Sales Forecast Accuracy Scorecard

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

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

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

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.