Don’t Worry, it’s not You. The Data Governance Finish Line Has Moved
I’ve been a practitioner, analyst and all-around evangelist of data governance for the majority of my career. And during this time, I’ve never lost faith that executive leaders across all industries would eventually understand the need for data governance — and make it one of their company’s strategic priorities.
And we’ve witnessed some incredible changes in the world that have helped to raise data governance awareness. These include:
- The creation and widespread adoption of the Chief Data Officer role. Finally, a C-level leader who is not only responsible for data governance, but also WANTS to be responsible!
- The passing of data-centric, privacy regulations such as the General Data Protection Regulation (or GDPR) merge previously disconnected business initiatives around regulatory compliance and customer-centricity. These can no longer be considered mutually exclusive, and both require data governance to succeed.
- The ‘too-many-to-count’ data breaches around the world have combined to finally drive home the reality that our customers are asking the live-or-die question about your brand: “should I trust your company with my data?”
- The growth of the scope of data governance. While early efforts may have focused on single initiatives like regulatory compliance or business intelligence, increasingly the remit for a data governance function likely spans analytics, compliance, customer-centricity and other strategic initiatives.
- The growing maturity and adoption of enabling technology and services markets supporting data governance strategies, programs and roles
How exciting! Why aren’t you excited?? Is it because so many of you still feel like we’re not making any progress on data governance as a discipline despite these advances?
I’ve got some data to back up those feelings. In early 2013, I launched an open data governance best practices website called GovernYourData.com. As part of that site I included a free Data Governance Maturity Assessment tool with benchmarking data to help governance leaders educate and build business cases for their DG programs. Since its launch, GovernYourData has collected over 525 completed maturity assessments across 15+ industries.
While the total Average Maturity (scored between 0 and 5) across all assessments since 2013 is a low 1.61, that’s only part of the story. The real story is the fact that the average maturity scores are getting lower almost every year as the chart below illustrates.
While at first glance that might appear disheartening, I’m actually of the opinion that this data illustrates an amazing accomplishment. Remember, with any data analysis – it’s the data behind the data that tells the real story. (No, I don’t mean the metadata!).
The real story is what data challenges did data governance practitioners face in 2013 vs 2018.
Let’s consider data challenges in 2013 — only 5 years ago:
- Structured data: Most data governance initiatives focused on structured data within on-premises applications and analytic systems
- GRC-driven: For many (not all), regulatory compliance was the key DG driver for many industries, so scope of DG efforts was less holistic
- Small(er) Data: What constituted Big Data at the time was still primarily being managed in the enterprise data warehouse.
Now let’s consider the data challenges in 2018 and beyond:
- Hybrid: Most organizations must grapple with hybrid data management challenges — critical data on-premises, across multi-cloud environments, social data, and other 3rd party data feeds.
- Big Data is Real: Big data moved from being a star in Gartner’s “Hype Cycle for Emerging Technologies” in 2013, to being dropped from it entirely in 2015. At the time, Gartner explained that it was dropped because big data had become prevalent. It was no longer considered an emerging technology. And big data is no longer just for Hadoop. AWS, Azure, and Google Cloud all have major capabilities supporting big data, as well as many NoSQL and other traditional on-premises options. In addition, there’s been an explosion in data management technologies like MapR, Spark, and more.
- IoT = OMG: While still early for some industries, ingesting and analyzing streaming device and mobile data has become the digital lifeblood of others — especially in the manufacturing, utility, energy and logistics verticals. Big data ain’t seen nothing yet once the Internet of Things becomes a reality across all industries.
- AI/ML: While still an emerging IT strategy for some, data governance practitioners must now be part of the team that figures out how to only feed the most trusted, secure data to these machine learning algorithms to ensure artificial intelligence can be used to propel organization’s forward.
- Digital transformation: Like it or not, every company on the planet will need to determine what digital transformation means to them. Whether it’s adapting their business model to remain competitive, creating more relevant, differentiated experiences for their customers, developing new data-centric products and services, modernizing legacy infrastructure to cloud and next-gen analytic platforms — or simply reacting to competitive pressures to innovate to avoid being disrupted and put out of business.
Why am I excited about the future of data governance? Because with this absolute deluge of new, complex data requirements over the past few years, the only way data governance maturity levels haven’t completely fallen off the cliff is because innovation and progress HAS been happening. The data governance community is making a difference. And even though we’re at the epicenter of a generational market disruption in data, you’re still very well positioned to make enterprise data governance a reality within your organization — and be the next intelligent disruptor of your market.