Levers for Change - Exec Summary

Executive Summary

Data Transformation Insights | Data Leaders Executive Lounge | 29th January

This Data Leaders Executive Lounge brought together senior data leaders to explore the real drivers of successful data transformation, moving beyond technology adoption to focus on operating models, leadership, culture, and capability.

The session featured insights from Zoe Kelly, Head of Data & Insights at Serco, and Pedro Cosa, CDAIO at Data Minds, drawing on Pedro’s experience across Channel Four, Warner Bros, and News UK.

A consistent message emerged: data transformation fails not because of tools, but because of unclear ownership, misaligned operating models, and unrealistic expectations of data leadership roles.

Both speakers reinforced that sustainable transformation requires deliberate design of decision rights, strong executive sponsorship, and ongoing engagement with the wider business.

The discussion also explored the evolving and often misunderstood role of the Chief Data Officer, highlighting tensions between centralised and embedded data models, persistent hiring challenges, and the risk of reverting data functions back into IT when business alignment is weak.

Key Learnings & Insights

1. Operating Model Beats Tooling

Investing in modern platforms enables scale, but does not create transformation on its own. Without clear ownership, decision rights, and ways of working, organisations simply recreate old problems on new technology.

“Changing the tooling doesn’t create the transformation - it just enables it.”

2. Clarity of Ownership Is Critical

Ambiguity around who owns what, who decides, and how conflicts are resolved is one of the biggest blockers to progress - especially in hybrid or hub-and-spoke models. These decisions must be designed early, not left to evolve organically.

3. Change Fatigue Is Real - and Predictable

Continuous transformation without pause leads to disengagement. Leaders must plan deliberate pause points, communicate them clearly, and allow teams time to embed new ways of working before introducing further change.

4. Capability Must Precede Use Cases

Building data capability purely in response to immediate use cases creates fragility. Sustainable value comes from investing in foundational capability first, with AI acting as an accelerator rather than a shortcut.

5. The CDO Role Remains Poorly Understood

The session highlighted widespread confusion around what CDOs are accountable for versus what they are empowered to change. Many data leaders are given responsibility without authority, limiting their ability to drive enterprise-level change.

6. Hiring the “Wrong” Data Leaders Is a Systemic Issue

Organisations often seek unicorn roles - leaders who are simultaneously deep technologists, hands-on engineers, strategists, and business partners. This misalignment contributes to failure and, in some cases, the decision to fold data back into CIO functions.

7. Data Is a Team Sport

Successful transformation depends on strong partnerships across CIO, CTO, CFO, HR, and business leadership. Data leaders must be effective storytellers, able to translate data strategy into business value narratives that resonate beyond the data function.

8. Culture Change Is the Hardest - and Most Important - Part

Both speakers reinforced that data transformation is ultimately a human and cultural challenge, not a technical one. Continuous stakeholder engagement, honest conversations, and visible leadership commitment are essential to maintaining momentum.

Practical Next Steps

• Finalise and operationalise a hybrid hub-and-spoke operating model with clear ownership and access rights
• Define and publish decision forums and escalation paths early
• Introduce intentional pauses in transformation roadmaps
• Strengthen cross-functional collaboration and leadership dialogue