Forecasting (sales forecasting) is the process of estimating future revenue based on pipeline data, historical patterns, and probability assessments. For sales organizations, forecasting means not only revenue predictions but also forecasting commission costs and incentive payouts. According to Gartner (2024), companies with advanced forecasting have 28% higher revenue attainment than those with basic methods.
Accurate forecasting impacts multiple aspects:
According to CSO Insights (2024), only 24% of companies have "high confidence" in their forecasts.
| Method | Description | Accuracy |
|---|---|---|
| Pipeline-weighted | Deal value × stage probability | Moderate |
| Historical | Based on past periods + growth rate | Low-moderate |
| Rep assessment | Salespeople's own estimates | Variable |
| AI-driven | Machine learning on CRM data | High |
The most common method uses stage probabilities:
Weighted value = Deal value × Win probability
| Deal | Value | Stage | Probability | Weighted |
|---|---|---|---|---|
| Acme Corp | $60,000 | Negotiation | 80% | $48,000 |
| TechStart Inc | $40,000 | Proposal | 50% | $20,000 |
| Global Systems | $80,000 | Discovery | 20% | $16,000 |
| Green Energy LLC | $50,000 | Verbal commit | 90% | $45,000 |
| Total | $230,000 | $129,000 |
Expected revenue: $129,000
For salespeople, forecasting is closely tied to motivation. When an employee can see a realistic commission projection, it creates a stronger connection between effort and reward.
Setup:
| Scenario | Expected Sales | Attainment | Expected Commission |
|---|---|---|---|
| Pessimistic | $127,500 | 75% | $10,200 |
| Expected | $170,000 | 100% | $13,600 |
| Optimistic | $212,500 | 125% | $18,700 |
Forecasting can be used to simulate the effect of new incentive models by testing them against historical data. According to Alexander Group (2024), only 31% of companies test new compensation plans against historical data before implementation.
A company wants to introduce a new accelerator at 120% attainment. By running last year's data through the new model, leadership can see:
This provides a basis for evaluating whether the model is economically sustainable and provides the desired motivation.
| Category | Description | Typical Timing |
|---|---|---|
| Commit | Deals the rep is confident will close | Within period |
| Best case | Deals with good probability | Within period |
| Pipeline | All active opportunities | Varies |
| Upside | Potential deals that could be accelerated | Possible within period |
Use consistent stage definitions: All reps should understand what each stage means and what probability belongs to it.
Calibrate probabilities: Compare forecast vs. actual over time and adjust probabilities based on real win rates.
Forecast regularly: Weekly or bi-weekly forecast reviews keep projections current.
Combine methods: Use pipeline-weighted, historical, and rep assessment together for more accurate estimates.
Best-in-class organizations have forecast accuracy of ±10%. According to Salesforce (2024), the average is ±25% variance.
Use weighted close dates and adjust probabilities based on time in pipeline.
Reps are responsible for deal-level forecasts, while leadership is responsible for aggregate projections and methodology.
Forecasting is the foundation for a modern incentive culture. With Prowi, you can automate forecasting by pulling data directly from CRM, connecting it with the commission model, and providing a continuous picture of expected commission—for both reps and leadership.