Guesstimate Calculator

Build quick Fermi-style estimates with uncertainty. Break a big question into factors, assign ranges, and see the distribution of possible answers.

Factors & Assumptions

For each factor, enter a low / best / high estimate and choose how it combines with the previous result.

# Factor description Low Best High Combine Unit / note

More runs = smoother distribution, but slightly slower.

Results

Set up at least one factor and click “Run simulation” to see your guesstimate.

Quick example: coffee cups sold in a city

Click the button below to load a ready-made Fermi estimate. Adjust the numbers and re-run the simulation.

What is a guesstimate?

A guesstimate is an approximate answer based on rough numbers, assumptions and reasoning instead of precise data. In consulting, product management and tech interviews it usually means:

  • Taking a vague question (e.g. “How many piano tuners are in Chicago?”)
  • Breaking it into smaller factors (population, households, pianos per household, tunings per year, capacity per tuner…)
  • Making reasonable assumptions for each factor
  • Combining them to get a ballpark, order-of-magnitude answer

How this guesstimate calculator works

Instead of a single point estimate for each factor, you enter a low, best and high value. The calculator then runs a Monte Carlo simulation:

  1. For each run, it randomly samples a value for every factor between your low and high.
  2. It combines factors using your chosen operators (×, ÷, +, −).
  3. It repeats this thousands of times to build a distribution of possible answers.
  4. It reports key statistics: median, 10–90% range, mean and standard deviation.

Triangular sampling for a factor

For a factor with low \(a\), best \(m\) and high \(b\), we sample from a triangular distribution:

  • Values near \(m\) are more likely.
  • Values near \(a\) or \(b\) are less likely but still possible.

Why use ranges instead of single numbers?

Real-world assumptions are rarely exact. Ranges:

  • Force you to think about optimistic vs pessimistic scenarios
  • Make your uncertainty explicit
  • Produce a distribution instead of a single misleadingly precise number

Step-by-step: doing a Fermi guesstimate

  1. Clarify the question. What exactly are you estimating? Units? Timeframe?
  2. Decompose into factors. Think of a formula that would give the answer.
  3. Estimate each factor. Use intuition, analogies, or quick lookups if allowed.
  4. Assign low / best / high. Ask yourself: “What’s a plausible worst case? Best case?”
  5. Run the simulation. Look at the median and the 10–90% range.
  6. Sanity-check. Does the result feel reasonable? If not, revisit your factors.

Typical use cases

  • Interview questions (consulting, product, data, strategy)
  • Market sizing when data is sparse
  • Back-of-the-envelope business cases
  • Prioritisation: is this opportunity 10× bigger than another?
  • Everyday decisions: commute time, event planning, rough budgets

Tips for better guesstimates

  • Prefer simple, transparent formulas over complex ones.
  • Keep factors independent where possible (to avoid double-counting).
  • Use orders of magnitude (10, 100, 1,000…) when you’re very uncertain.
  • Explain your reasoning out loud in interviews; the process matters more than the final number.