Academic Analytics is a subscription data platform, not a place for a faculty member to log their own CV. Universities license it at the institution level so that a provost’s office, a dean, or a department chair can see how their faculty’s scholarly output compares to peer programs nationally — built almost entirely from data collected about faculty from outside sources (publishers, funding databases, patent offices), rather than data faculty type in themselves. That distinction — externally sourced benchmarking data versus a self-service system a researcher maintains — is the single most important thing to understand before evaluating it, comparing it to a vendor like Watermark’s faculty suite, or deciding how (or whether) to use it in a personnel process.
What Academic Analytics is
Academic Analytics was founded in 2005 to give university leaders a way to benchmark scholarly productivity across institutions rather than relying on department-by-department self-reporting. Its original product, the Faculty Scholarly Productivity Index (FSPI), was built on methodology developed by Lawrence B. Martin and Anthony Olejniczak at Stony Brook University, drawing on research into faculty productivity measurement Martin had pursued since the mid-1990s. The core idea has stayed constant even as the product line has grown: instead of asking faculty to self-report, Academic Analytics assembles a dataset from sources external to the institution and turns it into comparable, discipline-specific benchmarks.
Concretely, per the methodology described by university offices that license the platform (institutional research and provost’s offices publish their own explainer pages for faculty, since access is normally restricted to administrators), the core productivity metrics draw on:
- Journal articles with a registered DOI, matched against citation counts sourced from Crossref
- External research funding and federal grant awards
- Books and book chapters
- Patents
- Clinical trials
- Honors and awards
Each metric runs on its own rolling window rather than a faculty member’s whole career — for example, grants and citations are typically counted over roughly a five-year window, articles over roughly four years, and books and patents over roughly ten years, per the methodology description published by the University at Buffalo’s Office of Institutional Analysis. The same source is explicit that the core productivity metrics exclude book citations, exhibited creative/art work, instructional teaching load, and service — none of that enters the benchmarking calculation, even though it may matter enormously to an individual faculty member’s actual job.
Because the underlying data comes from publishers, Crossref, and funding agencies rather than from faculty themselves, coverage has real edges: an article can be missing from a faculty member’s profile if a journal never registered it with Crossref, and disciplines that publish more in books, conference proceedings, or non-DOI’d venues are represented less completely than disciplines that publish primarily in DOI-indexed journals. University methodology pages that describe the tool to their own faculty routinely flag this as a known limitation, not a secret one.
The product suite today
Academic Analytics has expanded well beyond the original FSPI benchmark into a named suite of modules, each aimed at a different institutional buyer:
- Research Insight — department- and program-level benchmarking against peer institutions, plus faculty-level profiles of publications, citations, grants, and awards, used to support strategic planning and resource allocation.
- Faculty Insight (Faculty Insight Suite) — the part of the product line that overlaps most with a conventional faculty activity reporting (FAR) tool. It layers institution-owned data — teaching, service, mentoring, and other information pulled from a university’s own systems — on top of the externally sourced scholarly record, and is positioned for annual reporting, promotion and tenure dossiers, and accreditation evidence.
- Medical Insight — the same benchmarking approach adapted for medical school departments and clinical faculty.
- Alumni Insight — tracks career outcomes of graduate program alumni, used for program review and accreditation.
- Strategic Insight Suite / Industry Insight — higher-level portfolio views for research-strategy and industry-alignment planning.
- External Discovery Site (EDS) — a public-facing faculty-expertise directory built from the same underlying data, distinct from an ORCID record or institutional profile page.
The existence of Faculty Insight matters for how this platform should be described: Academic Analytics is no longer purely an externally sourced benchmarking tool — it has grown a self-entry layer that competes more directly with FAR-only vendors. But its market identity, and the reason institutions typically bring it in alongside (not instead of) a FAR system, is still the externally sourced comparative dataset that a faculty-entered system has no way to produce on its own: nobody can self-report how their department’s output compares to the same discipline at 400-plus other research universities.
