Chief Data Officers Are In Trouble, Part III: Striking The Right Organisational Balance
In the first two parts of this series, we explored the growing difficulties facing Chief Data Officers (CDOs) and the structural challenges that have led to their roles being questioned within many organisations. As we saw, this is a nuanced issue where it is not automatically the CDO or the wider business who are at fault. Today, we turn our attention to a crucial consideration: is descoping or even eliminating data leadership a mistake? Our answer may surprise you.
Ryan den Rooijen
Ryan den Rooijen
Descoping Data Leadership
For certain types of organisations, eliminating the CDO role and consolidating data responsibilities under a Chief Product Officer (CPO) can streamline decision-making and tie data initiatives more closely to product development. This structure is particularly effective in companies where data-driven product development is critical to competitive success—think frequent releases. Through integrating data management directly into the product lifecycle with product analytics, organisations can ensure these capabilities are closely aligned with customer needs—accelerating innovation, improving agility, and reducing cost.
Similarly, for organisations with a heavy reliance on physical processes, such as in manufacturing and the wider industrial sector, folding data under a Chief Operating Officer (COO) can remove friction and accelerate the time-to-value for data initiatives. This way, data functions can easily be deployed on-site. The same goes for organisations with mature commercial functions whereby a Chief Commercial Officer (CCO) takes ownership of data capabilities as a means of creating a more dynamic and customer-centric go-to-market structure.
However, all these scenarios only work when the CPO, COO, or CCO has the expertise and bandwidth to manage data as a strategic asset—or is willing to empower their leaders who have these abilities. In companies where product management or operating processes are tightly coupled with data, the removal of a standalone CDO role might make sense. But for many organisations, the reality is different, and the more likely outcome is a merger with the IT function.
The Risk of Folding Data Into IT
Many of the examples we have heard over the past weeks and months involved data functions being folded into IT, often due to cost and governance concerns. Yet, by subsuming data into traditional IT structures, organisations risk throwing out the baby with the bathwater. Data is not just infrastructure, it is an evolving business asset that requires dynamic governance, commercial insights, and strong product management. Unfortunately, most IT organisations—particularly those in large enterprises—were never designed with these needs in mind.
IT’s focus often centres around stability, systems integration, and maintaining enterprise-wide architecture. This approach is crucial for deploying and managing foundational technologies like ERPs, but data-driven organisations require something more. Data products, by their nature, are more dynamic than traditional enterprise software. They continuously evolve, requiring ongoing refinement, experimentation, and rapid iteration. The governance models that work for enterprise portfolio management are ill-suited to the fluid nature of data products, not to mention the business change expertise required for impact.
There is also a lack of commercial focus in many IT organisations. Ask yourself: how often do people talk about ERP-driven margin expansion? IT investments tend to be seen as cost centres. This is a fundamentally different mindset from what is needed to drive successful data initiatives. For data teams, the conversation should usually centre around commercial value—how can data drive revenue growth, increase margins, or improve customer experience? Some forward thinking CIOs and CTOs might champion this mindset, but we have trouble naming any IT organisation where this is the norm. This void can result in under-leveraged data assets, missed opportunities, and stagnation in innovation.
The Trick of Goldilocks Governance
While this is a rapidly developing area, if organisations choose to divest themselves of their CDO or senior data leaders, we see the key to success being how organisations choose to do so. Careful judgment is required, meaning that rather than consolidating everything under IT, a more nuanced approach is needed—whereby functions’ strengths and weaknesses are considered.
Here are trends we have observed in forward-thinking organisations:
Platform engineering and infrastructure components should fall under IT – where they can benefit from security, reliability, and scalability. The caveat is that these teams need to be able to operate with agility, excepted from stringent change approval boards and governance procedures—within reason. After all, these teams need to be seen as an integral part of the wider data function.
Analytics and data science teams belong in operational functions – with a clear line-of-sight to business impact. Teams should sit under a CPO, COO, CCO, or equivalent, ensuring a direct connection between data insights, business operations and importantly, the P&L. These teams should also embed data governance and quality functions as these will indirectly impact margins. Mature organisations might choose to staff product management here to drive scale.
COEs are important, provided there is clarity – as they can act as impact catalysts. However, COEs are only as successful as the organisation's alignment around budgets, communication, and prioritisation. While operating models come in several flavours (hub and spoke, guilds, etc.) the only thing that matters here is process adherence. The whole organisation needs to play by the rules to enable central functions to succeed, lest budgets and opportunities be wasted.
As for AI... – we might need more than a paragraph, perhaps a future blog?
The evolving role of the Chief Data Officer reflects a broader challenge: how to manage data as both a technical asset and a key business driver. For some companies, bringing data capabilities under a different leader, such as a Chief Product Officer, may make sense. But for many others, the real risk is in treating data as just another technology function. Organisations that recognise the need for commercial insight, dynamic governance, and a tailored approach to team structure will be better positioned to unlock the full potential of their data assets.
Stay tuned for next week's instalment, as we reflect on what this means for present and future data leaders—and how their roles are likely to evolve as a result. Click here to subscribe and be notified when this gets published. In the meantime, we look forward to hearing your comments and experiences again!
– Wade & Ryan
Cover image by DALL·E
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