Sales Forecasting
Why Forecast?
Accurate forecasting enables resource planning, inventory management, revenue projections, and executive decision-making. Siebel provides multiple forecasting methods based on pipeline data.
Forecasting Methods
1. Pipeline-Based Forecasting
- Formula: Sum of (Opportunity Revenue× Probability)
- Example: 10 opportunities at $100K each, 50% avg probability = $500K forecast
- Pros: Simple, real-time updates
- Cons: Relies on accurate stage probabilities
2. Historical Trend Analysis
- Analyze past quarters' win rates and sales cycles
- Apply historical conversion rates to current pipeline
- Example: Q1-Q3 show 30% lead → close rate → Apply to Q4 pipeline
3. Sales Rep Input
- Reps manually adjust forecast for opportunities they own
- Managers roll up team forecasts
- Use case: Reps have insight system doesn't (e.g., budget freeze rumors)
Forecast Categories
Commit Levels:
- Best Case: All opportunities close (100% probability) = $2M
- Commit: High-confidence deals (Negotiation stage+) = $1.2M
- Most Likely: Weighted pipeline (Revenue× Probability) = $800K
- Closed: Already won this period = $600K
Forecast Rollups
- Individual Rep: Alice's Q1 forecast = $300K
- Team Level: West Coast Team (5 reps) = $1.5M
- Regional: Western Region (3 teams) = $4.5M
- Company-Wide: All regions = $18M
Forecast Accuracy Metrics
- Forecast vs Actual: Did we hit the $18M target? (Actual: $16.2M = 90% accuracy)
- Pipeline Coverage: Pipeline value / Quota (Healthy = 3x coverage)
- Win Rate Variance: Expected 30% win rate, actual 25% → Adjust next quarter
Example: Q1 Forecast Review
Scenario: Sales Manager reviews pipeline on Jan 15
- Total Pipeline: 40 opportunities, $6M total value
- Weighted Forecast: $1.8M (based on stage probabilities)
- Commit Forecast: $1.2M (Negotiation+ only)
- Already Closed: $400K
- Gap to Quota: $2M quota - $1.2M commit = $800K gap
- Action: Accelerate 5 top opportunities, add new leads