Enter your forecasted and actual revenue for up to 4 quarters. We will calculate your accuracy and show where variance concentrates.
How to read your score
Forecast accuracy is calculated as: 1 - |Forecast - Actual| / Forecast, expressed as a percentage. A score of 95% means your forecast was within 5% of actual revenue.
Here is how your accuracy stacks up against published B2B SaaS benchmarks:
| Accuracy Range | Assessment | Context |
|---|---|---|
| 95%+ | Excellent | Top decile. Gartner reports only 7% of companies achieve 90%+ consistently. You are operating at a level most companies aspire to. |
| 85-95% | Strong | ORM's target range for client engagements. At this level, your board can trust the number and plan around it. |
| 75-85% | Average | Typical for B2B SaaS companies using CRM-based forecasting without predictive models. |
| Below 75% | Needs work | Forecast misses at this level create board-level credibility problems and make resource planning unreliable. |
What the bias tells you
Forecast bias is as important as accuracy. Consistent over-forecasting (actuals come in below forecast) usually signals one of three problems: reps sandbagging pipeline quality, conversion assumptions that are too aggressive, or deals slipping that are not being flagged early enough.
Consistent under-forecasting (actuals beat forecast) is less common but signals conservative assumptions or an acceleration in deal velocity that the model is not capturing.
At ORM, we decompose variance by segment, deal type, rep, and pipeline stage. That granularity reveals whether your accuracy problem is structural (the model is wrong) or behavioral (reps are not updating pipeline accurately). The fix is different in each case.
ORM's take: accuracy is the output, not the goal
Most companies treat forecast accuracy as a metric to improve. We treat it as a diagnostic of the revenue engine. When accuracy is low, the question is not "how do we get the number closer to actual." The question is "what is the underlying pipeline dynamic that the forecast is not capturing."
A custom model built on your data, calibrated to your conversion rates, and adjusted for your specific seasonal patterns will consistently outperform any spreadsheet, CRM roll-up, or generic platform algorithm. That is not because the math is more complex. It is because the model is specific to your business.
Get to 85-95% accuracy
ORM builds custom forecast models that deliver board-ready accuracy. No dashboards to interpret. Just the number and what to do about it.
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