Finance Metric Library
Look up any finance metric to see its formula, what a healthy range looks like, the definition traps that make two teams compute it differently, and the questions to ask before you report it.
Where can I look up finance metric formulas and benchmarks?
This library covers the metrics a mid-market finance team actually reports, each with its formula, a healthy range where one exists, the definition traps that cause two teams to compute it differently from the same data, and the questions worth asking before you put it in front of a board. Search by metric name or browse by category, every entry is written to be read in under a minute.
How to use this tool
- 1
Search or browse
Type a metric name, or filter by category to see everything in one family.
- 2
Read the formula and the trap
Each entry gives the calculation, a healthy range, and the definitional choice that most often causes disagreement.
- 3
Take the questions with you
Every metric lists what to ask before reporting it, so the number arrives with its caveats attached.
A metric is only meaningful once you know whose definition it uses
Most finance disagreements are definitional, not arithmetic. Four ways the same metric name produces different numbers.
The same name, two formulas
Net retention, CAC, and EBITDA all have multiple accepted calculations. Neither party is wrong; they are answering slightly different questions with the same word, and nobody notices until the numbers are compared.
Boundary decisions
Does customer success sit in COGS or operating expenses? Does a pilot count as a customer? Is a signed but unstarted contract in the pipeline? These choices are invisible in the final number and can move it by double digits.
Period conventions
Trailing twelve months, calendar year to date, and annualised last quarter produce three different growth rates from one dataset. Dashboards frequently mix conventions across tiles without labelling which is which.
The company-specific rule
Every business carries exceptions: a commission plan that recognises differently, a seasonal pattern that makes one quarter incomparable, a legacy contract excluded by agreement. These rules usually live in one person's head, and any analysis produced without them is wrong in ways nobody can see.
Why a shared definition is the hard part
A library gives you the standard definitions. Your business runs on its own, which revenue counts as recurring, how commissions are recognised, which quarter is genuinely comparable, which customer is excluded from cohort analysis for a reason someone agreed to three years ago. When those rules are not written down anywhere, every analysis silently re-derives them, and every general-purpose AI tool gets them wrong with complete confidence. Capturing them once, so every subsequent answer applies them automatically, is the entire premise of DataWyse's knowledge graph.
See how DataWyse answers thisQuestions finance teams ask about this tool
Why do two teams calculate the same metric differently?
Because most finance metrics have several accepted formulas and a set of boundary decisions that are rarely written down. Whether customer success costs sit in COGS, whether a pilot counts as a customer, and whether growth is measured on trailing twelve months or year to date all change the answer without changing the underlying data.
What is the difference between a metric and a KPI?
A metric is any measurement. A key performance indicator is a metric someone has committed to acting on, with a target and an owner. Most finance teams track far more metrics than they have decisions to make, which is how dashboards grow without anyone's behaviour changing.
How many metrics should a board pack contain?
Enough to answer the questions the board actually asks, which is usually between five and ten headline figures with detail available behind them. A pack with forty metrics and no narrative gets skimmed; a pack with eight and a clear explanation of what moved gets discussed.
Should I use industry benchmarks?
Use them to sanity-check, not to set targets. Published benchmarks rarely disclose their classification choices, sample composition, or company stage, so a gap against a benchmark may reflect a definitional difference rather than a performance difference. Your own trend is almost always the more reliable comparison.
Is this tool really free?
Yes. No signup, no email required, no usage limit. It runs entirely in your browser: nothing you type is uploaded to a server or stored anywhere. We build these because the people who find them useful are the people who eventually need a financial analyst that works the same way.
DataWyse answers the next thirty
Variance deep-dives, cash re-forecasts, scenario plans, board prep: asked in plain English, answered in minutes, with every number traceable to its formula and source data.