Five forecasting models. One closed quarter.
Every model is confident. Only one was right. Pick a method, run it against a quarter that has already closed, and see exactly how far off the number was — then watch a Monte Carlo simulation put honest error bars around the forecast you actually present to your board.
How does your team call the number?
Pick the one closest to how you forecast today. You'll see all five compared regardless.
A quarter, as it looked at forecast time.
This is a real-shaped book of business with the usual optimism baked in. Edit amounts, stages, and rep calls — or run it as-is. The outcomes are hidden until you run it.
| Deal | Amount | Stage | Rep call |
|---|
The quarter actually closed at $0.
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Bars show forecast size; the dashed line is what actually closed. Signed error is the honest measure of forecast quality.
Monte Carlo: a range, not a point.
A single number hides the risk. Running the pipeline 5,000 times — each deal winning at its stage's calibrated probability — gives you the distribution of plausible outcomes and the real odds of hitting quota.
The catch: —
The model is the easy part. The inputs are the problem.
Every model here ran on clean, complete data. Yours won't — stale stages, missing close dates, deals parked in "Negotiation" for two quarters. Forecasting Trust measures accuracy, pipeline hygiene, methodology, and whether leadership actually believes the number. It's the integration test for everything underneath. See where you land.