Adjusting Your Forecast for Stuck Deals - The Key to Accuracy

Sales forecasting is only as accurate as the data that feeds it. Yet, many B2B companies fall into the trap of treating every opportunity in the pipeline as equally viable, even when a significant portion of deals are stalled in a particular stage. Without properly accounting for stuck deals, forecasts become overly optimistic and unreliable, leading to missed revenue targets and misallocated resources.

Why Stuck Deals Distort Forecasting

• Inflated pipeline value – Revenue projections assume that all deals will progress, when in reality, many are unlikely to close.
• Resource misalignment – Sales teams may focus on older, stuck deals instead of prioritizing higher-velocity opportunities.
• Inconsistent win-rate assumptions – Win rates are typically calculated on historical data, but including stalled deals in that equation leads to false confidence.

A More Reliable Approach to Forecasting

Rather than treating all deals the same, high-performing RevOps teams incorporate deal velocity into their forecasting models. Here’s how:

1. Exclude or Deprioritize Stuck Deals – Define a clear threshold for when a deal is considered stuck (e.g., 2x the expected time in stage). Any deal past this threshold should either be removed from the forecast or weighted at a lower probability.
2. Use Stage-Specific Probabilities – Instead of assigning a blanket probability to deals based on total pipeline value, assign different probabilities based on sales velocity within each stage.
3. Segment Forecasts by Deal Type – Different revenue streams (new logos, renewals, upsells, cross-sells, enterprise, SMB, and geographic regions) have unique sales cycles. Separating these in the forecast prevents the data from being skewed.
4. Incorporate Historical Win Rates from Successful Deals – Forecasting should be based on the actual stage velocity of won deals, rather than an average that includes lost deals.

How This Approach Improves Forecast Accuracy

By applying these forecasting adjustments, companies can expect:

• More realistic revenue projections – Instead of relying on an inflated pipeline, forecasts reflect actual deal movement.
• Better sales prioritization – Reps can focus on active, high-velocity deals instead of chasing long-stalled opportunities.
• Stronger executive confidence – Leadership can make strategic decisions with clearer insight into revenue expectations.

Bringing It All Together: Sales Velocity as the Foundation of Forecasting

RevOps leaders who incorporate stuck deal analysis into their forecasting models gain a major competitive edge. By shifting from static pipeline views to dynamic, velocity-based forecasting, they enable their companies to:

• Accurately predict revenue shortfalls before they happen.
• Take corrective action to improve sales execution.
• Align investment and resources based on where deals are truly progressing.

Final Thoughts

This concludes our series on Sales Velocity by Stage and how RevOps can transform forecasting accuracy, sales execution, and overall revenue performance.

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