What is Intuitive Forecasting?
Intuitive forecasting is the oldest method and still indispensable for complex deals, where a rep's read on a buying committee beats any model.
Its weakness is human bias. Optimistic reps overcall, cautious reps sandbag, and without calibration the roll-up drifts from reality.
Short answer
Intuitive forecasting builds the number from human judgment: reps and managers call which deals will close based on experience and firsthand knowledge of each deal. It captures nuance that models miss, which matters for complex enterprise deals, but it is only as reliable as the caller's calibration and honesty, making it prone to happy ears and sandbagging.
Key takeaways
- Built from rep and manager commit judgment.
- Captures nuance that statistical models miss.
- Essential for complex, low-volume enterprise deals.
- Prone to happy ears and sandbagging without calibration.
Why it matters
For deals too unique or too few for a model, human judgment is the best signal available. But that judgment must be tracked and calibrated, or the forecast swings with each rep's temperament rather than the deals.
How Ardovo handles it
Ardovo records each rep's commit calls and compares them to real engagement signals and their own historical accuracy, so Rook can flag overcalls and sandbags and coach reps toward calibrated judgment.
Frequently asked questions
Is intuitive forecasting reliable?
It is reliable only when the caller is calibrated. Experienced, honest reps produce excellent commit calls on complex deals; optimistic or cautious reps skew the number. Tracking accuracy over time is what makes intuition trustworthy.
When should I use intuitive forecasting?
For complex, high-value, low-volume deals where each opportunity is too unique for a statistical model. Layer rep judgment on top of a weighted or stage method rather than using it alone.
How do I reduce bias in intuitive forecasting?
Track each rep's forecast accuracy, compare commit calls to engagement signals, and coach the pattern. Reps calibrate quickly when their overcalls and sandbags are surfaced with data.