Why data projects stall—and how to build resilient data teams

I've been reflecting on this in several client projects over the years. Why do data initiatives stall despite having skilled individuals? Why does progress slow even with top experts on board? The answer often points to team dynamics and how knowledge is built and shared.

The risks of relying on one data expert in your team

In many projects, progress depends on a single "data wizard"—a go-to person who holds the deepest expertise. This person is expected to solve complex issues and understand all systems. While such individuals can be brilliant, relying solely on them creates a bottleneck. Others are sidelined, documentation fades, and key knowledge stays stuck in one person’s head. And what happens if that person leaves, gets sick, or burns out? The risk is real, especially in organizations still early in building their data capabilities. Google's Project Aristotle research found that psychological safety—a team's culture of trust and openness—is the most significant factor in team effectiveness, surpassing individual expertise.

Why data team success depends on shared learning, not just tools

Development shouldn't rest on individual shoulders. It must be built into teams that dare to ask questions, share unfinished ideas, and learn collectively.

According to McKinsey, by 2025, organizations that embed learning into their operations will outperform those that don't. Similarly, the World Economic Forum's Reskilling Revolution emphasizes adaptability and continuous learning as key to future success.

Coursera's 2024 Global Skills Report echoes this: adaptability and application of knowledge matter more than certifications alone.

How consultants can help build internal data capability

Our role as consultants extends beyond delivering technical solutions. Our goal is to empower clients to build teams that can thrive independently. This involves:

• Integrating various technologies and methods tailored to the client’s needs, rather than pushing a one-size-fits-all tool.
• Strengthening internal practices: documentation, testing, version control, and knowledge sharing.
• Encouraging proactive thinking: “What happens if our key person isn’t here tomorrow?”

We aim to be long-term partners, not short-term executors—focused on helping teams grow in confidence and independence. This approach fosters trust, continuity, and mutual value.

How to build sustainable, adaptable data teams

Change is constant. New technologies emerge, tools evolve, and demands increase. This can be daunting—but it doesn’t have to be.

When a team is built to share knowledge and learn actively together, changes in technology become opportunities rather than threats. In such environments, there’s no fear of “wasting money on yet another new tool” because the team is equipped to adapt and embrace change collectively.

Shared success is the strongest architecture

Let’s build data teams that don’t rely on individual heroes but on collective capability. Let’s support each other, share knowledge, and grow together. Because the future of data capability isn’t just about tools—it’s about a culture that withstands change.

And when we do this with our clients—not for them—we unlock long-term success that lasts well beyond the next tech trend.