Forecast accuracy tracker
Most teams measure forecast accuracy once, at quarter end, as a single percentage. That tells you whether the quarter was a surprise, not why. Accuracy that is only measured in week 13 is almost always good, because by then the number is mostly closed. This tracker measures accuracy and bias at fixed weeks of the quarter and by rep, which shows you when the forecast becomes reliable and whose calls consistently miss in the same direction.
- Category:
- Pipeline & Forecasting
- Formats:
- PDF + CSV + web view
- Sections:
- 6
- Updated:
What you get
- A weekly team tracker of called vs actual with error, accuracy, and bias
- A rep-level tracker at a fixed checkpoint week, so calls are compared fairly
- Formulas for accuracy and bias written in plain arithmetic
- A worked example showing how a rep with high bias hides inside a good team number
- A review checklist for the quarter-end accuracy retro
Who it's for
- RevOps analysts who own the forecast roll-up and report accuracy
- Sales leaders deciding whose calls to trust
- Finance partners who plan spend against the sales forecast
What's inside
- 1
Team accuracy by week of quarter
7 columns, 4 worked example rows
- 2
Formulas
3 columns, 4 worked example rows
- 3
Rep accuracy at week 6
7 columns, 3 worked example rows
- 4
Quarter summary
6 fields to complete
- 5
Quarter-end accuracy retro
7-point checklist
- 6
Why quarter-end accuracy is the wrong measure
Guidance notes
Preview of section 1
Team accuracy by week of quarter
Worked example: quarter actual was 1,000,000. Accuracy and bias are calculated once the quarter closes.
| Quarter | Week of quarter | Called number | Actual result | Error (called - actual) | Accuracy | Bias |
|---|---|---|---|---|---|---|
| Q2 | 2 | 1,150,000 | 1,000,000 | 150,000 | 85.0% | +15.0% |
| Q2 | 6 | 1,080,000 | 1,000,000 | 80,000 | 92.0% | +8.0% |
The preview shows part of section 1. The full template has all 6 sections (5 not previewed here), with blank rows ready to fill in. Download the full template
How to use it
- 1
Snapshot the call every week
Record the team call and each rep's call on the same day every week and never overwrite it. The value of the tracker is the history; if last week's call can be edited, there is nothing to measure.
- 2
Pick checkpoint weeks and compare at those
Compare accuracy at fixed weeks, for example week 2, 6, and 10 of a 13-week quarter. Week 6 accuracy is the one that matters for planning, because it is the last point where you can still act on the number.
- 3
Track bias separately from accuracy
Accuracy tells you how far off a call was. Bias tells you in which direction. A rep who is 20% high every quarter is predictable and can be adjusted for; one who swings between high and low cannot.
- 4
Compare rep call vs manager call
If you collect both, measure both. Over two or three quarters it becomes clear whether managers improve on their reps' calls or just add noise, which is worth knowing when you decide whose number goes to finance.
Frequently asked questions
How do you calculate forecast accuracy in sales?
Accuracy = 1 - (absolute value of (Called - Actual) / Actual). If you called 1,080,000 and closed 1,000,000, accuracy is 92%. Track bias alongside it: Bias = (Called - Actual) / Actual, which shows whether you are consistently high or low.
What is good sales forecast accuracy?
It depends on the week you measure and your deal mix. Rather than chase an external benchmark, set a threshold from your own history and track the week of the quarter at which your forecast first reliably clears it. Moving that week earlier is the real improvement.
When should forecast accuracy be measured?
At fixed checkpoints during the quarter, such as weeks 2, 6, and 10 of 13, and at quarter end. Mid-quarter accuracy matters most because that is when the business still acts on the number.
What is forecast bias?
The direction of forecast error. Positive bias means calls are consistently higher than results (optimism); negative bias means consistently lower (sandbagging). Consistent bias can be corrected for; erratic error cannot.
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