There is no perfect place for a Chief Data Office to sit. The real work is building the mandate, sponsorship and evidence of value that allow data leadership to make change happen wherever it reports.
Most government data leaders I meet are quietly convinced they have been placed in the wrong box. If only the data office reported somewhere else — to the Chief Operating Officer, say, or out from under Digital — they would finally have the clout to make change happen. So the question they bring me, more than almost any other, is where the Chief Data Office should really sit. My answer tends to disappoint them: the box is rarely what is holding them back.
The instinct behind the question is understandable: look across government, find whoever has got the structure right, and copy them. But it is the wrong question. There is no single model that works everywhere. The best reporting line depends on the department, its data maturity, its current pain points and the kind of change the CDO is being asked to lead.
In my own research, the government picture splits roughly three ways. Around a third of data offices sit within Digital, as part of the technology function. Another third sit under the Chief Analyst or Chief Scientist, alongside the analytical professions. The rest report somewhere else again, often directly to the Chief Operating Officer.
It is not an unreasonable question to ask. The CDO role is still relatively new in government and has not yet settled into the executive architecture in the way finance, HR or digital roles have. In many departments it sits at deputy director level, expected to drive organisation-wide transformation without always having the formal authority, budget or access to do so. That tension is not unique to government. In the private sector too, the role has evolved through different phases as organisations have worked out whether data is primarily a technology issue, an analytics issue, a governance issue or a business transformation issue.
So when I’m asked the question, my honest answer is: it depends. Each reporting line gives you something and takes something away. The right question is less “where should the CDO sit?” and more “what mandate does the CDO need at this point in the department’s maturity?”
Put the data office inside Digital and it can get close to the technology: platforms, systems, architecture, standards, the plumbing. That can be powerful. Data platforms and tooling are more likely to be treated as part of the wider digital estate, designed properly from the outset rather than bolted on afterwards. The data engineers and architects often feel more at home there too. But data can also become the poorer cousin to digital delivery. Worse, the rest of the business can start to see data as someone else’s problem, rather than something they own, steward and use every day. I know one department that celebrated moving out from under Digital because it gave data more space to breathe, and another that celebrated moving in because it meant the technology it needed could finally move faster. Both were right in their own context.
Put the data office under the Chief Analyst or Chief Scientist and you may gain a committed senior sponsor who already understands the value of good data. Analysts are often among the biggest and most vocal clients of the data office, so the relationship can be productive and energising. But there is a risk here too. Data can become framed too narrowly as something that exists for analysis, evidence and reporting, rather than as an operational asset that shapes services, decisions and delivery. I have seen an organisation deliberately move its data team out from under the analytical function for exactly this reason: the problem it needed to solve was no longer just better analysis, but better data ownership across the whole department.
Put the data office under the Chief Operating Officer and it can connect more directly to transformation, performance and the running of the organisation. That can be particularly helpful where the COO understands that data change is cultural and operational, not just technical. It can bring data ownership closer to the parts of the organisation that create and rely on the data every day. But it can also mean data is not recognised as a profession in its own right, or that longer-term capability building loses out to immediate operational pressures.
Lately a new question has been layered on top: what happens to the data office when AI arrives? Some departments are standing up a separate Chief AI Officer. Others are folding AI into the CDO’s remit, or simply into their title. Which of those helps, again, depends on maturity. Where data still needs sustained investment and senior attention, hitching it to the AI agenda can create urgency and sponsorship that were hard to find before.
But it is worth being clear-eyed about what AI does and does not change. Data is the fuel that AI runs on, and no amount of AI ambition removes the need for someone to own the quality, governance and strategy of that data; if anything, it raises the stakes. AI itself is not mainly a technology problem either. The real transformation comes from changing processes, incentives, ownership and organisational habits, and that is a different job again from stewarding the department’s data. Neither of those jobs is solved by a new title. Whether they sit with one leader or two, they still have to be done, and done well.
So my advice to existing CDOs is this: do not spend too long waiting for the perfect box on the organisation chart. It probably does not exist. Wherever you sit, the work is to build mandate and sponsorship deliberately. Educate senior leaders on what data leadership is for. Demonstrate value in terms they care about. Make the connection between better data and the outcomes the department is already trying to deliver. Build alliances across Digital, Analysis, Operations, Finance, Policy and the frontline. The reporting line matters, but it will never do the whole job for you.