Catalyst Analytics R
Catalyst Analytics R is a reproducible analysis layer for Sustainable Catalyst—built for scenario work, indicator computation, and auditable exports.
It’s designed to pair with Catalyst Data so results remain traceable.
Principle: an analysis isn’t “real” unless someone else can rerun it and get the same answer.
A visual representation of Catalyst Analytics R, combining statistical modeling, reproducible analysis, and analytical communication.
What it is
Catalyst Analytics R is an R-based workflow layer for building decision-quality analysis: consistent inputs, explicit assumptions, reproducible outputs, and clear documentation.
It favors stability and interpretability over black-box automation.
- Indicator computation — define, calculate, and version metrics
- Scenario analysis — structured what-if exploration
- Exports — tidy outputs and artifacts that travel
- Reproducibility — scripts, methods, and assumptions that can be reviewed
Why it matters
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Reproducibility over analysis theater
Slide decks and dashboards often hide assumptions. Catalyst Analytics R makes methods and steps visible so results can be checked, rerun, and improved.
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Scenario thinking, not fake prediction
Sustainability and finance decisions live under uncertainty. This tool is built for what-if reasoning and tradeoffs, not pretending to forecast the future perfectly.
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Consistent indicators
Indicators are only useful if definitions remain stable and changes are recorded. Analytics R supports consistent computation and versioned methods.
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Exports that travel
Outputs should be portable: clean tables, clear metadata, and artifacts that can be shared without losing context.
What it does
Catalyst Analytics R focuses on repeatable workflows. Typical components include:
- Ingest — pull measurements from Catalyst Data, or structured exports
- Transform — tidy pipelines with transparent definitions and units
- Compute — indicators, ratios, indices, and derived metrics
- Test — validation checks to catch missing values and broken assumptions
- Model — scenario runs with stated parameters
- Export — tables and documentation artifacts for review and reuse
How it connects to other modules
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Catalyst Data
Provides the shared system of record: entities, sources, indicators, and measurements that keep analytics grounded.
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Global Impact Catalyst
Uses indicator pipelines and reproducible workflows for reporting, evaluation, and scenario work.
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Catalyst Finance
Applied microeconomics and pricing analytics can be implemented as reproducible workflows with explicit assumptions.
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Infrastructure
Analytics R relies on shared standards: provenance, documentation discipline, and durable outputs.
Boundaries
Catalyst Analytics R is not a managed analytics service, not a real-time data feed, and not a replacement for domain judgment.
It’s a reproducible workflow layer designed to keep methods visible and outputs reviewable.