Forecast Mechanics
Core Premise: Forecasting is not prediction. It is pattern recognition. Accurate forecasts require separating commit from upside from fantasy. The Commit Protocol enforces evidence standards.
The Prediction Problem
The word "forecast" implies prediction. This framing is wrong.
Forecasting is not prediction. It is aggregation.
A forecast aggregates evidence from individual deals. The accuracy depends entirely on the quality of that evidence.
The Commit Protocol
Remotir's Commit Protocol replaces subjective assignment with evidence requirements.
Category Definitions
Commit: Will close this period.
Evidence required: - Verbal commitment from economic buyer (documented) - Contract in legal/procurement process - No outstanding objections or blockers - Close date confirmed by buyer
Upside: Should close this period, pending resolution of identified factors.
Evidence required: - Champion has confirmed intent to recommend - Decision timeline within the period - Budget has been identified - Known factors to resolution are documented
Best Case: Could close this period if conditions align.
Evidence required: - Opportunity is qualified - Buyer has expressed intent to move forward - Timeline is plausible - Factors to resolution are not fully identified
The Evidence Chain
- Commit = Upside + economic buyer verbal + contract in process
- Upside = Best Case + champion committed + budget confirmed + timeline set
- Best Case = Qualified + buyer intent + plausible timeline
Movement up the chain requires evidence addition.
The Weighted Probability Matrix
| Category | Typical Conversion | Range |
|---|---|---|
| Commit | 90-95% | 85-98% |
| Upside | 55-70% | 45-75% |
| Best Case | 20-35% | 15-40% |
Building the Forecast
- Categorize - Every in-period deal assigned based on evidence
- Weight - Multiply deal value by category probability
- Sum - Aggregate weighted values
The Confidence Interval
Floor: Commit × 85% + Upside × 45% + Best Case × 15% Ceiling: Commit × 98% + Upside × 75% + Best Case × 40%
Forecast Cadence
Weekly: Review and update category assignments, new evidence, deals at risk.
Monthly: Compare current to beginning-of-period forecast, analyze accuracy, recalibrate.
Quarterly Post-Mortem: What was forecasted vs. actual? What process changes would improve accuracy?
Case Study: The Forecast Transformation
A Remotir client ($40M ARR) had forecast accuracy averaging 71%.
Audit findings: - 60% of "Commit" deals lacked documented economic buyer commitment - 45% of "Upside" deals had no confirmed decision timeline - Category assignment was based on rep confidence, not evidence
After implementing the Commit Protocol: - Forecast accuracy improved from 71% to 92% - Commit conversion rose from 78% to 94% - Category migration decreased from 35% to 12%
The company did not get better at predicting. They got better at gathering evidence.