As organizations work to get the most value from their data, data transformation – changing how they use it – becomes more than just a goal; it’s essential.
But here’s the problem: when the leader who drives this transformation leaves, many efforts lose steam or fall apart.
Knowing why this happens and how to avoid it is crucial for creating data strategies that last beyond one person – because true change in data transformation isn’t tied to a single leader.
The Leadership Factor in Data Transformation
Data transformations often begin with a strong leader who sets the strategy, encourages teamwork, and leads the change. However, when this leader leaves, organizations often lose momentum, lose direction, and slip back into old habits. This happens because many transformations depend too much on one person instead of being built into the company’s culture and everyday processes. [external link] A 2025 industry overview indicates that approximately 70% of digital transformation initiatives fail to meet their objectives, often due to a lack of cohesive strategy, leadership, and an adaptable organizational culture.
Caroline Carruthers, Chief Executive at Carruthers and Jackson, reflecting on her experience as a Chief Data Officer, points out –
As a Chief Data Officer, I’ve led lots of data transformations. The very first time it happened to me, I was so disappointed that once I left, a lot of the things I had put in place started to fall apart. It wasn’t that the team wasn’t fantastic or that they didn’t have a vision, but without that central leadership, things started unraveling.
Caroline Carruthers, Chief Executive at Carruthers and Jackson
Leadership is key to the success of data-driven initiatives, but for these efforts to last, it takes more than just one person. Sustainable transformation happens when leadership is shared across teams, and when data-driven values are deeply rooted throughout the entire organization.
Lessons from Failed and Successful Transformations
A key lesson from past transformations is that success isn’t just about using new tools or processes; it’s about creating a strong data culture. When data transformations fail after a leadership change, a few common problems often arise:
- Lack of distributed leadership. Too often, organizations depend on one data leader to drive transformation. When that person departs, progress stagnates. Sustainable success requires empowering multiple leaders and champions within the organization.
- Failure to embed data into organizational culture. A successful data transformation should not be an isolated project. Instead, it should be woven into the company’s DNA, ensuring that data-driven decision-making becomes second nature to all employees.
- Insufficient documentation and knowledge sharing. Critical insights, strategies, and best practices must be recorded and accessible to ensure continuity. Data-driven organizations prioritize documentation and institutional knowledge transfer.
- Overreliance on individual visionaries. While having a passionate data leader is beneficial, transformation should not be tied to a single person’s vision. Instead, organizations must foster a shared vision that extends beyond any one individual.
How to Build a Resilient Data Culture
To achieve lasting success in data transformation, organizations need to move away from relying solely on one leader and instead build a strong, team-based approach. Think of it like a sports team where everyone plays a role, working together toward a common goal. Here’s how organizations can make that shift to ensure long-term growth and success:
1. Build a team of leaders.
Data leadership shouldn’t depend on just one person. Organizations need to create a team of leaders at all levels. This way, knowledge, excitement, and strategic ideas are shared by more people. Training programs and leadership development help make this happen.
2. Encourage learning from mistakes.
Successful data-driven companies are always learning and adapting. Teams should feel safe to try new things, make mistakes, and learn from them. As Caroline says, “If you aren’t failing, you aren’t trying hard enough. Failing is part of learning and improving.” Companies should see failures as chances to grow and use those lessons to get better next time.
3. Focus on results, not just tasks.
A big mistake in data transformation is focusing only on tasks, without thinking about the bigger impact. Organizations should set clear goals and ask ”What does success look like? Is it about increasing sales, improving customer experience, or making processes more efficient?” These results matter more than just the tools or tasks.
4. Work together across teams.
Data transformation isn’t a one-person job. It requires everyone – IT teams, business units, analytics teams, and leaders – to work together. Different groups need to collaborate and make sure data initiatives align with the company’s big-picture goals. This teamwork ensures that data strategies bring real value.
5. Keep the knowledge flowing.
Organizations need to keep track of the best practices, lessons learned, and insights from data projects. Creating a shared space for everyone to access this information helps avoid losing key knowledge, especially when leaders change.
The Role of Passion in Data Leadership
Successful data leaders aren’t just experts in technology; they also believe in the power of data to make a real difference. Their passion inspires others in the organization to trust and use data for making better decisions. Caroline stresses how important this passion is in driving change –
The core fundamental thing for every data professional is to genuinely believe in the difference that we can make and the power of what we have at our fingertips.
Caroline Carruthers, Chief Executive at Carruthers and Jackson
Passion is important, but it’s not enough on its own. Leaders need to communicate clearly, tell stories, and show how data can actually improve things. When companies share the success stories of their data projects, they build excitement and energy that lasts, even after the original leader moves on.
Creating a Future-Proof Data Strategy
Sustainable data transformation is more than just completing one-off projects – it’s about creating a journey of improvement. It’s like building a house that grows with your needs, constantly evolving to stay adaptable. For businesses to stay ahead in the future, they need to approach data transformation as an ongoing process. Here are some key steps organizations can take to future-proof their data initiatives:
- Build adaptable data architectures that can scale with business needs.
- Establish governance frameworks to maintain data quality and compliance.
- Invest in automation and AI to drive efficiency and innovation.
- Measure progress using clear KPIs to ensure continuous improvement.
- By embedding these principles into their strategy, organizations can ensure that their data transformations persist, evolve, and continue delivering value – regardless of leadership changes.
Final Thoughts
Data is a powerful asset, but unlocking its full potential requires more than leadership – it requires a sustainable approach. Organizations that build a strong data culture, empower leaders at all levels and embed data-driven thinking throughout will thrive.
The key to long-term success is not just having a visionary leader, but ensuring leadership and strategy are integrated across the organization. This protects data initiatives from leadership changes and ensures lasting impact.
To dive deeper into the challenges organizations face during data transformations, don’t miss our interview with Caroline, where she explains why these initiatives often unravel when leadership transitions occur. Caroline will expand on this crucial topic at the Data Innovation Summit 2025, sharing strategies to build resilient, long-term data-driven cultures. Her presentation, happening this May, will offer insights into how organizations can safeguard their data transformations and ensure lasting success, no matter who’s at the helm.
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