In light of the General Data Protection Regulation (GDPR) taking effect in just three months, an understanding of data governance readiness has become paramount. Organizations need to make sure they’re ready to meet the world’s most comprehensive data privacy law’s requirements:
GDPR becomes effective in an age of rapidly proliferating customer data. For organizations to meet its demands, data governance (DG) must become operational. Done right, it holds great promise not only for regulatory compliance but also for creating data-driven opportunities that drive innovation and greater value.
The 2018 State of Data Governance Report shows that customer trust/satisfaction, decision-making, reputation management, analytics and Big Data are the key drivers of data governance adoption, behind meeting regulatory obligations.
There’s no question data governance is important and should be the cornerstone of data management to both reduce risks and realize larger organizational results, such as increasing customer satisfaction, improving decision-making, enhancing operational efficiency and growing revenue. The question is how to implement DG, so it does all that.
The boom in data-driven business, as well as new regulatory pressures, have thrust DG into a new spotlight. But the historical approach to DG, being housed in IT siloed from the parties who could use it the most, won’t work in the age of digital power brands like Airbnb, Amazon and Uber.
Data governance done right requires the participation of the entire enterprise and should be measured and measurable in the context of the business. Fortunately, Data Governance 2.0 builds on the principle that everyone in the organization has a role in the initiative, which is ongoing.
IT handles the technical mechanics of data management, but data governance is everyone’s business with stakeholders outside IT responsible for aligning DG with strategic organizational goals.
This creates an environment in which data is treated as an organizational asset that must be inventoried and protected as any physical asset, but it also can be understood in context and shared to unleash greater potential.
If you accept that data governance is a must for understanding critical data within a business context, tracking its physical existence and lineage, and maximizing its security, quality and value, are you ready to implement it as an enterprise initiative?
We’ve identified what we believe to be the five pillars of data governance readiness.
Without executive sponsorship, you’ll have difficulty obtaining the funding, resources, support and alignment necessary for successful DG.
DG needs to be integrated into the data stewardship teams and wider culture. It also requires funding.
Most successful organizations have established a formal data management group at the enterprise level. As a foundational component of enterprise data management, DG would reside in such a group.
DG is foundational to enterprise data management. Without the other essential components (e.g., metadata management, enterprise data architecture, data quality management), DG will be struggle.
Successful and sustainable DG initiatives are supported by specialized tools, which are scoped as part of the DG initiative’s technical requirements.
We’re going to explore these pillars of data governance readiness in future blog posts and through a new, free app to help you build – or shore up – your data governance initiative. By applying them, you’ll establish a solid data governance foundation to achieve the desired outcomes, from limiting the risk of data exposures to growing revenue.
In the meantime, you might want to check out our latest white paper that focuses on the impending GDPR and how to increase DG expertise because no organization with even one customer in the EU is outside its grasp. Click here to get the white paper.