How it differs from a faculty-facing activity-reporting system or CRIS
It’s easy to lump Academic Analytics in with a research information management (RIM) platform or a faculty activity reporting tool because all three eventually feed similar downstream documents — a dossier, an accreditation report, a CV. The underlying model is different enough that conflating them causes real confusion in procurement conversations and in press coverage of the tool. A rough comparison:
| Dimension | Academic Analytics (core benchmarking data) | A faculty-facing FAR system (e.g. Watermark’s faculty suite) or a CRIS |
|---|---|---|
| Where the data comes from | External, publicly available sources (publishers, Crossref, funders, patent offices) | Faculty enter or import their own record; a CRIS may also pull from institutional HR/finance systems |
| Who is the primary user | Provosts, deans, department chairs, institutional research staff | The individual faculty member, plus department/college reviewers |
| Primary purpose | Comparative benchmarking against peer programs and disciplines nationally | System of record for one person’s or institution’s own activity, reporting, and compliance |
| Typical output | Department/program dashboards, peer-comparison reports | Annual activity reports, promotion and tenure dossiers, CVs, accreditation packets |
| Faculty visibility into their own data | Historically limited — a recurring point of institutional debate, discussed below | Full — the faculty member is the one entering and correcting it |
This is also a useful distinction to keep separate from effort reporting, which is a federal cost-compliance requirement under 2 CFR 200.430 documenting how much of a person’s paid effort a sponsored project consumed. Effort reporting, faculty activity reporting, and Academic Analytics-style benchmarking all touch “what did this person do,” but they answer different questions, for different audiences, under different rules.
Typical use cases
Based on how partner institutions describe their own use of the platform, Academic Analytics is typically deployed for:
- Departmental and institutional benchmarking — comparing a program’s scholarly output to equivalent programs in the same discipline at peer or aspirational institutions.
- Program review and accreditation evidence — supplying quantitative context for periodic academic program reviews and specialized accreditation self-studies.
- Ph.D. program and graduate-alumni evaluation — using Alumni Insight to track where graduates land and how programs compare on that outcome.
- Faculty hiring and honors/awards strategy — identifying scholars active in a given subfield, or faculty whose profile matches the eligibility criteria for a specific award or honorary society nomination.
- Funding-opportunity discovery — surfacing grant programs that match a faculty member’s existing funding and publication history.
- Strategic planning and resource allocation — giving a provost’s or dean’s office a portfolio-level view of where an institution’s research strengths and gaps sit relative to peers.
Access is generally restricted to a defined group of administrators (provost, deans, associate deans, department chairs, institutional research staff) who complete a credentialing process with the university before using the platform — it is not typically an open, self-service dashboard for every faculty member, unlike a CRIS profile or an ORCID record.
The tenure-and-promotion debate
Because Academic Analytics’ core benchmarking data was never entered or verified by the faculty it describes, its use in decisions that affect an individual person’s career has been genuinely contested — this is not a settled question, and CASRAI takes no position on it beyond describing the debate accurately.
The American Association of University Professors addressed this directly in its Statement on “Academic Analytics” and Research Metrics, approved by the AAUP Council’s Executive Committee on March 22, 2016. The statement urges institutions to exercise “extreme caution” in subscribing to external productivity-metrics services and recommends refraining from using such data in tenure, promotion, compensation, or hiring decisions; where the data is used at all, the AAUP’s position is that it must remain subordinate to peer review, and that individual faculty members must have access to — and the ability to correct — any data used to evaluate them.
That caution was not abstract: in May 2016, Rutgers Graduate School faculty voted 114-2 to oppose the use of Academic Analytics data in resource-allocation and personnel decisions, and demanded access to their own individual data profiles. In response, Academic Analytics itself has stated its data is meant to supplement, not replace, traditional peer evaluation, and that it does not believe institutions should use its information to make individual personnel decisions on its own. Similar debates about vendor coverage gaps, discipline bias (book-heavy fields versus article-heavy fields), and faculty access to their own profiles have recurred at other universities since.
The practical takeaway for a research-administration audience: Academic Analytics data can be a defensible input to a program-level or departmental benchmarking exercise, where the unit of analysis is large enough to average out individual coverage gaps. Using the same data as a primary input to an individual tenure, promotion, or compensation decision is the part that has drawn sustained objection from faculty governance bodies — and, per its own public statements, from the vendor as well.
