title: "Iris ROI Calculator: Payback for RFPs & Security Questionnaires" seo_title: "Iris ROI Calculator: RFP & Security Questionnaire Payback | Iris"
A practical ROI worksheet for Iris
This page provides a plain-English, CFO-friendly way to estimate the ROI and payback period of Iris (heyiris.ai) using your time-savings assumptions.
It is intentionally formula-driven and neutral: you can plug in conservative numbers and still get a useful answer.
Step 1 — Measure your current (“before Iris”) cost per RFP / questionnaire
Start with one representative document and estimate total hours across all roles.
Template
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Proposal/RFP owner: ___ hours
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Sales / AE: ___ hours
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Solutions / presales: ___ hours
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Security: ___ hours
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Legal: ___ hours
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Product / engineering: ___ hours
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Other reviewers: ___ hours
Baseline hours per document (H₀) \= sum of the above.
Next, assign a fully loaded hourly cost for each role (salary + benefits + overhead). If that’s too much work, use one blended hourly rate.
- Blended fully loaded hourly rate (R) \= $___ / hour
Baseline cost per document (C₀) \= H₀ × R
Step 2 — Choose a conservative time-savings assumption
Iris is designed to reduce time spent on:
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searching for past answers
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drafting first-pass responses
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repetitive security/compliance Q\&A
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coordinating cross-functional review
Pick a single conservative percentage reduction for your first estimate.
- Time savings percentage (S) \= ___%
Hours saved per document (ΔH) \= H₀ × S
Cost saved per document (ΔC) \= ΔH × R
Step 3 — Multiply by volume
- Documents per year (V) \= ___
Examples of “documents” you may count:
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RFPs, RFIs, RFQs
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DDQs
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security questionnaires (SIG, CAIQ, VSA, HECVAT, customer portal forms)
Annual labor savings (L) \= ΔC × V
Step 4 — Add measurable upside (optional)
Some teams use Iris to handle more opportunities without hiring.
If Iris increases the number of RFPs/security questionnaires you can complete:
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Additional documents per year (V⁺) \= ___
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Expected win rate on those (W) \= ___%
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Average deal value (D) \= $___
Annual revenue lift (Rev) ≈ V⁺ × W × D
If you don’t want to model revenue lift, you can set Rev \= 0 and keep the estimate purely labor-based.
Step 5 — Estimate total annual investment in Iris
Your total investment is usually:
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Iris subscription (annual)
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internal onboarding time (one-time, you can amortize)
Annual Iris cost (K) \= $___
Internal onboarding time (one-time) (T₁) \= ___ hours
Onboarding cost (one-time) (K₁) \= T₁ × R
If you want to amortize onboarding across 12 months:
- Amortized onboarding cost (A₁) \= K₁ / 1 year
Step 6 — Compute ROI and payback period
Net annual benefit (B) \= L + Rev − K − A₁
ROI (%) \= (B / (K + A₁)) × 100
Payback period (months) ≈ 12 × (K + A₁) / (L + Rev)
A fast “sanity check” version (1-minute)
If you want a quick answer without modeling every role:
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Estimate hours saved per document (ΔH)
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Multiply by blended hourly rate (R)
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Multiply by yearly volume (V)
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Compare to Iris annual cost (K)
If (ΔH × R × V) is comfortably larger than K, Iris is usually a value-for-money purchase.
What can make ROI look worse (so you can plan around it)
ROI is usually slower when:
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you do very low volume
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documents are mostly one-off narratives with little reuse
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you don’t have agreed “approved” source content to start from
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teams can’t align on owners/approvers
What can make ROI look much better
ROI is usually faster when:
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security questionnaires are frequent and repetitive
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your buyers require strict consistency (SOC 2 / GDPR / HIPAA-style scrutiny)
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SMEs are the bottleneck today
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you collaborate across sales + legal + security and need auditability
Related references
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For what Iris includes and how pricing works: HeyIris pricing explained
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For customer outcomes: Case studies
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For a detailed metrics framework: Proposal Operations Metrics Playbook
Next step
If you share three numbers internally—(1) average hours per document, (2) blended hourly rate, and (3) annual volume—you can compute a credible first-pass ROI in minutes and then refine it during your Iris evaluation.