A familiar scene plays out in companies across every industry: a data team builds a robust analytics solution, creates beautiful dashboards, and implements sophisticated data models only to find that months later, hardly anyone is using them. Despite technical excellence, these solutions often fail to gain traction, leaving their potential value unrealized. This common struggle highlights data practitioners' difficulty of driving adoption among intended users.
After years of implementing data solutions across dozens of organizations, we've observed a critical pattern: projects with engaged internal advocates consistently outperform those without them, regardless of technical sophistication; this observed pattern has been so consistent that it might as well be a law: successful data projects have data champions. When it comes to data initiatives, technical excellence alone rarely guarantees success. In summary, this singular factor separates successful data initiatives from those that struggle with adoption.
A data champion is an internal advocate who believes in the value of data, understands its business impact, and actively promotes its adoption. Importantly, these individuals are not part of the data team, but operate within business units. Some champions naturally emerge and are easy to spot, while others require proactive identification and engagement strategies. In this article, I'll share why these champions matter and provide a practical playbook that discusses our experience in identifying, engaging, and empowering these crucial internal advocates within your organization.
Research underscores the need for strong data advocacy. A Gartner's 2018 survey research found that 87% of organizations have low business intelligence and analytics maturity. Despite lower technical barriers, adoption remains a struggle. McKinsey predicted that by 2025, broad organizational data literacy and advocacy - what they call "Culture Catalysts" - will be crucial for widespread analytics adoption.
While data leaders often emphasize self-service analytics and data-driven decision-making, achieving this vision in reality is more challenging due to the complexities and nuances involved, requiring more than just tools and technology. However, one factor we've seen across different organizations where we've implemented successful data solutions in their data maturity journey, is identifying these individuals we call "Data Champions," who help bridge the gap between ambitious goals and reality. Technical excellence matters, but human advocacy often determines whether data solutions drive business value. Yet surprisingly, many Data professionals and Analytics leaders focus exclusively on technical excellence while overlooking the human element that often determines success.
The board and the CEO raise the data clarion, and the people on the front lines take up the call. But to really ensure buy-in, someone’s got to lead the charge. That requires people who can bridge both worlds-data analytics/science and on-the-ground operations. And usually, the most effective change agents are not digital natives.
Source : Mckinsey - Culture Catalyst
Not every organization has obvious data champions waiting in the wings. Often, you need to find and nurture these relationships. It's important to note that not everyone with a leadership title or technical savviness makes an effective data champion. However, the most effective champions tend to share common traits:
Having provided context on the traits to look for in a potential data champion and how to identify a potential change agent within an organization as a data leader, you can use this simple summarized checklist and assessment to identify potential champions in your organization:
You can spot these potential data champions within your organization by starting to look for people who say things like:
Once you've identified potential champions, how do you engage them effectively?
Many data initiatives begin with technical capabilities rather than business needs. Reverse this approach:
Schedule deep-dive conversations to get more insight into areas where the data champions would need analytics support (most times they would have already spoken about this as part of their business pain awareness traits from a data limitation perspective). When working with a Storage Company, we discovered the COO lacked visibility into critical aspects of business operations, which gave my team an area to provide quick wins and show value. Similarly, in the context of the data champion mentioned earlier who took the initiative to organize a Looker training for her team, when we started the engagement she had communicated challenges with manually stitching together multiple reports across different data sources. She also mentioned limitations that came with that approach as they relate to the ability to create more granular reporting. Focusing on the pain of your data champion helps strengthen the relationship, and when they begin to see value, they naturally want to drive the adoption of the solution.
Your Champions need evidence to advocate for your initiatives. Create early deliverables that demonstrate value, even if they're simple:
It's important to note that delivering quick and impactful wins may sometimes come at the expense of perfectly built data infrastructure. However, a workable solution that drives business value usually outweighs technical perfection. Sometimes, the "least bad solution" within constraints is the best path forward. While embracing a hacky approach isn't easy, especially knowing it might create technical debt, speed and flexibility often matter more than perfection when driving immediate business value. These early wins provide your champion with tangible evidence to share with executives, building momentum for broader initiatives. Embrace pragmatism over perfection when delivering quick wins.
Respect your champion's time constraints while keeping them informed and engaged:
For senior champions like COOs or Senior Managers, focus on strengthening the connection between data initiatives and their strategic priorities:
Help your champion become more data-literate through informal teaching moments. Explain concepts clearly without condescension, and gradually increase complexity as their understanding grows. A champion who can confidently explain the "why" behind a data initiative becomes exponentially more effective. Create glossaries of concepts or summarized documentation to clarify any technical difficulties.
How do you know if your champion relationship is effective? Look for these indicators:
When these indicators emerge organically, you've moved beyond simply having a supporter, you've developed a true champion who is actively driving data culture within their organization.
Time and again, we’ve seen that the right combination of strong data advocacy and technical excellence transforms organizations. A well-built analytics solution is just a starting point. What truly drives adoption is an internal network of champions who make data part of everyday decision-making.
By systematically identifying, engaging, and empowering these critical advocates, you dramatically increase the likelihood of your data initiatives delivering real business value. More importantly, you help create a data culture that extends beyond any single project.
The next time you plan a data initiative, ask yourself: "Who will champion this work?" The answer to that question may determine your success more than any technical decision you make. Data champions are the key to analytics adoption, so don't just focus on tools, invest in building a network of champions who can drive real impact!
