are used and the associated auditing requirements increase. With data, technology, and effectiveness being key drivers behind good governance, we will continue to see radical shifts in the digital landscape to help shape what data can do for us as we follow the growth and change in our industry.