Forecast Inputs
Example Opportunity Table
| Name | Owner | Stage | Status | Close date | Amount | Probability % | Notes |
|---|---|---|---|---|---|---|---|
| Northwind expansion | Hassan | Negotiation | Open | 2026-04-10 | $45,000.00 | 70 | Security review in progress. |
| BlueSky renewal | Ayesha | Verbal Commit | Open | 2026-03-28 | $18,500.00 | 85 | Final signature expected this week. |
| Zenith pilot | Imran | Proposal | Open | 2026-05-05 | $12,000.00 | 50 | Awaiting proposal feedback. |
Formulas Used
1) Effective probability with slippage
Lower-probability deals are more likely to slip, so they receive a larger reduction.
slippageFactor = 1 − (slippageRisk × (1 − p))
effectiveProb = p × clamp(slippageFactor, 0, 1)
2) Weighted pipeline (expected value)
3) Adjusted forecast
Adjustments help align expected value with execution confidence and real performance.
marketFactor = 1 + marketAdj/100
repFactor = repConfidence/100
historicalFactor = clamp(historicalWinRate / baselineWinRate, 0.5, 1.5)
adjustedForecast = weightedTotal × seasonalityFactor × marketFactor × repFactor × historicalFactor
How to Use This Tool
- Set the horizon (for example, 30, 60, or 90 days).
- Choose probability source: stage mapping or manual entry.
- Tune thresholds for Commit and Best Case if needed.
- Enter opportunities with close dates inside the horizon.
- Optionally edit stage probabilities to match your process.
- Add confidence, seasonality, and market adjustments carefully.
- Click Calculate forecast and review results above.
FAQs
1) What is the difference between pipeline and forecast?
Pipeline is the total value of deals in scope. Forecast is the expected value after applying probabilities, slippage, and adjustments to better reflect likely outcomes.
2) Should I use stage mapping or manual probabilities?
Stage mapping is consistent and fast for teams. Manual probabilities can be better when reps score deals reliably. Use one approach across your team to avoid mixed assumptions.
3) What does slippage risk do?
Slippage risk reduces effective probability, especially for lower-probability deals. This helps account for late-stage timing changes and reduces optimistic forecasts when timelines are uncertain.
4) How should I set Commit and Best Case thresholds?
Commit typically aligns with your “likely to close” stage, often 60–75%. Best Case is usually 80–90% for final-stage deals. Keep thresholds stable for quarter-over-quarter comparisons.
5) Why include a baseline win-rate?
Baseline win-rate sets a reference point. Historical win-rate is compared to it to scale forecasts up or down. The scale is clamped to prevent extreme swings from noisy data.
6) Can I forecast only overdue deals?
Yes. Enable “Include overdue close dates” and set a short horizon. This highlights deals that should have closed already and helps prioritize follow-ups and recovery actions.
7) What opportunities are excluded automatically?
Deals without a close date are excluded. Deals outside the horizon are excluded. Closed won and closed lost are excluded unless you enable them in the filters.
8) What exports are available?
CSV export includes every in-scope deal with effective probability and weighted amount. PDF export provides a concise summary and top opportunities for easy sharing with stakeholders.