Seeing data governance functions pigeonholed into compliance and data
security responsibilities drives me a little nuts.
First, it misses the key business value proposition of data governance,
which should be on helping people in the organization, customers, and
partners leverage data in decision-making in reliable and compliant ways. I
advise chief data officers and governance leaders to call the function
proactive data governance
and focus on data quality, reliability, timeliness, and data trust. These
are the offensive aspects of the role as they deliver business value, as
opposed to taking a defensive posture and focusing on what regulations and
compliance require.
Second, getting anyone excited about participating in compliance functions
is incredibly challenging. Ask anyone working in risk management or
security! Data governance wants and needs business participation and seeks
to identify data owners to oversee data quality and policies. When leaders
don’t position the data governance role for the business value it delivers,
gaining supporters willing to take on time-consuming responsibilities is
incredibly challenging.
Attention data governance leaders, you can do plenty to advance your role in
the organization and your career, even if your leaders are shortsighted and
don’t grasp the business impacts of your responsibilities.
Trust me; there are people out there who get it. For example, here’s what
Sunil Senan, SVP and business head of data and analytics at
Infosys, says about data governance
responsibilities.
“Today’s data governance leaders are responsible for more than just data
governance and are seen as strategic business leaders,” says Senan.
“Successful leaders focus on transforming data management to data sharing,
moving from data compliance to data trust.”
So, here are three ways data governance leaders can accelerate their
careers.
1. Focus on delivering value, not just compliance
The key first step is a shift in mindset and objectives. Data governance
leaders must find people who deliver revenue, operational efficiencies,
or other business benefits from data, analytics, ML, and AI. Treat
these people like customers, and demonstrate how data governance impacts
their objectives.
“Data governance leaders need a fresh mindset to advance in their careers,”
says Myles Suer, #CIOChat facilitator and strategic marketing director at
Privacera. They need to think like product managers for data – how to
deliver data with substantial business value.”
Suer clarifies what it means for data governance leaders to think like
product managers. “This is about making data appropriate for business
functions, accurate, and solving real business problems,” he says. “It is
also about providing and provisioning data in a non-invasive way to those
with an authorized business purpose. In sum, they need to be able to do data
offense and defense at the same time.”
Senan says it’s important for data governance leaders to focus on the
opportunities and risks of the organization’s AI initiatives. “The surge in
AI adoption will need to be supported by a trusted data foundation, strong
AI governance frameworks, and models that address trust, ethics, privacy,
and compliance perspective,” he says. “Bringing an emerging perspective to
AI and data can rapidly advance your career.”
2. Partner with citizen data scientists
Finding strategic partners seeking business value from data and analytics is
a top-down relationship-building skill every data governance leader must
master. I tell my stories of partnering with the CMO on the data required
for a lead gen program in Chapter 7 of my book,
Digital Trailblazer.
But the success of the approach I describe comes from a complementary
bottom-up approach where I seek citizen data scientists in the marketing
department and provide them with tools, training, and best practices.
Data governance leaders – you have citizen data scientists in your
organization! They are building dashboards in Tableau, Microsoft Power BI,
or another self-service dashboarding tool. Some are data wrangling in
Microsoft Excel and Google Sheets and doing all the manual and messy work
that leads to unmanaged and duplicate data sources.
I seek out these citizen data scientists and partner with them to
establish a citizen
data science center of excellence. To advance your career, show how you can democratize and scale analytics
across the organization and use these efforts to improve data quality.
3. Dejargon by focusing on the why, when, and where
One last career recommendation is to learn how to de jargon the technology
and practices tied to data governance, data management, and dataops. Review
some of my recent posts where I help
explain data meshes, data fabrics, and distributed data clouds
to business executives and another where I
define the machine learning lifecycle.
In Digital Trailblazer, I describe what happens when tech and data leaders can’t explain the
technojargon to business leaders. “If I answered the question [with
technojargon] to the board of directors, I would be shown the virtual
elevator down to the CTO morgue. That is where geeks with ties go when they
can’t explain technical concepts in simple language.”
Want to learn more about advancing your career as a data governance leader?
One of the free tools I offer is a
Career Checklist for Digital Trailblazers, which includes a section for how data leaders can develop their skills
and experiences for more challenging leadership roles.
It’s an incredible time to be a data governance leader, but to advance your
career, you’ll need to align efforts to business value while delivering
compliance as a by-product of strong partnerships and smart collaborations.
