You Can't Cherry-Pick Governance Adoption Around Your Enterprise Data.
Creating a trusted, business-ready data environment needed for today's competing data demand requires a holistic mindset around the governance of our enterprise data. One of the biggest mistakes many organizations are making today is trying to execute governance with shortcuts to address their most pressing data demands in a microwave way.
Many simply ignore the foundational pillars needed for their governance adoption to be successful at the expense of 'quick and dirty delivery.
It's true that most drivers for data governance adoption in many organizations are led by critical data demands and mandates that require an organization to resolve its data maladies within a short period to avoid hefty penalties. i.e, Your organization might be under heavy regulatory scrutiny and audit reviews that demand getting your data in order and fulfilling current gaps in your data to avoid reputational risk or financial penalties.
You might have a case where you've been issued an MRA or MRIA around your regulatory report, and you need to move swiftly to respond to your regulatory bodies.
While remediation of your MRAs and MRIAs is non-negotiable, it is critical to build and deploy holistic data governance and quality capabilities to mitigate other risks around your enterprise data. You cannot afford to simply use that as an excuse to cherry-pick your governance execution.
Ignoring the foundational pillars around your data governance execution is a setup for failure, and this would end up costing you more than you bargain for.
What is a holistic approach to governance?
A holistic approach is a data governance strategy with an enterprise-wide mindset. With this mindset around your data asset, you position yourself with an opportunity to review your competing data demands side by side and apply an effective prioritization framework to govern your most critical data in a strategic way with urgency and an agile manner that paves way for you to expand out and build on your quick-wins.
A holistic approach to governance allows you to be agile with your governance execution without compromising the needful fundamentals for your adoption success.
It allows you to build enterprise value-add delivery for your enterprise as a whole.
It's foundational to a sustainable data culture around your enterprise data value chain.
It allows you to prioritize your regulatory requirements and business imperative.
It allows you to address your urgent MRAs and data gaps tactically while Enterprise Data Governance capabilities are being established at the same time.
What Does A Cherry-Picked Governance Environment Look Like?
Here’s what a typical cherry-picked governance environment might look like:
You’ve kicked off data governance activities around pockets of your data without a holistic plan around other enterprise data.
There’s no formalized operating model of execution to drive accountability around your governance execution.
You have data roles that are not adequately trained and equipped around their roles and expectations.
Your governance execution lacks internal allies and business SMEs to champion its success.
Cross collaboration and standardization are lacking in your execution, and your governance progress is hard to measure.
You have a Data Governance Council without a mandate of operations and oversight.
You’re checking off your pressing data demands with unsustainable temporal solutions
You’re driving your governance execution without a proper framework.
You’re driving data governance from a technology lens.
---and more
How Do You Avoid Cherry-Picking Your Data Governance Adoption?
The following are critical and essential fundamentals for building holistic governance in a highly regulated environment.
· Define data governance policy and Standard as part of your key fundamentals
· Define your governance operating model and establish accountability around your enterprise data asset
· Prioritize and address your pressing data needs as your MPV data to govern. i.e., MRA/MRIA Control Gaps
· Deploy key policies, procedures, and controls to govern your enterprise data, not a subset.
· Clearly define and accelerate the adoption of your operating model and accountabilities
· Establish and formalize an effective Governance Council and Executive Oversight
· Define and implement domain taxonomies with proper accountabilities
· Deploy enterprise data quality monitoring DQ issue management
· Activate change management around your governance execution
In a nutshell, to win and keep winning with your data governance adoption, you must be intentional about your execution strategy and your end in mind. You cannot cherry-pick your governance execution by ignoring your foundational pillars for success.
It will be a disservice to your governance's success and overall data maturity goals.
Need some help developing a practical playbook for your data governance execution? Book a Free Call with me to discuss your current challenges, and we can explore simple strategies to actualize your governance success.