From insights to decisions: What research institutions need from research intelligence
Web of Science Research Intelligence reflects a shared vision to help institutions connect fragmented evidence, scale trusted insights, assess the societal impact of research, and make more confident decisions.
Research institutions must answer difficult questions: Where should we invest? Which research areas are gaining momentum? Who should be working together? Which funding opportunities align with our strengths? How do we show the value of research beyond academic outputs? And, most importantly, what should we do next?
These questions shaped two recent webinars featuring speakers from the University of Colorado Boulder, The Chinese University of Hong Kong and Murdoch University, alongside Clarivate experts. Across the sessions, institutions described a common set of pressures: the need to diversify funding, strengthen research visibility and reputation, demonstrate societal impact and make trusted, evidence-based decisions with limited resources and disconnected systems.
One theme was clear: institutions do not simply need more data. They need better ways to connect, interpret and act on the evidence they already have. Web of Science Research Intelligence is designed to meet this need, bringing together trusted data, responsible AI and connected workflows to help institutions increase funding, optimize strategy and demonstrate impact.
Research teams need synthesis, not just more data
At many institutions, the evidence needed to answer strategic research questions already exists. The challenge is that it often sits across different systems: publications in one place, funding opportunities in another, internal proposal and award data somewhere else, with faculty profiles, agency priorities, policy signals and peer activity adding further context.
For Lisa Nanstad, Research Intelligence Strategist at the University of Colorado Boulder, this is where research intelligence becomes essential. Research development teams are being asked to help leaders, deans, center directors, researchers and collaborative teams make sense of a larger, more dynamic and more fragmented information environment.
The challenge is no longer access to information, but synthesizing evidence into insight and action. That means moving beyond static dashboards or isolated metrics toward connected workflows that can help answer real institutional questions, such as where the university has the potential to lead.
“Answering those questions requires multiple sources, careful interpretation, and a clear answer to three things: What do we know? Why does it matter? And what should we do next?”
Web of Science Research Intelligence brings this activity together in one workflow, helping users explore topics, find collaborators, align strengths to funding and understand signals of scholarly and societal impact. For research development teams, that means less time assembling information and more time applying human judgment to strategy, foresight, and decision-making.
Research support teams need transparent, repeatable workflows
As research questions become more complex, libraries and research support teams are increasingly being asked to provide deeper analysis. Stakeholders may need insight into publication performance by department, faculty or topic; university rankings; geographic collaboration; and broader indicators of influence, including books, policy documents and other impact measures.
At The Chinese University of Hong Kong Library, these requests are not always simple or fully defined. Ella Fu, Head of Scholarly Communication, emphasized the value of being able to see how the AI assistant in Web of Science Research Intelligence interprets a question before results are generated.
“The AI assistant shows me the filters and other search strategy details as well, so I know exactly how the search is conducted.”
This transparency helps users confirm whether the question was understood correctly and gives experienced analysts a way to compare the assistant’s approach with their own methodology. It also helps reduce the manual effort required to move from analysis to output. Users can review results, verify underlying records, edit charts and add them directly to reports rather than downloading data into spreadsheets and building charts from scratch. For library teams, this means faster, more repeatable analysis that is easier to communicate.
Institutions need to scale insight beyond specialist teams
Many institutions are seeing rising demand for research insight while the teams responsible for delivering it face resource constraints. At Murdoch University, a lean research office supports institutional strategy, research performance and researcher engagement under these conditions. Alasdair Macdonald, Director of Research and Innovation, pointed to three challenges: limited capacity, fragmented data across systems and varying capability across the institution to translate raw data into insight.
Web of Science Research Intelligence helps lower the technical barrier to using research data. Instead of requiring research managers, leaders and academics to navigate multiple dashboards or rely on specialist analytics support, the platform supports a more question-driven way to explore evidence, drill into data and identify insights that can inform strategy.
“It provides broader access and engagement, more ability for self-service research data, and helps people engage with that data and get to what they need very quickly.”
By making insights more accessible, the platform helps broaden research intelligence beyond specialist teams. This can help researchers find relevant funding opportunities more quickly, reduce the need for central teams to produce every report manually and create more informed conversations around shared evidence.
Assessing the societal impact of research responsibly
As funders, governments and communities place greater emphasis on the broader value of research, institutions need credible ways to show how research contributes beyond academia. The webinars included a closer look at the Institute for Scientific Information’s framework for assessing the societal impact of research.
The ISI presentation reinforced an important point: societal impact is complex and cannot be reduced to a single score. Research may influence society through many pathways, and evidence of that influence may appear over different time horizons and through different signals.
To support more responsible assessment, the societal impact framework in Web of Science Research Intelligence organizes impact across multiple societal facets and distinguishes between signals of potential impact and signals of observed impact. Potential signals can help identify pathways where research may contribute to future societal benefit, while observed signals show where research has already been taken up beyond academia, such as through patents, clinical trials, policy documents, news mentions and other real-world evidence.
The next step is moving from insight to action
The customer presentations reflected different institutional contexts, but they pointed to the same broader need. Research institutions need trusted evidence, transparent AI, and connected workflows that help teams move from analysis to action.
Web of Science Research Intelligence supports this shift by helping institutions make better decisions about where to invest, where to collaborate, where to seek funding, and how to demonstrate impact—how to lead research forward in a changing world.
See Web of Science Research Intelligence in action
Watch the webinars to hear directly from customer speakers and see how AI-guided workflows can turn complex research questions into evidence-based insight.
- Watch the webinar featuring the University of Colorado Boulder
- Watch the webinar featuring The Chinese University of Hong Kong and Murdoch University
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