Supply Chain

Market-cap & supply-chain intelligence, auto-updated

Executive summary — Supply Chain is an interactive market-intelligence map of the dependency networks behind the world's 100 largest public companies by market capitalization. Analysts, strategists, and risk teams use it to trace upstream inputs, service and channel partners, demand relationships, and credit-rating context — with every relationship carrying a source link and a confidence level. Market-cap rankings refresh automatically each week, so the picture stays current without manual upkeep.

✨ Highlights

• Interactive D3 network graph of the top-100 public companies, organised by economic layer (semiconductors → materials → industrials → finance → consumer demand) and country.
• Per-company profile cards mapping each anchor company's upstream inputs, services & risk, channels, and demand relationships.
• Source-linked provenance on every edge — relationships carry an originating source and a stated confidence band (e.g. high (company disclosure), medium (source-backed)).
• Credit-rating overlay generated from a dedicated ratings dataset for additional risk context.
• Auto-updating market caps — a scheduled GitHub Actions workflow refreshes rankings weekly, validates the result, and commits only when the data actually changed.
• Zero-backend, static delivery — vanilla JavaScript + D3 served from GitHub Pages; nothing to provision, fast to load.
• Test-guarded data integrity — a Node test suite enforces provenance wiring, confidence scoring, country-code hygiene, and UI integrity before anything ships.

🖼️ Preview

🧭 What it does

Supply Chain turns a flat market-cap leaderboard into a navigable dependency graph. It answers questions a ranked list cannot: who supplies the suppliers, where the concentration sits, and how confident we are in each link.

Global map. The landing view is a force-directed D3 graph of 100 anchor companies positioned across ten economic layers and coloured by country of domicile. Node size and labels carry rank and market cap; edges encode layer-adjacency and structural relationships.

Company profiles. Selecting a company opens a focused sub-graph centred on that firm, decomposed into tiers — Upstream Inputs, Services & Risk, the Company anchor, Channels, and Demand. Each node states what it represents and why it matters to the anchor.

Risk context. A credit-ratings overlay adds rating context on top of the structural map, helping analysts weigh exposure alongside topology.

Trust signals. Confidence bands and source references are first-class — surfaced in the UI rather than buried in a data file — so an analyst can see how much to trust a given relationship at a glance.

🗂️ Data & provenance

Per Monarch Castle doctrine — evidence before assertion. Supply Chain is built so that no number stands alone:

• Market-cap rankings are sourced from companiesmarketcap.com (public CSV export). The dataset's meta block records the originating source URL and a lastUpdated / generatedAt timestamp on every regeneration.
• Credit ratings are generated from a dedicated ratings pipeline (Fitch public search endpoint) into data/credit-ratings.*, with the source endpoint recorded in the data.
• Relationship-level provenance. Each profile node and link carries a sourceId and a confidence label (for example high (company disclosure), medium (source-backed), medium (structural)), so collection method and trust level travel with the datum.
• Auditability. The auto-update workflow timestamps backups and commits, and validation tests run before any refreshed data is published — keeping the source → extraction → store → dashboard chain intact and reproducible.

Lawful collection only: data is drawn from open, publicly accessible sources and official-style endpoints; provenance and confidence are preserved end-to-end as the product's core value.

🛠️ Tech stack

• Frontend / visualisation: Vanilla JavaScript + D3.js 7 (CDN-loaded), modular js/ packages — viz, ui, data, trust, analytics.
• Styling: Hand-authored CSS (styles/base, layout, components, theme).
• Data tooling: Node.js 20+ ES-module scripts (scripts/) for generation, market-cap updates, ratings fetch, macro data, and verification.
• Testing: Node's built-in test runner (node --test) plus Playwright for mobile/keyboard and UI integrity checks.
• Automation: GitHub Actions — auto-update-data.yml (weekly market-cap refresh) and deploy-pages.yml (static build & deploy).
• Hosting: GitHub Pages (static _site artifact).

🚀 Getting started

Live site: https://monarchcastletech.github.io/supplychain/

Run locally

npm install
npx http-server . -p 8080
# open http://localhost:8080

Regenerate / refresh data

node scripts/generate-top100-data.mjs     # build the top-100 company map
node scripts/update-marketcap-data.mjs     # refresh market caps and merge profiles
node scripts/fetch-fitch-ratings.mjs       # build the credit-ratings dataset
node scripts/verify-data.mjs               # run data verification checks

Test

npm test                                    # full data + UI integrity suite
node --test tests/profile-link-metadata.test.mjs   # focused run

Deploy. Pushing to master triggers deploy-pages.yml, which assembles the static site (index.html, data/, js/, styles/, assets/) and publishes it to GitHub Pages. Market-cap data refreshes automatically every Monday via auto-update-data.yml, committing only when values change.

🧱 Part of Monarch Castle

A product of Financial Intelligence · Monarch Castle Technologies — an operating company of Monarch Castle Holdings. Sister companies: Monarch Castle Technologies · Strategic Data Company of Ankara

📜 License

See LICENSE. © 2026 Monarch Castle Holdings · Ankara, Türkiye.

_{🏰 Monarch Castle Holdings — turning open-source noise into lawful, verified, decision-grade intelligence.}

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Interactive market-cap & supply-chain intelligence map for the top 100 public companies — D3 dashboard with source-linked provenance, auto-updated weekly.

Repository status

Lifecycle: Active. The badge and this statement describe maintenance status, not service availability.

Public access

Open the published project

Screenshots

The preview is maintained as a repository asset; the live interface or generated output remains authoritative.

Data and methodology

• FACTUAL_DATA_VERIFICATION.md

These repository-specific sources define the methodology or provenance boundary. Source dates, transformation steps, and known gaps must travel with analytical outputs.

Update frequency

The published data workflow targets a weekly refresh and records source-linked provenance.

Quick start

npm ci

python -m http.server 8080

Run only in a trusted development environment and review repository-specific prerequisites before using networked or hardware features.

Architecture

• js/ — repository-specific implementation, data, or configuration boundary.
• data/ — repository-specific implementation, data, or configuration boundary.
• scripts/ — repository-specific implementation, data, or configuration boundary.

Tests

npm test

Provenance

Original software history is maintained in Git. External datasets, reports, trademarks, screenshots, and assets are not relicensed by this repository; see THIRD_PARTY_NOTICES.md before reuse.

Forecast limitations

This repository does not publish a guaranteed forecast. Any scenarios, scores, or forward-looking language are analytical aids, not facts or advice; review source dates and methodology before use.

Security

Do not publish vulnerabilities in an issue. Use GitHub's private vulnerability-reporting flow when available, or follow the organization security policy.

License

Original repository code and documentation are available under MIT; see LICENSE. That license does not override third-party terms documented in THIRD_PARTY_NOTICES.md.

Citation

Use the machine-readable CITATION.cff. Cite the specific commit and, for analytical use, record the data or model snapshot date.

Masterbrand endorsement

Supply Chain Intelligence is a Monarch Castle Technologies project. Part of Monarch Castle Technologies.