Introduction
IR leaders asking for budget to invest in conversational AI need a defensible number for what the status quo costs. Our data request workflows whitepaper, based on 50+ interviews with IR and IE professionals across 19 US states, quantified the ad-hoc request burden by team size. This post is the benchmark table pulled out of the research so you can use it in a cabinet memo or a budget case.
The Headline Benchmarks
| Metric | Benchmark | Source |
|---|---|---|
| Capacity consumed by ad hoc requests | 40 to 60% of team capacity | 50+ IR/IE interviews |
| IR teams facing significant workflow challenges | 91% | 50+ interviews, 19 states |
| Clarification cycles per ad hoc request | 2 to 5 cycles | 50+ interviews |
| IR teams operating with 1 to 3 staff | Over 50% | 50+ interviews |
| Hours reclaimable annually with AI-enabled workflows | 220 to 3,200 hours | 50+ interviews |
Benchmarks by Team Size
| Team size | Avg utilization | Peak utilization | Gross ad hoc hours/yr | Primary challenge |
|---|---|---|---|---|
| Small (1 to 3 staff) | 47.6% | 90% | ~550 (69 days) | Resource scarcity; doing everything with minimal capacity |
| Medium (4 to 7 staff) | 40% | 75% | ~1,584 (198 days) | Process transition; formalizing workflows as team grows |
| Large (8+ staff) | 62.9% | 85% | ~5,333 (667 days) | Scale and complexity; managing breadth across the institution |
Hours Reclaimable
Gross hours consumed by ad hoc requests run 550 to 5,333 per year depending on team size (roughly 69, 198, and 667 workdays for small, medium, and large teams respectively), per the same 50+ interview research. That is the full cost of the status quo; the 220 to 3,200 hours annually reclaimable range is the portion of that gross figure an AI-enabled workflow can realistically recover. The low end reflects small teams (1 to 3 staff) with lower absolute request volume but the highest proportional capacity drag; the high end reflects large teams (8+ staff) where the absolute hours consumed by repeat questions compound across more analysts. The mid-range, 800 to 1,500 hours, maps to most medium-sized IR offices.
To put that in budget terms: 1,000 reclaimed hours is roughly half an FTE. At a fully loaded IR analyst cost of $80,000 to $120,000 per year, that is $40,000 to $60,000 of capacity redirected from repeat question answering to strategic analysis. Clema is free to start, with published plans from $99 per month (the Pro plan, $1,188 per year). The math is the budget case.
How to Use These Benchmarks
- Cabinet memo: cite the 40 to 60% capacity figure and your team size to put a number on the ad-hoc request burden. Pair with the 220 to 3,200 reclaimable hours range to size the investment case.
- Budget case: hours reclaimable times your analyst fully loaded cost gives the dollar value of the status quo; set that against the published price (free to start, $99 per month for the Pro plan, or $1,188 per year) for the ROI calculation.
- Accreditation: the 2 to 5 clarification cycles per request benchmark is a process-quality signal. AI-enabled intake reduces it to one round, which is a defensible improvement to cite in a self-study.
- Team-size peer comparison: if you run a small IR office (1 to 3 staff), the 90% peak season impact benchmark is the figure that explains why your team feels underwater during IPEDS or accreditation cycles.
See the benchmarks on your team
Book a demo and we will map these benchmarks to your institution size and request volume. Published pricing, free to start, from $99 per month, no implementation fee.
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