Sales Forecast Accuracy Calculator
Enter last quarter's forecast vs. actuals to get your forecast-accuracy percentage plus which direction the bias is running — over-forecasting (happy ears) or under-forecasting (sandbagging).
What's inside
- Forecast Accuracy % formula: 100% − (|Actual − Forecast| ÷ Forecast × 100)
- Bias-direction formula distinguishing over-forecasting from under-forecasting
- Fully worked example calculation ($1M forecast vs $760K actual = 76%, 24% over-forecast)
- Fill-in worksheet for your own numbers
- Per-rep table so team rollups don't hide individual bias
- Score-reading bands: 90-100% Excellent through Below 70% Systemic
- Diagnostic guide for what consistent over- vs under-forecasting each imply about your process
- Quarter-over-quarter tracking table to separate a one-off miss from a pattern
The formula
`` Forecast Accuracy % = 100% − ( |Actual − Forecast| ÷ Forecast × 100 ) ``
Bias Direction: `` If Actual < Forecast → Over-forecasting (optimism / "happy ears" bias) If Actual > Forecast → Under-forecasting (sandbagging bias) If Actual = Forecast → No directional bias ``
Bias Magnitude % = (Actual − Forecast) ÷ Forecast × 100 — negative = over-forecast, positive = under-forecast (sandbag).
Worksheet — fill in your numbers
| Field | Your Number |
|---|---|
| Forecast committed at start of quarter ($) | ___________ |
| Actual closed-won at end of quarter ($) | ___________ |
| Variance ($) = Actual − Forecast | ___________ |
| Variance (%) = Variance ÷ Forecast × 100 | ___________ |
| Forecast Accuracy % (formula above) | ___________ |
| Bias direction (over-forecast / under-forecast / none) | ___________ |
Worked example
- Forecast: $1,000,000
- Actual: $760,000
- Variance: −$240,000 (−24%)
- Forecast Accuracy % = 100 − (240,000/1,000,000×100) = 76%
- Bias direction: Over-forecasting by 24% (optimism bias / happy ears)
Do this per rep, then roll up
Repeat the worksheet for every rep, then for the team total. A team accuracy score can look fine while masking two reps who wildly over-forecast and two who sandbag — the rollup hides it. Always calculate per-rep before you calculate for the team.
| Rep | Forecast | Actual | Accuracy % | Bias |
|---|---|---|---|---|
| Team Total |
Reading the score
- 90–100%: Excellent. Forecast is a reliable planning input.
- 80–89%: Good. Minor noise, not a systemic issue — spot-check the worst-variance rep.
- 70–79%: Caution. Something in the qualification or deal-review process is letting unverified deals into the number (see the companion Deal Review Checklist).
- Below 70%: Systemic. The forecasting process itself — not any one rep — needs to change. Look for a pattern: is it concentrated in one segment, one rep, one stage?
Reading the direction (this matters more than the score)
- Consistent over-forecasting (Actual < Forecast, repeatedly): Deals are being called Commit/Best Case without verified economic-buyer access or a compelling event. Fix at the deal-review layer, not the number.
- Consistent under-forecasting (Actual > Forecast, repeatedly): Reps are sandbagging — holding deals out of the forecast to guarantee they "beat the number." This inflates confidence in the wrong direction and causes leadership to under-resource. Fix by rewarding forecast accuracy, not just overachievement.
- Bias flips quarter to quarter with no pattern: Deal timing/close-date discipline is the issue, not confidence calibration.
Track it over time
| Quarter | Forecast | Actual | Accuracy % | Bias Direction |
|---|---|---|---|---|
| Q1 | ||||
| Q2 | ||||
| Q3 | ||||
| Q4 |
A single quarter tells you the score. Four quarters tell you whether it's a person problem or a process problem.
How to use it
Drop last quarter's committed forecast and actual closed-won into the worksheet at the start of every QBR to get your accuracy score and bias direction, then track it quarter over quarter to see if the bias is a person issue or a process issue.