Testing a proposed valuation
Assesses whether a target’s proposed valuation is supported by peer trading multiples. Provides an argued range and explains the case for a premium, discount or position near the peer median.
— Finance & Investment
Comparable Company Analysis
Computes EV/Revenue and EV/EBITDA per peer, tests with live research whether the peer set is genuinely comparable, and argues the valuation range and where the target should sit within it.
- Finance & Investment
- Traceable reasoning
- Runs anywhere
1–2 weeks → ~25 minutes
For a full population, not a sample
No coding required
- Input
- Target company identity and business context
- Output
- Peer selection rationale and comparability assessment
- Runs in
- Skillsize · ChatGPT · Claude · Copilot
- Export
- SKILL.md · MCP
- Time saved
- ~1–2 weeks per run
— USE CASES
What people use Comparable Company Analysis for
Defending peer selection
Tests the comparability of proposed peers using current research and operating metrics. Provides a clear selection rationale and highlights differences that limit the usefulness of individual benchmarks.
Preparing an investment assessment
Provides a comparable company assessment covering peer rankings, median multiples and the target’s relative position. Gives advisers a concise evidence base for valuation recommendations and investment discussions.
Reviewing divergent peer multiples
Highlights differences in EV/Revenue and EV/EBITDA across the peer set. Assesses whether operating characteristics help explain the spread and what that means for the target’s valuation.
What it works from
- Target company identity and business context
- Proposed peer company names
- Peer enterprise values, revenue and EBITDA
- Available target operating metrics
What you get back
- Peer selection rationale and comparability assessment
- Operating-metric comparison
- Calculated EV/Revenue and EV/EBITDA multiples
- Peer rankings and median multiples analysis
— HOW IT BEHAVES
How Comparable Company Analysis produces its result
The mechanics behind this specific template — what it reads, what it calculates, and where a human stays in the loop.
Live research on the reporting period in scope
Current external sources on the reporting period in scope are researched during the run rather than recalled from training data, and every source travels with the output.
Every row of the reporting period in scope
Each row of your export is processed on the same basis, so no line item is skipped however long the table is.
The pattern charted
Movement across the reporting period in scope is visualised from the computed data, so the trend is legible at a glance.
Composed as work product
Findings on the reporting period in scope are written up as a document that reads like professional output, with each claim tied back to a line item.
Roll-up alongside line item-level detail
Detail rows are summarised into the grouped view of the reporting period in scope without losing the underlying line items.
Why this is expensive by hand
Comparable company valuations depend as much on peer selection as on arithmetic. Testing a proposed valuation is the typical trigger — assesses whether a target’s proposed valuation is supported by peer trading multiples. Provides an argued range and explains the case for a premium, discount or position near the peer median. Get it right and the conclusion holds up in the room; get it rushed and it gets picked apart. Either way it costs roughly 1–2 weeks of experienced attention.
How this Skill produces it
Skillsize turns that work into a Skill: you supply the material, and what comes back is peer selection rationale and comparability assessment, with operating-metric comparison. The judgement is built in — how items are broken up, what standard they are held to, and where the run stops for a human review. In effect, 1–2 weeks of senior time compresses into ~25 minutes — and the output is comparable across clients, quarters and colleagues instead of shaped by whoever ran it.
Who it's for
- Finance directors and FP&A teams
- Investment, deal and corporate development teams
- Controllers and reporting managers
- Consultants building or reviewing business cases
Run it in Skillsize — or export it anywhere
Comparable Company Analysis exports as a structured SKILL.md file and is MCP-ready, so the same method runs in ChatGPT, Claude, Copilot or your own AI products. Adapt it to your methodology, and the intelligence stays yours — not locked to one vendor.
ChatGPTClaudeCopilotAI Products (MCP)
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