The Budget and the introduction of DSIT’s new bucket framework mark a shift in how government wants to think and talk about research and innovation. With growth now central to the government’s agenda, it is a clear attempt to answer Treasury’s perennial question: what does the public get for its money?
At the centre of this shift sits the idea of R&D “buckets”: a four-part categorisation of public R&D funding into curiosity-driven research, government priorities, innovation support and cross-cutting infrastructure.
The logic behind the buckets is easy to understand. The UK system is complex, with budget lines stretching across a maze of research councils, departments, institutes, academies and government labs. Even seasoned insiders need a cup of coffee before attempting to decipher the charts on one of UKRI’s much-valued budget explainers.
From the Treasury’s perspective, the lack of clarity is a barrier to the value of government investment. DSIT’s response is the bucket model: a clearer way of presenting public investment that moves the conversation away from budget lines and towards outcomes that matter to citizens. If this helps build broader support for R&D across departments and with the public, as CaSE’s latest research suggests is needed, it could be hugely valuable.
The outcomes challenge
One consequence of an outcomes-driven model, however, is that different types of research will find it easier or harder to demonstrate their value. Basic and curiosity-driven research can be difficult to evidence through simple KPIs or narrow ROI measures.
In contrast, some forms of applied R&D lend themselves more easily to straightforward metrics. The Higher Education Innovation Fund (HEIF) is a good example. It can demonstrate a return on investment of £14.80 to £1 in ways that are simple to communicate and easy for officials to interpret. In a system that places a premium on measurable outcomes, this kind of clarity is powerful.
If outcomes become the dominant organising logic, there is a risk that bucket one, which covers curiosity-driven research, could appear on paper to be the least “investable” – especially under a future minister who is less supportive of blue-skies research. The danger is not deliberate neglect, but an unintended shift in perception, whereby discovery research is viewed as separate from, rather than essential to, mission-led or innovation-focused work.
The challenge becomes even clearer when we look at quality-related research funding (QR). Few funding mechanisms are as versatile or as important to the health of the research ecosystem. QR supports discovery research, helps universities leverage private investment, underpins mission- and place-based activity, and fills the gaps left by research council and charity grants. It is the flexible connective tissue that keeps the system functioning.
Trying to code QR neatly into a single bucket, as bucket one, doesn’t reflect reality. It may make the diagrams tidier, but it also risks narrowing Whitehall’s understanding of how QR actually works. Worse, it could make QR more vulnerable at fiscal events if bucket one is cast as the “future problem” bucket, the category that can be trimmed without immediately visible consequences.
The trap of over-simplification
That brings us to a wider point about the buckets themselves. The intention with buckets is to draw a much more explicit line between priorities, investment and impact. This is a reasonable goal. But the risk is that it invites interpretations that are too neat. Most research does not sit cleanly in any one category. The system is interdependent, porous and overlapping. Innovation depends on discovery research. Regional growth depends on long-term capability. And capability only exists if the UK continues to invest in talent, infrastructure and basic research.
Rather than accepting a model that implies hard boundaries, it may be more helpful to embrace, and actively communicate, this interdependence. A Venn diagram might be a more honest reflection than three or four boxes with solid walls.
The aim is not to relabel the buckets, but to strengthen the narrative around how the types of research we fund reinforce each other, rather than competing for space in a zero-sum system. This kind of framing could also help government understand why certain funding streams look costly on paper, but yield value across a wide range of outcomes over time.
One argument is that by identifying curiosity-driven research as a distinct bucket, it will be harder for future governments to cut it without doing so publicly. There is some truth in this. Transparency can raise the political cost of reducing support for basic research. But the counterargument is also important. Once bucket one becomes a visible and discrete line of spend, it could also become more vulnerable during fiscal consolidations. Ministers looking to free up resources for missions or innovation-focused interventions may see it as an easier place to make adjustments, especially if the definition of “impact” narrows over time.
Shovel ready
This is why the narrative around the buckets matters as much as the buckets themselves. If they are understood as three separate spaces competing for limited resources, the system loses coherence. Discovery becomes something distant from growth, rather than the engine that drives it. Missions appear disconnected from the long-term capability required to achieve them. Innovation emerges as a standalone activity rather than as part of a pipeline that begins with public investment in fundamental science.
The bucket framework is not going away. It will shape how government talks about R&D for years to come. This makes the next phase critical: there is an opportunity now to influence how the buckets are interpreted, how they are used in practice and how the narrative around them is constructed.
If treated as rigid boundaries, the buckets risk weakening the case for long-term investment in capability. But if used as a way of telling a more coherent story about the interdependence of discovery, missions and innovation, they could help build stronger cross-government support for R&D. The challenge is to make sure the latter happens.
