peer-benchmarking
Installation
SKILL.md
Peer Benchmarking
When to use
Use whenever a performance claim needs external context, "our margin is strong" means nothing without knowing what peers actually post, or when preparing a board or investor update that will get challenged on comparability. Also use to check a benchmarking claim someone else made, where the peer set and exclusions were never stated.
What it does
Builds a defensible peer comparison: a real peer set (not cherry-picked), calendarized to the same period, with median and quartile ranges per metric, and an explicit note on which companies were excluded and why. The output is a range with a position in it, not a single flattering number lifted from the best comparison available.
Method
- Define the peer set by real comparability criteria — similar business model, similar scale (revenue or headcount band), similar growth stage, similar geography — not just "companies in the same industry label."
- State exclusions explicitly. If a company in the obvious peer group is excluded (different fiscal year, recent M&A distorting the numbers, private and unreported), name it and why. An unexplained exclusion is exactly how benchmarking gets cherry-picked.
- Calendarize before comparing. Companies with different fiscal year ends are not directly comparable on a raw calendar-quarter basis — align to trailing twelve months or the nearest common period.
- Compute median and quartile range per metric, not just an average — an average can be dragged by one outlier peer; the quartile range shows where the real distribution sits.
- Place the subject company's actual number inside that range and state the percentile plainly: "24th percentile on gross margin" is a finding; "below average" is not.
- Separate metrics where the company is structurally different (different revenue recognition, different capital intensity) — flag these instead of forcing a comparison that isn't apples-to-apples.
- State what the benchmark implies for action, not just where the company sits — a bottom-quartile metric with a plausible structural explanation needs different follow-up than one with no explanation at all.