Slip Rate

Definition Slip Rate quantifies forecast reliability by tracking what percentage of deals forecasted to close in a specific period (week, month, quarter) actually slip out of that period. In B2B SaaS, it's a key pipeline health metric that reveals gaps in buyer commitment, deal progression, or forecasting discipline. Unlike broader slippage (which measures days late), Slip Rate is binary: did the deal close in its forecasted period or not? High slip rates (>30%) signal execution issues, poor mutual action plans, or overly optimistic forecasting. How to Calculate Slip Rate Slip Rate Formula (%) Slip Rate = Deals Forecasted to Close that Did Not Close in Period ÷ Total Deals Forecasted to Close in Period × 100 Step-by-Step Calculation Identify all deals forecasted to close in the period (commit + best case). Count how many actually closed-won in that exact period. Subtract from total forecasted (# that slipped). Divide slipped deals by total forecasted. Example Q1 forecast: 10 deals to close 4 deals closed on time 6 deals slipped (3 closed late, 3 still open) Slip Rate = 6/10 = 60% Why Slip Rate Matters Slip Rate directly impacts quota attainment, cash flow predictability, and sales capacity. High rates create… EOM crunches (everything rushes to quarter-end) Unreliable forecasts (Q1 "commits" become Q2 reality) Pipeline compression (healthy pacing → chaotic closes) Manager distraction (chasing "sure things" that slip) CROs target Slip Rate <20–25% for mature orgs. Reducing it smooths revenue, improves attainment, and builds forecast credibility. Industry Benchmarks Org Maturity Typical Slip Rate Notes Early-Stage 35–50% Optimistic forecasting common Growth-Stage 25–35% Process improvements needed Mature 15–25% Strong MAPs, buyer commitment Best-in-Class <15% Forecast discipline + execution Real-World Examples A mid-market SaaS team with 45% Q1 Slip Rate implements a "forecast only if MAP signed by EOM1" policy; Slip Rate drops to 22%. An enterprise sales team sees 38% slip in the Negotiation stage; a new executive sponsor requirement cuts it to 18%. RevOps flags reps with >40% Slip Rate; they coach the reps on buyer signals and team average improves from 32% to 24%. Common Mistakes Forecasting without buyer commitment (verbal "next week" ≠ signed intent). No slip thresholds (all deals treated equal regardless of risk). Ignoring patterns (slippage spikes proposal → legal). Rep date gaming (moving forecast 1 day forward). No accountability (same deals slip repeatedly). The Fix: Require MAPs for commits, set slip thresholds (re-forecast if >14 days late), track by stage/rep, coach realistic forecasting. Frequently Asked Questions What's the difference between slip rate and slippage? Slip Rate = % of deals that slip (binary). Slippage = average days late (continuous). Should still-open deals count in slip rate? Yes. They missed their forecast period and they tie up forecast capacity. What's an acceptable Slip Rate for enterprise? 25–35% is common due to longer cycles. Target <25% with better sponsors/legal prep. Does high slip rate impact attainment? A high slip rate creates EOM chaos, burnout, discounting pressure. A low slip rate leads to smooth pacing and better attainment. Can slip rate be zero? Rarely. Some legitimate slippage occurs (buyer delays, holidays). Target <20%. Last Updated: December 18, 2025 Reviewed by: Ben Hale