January 20, 2026
An overview of the REACH Network
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Summary of our January 20, 2026, webinar with Dr. Baron Wolf, Director of Research Analytics at the University of Kentucky
For the kickoff session of Atom's 2026 webinar series, we hosted Dr. Baron Wolf for a deep dive into the Research Evaluation and Analytics Capacity Hub (REACH). As the leader of this NSF funded initiative, Baron shared a vision for moving research administration away from reactionary data requests toward a proactive and data informed strategy.
The central takeaway is that research analytics is not just about the tools you use; it is about the community you build. In an ecosystem where data is often fragmented and siloed, REACH provides the first global home for the practitioners who turn that data into institutional strategy.
Most research offices operate on a reactionary basis by responding to the loudest requests for resources. Baron reframed this by introducing the Research Analytics Capabilities Framework, which balances technology with human capital.
To build a successful analytics journey, institutions must focus on two pillars:
Human Capital: Leadership commitment, data governance policies, and a culture that values evidence over intuition.
Technology and Skills: Moving beyond spreadsheets to high quality data processes and skilled staffing while meeting practitioners where they are, even if they only have access to Excel.
REACH was established to address the lack of specialized training for data practitioners in research administration. Baron outlined five core activities:
REACH develops open access expertise in research analytics, responsible evaluation, and AI. This ensures that even small institutions can access high level strategic insights without high costs.
This six month peer to peer program pairs emerging analysts with experts.
A major focus is ensuring that data is used ethically. This involves moving away from prestige metrics and using data driven approaches to reduce bias when evaluating faculty or investing in thematic research areas.
During the Q&A, the discussion turned toward the AI hype cycle. Baron and Tomer provided a balanced view of where AI fits into research administration today:
The Case for Skepticism: Baron shared a recent example where AI generated benchmarking data was off by 25 million dollars. He warned that you can always get a number out of a tool but it does not mean it is the correct number.
The Case for Utility: Tomer highlighted that while AI struggles with raw math, it excels at natural language connections.
The Privacy Mandate: For confidential research IP, both speakers urged the use of closed enterprise grade AI environments rather than free public models.
To comply with increasing federal regulations such as export controls or open science mandates, Baron argued that we must flip the script.
Too often, we try to make our data fit the system versus creating the system to capture the data we need. We need to think about data capture from the front end and not as an afterthought.
The REACH Network is more than a grant funded project; it is an invitation to join a global shift toward professionalized research intelligence. Whether you are a librarian, a data scientist, or a senior VP for Research, the path forward involves sharing best practices and building the collective capacity to lead with data.