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Most compensation data fails at the point of use because it is averaged across companies that are nothing like yours. A national median for a chief financial officer spans a listed conglomerate and a forty-person startup. It is arithmetically correct and useless for deciding what to offer.
The first conversation is not about numbers. It is about which companies you genuinely compete with for this person, which is often a different list from the one you compete with commercially. A payments business and a bank may fight over the same engineering leadership while sharing no customers.
Base, target bonus, actual bonus paid where observable, and the gap between the two. A target bonus that never pays is a number in a contract, not compensation.
Quantum, vesting schedule, cliff and whether the instrument is liquid. Illiquid equity at a private company is not comparable to listed stock and should not be added to a total as though it were.
Adjusting for what the person actually runs. Two chief financial officers on the same base are not comparable if one owns treasury, tax and investor relations and the other owns reporting.
How many data points sit behind each range and how they were obtained. Where a sample is too thin to be meaningful we say so rather than publish a precise looking number.
Everyone benchmarking to the upper quartile is arithmetically impossible and, pursued collectively, is a mechanism for pay inflation rather than a strategy. If your answer to every benchmark is to move to the seventy fifth percentile, you have not made a decision, you have made a commitment.
Benchmarks also say nothing about whether an individual is worth the range. They describe a market, not a person. Someone who has done the job twice at greater scale may be worth more than the top of the band, and the band is not a reason to lose them. For a specific appointment, market data is an input to the offer rather than the offer itself. See retained executive search.
And a benchmark is a photograph. In functions where demand moves quickly, a range more than a year old should be refreshed before it is relied on. For sector-level context we publish observed figures openly, including what CXO pay data actually shows in India.
Observed compensation from search and mapping work, disclosed remuneration in filings and annual reports where companies are listed, and structured primary conversations. It is what we saw in a defined population, not a survey response extrapolated to a market.
A survey gives you a large sample across a broad definition. This gives you a smaller sample against a comparison set you chose, normalised for scope. Surveys are better for a general policy view across many roles. This is better for deciding what to offer one person.
Only loosely, and we would say so. Compensation follows scope, so a benchmark for a poorly defined role produces a wide range that is technically accurate and not decision-useful. If the scope is genuinely open, market intelligence is the better first step.
Yes, with caveats stated. We report quantum and terms, and we do not convert illiquid private equity into a headline total as though it were cash. Whether that instrument is worth anything depends on an outcome nobody can benchmark.
Enough companies to give a defensible range and few enough that they are genuinely comparable. That trade-off is agreed with you at the start. Adding companies to make the sample look larger while making it less relevant is the most common way this work goes wrong.
It will tell you where they sit against the market you compete with, which is usually the question behind the question. What it will not tell you is who is likely to leave over it. Pay is one input to that, and frequently not the decisive one.
Tell us about the mandate or challenge you are facing and we will show you what a tailor-made, partner-led engagement really looks like.