I'm one month into my role of Research and Impact summer intern and I'll admit "impact" was a word I'd heard thrown around constantly without quite grasping why it gets so much airtime. So when I sat in on Julie Bayley's session, "Making a Meaningful Difference – A Society and Impact Literate Approach," I expected a fairly dry refresher. Instead, a few reframmings landed hard enough that I thought they were worth sharing, partly because they're a good reminder even for people who live and breathe this stuff and partly because hearing it explained fresh, to someone with zero prior context might surface an angle worth revisiting. Here's what stuck with me.
Impact isn't just "doing good research"
Julie opened with a working definition that's stayed in my head:
Impact = the provable effects (or benefits) of research in the real world.
"Benefits" is in brackets because impact isn't automatically positive as there's a flip side, called "Grimpact" where research causes harm (the MMR (Measles, Mumps and Rubella) vaccine-autism scare, a debunked study that caused a global drop in vaccination rates, was the example used). And "provable" was the bit that landed hardest for me as a newcomer: you can't simply assert impact happened, you have to be able to demonstrate it. The bit I suspect is most useful as a reminder to people closer to this: citations, reputation and being well known within your field don't count as impact on their own - none of that is change outside the university.
You don't need a "unicorn" to have impact
One of my favourite lines from the whole session: "chase meaning, not unicorns."
It's tempting to think impact only counts if it's the big, headline kind like a new law, a multi-million-pound saving or a policy overhaul. But Julie was clear that impact sits on a much wider spectrum than that. Reducing stigma around a health condition counts. Preserving a piece of local heritage counts. Helping one community feel heard counts.
There was a story that really brought this home: in a study on multiple sclerosis (MS), participants said the thing that mattered most to them wasn't symptom relief (which is what the researchers had assumed would matter) - it was simply being believed by doctors. That's not a flashy outcome but it's a real one. Julie's suggested better question isn't "what impact could this have?" but "why would someone actually use our research?" It's smaller and much more honest.
A simple framework for "is this impact?"
Julie introduced impact as falling into four buckets which I found genuinely useful as a mental checklist:
- Something new: a new policy, service, or product
- Changing something that wasn't working
- Preventing something (common in health research)
- Preserving something: knowledge, heritage, even someone's wellbeing
And there's a useful three-part typology for kinds of impact, borrowed from the Economic and Social Research Council (ESRC), one of the UK's major research funding bodies:
- Instrumental: a direct, measurable change (a new policy, an updated service)
- Capacity building: improved skills, confidence, or knowledge
- Conceptual change: a shift in how something is understood or talked about, which is harder to measure but just as valid
It was reassuring to hear that "harder to measure" doesn't mean "doesn't count." A campaign that shifts public attitudes toward a health condition, even without a clear before-and-after statistic, is still doing something real.
Impact is a team sport
This was the section that felt most relevant to me as someone brand new to a research-adjacent environment. Julie pointed out that funders and frameworks like REF tend to individualise impact, naming a few "key" researchers, when in reality almost no impact happens through one person's work alone. She used a Ted Lasso reference to make the point.
Impact relies on a whole ecosystem: people inside your organisation (including comms teams, librarians, technicians and more) and people outside it (the communities who benefit, the people who can actually implement change, the people who can confirm the change actually happened, since researchers often don't see the outcome themselves). That last point genuinely surprised me that a researcher might need a teacher or a nurse to confirm their work made a difference because they'd never see it firsthand otherwise.
Evidence: not everything needs a smoking gun
The last part of the session covered how you actually prove impact and it was more nuanced than expected. There's a rough hierarchy:
- Hard proof: a direct, undeniable link (your research is cited in a new policy)
- Combined soft proof: stitching together a proof of connection (your research led to X) and a proof of effect (X led to a measurable change)
- Proxy measures: indirect indicators used when direct evidence isn't possible (engagement figures or "gatekeeper" testimony from someone like a parent or carer speaking on behalf of someone who can't)
- Logical argument: a last resort, used when the only explanation for an outcome is your research (a kind of "Sherlock Holmes" approach)
What I appreciated here was the honesty: you're not expected to rule out every other explanation just to make a credible case. Sometimes the strongest evidence is simply a practitioner saying "we changed what we did because of this research" and that counts.
My takeaway, one month in
Coming in fresh, "impact" sounded like a slightly vague buzzword attached to research to satisfy funders. An hour with Julie's framing changed that it's a discipline with its own logic and evidence standards.
If any of this resonates, the question Julie suggested swapping in is a good one to keep close: not "what impact could this have?" but "why would someone outside our field actually want to use this?"
Julie has also written a book, Creating Meaningful Impact: The Essential Guide to Developing an Impact Strategy, which expands on everything covered in the session and comes highly recommended for anyone wanting to go deeper. It's available via Google Books and most academic libraries.
For those working in a research environment, it's also worth knowing that formal impact assessment, including the upcoming Research Excellence Framework 2029 cycle, uses a very similar logic. The narrative structure Julie recommended maps directly onto it: "We did research on ____. We connected this research to society by ____. Because of this research, ____ changed, as demonstrated by ____."
At the University of Bath we use a complementary framework called CARE — Context (why did this research matter?), Activities (how was the impact achieved?), Results (what changed, and for whom?), Evidence (how do we know?), which follows the same thread. Four questions, one coherent story.
Whether you are a researcher trying to make sense of where your work lands in the world, or someone who is is still figuring out what “impact” actually means in practice, the takeaway is the same: start with who needs your research and why, and the rest tends to follow. Impact is not something that happens to research but something you have to actively connect, evidence and care about.
This blog post was written by Alina Sachuck, BSc Chemistry student at the University of Bath, and Research and Impact Insights Intern.
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