IR Capacity Benchmarks: The Real Cost of Ad Hoc Data Requests

What 50+ interviews with IR teams reveal about how much time ad hoc requests actually consume, by team size

CRT
Clema Research Team
July 7, 2026
7 mins read
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Table of Contents

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

MetricBenchmarkSource
Capacity consumed by ad hoc requests40 to 60% of team capacity50+ IR/IE interviews
IR teams facing significant workflow challenges91%50+ interviews, 19 states
Clarification cycles per ad hoc request2 to 5 cycles50+ interviews
IR teams operating with 1 to 3 staffOver 50%50+ interviews
Hours reclaimable annually with AI-enabled workflows220 to 3,200 hours50+ interviews

Benchmarks by Team Size

Team sizePeak season capacity impactPrimary challenge
Small (1 to 3 staff)90%Resource scarcity; doing everything with minimal capacity
Medium (4 to 7 staff)75%Process transition; formalizing workflows as team grows
Large (8+ staff)85%Scale and complexity; managing breadth across the institution

Hours Reclaimable

The 220 to 3,200 hours annually reclaimable range comes from the same research. 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 publishes at $499 per month, or about $6,000 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 $499 per month published price 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 $499 per month pricing, no implementation fee.

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Frequently asked questions

How much IR capacity do ad hoc data requests consume?

40 to 60% of team capacity on average, based on 50+ interviews with IR and IE professionals across 19 US states. The burden is highest proportional to capacity at small teams of 1 to 3 staff, where peak season impact reaches 90%.

How many hours can an IR team reclaim with AI-enabled workflows?

220 to 3,200 hours annually, depending on team size and request volume. A medium IR office typically reclaims 800 to 1,500 hours, roughly half an FTE. At a fully loaded analyst cost of $80,000 to $120,000, that is $40,000 to $60,000 of capacity redirected to strategic work.

Where do these IR capacity benchmarks come from?

The benchmarks are drawn from the Clema data request workflows whitepaper, based on 50+ interviews with IR and IE professionals across 19 US states. The full research is available as a free download at clema.ai/data-request-workflows.

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