Sales Forecasting
A forecast the leadership can actually trust.
Workflow
Step 1Historical Analysis
ObjectiveLearn from the past.
InputHistory, results
OutputBaseline
Key activities
Analyze conversion, cycles, accuracy
Decision points
What has happened before?
Tools: AnalyticsRoles: Analytics
Success: Baseline known
Quality gate: Go: history clear. Loop back: no data.
Why it matters
- The forecast drives hiring, spend, and investor expectations. A trustable forecast is a strategic asset; a hope is a liability.
Best practices
- Forecast from stage and evidence, not rep optimism.
- Run scenarios — base, best, worst.
- Review and challenge the number weekly.
- Measure accuracy and feed it back.
Common mistakes
- Averaging incompatible rep guesses.
- No reconciliation of forecast vs. actual.
- Forecast games — sandbagging or inflation.
Key questions
- What evidence supports each committed dollar?
- What would change the forecast?
Agents that drive this
Forecast AnalyserPipeline Auditor
Tools we use · alternates in [ ]
Metabase[ Looker Studio, Power BI, Grafana ]HubSpot[ Salesforce, Pipedrive, Attio ]