Forecast Accuracy

Forecast accuracy is the degree to which your revenue predictions match actual closed revenue at the end of a given period, usually measured as the percentage variance between forecasted and actual numbers.

Getting forecasting right is one of the hardest and most important jobs in GTM operations. When forecasts are accurate, leadership can make confident decisions about hiring, budget allocation, and investment. When they’re consistently off, the entire business operates on bad assumptions.

The standard calculation is: forecast accuracy = 1 - (|forecasted revenue - actual revenue| / actual revenue). If you forecasted $1M and closed $900K, your accuracy is 90%. Most companies aim for 85-95% accuracy, though many fall well short.

The biggest enemies of forecast accuracy are sandbagging (reps lowballing their numbers to look good), happy ears (reps inflating deals based on optimism rather than evidence), and inconsistent deal qualification. If your team doesn’t have a shared definition of what makes a deal “commit” versus “best case,” your forecast will always be noisy.

Improving forecast accuracy starts with pipeline hygiene. Make sure deal stages have clear, verifiable exit criteria. Require reps to document next steps and stakeholder engagement. Use historical conversion rates by stage to apply probability-weighted math rather than relying solely on rep judgment.

The best RevOps teams layer multiple forecasting methods — rep-submitted, manager-adjusted, and algorithm-based — and compare them to spot discrepancies early.

Analytics tools that track deal progression and historical close rates give you the data foundation needed for accurate forecasting.