About & Methodology

How scores are calculated, where data comes from, and how to use the platform.

Project Overview

Strategic Industrial Intelligence is an open-source dashboard for U.S. industrial base health and supply chain dependencies across national security sectors. It provides a map-first interface for exploring critical mineral supply chains, defense manufacturing capacity, energy infrastructure, and global logistics.

The platform uses exclusively public data. No classified or proprietary inputs are used. Anyone can reproduce the analysis. All scores are relative rankings, not absolute predictions — they provide structural insight into where vulnerabilities exist.

Users switch between sector “lenses” (Metals & Mining, Manufacturing, Energy, Logistics) and the map transforms to show that sector's data. The unique value is cross-sector connection mapping: click on a mineral and see which manufacturing sectors depend on it.

Scoring Principles

Transparency

Every score is decomposable. Users can click through to see exactly which inputs produced which number.

Public data only

No classified or proprietary inputs. Anyone can reproduce the analysis.

Directional, not precise

Structural insight, not precision forecasting. All scores are relative rankings.

Cross-sector awareness

Scores reflect dependencies between sectors where possible.

Metals & Mining Scoring

HHI (Herfindahl-Hirschman Index)

HHI = Σ(market_share_i²) for all countries i

Range: 0.0 (perfect competition) to 1.0 (monopoly). Applied per mineral per supply chain stage (mining, processing, refining).

Concentration Risk (0–100)

concentration_risk = (0.25 * HHI_mining + 0.40 * HHI_processing + 0.35 * HHI_refining) * 100

Processing weighted highest: hardest to replicate, where China has invested most aggressively.

Adversary Dependency (0–100)

adversary_share = Σ(share_i) for i in {China, Russia, Iran, North Korea, ...}
adversary_dependency = (0.25 * adv_mining + 0.40 * adv_processing + 0.35 * adv_refining) * 100

Measures total share of supply controlled by adversary nations across all stages.

Single Source Risk (boolean)

True if any country controls >50% of any supply chain stage

Overall Mineral Risk (0–100)

overall_risk = (0.30 * concentration_risk +
                0.25 * adversary_dependency +
                0.20 * import_dependency +
                0.15 * defense_criticality_score +
                0.10 * substitutability_penalty)

Manufacturing Health Scoring

Sector Health Score (0–100, per NAICS sector)

ComponentWeightSourceMeasures
Capacity utilization0.30FREDAre factories running? 80%+ = healthy
Employment trend0.25BLSGrowing = positive (3-year trend)
Output trend0.20Census ASMValue of shipments trend (3-year)
Geographic diversity0.15BLS/CensusHHI of employment by state
Investment pipeline0.10IndustrialSage/CHIPSNew facilities announced or under construction

Defense Concentration Risk (0–100)

defense_concentration = (
  0.40 * contract_hhi +
  0.30 * sole_source_pct +
  0.30 * facility_density
)

Higher score = more concentrated = higher risk. Measures how much critical defense manufacturing is concentrated in a single area.

Cross-Sector Disruption Modeling

A disruption scenario consists of a trigger (country X restricts resource Y), direct impact (supply drops by N%), cascade analysis (which downstream sectors depend on Y), severity assessment (based on substitutability and stockpile levels), and estimated recovery time.

Trigger: China restricts gallium exports
→ Direct: Gallium supply drops 98%
→ Cascade: Semiconductor fabs lose feedstock
→ Cascade: Radar/EW systems lose GaAs components
→ Severity: Critical (no near-term substitutes)
→ Recovery: 5–8 years

Explore scenarios interactively on the Disruption Scenarios page.

Confidence Levels

High

Based on structured, regularly updated government data (FRED, EIA, USGS, USAspending).

Medium

Based on compiled public reports and estimates (munitions rates, reshoring announcements).

Low

Based on press reports, expert estimates, or extrapolation (sub-tier suppliers, stockpile adequacy).

Data Sources

USGS Mineral Commodity Summaries

2025

Production, trade, and reserve data for 90+ minerals.

FRED (Federal Reserve Economic Data)

Current

Capacity utilization, industrial production indices.

BLS (Bureau of Labor Statistics)

Current

Manufacturing employment by sector and state.

Census Bureau (County Business Patterns / ASM)

2022-2023

Establishment counts, employment, and output by NAICS code.

USAspending.gov

FY2024

Federal contract obligations including DoD contracts by state.

World Bank Open Data

2022

Manufacturing value added, GDP composition by country.

MSHA (Mine Safety & Health Administration)

Current

Active mine locations, operators, employment, commodities.

DOE Loan Programs Office

Current

Loan guarantees for critical mineral and energy projects.

EIA (Energy Information Administration)

Current

Electricity generation, capacity, fuel mix, and grid data.

UNCTAD Review of Maritime Transport

2024

Shipping fleet statistics, port throughput, chokepoint data.

CRS/GAO Reports

Various

Shipbuilding assessments, defense industrial base studies, sealift capacity.

How to Use

1

Choose a sector lens

Use the pills at the top of the map (or press 1-4) to switch between Metals & Mining, Manufacturing, Energy, and Logistics.

2

Explore the sidebar

The left panel lists entities for the active lens, sorted by risk. Click any item to see its detail panel.

3

Drill into details

The right panel shows risk scores, supply chain breakdown, trade data, defense applications, and linked cross-sector dependencies.

4

Use the map

Markers show mine locations, shipyards, investments, and trade flow arcs. Toggle layers with the controls in the bottom-left corner.

5

Search anything

Press / to focus the search bar. Find minerals, sectors, facilities, investments, or defense programs by name.

6

Compare minerals

Visit the Compare page to see side-by-side risk scores for any two minerals.

Keyboard Shortcuts

/Focus search
EscClose panel / blur search
1Metals & Mining
2Manufacturing
3Energy
4Logistics

Known Limitations

  • 1.No classified data. Cannot replicate DoD internal tools (Govini, Advana, SCREEn). Sub-tier supplier data is not available publicly.
  • 2.Data lag. FRED is ~2 weeks. Census ASM is ~2 years. USGS is ~1 year. We show structural trends, not current-day status.
  • 3.Processing/refining data is weakest. USGS tracks production, not processing capacity. This is the biggest blind spot in critical minerals analysis globally.
  • 4.Munitions data is approximate. Production rates assembled from press reports, not official databases.
  • 5.Scores are relative, not absolute. A score of 75 means "high risk relative to other entities in this dataset," not "75% probability of disruption."
  • 6.No demand-side modeling. We show supply concentration but not consumption patterns or inventory levels (mostly classified for defense).

Public data only. No classified inputs. MIT License.