revenue-forecasting-pipeline
Revenue forecasting orchestrator covering pipeline ingestion, scenarios, and variance reporting
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Revenue forecasting orchestrator covering pipeline ingestion, scenarios, and variance reporting
Installation
npx claude-plugins install @gtmagents/gtm-agents/revenue-forecasting-pipeline
Contents
Folders: agents, commands, skills
Included Skills
This plugin includes 3 skill definitions:
executive-briefs
Use to craft concise revenue updates for executives and boards.
View skill definition
Executive Brief System Skill
When to Use
- Delivering forecast updates to ELT or board audiences.
- Summarizing revenue risks/opportunities with clear asks.
- Packaging meeting-ready decks or memos that pull from forecast + variance analysis outputs.
Framework
- Audience Lens – capture what the audience cares about (growth, margin, cash, runway) and tailor tone.
- Story Arc – set context, state the headline (ahead/behind), outline drivers, and present mitigation plan.
- Evidence Layer – include key charts/tables with consistent formatting + footnotes.
- Decision & Ask – specify what approval, resource shift, or unblock is needed.
- Appendix & Audit Trail – link to deeper dashboards, logs, and forecast files for transparency.
Templates
- One-slide executive summary (headline, numbers, drivers, actions).
- Board memo outline (context, highlights, lowlights, requests).
- Risk register snippet for ongoing tracking.
Tips
- Use consistent metric definitions and color-coding to avoid confusion.
- Keep main section under one page/slide, move detail to appendix.
- Reference
variance-analysisfindings andforecast-modelingassumptions in footnotes.
forecast-modeling
Use when designing, tuning, or auditing revenue forecast models.
View skill definition
Forecast Modeling System Skill
When to Use
- Launching new forecasting cadences or revisiting methodology.
- Running scenario planning ahead of board meetings or budget cycles.
- Auditing deviations between forecast, pipeline, and actuals.
Framework
- Method Selection – pick bottom-up CRM, top-down macro, cohort, or blended models and document assumptions.
- Driver Mapping – define win rates, velocity, expansion, churn, pricing, and seasonality inputs.
- Scenario Logic – establish base/upside/downside cases with tunable levers for sensitivity analysis.
- Model Governance – list data sources, refresh cadence, validation checks, and ownership.
- Output Packaging – standardize tables, charts, and narrative prompts for exec review.
Templates
- Driver tree diagram connecting levers to KPIs.
- Scenario sheet (assumption → base/upside/downside values).
- Model QA checklist (data freshness, formula audits, version history).
Tips
- Keep raw inputs + assumptions in version control for auditability.
- Pair with
variance-analysisskill to recalibrate after each cycle. - Automate sensitivity runs to answer “what-if” questions during reviews.
variance-analysis
Use to attribute forecast vs actual deltas and recommend remediation
View skill definition
Revenue Variance Analysis Skill
When to Use
- Preparing forecast reviews or board updates that require variance explanations.
- Investigating misses/exceeds across segments, products, or channels.
- Prioritizing remediation plays tied to specific variance drivers.
Framework
- Driver Taxonomy – classify deltas into volume, conversion, price/mix, churn, expansion, currency.
- Attribution Logic – define formulas for each driver and maintain consistent baselines.
- Root Cause Layer – connect drivers to operational issues (pipeline quality, capacity, enablement, macro).
- Action Mapping – translate each root cause into specific plays with owners and expected impact.
- Feedback Loop – update forecasting assumptions once variance is understood.
Templates
- Variance waterfall chart setup instructions.
- Driver worksheet (metric → delta → driver → root cause → owner → due date).
- Remediation tracker with status and forecast impact.
Tips
- Keep a glossary so stakeholders interpret drivers consistently.
- Combine quantitative attribution with qualitative context from GTM leaders.
- Feed learnings back to
forecast-modelingto tighten assumptions next cycle.