“Academic Analytics” vs. the “AAR” — a naming collision worth clearing up
Searches that pair “Academic Analytics” with “AAR” are usually running into two unrelated things that happen to share initials. “AAR” in higher-education faculty affairs commonly stands for Annual Activity Report — the yearly self-reported summary of teaching, research, and service that many universities require of faculty regardless of which vendor’s software they use (North Carolina State University, for example, runs its faculty evaluation process around a page titled simply “Annual Activity Reports (AAR)”). That document is a typical output of a faculty-facing FAR system such as Watermark’s faculty suite, where the faculty member enters the underlying data themselves.
Academic Analytics the company does not use “AAR” as a name for itself or for its own product line — its modules are named Research Insight, Faculty Insight, Medical Insight, Alumni Insight, and so on. If what you’re actually looking for is guidance on producing an annual activity report, that’s a faculty-facing FAR workflow question, not an Academic Analytics benchmarking question — the two are adjacent parts of the same faculty-affairs technology stack, not the same tool.
Where this fits in the broader CRIS/RIM landscape
Faculty activity reporting and research-analytics platforms like Academic Analytics sit alongside, and increasingly need to exchange data with, the persistent-identifier and research information management infrastructure covered elsewhere on this site. A full CRIS such as Pure, Symplectic Elements, or DSpace-CRIS — see CASRAI’s own CRIS vendor comparison — is typically the system that already holds an institution’s publication, grant, and person records, tied together with persistent identifiers such as ORCID iDs. Where a CRIS aims to be the institution’s authoritative, interoperable system of record, Academic Analytics is deliberately narrower: a benchmarking layer that compares an institution’s output to its peers, whether or not that institution also runs a CRIS underneath.
The debate over whether quantitative productivity counts — citation counts, journal impact factor, grant dollars — should drive individual assessment at all is also the subject of a broader, organized reform movement in research assessment: the San Francisco Declaration on Research Assessment (DORA) and the Coalition for Advancing Research Assessment (CoARA) both argue for reducing reliance on journal-level and count-based metrics in favor of qualitative, narrative-based evaluation. See CASRAI’s comparison of DORA and CoARA commitments for how that movement intersects with tools like this one.
Frequently asked questions
Is Academic Analytics the same thing as a CRIS?
No. A CRIS (current research information system) is generally the institution’s own system of record for research information, often interoperable via standards such as CERIF. Academic Analytics is a third-party benchmarking dataset an institution subscribes to; some universities run both, feeding CRIS-held data into their own comparisons or vice versa.
Do faculty enter their own data into Academic Analytics?
Not for its core productivity metrics, which are built from externally sourced, publicly available records (DOI’d publications, Crossref citation counts, external funding, patents, and similar). Its newer Faculty Insight module does incorporate institution-owned data pulled from a university’s own systems, narrowing but not eliminating that distinction.
Can Academic Analytics data be used in tenure and promotion decisions?
This is contested. The AAUP’s 2016 statement recommends against using it as a primary basis for tenure, promotion, compensation, or hiring decisions, and Academic Analytics has itself stated the data is meant to supplement, not replace, peer review. Institutional practice varies, and this is an area where a research-administration office should expect faculty governance scrutiny.
What does “AAR” mean when people search for Academic Analytics?
Usually “Annual Activity Report” — a standard faculty-affairs document distinct from Academic Analytics the company, most often produced through a faculty-facing FAR system like Watermark’s faculty suite rather than through Academic Analytics itself.
How is Academic Analytics different from Watermark’s faculty suite?
Watermark’s faculty suite (formerly Digital Measures/Activity Insight) is a faculty-entered activity-reporting system built to generate annual activity reports, dossiers, and CVs from data the faculty member submits. Academic Analytics’ core product is an externally sourced, provost/dean-facing benchmarking dataset used to compare an institution’s output to its peers — though its Faculty Insight module now competes more directly in the activity-reporting space as well.
