Electricity: Full Value Chains — What It Is Made Of and What It Became Part Of (v3, ~1900)
A systemic decomposition: 5 parallel industry chains + cross-cutting layers of labor and logistics. Lighting and the electric motor reconstructed downstream.
cases/03-market-formation-2026-05 · S2b full value chains · anchor ~1900
13 deep tracksUPSTREAM · 5 chainsDOWNSTREAM · 9 industriesMcKinsey style
Graph A — Upstream
What it is made of and how it is produced: extraction → processing → equipment manufacturing → transmission → CORE
Five columns left to right + two cross-cutting bottom bands (labor · logistics). Each inbound branch is a distinct industry with its own value chain.
Extraction / raw materialsProcessingElectrical equipment manufacturingTransmission and deliveryCoreCross-cutting layers
Electrolysis loop (the ALCOA loop): current ← electrolysis → refines copper / smelts aluminum → back into wire. Electricity is a reagent in its own supply chain.
Graph B — Downstream
What it became part of: CORE → technology nodes → new industries
Electricity enters the economy through technology nodes (the precise mode of entry) and creates or reshapes industries. Lighting and the electric motor are the reconstructed killer nodes.
CoreTechnology nodesIndustries
The bridge between upstream and downstream: delivering current (the grids) and manufacturing equipment (branches C, D) are themselves major new industries born of electricity. Upstream and downstream are interwoven: electrical-equipment manufacturing and the grids are both "what it is made of" and "what it gave rise to."
Systematization
What this gives us
Electricity is a system, not a material. 5 parallel industry chains (fuel · conversion · equipment manufacturing · transmission · materials) + 2 cross-cutting layers (labor · logistics). Each branch unfolds as a full chain: extraction → processing → manufacturing → delivery.
Where the margin is. Not in raw materials, but in equipment manufacturing backed by a patent pool (GE/WH), in the copper bottleneck (electrolytic refining), in the patented component (silicon Si-steel, the turbine), and in the downstream "elevator" nodes.
Transfer to your bet. When mapping the AI upstream (chips · data · energy · algorithms · production of tools/engines · delivery/inference · labor/training · data logistics), look for your own analog of "equipment manufacturing with a patent pool" and of the "bottleneck" — and identify which downstream "elevator" to open.