It’s an unfortunate truth of data governance: As passionate as you may be about democratizing access to clean, trustworthy data, not everyone in your organization will share the same enthusiasm.
Many companies embark on data governance initiatives only to encounter administrative roadblocks, insufficient funding, and a general reluctance to adopt a new system. For a data champion, few things are more frustrating than seeing a brilliant plan to centralize enterprise databases tumble to the bottom of a manager’s priority list.
This was the situation Rebecca Royster found herself in as the Data Enablement Lead at UCB. The Belgium-based pharmaceutical company invested in the Collibra platform in 2019 before expanding its data governance initiative to its U.S. office in Atlanta. But despite the program’s potential to streamline analytics and improve quality control, it simply wasn’t gaining traction.
“The biggest feedback we received was that the teams rolled out a wonderful product, and relatively few people were using it,” Rebecca recalls.
To inspire a higher adoption rate, UCB enlisted the help of data consulting firm First San Francisco Partners (FSFP). As specialists in using data to unlock competitive advantages, FSFP recommended a five-step process to develop an aligned data strategy involving key stakeholders in all departments and at all levels of the organization.
“These [five] core components are required to build a strategy that actually engages people,” explains Principal Consultant Becky Lyons. “We know that data governance can be enabled by Collibra in some really exciting ways, and if we can get people on board with data governance, that’ll help drive adoption.”
Becky and Rebecca shared the strategy and its results at UCB during Collibra’s Data Citizens 2024 conference.
Keep reading to learn the steps for driving effective data governance adoption at organizations of any size.
Start with corporate objectives
Many data governance programs stall because they aren’t adequately resourced. Allocating the time and budget for enterprise-wide adoption can be challenging. It’s important to recognize that data governance will rarely feel like a strategic priority to business leaders — at least, not until they understand how it aligns with other company goals.
“If you’re aligning with corporate objectives, you’re going to get more interest up and down the organization,” Becky says. “You’re also going to be able to work with different mechanisms for obtaining resources to do the work.”
For USB, the data governance initiative aimed to standardize processes in the U.S. regional office under guidance from the company’s global data office in Belgium. Phrased like that, it doesn’t exactly sound inspiring. FSFP’s strategy helps to reframe the messaging.
Step 1: Vision
“The first part of the framework is vision — your big, hairy, audacious goal,” Becky explains. “What are you going after? This is something that needs to be inspirational because, while we’re excited about data governance, very few other people are.”
The key is to move from a logistical reality to an emotional motivation. The most successful visions are rich images of a desired future. At USB, Rebecca saw internal data governance as a benefit to patients needing innovative, high-impact pharmaceutical products.
“Our vision is [to have] better solutions for patients through faster, better data and analytics,” Rebecca says. “We want to bring novel things to our patients to help improve their quality of life.” Anyone in the company can feel aligned with that goal.
Step 2: Purpose
Once the vision is set, the next phase is to establish a business reason for realizing the dream. In other words, why is the company executing this vision? Becky recommends framing the value of the vision in business language that key decision-makers will understand.
“We could talk about things like efficiency, avoiding risk, or increasing revenue,” Becky suggests. In the case of a pharmaceutical company such as USB, improved productivity, consistency and regulatory compliance all fit the bill to catch a business leader’s attention.
Rebecca’s team members interviewed their peers to understand the biggest frustrations related to company data. Some employees mentioned unclear roles and responsibilities, while others mentioned trouble accessing the information they needed to complete analytics.
With this input, the data governance team could confidently share a purpose that directly spoke to these issues. “It’s an easier pitch to talk about governance if you can speak about the pain points and the challenges your teams are experiencing in ways that are meaningful to them,” Rebecca adds.
Step 3: Picture
Next is a picture — a clear articulation of how internal systems will look and function differently with the widespread adoption of a data governance program. Whether you use a Venn diagram or a chart, it’s useful to delineate a before and after.
For instance, before implementing a governance program, datasets may have inaccuracies or confusing layouts. After adopting the program, everyone can trust and understand the data.
“This is a really important piece of the strategy because it’s something that people can get behind,” Becky says. The picture may also describe new operating procedures or include measurable data about the time and money saved through new efficiencies. The goal is to move from why we should do this to how this will work.
Step 4: Plan
With the picture in mind, the next step is to create a timeline with key milestones and a clear articulation of what needs to happen to reach each checkpoint.
In developing a timeline for USB, Rebecca and her team considered potential roadblocks in order to set realistic expectations. She notes, “We don’t have an endless budget. We want to be very clear in our scope and where we’re going to start.”
Most organizations map out a data governance plan that spans several years. Really, the work is never done as long as the enterprise continues to gather new information and increase data quality.
Becky recommends thinking of the initial plan as laying a foundation. “We want it to be sustainable going forward,” she says. A good plan starts with the key activities that most directly respond to the common pain points in the organization.
Step 5: Participation
Finally, the last step is helping everyone understand their roles in curating organized, accessible, trustworthy data.
“By this time, we hope that [your team] is excited because they can see themselves reflected in their problems being solved with the roadmap, and they want to be engaged,” Becky explains.
An operating model can define who makes key decisions, how departments will collaborate, and what escalation paths need to exist. Start by looking at how people are already organized and making decisions around the company data. Then build from those existing workflows.
“I’ve used this [alignment] framework for everything from a very small program all the way to a holistic data strategy that incorporates multiple data management and data governance capabilities for international organizations,” Becky says. “It’s really versatile.”
The more people understand their part in enacting a data governance strategy, the faster program adoption will expand.
How Collibra helps
At Collibra, we’re committed to uniting organizations with data that’s easy to find and understand. Our Professional Services and our partner ecosystem teams are available to help data champions talk about Collibra’s functionality and learn how to develop a sustainable roadmap for enterprise-wide adoption.
At the end of the day, not everyone is going to geek out about data governance. But when business leaders see not only the value of a governance program but also the clear steps to realizing a greater vision, that’s what pulls data initiatives out of the weeds and puts them on the path to success.
***
This article is based on a breakout session at Collibra’s Data Citizens 2024 conference in Orlando, FL. Register now for free on-demand access, request a personalized, one-on-one demo with a Collibra expert, or check out our partner page to learn more.
