The Scenario
In our 50-interview whitepaper, 50% of institutions told us they run IR with one to three people. Several described being an "office of one," handling everything from federal IPEDS reporting to ad-hoc executive requests. During peak season (September, January, May), small teams hit an average utilization of 47.6% and a maximum of 90%.
This is a scenario walkthrough for the IR director in that position. They are the only analyst at a 4,500-student masters university. The IPEDS Fall collection is locking next week, and a dean just emailed asking for first-generation retention by cohort. Pre-Clema, those two tasks could not happen in parallel. With Clema, they can.
The Setup
- Clema is connected to the warehouse (Snowflake) and the SIS (Banner), with the [IPEDS AI agent](/ipeds) live.
- Data governance is in place: role-based access, a signed BAA, and the IR director is the named admin.
- The IR director runs the [14-day free trial](/get-started) on a sample source first to confirm Clema speaks the institution's definitions.
How Clema fits the peak-season day
IPEDS pull, in plain English
The IR director opens Chat and asks: "What is our fall-to-fall retention rate for first-time, full-time students in the latest IPEDS year, with the GRS definition applied?" Clema returns the cohort size, the re-enrolled share, the IPEDS component, the collection year, and the source link. That figure feeds the IPEDS Fall collection directly.
The dean ask, drafted while the IPEDS pull runs
In parallel, the dean's request ("first-generation retention by cohort") comes in through Data Requests. Clema's agentic intake clarifies which cohort and which definition, drafts a sourced response from the warehouse, and queues it for the IR director to review and ship. The IR director is not the bottleneck between the dean's question and the answer.
Both answers ship with the source
The IPEDS figure carries the NCES source. The dean's answer carries the warehouse table, the cohort definition, and the calculation method. Both are defensible to an accreditor or to the cabinet without a second pull.
The audit trail lives on
Every query is logged with source, calculation, and user. When the next peak season arrives, the IR director can pull the same figures from the audit trail instead of reconstructing them.
What This Scenario Shows
The structural finding from the whitepaper was that small IR teams hit 90% peak-season utilization because they cannot parallelize retrieval work. Clema does not add capacity by cloning the analyst; it makes the analyst's time stop being the bottleneck between question and sourced answer. The IPEDS pull and the dean ask happen in parallel because the analyst reviews and ships instead of pulling and assembling.
For the office of one, the math is direct: the 220 to 330 hours small teams can reclaim annually (per the whitepaper) maps to roughly 28 to 41 days of capacity that move from repeat question answering to IPEDS, accreditation, and strategic analysis. That is the peak-season headroom the office of one does not have today. See how Clema works for the full path from question to sourced answer.
Run this scenario on your data
Book a demo with the office-of-one scenario built for your institution, or start a 14-day free trial on a sample source.
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