What is Forecast Model?
A forecast model is the recipe behind the number: which inputs, which probabilities, which rules produce the forecast. Ad hoc forecasting cannot be improved because it cannot be measured.
The best models are consistent and transparent, letting a team track accuracy and refine the method rather than starting from scratch each period.
Short answer
A forecast model is the structured, repeatable method a team uses to predict revenue, combining inputs like pipeline, win probabilities, historical trends, and rep judgment into a defined process. A good model is consistent, so its accuracy can be measured and improved over time, and transparent, so leaders can trace the number to its drivers rather than trusting a black box.
Key takeaways
- The structured method used to predict revenue.
- Combines pipeline, probabilities, trends, and judgment.
- Consistency lets accuracy be measured and improved.
- Transparency lets leaders trace the number.
Why it matters
You cannot improve what you cannot measure. A defined forecast model produces a number you can track against actuals period after period, revealing where the method is off and how to sharpen it.
How Ardovo handles it
Ardovo runs multiple forecast models side by side and tracks each one's accuracy over time, so Rook can tell you which model best predicts your actuals and where a model's inputs are drifting from reality.
Frequently asked questions
What is a forecast model?
It is the structured, repeatable method a team uses to predict revenue, combining inputs like pipeline, win probabilities, historical trends, and rep judgment into a defined process. Consistency and transparency are what make it improvable.
What makes a good forecast model?
Consistency, so accuracy can be measured over time; transparency, so the number traces to its drivers; and fit to your data and deals. The best model for your team is the one that most reliably predicts your actuals.
Should I use more than one forecast model?
Running two, such as a weighted model and a rep-commit roll-up, is valuable. The gap between them highlights risk, and comparing each model's historical accuracy tells you which to trust most for your business.