Sales Forecast Accuracy Scorecard
Grade every rep's forecast calls against what actually closed, so you can see who's sandbagging, who's happy-earing, and who's precise enough to build a company forecast on.
How to use it
Score every closed deal at month-end against the rep's own forecast call, bucket each rep into a band, and use the Step 6 coaching actions in your next 1:1 rather than treating a single miss as a one-off.
What's inside
- Forecast category definitions (Commit / Best Case / Pipeline / Omitted)
- Per-deal scoring formula weighting amount, date, and category accuracy
- Rep Accuracy Score roll-up table
- Sandbagging Index formula with a 30% flag threshold
- Happy-Ears Index formula with a 25% flag threshold
- Four rep bands: Precision Caller, Optimist, Sandbagger, Coin-Flipper
- Manager coaching actions mapped to each band
- Team-level quarterly rollup table with trend and targets
Purpose: Grade every rep's forecast calls against what actually happened: not to punish misses, but to find the pattern behind them. Chronic under-callers (sandbaggers) and chronic over-callers (happy-ears) both break a company forecast; this scorecard tells you which each rep is, deal by deal and over time.
Cadence: Score at the end of each month for the deals that were supposed to close that month. Roll up quarterly.
Step 1, Forecast category definitions
Have reps categorize every open deal at the start of each forecast period using these categories (add them to your CRM if they don't already exist):
- Commit, "I will close this by the date and amount stated. I'd bet my own money."
- Best Case: "Realistic upside if things go right, not the base case."
- Pipeline: "In motion, no confidence about this period."
- Omitted: deliberately left out of forecast
Step 2: Score each closed deal
For every deal that was supposed to close in the period, score three dimensions:
Amount Accuracy
- 100%: closed within ±10% of forecasted amount
- 50%: closed within ±25% of forecasted amount
- 0%: closed outside ±25%, or amount wasn't forecasted
Date Accuracy
- 100%: closed within the same forecast period predicted
- 50%: closed one period late/early
- 0%: closed two+ periods off, or never closed
Category Accuracy
- 100%, a "Commit" deal closed; a "Pipeline"/"Best Case" deal did NOT close in-period
- 0%, a "Commit" deal did NOT close in-period; or a deal not forecasted at all closed unexpectedly
Deal Forecast Score = (Amount Accuracy × 0.4) + (Date Accuracy × 0.3) + (Category Accuracy × 0.3)
Step 3, Roll up to a rep score
Rep Accuracy Score (period) = average Deal Forecast Score across every deal the rep forecasted that period
| Rep | # Deals Forecasted | Avg Amount Acc. | Avg Date Acc. | Avg Category Acc. | Rep Accuracy Score |
|---|---|---|---|---|---|
Step 4: Detect the two failure patterns
Sandbagging Index = (# deals that closed but were forecasted as "Pipeline" or omitted) ÷ (total deals closed)
- Above 30% → likely sandbagging: rep is winning deals they never called, inflating "beat the forecast" optics while making capacity/hiring planning blind
Happy-Ears Index = (# "Commit" deals that slipped or died) ÷ (total deals called "Commit")
- Above 25% → likely happy-ears: rep's Commit category is not trustworthy for company forecasting
Step 5: Assign a rep band
| Band | Criteria | What it means |
|---|---|---|
| Precision Caller | Rep Accuracy Score ≥ 85%, both indices < 20% | Forecast is bankable: build company numbers on their Commit |
| Optimist | Happy-Ears Index ≥ 25% | Consistently overstates Commit: discount their Commit by their historical slip rate |
| Sandbagger | Sandbagging Index ≥ 30% | Under-calls to guarantee "beats": surfaces late wins that break capacity/comp planning |
| Coin-Flipper | Rep Accuracy Score < 60%, no clear directional bias | Forecasting skill gap: needs coaching on deal qualification, not a personality trait |
Step 6, Manager coaching actions by band
- Precision Caller, no intervention needed; use as the forecast calibration benchmark for the team; consider peer-mentoring struggling reps
- Optimist, require a written "what has to be true" gate before a deal is called Commit; review the Commit list weekly and ask "what happened last time you called this deal Commit at this stage?"
- Sandbagger, investigate motive (does the comp plan reward beats? is there fear of being held to a number?); coach that under-calling breaks resourcing and territory decisions just as much as over-calling does
- Coin-Flipper: pair 1:1 deal reviews with qualification-framework coaching (MEDDIC/BANT-style); the issue is usually stage-gate discipline, not forecast honesty
Step 7, Team-level rollup
| Metric | This Quarter | Last Quarter | Trend |
|---|---|---|---|
| Team Rep Accuracy Score (avg) | |||
| Team Sandbagging Index | |||
| Team Happy-Ears Index | |||
| # reps in Precision Caller band |
Target: A mature forecasting team should have ≥60% of reps in the Precision Caller band and a team-level accuracy score above 80% within two quarters of introducing this scorecard.