Command: ingest-pipeline

command

Aggregates CRM/MAP data, cleans records, and prepares forecast-ready pipeline views.

# Command: ingest-pipeline

## Inputs
- **timeframe** – forecast period (Q1, Q2, FY, rolling-90).
- **segments** – comma-separated list of segments or regions.
- **detail** – summary | full output verbosity.
- **filters** – optional stage, product, or owner filters.
- **refresh** – optional flag to force data refresh vs cached snapshot.

## Workflow
1. **Data Extraction** – pull CRM opportunities, bookings actuals, MAP signals, and enrichment fields by timeframe.
2. **Normalization & QA** – dedupe, enforce stage definitions, check close dates, align currencies, and flag missing data.
3. **Scoring & Cohorting** – compute coverage, velocity, win rate assumptions, and stage-based risk scores.
4. **Segmentation** – split pipeline by segment, region, product, partner, and channel.
5. **Packaging** – output structured tables + dashboards for forecast architect + finance partner review.

## Outputs
- Pipeline dataset (CSV/Sheets) with commit/upside/sandbag buckets.
- Data quality log detailing issues resolved or pending.
- Snapshot summary (coverage %, attainment, risk flags) per segment.

## Agent/Skill Invocations
- `revops-analyst` – runs extraction + QA steps.
- `forecast-modeling` skill – provides scoring templates and coverage math.
- `variance-analysis` skill – tags known risk cohorts for later tracking.

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Command: ingest-pipeline

Inputs

timeframe – forecast period (Q1, Q2, FY, rolling-90).
segments – comma-separated list of segments or regions.
detail – summary | full output verbosity.
filters – optional stage, product, or owner filters.
refresh – optional flag to force data refresh vs cached snapshot.

Workflow

Data Extraction – pull CRM opportunities, bookings actuals, MAP signals, and enrichment fields by timeframe.
Normalization & QA – dedupe, enforce stage definitions, check close dates, align currencies, and flag missing data.
Scoring & Cohorting – compute coverage, velocity, win rate assumptions, and stage-based risk scores.
Segmentation – split pipeline by segment, region, product, partner, and channel.
Packaging – output structured tables + dashboards for forecast architect + finance partner review.

Outputs

Pipeline dataset (CSV/Sheets) with commit/upside/sandbag buckets.
Data quality log detailing issues resolved or pending.
Snapshot summary (coverage %, attainment, risk flags) per segment.

Agent/Skill Invocations

revops-analyst – runs extraction + QA steps.
forecast-modeling skill – provides scoring templates and coverage math.
variance-analysis skill – tags known risk cohorts for later tracking.