# Industry Map — Supply & Value Chain ## ⚠️ Data Verification — Do This Before Any Analysis Before running any analysis, always retrieve the latest market data for the ticker: 1. **Fetch current price** — use web search or ask the user for the live price, 52-week range, and market cap. Never assume a price from training data. 2. **Confirm key figures** — recent earnings, revenue, key ratios (P/E, P/S, etc.) as applicable to this skill. 3. **State your data source** — note where the numbers came from (e.g., "Google Finance, June 19 2026") at the top of the output. 4. **Flag stale data explicitly** — if live data is unavailable, display this warning before proceeding: > ⚠️ **Live data unavailable.** The following analysis uses training-data estimates which may be significantly out of date. Verify all prices and metrics before making any decisions. Never silently substitute training-data estimates for current prices. When in doubt, ask the user to paste the latest quote. --- Draw an industry's supply and value chain as a directed graph — from raw inputs upstream all the way down to the end user — so you can take a **bird's-eye view of a business**, see where a company sits in the flow, understand where value and pricing power concentrate today, and reason about where they will migrate next. ## Overview Most analysis looks at one company in isolation. This skill zooms out and answers a different question: **"How does this whole industry actually work, layer by layer, and who captures the profit at each stage?"** A value chain is a **directed graph**: nodes are the layers of production (raw materials → components → integrators → platforms → distribution → end users), and edges point in the direction goods and services flow — from supplier to customer. Once the chain is drawn, three things become visible that a single-company view hides: 1. **Position** — is the target company upstream (inputs), midstream (integration/manufacturing), or downstream (distribution / end demand)? Position determines cyclicality, margin profile, and who has pricing power over whom. 2. **Chokepoints** — the layer(s) with the fewest credible suppliers capture disproportionate value. Following the chain reveals bottleneck monopolies (e.g. EUV lithography, leading-edge foundry) that are the real toll-collectors of a theme. 3. **Value migration** — the profit pool is not fixed. It shifts down (or up) the chain over time as scarcity moves. Mapping the chain lets you form a thesis about *where the money goes next* — the "picks-and-shovels" and second-order plays. This complements — and does not duplicate — the other frameworks. Competitor analysis studies one company's moat *horizontally* against its direct peers; sector analysis ranks the 11 GICS sectors for rotation. This skill maps a theme or product *vertically*, cutting **across** sectors, to show the whole flow. Output feeds naturally into competitor analysis (pick a node, study its moat), stock screening (rank the tickers at one layer), and charting / report generation (render the graph). --- ## 1. The Value Chain Model Every physical or digital product can be decomposed into ordered layers. Use this generic template and adapt the layer names to the specific industry: ``` UPSTREAM ───────────────► MIDSTREAM ───────────────► DOWNSTREAM (scarce inputs, (integration, manufacture, (distribution, demand, tools, IP) assembly, platforms) the end customer) Raw materials / inputs → Enabling tools & equipment → Components / sub-systems → Integrators / OEMs → Platforms / aggregators → Channel / distribution → End users / demand ``` **Node attributes** — for each layer, capture: - **Layer name** and what it does in one line - **Representative public tickers** (2–5) and any dominant private players - **Position tag**: `Upstream` / `Midstream` / `Downstream` - **Concentration**: how many credible suppliers exist (monopoly / oligopoly / fragmented) - **Value capture today**: does this layer earn high or thin margins right now? **Edge attributes** — for each arrow (supplier → customer): - Direction of flow (always supplier → the layer that buys from it) - Dependency strength (sole-source / multi-source / commodity) - Whether the buyer can integrate backward, or the supplier forward --- ## 2. Step 1 — Define the Scope Clarify what is being mapped. The input is usually one of three things: | Input type | Example | What to map | |---|---|---| | **A theme / product** | "AI compute", "electric vehicles", "GLP-1 drugs" | The full chain end-to-end | | **A single ticker** | NVDA | The chain around it, then locate it | | **A layer** | "memory", "foundry" | That layer + its immediate up/downstream neighbors | Confirm the boundaries: where does the chain start (how far upstream — mined ore? refined wafer?) and where does it end (the paying end user)? State the scope explicitly at the top of the output so the graph is bounded and legible. --- ## 3. Step 2 — Build the Chain Map (the graph) Produce the directed graph. **Default to a Mermaid `flowchart`** (renders in Claude, Cursor, Gemini, GitHub, and the site); fall back to ASCII when Mermaid is unavailable. Hand off to a charting step for a richer HTML render or for a report export. **Mermaid flowchart (primary output):** ```mermaid flowchart LR MAT["Materials & Substrates
(silicon, rare earths)"] --> EQ["Fab Equipment
ASML · LRCX · AMAT"] EQ --> FAB["Foundry / Fab
TSMC · INTC · Samsung"] FAB --> MEM["Memory
MU · Hynix · Samsung"] FAB --> GPU["GPU / Accelerators
NVDA · AMD"] MEM --> GPU GPU --> NET["Networking / Interconnect
AVGO · ANET"] NET --> CSP["Cloud / CSP
AMZN · MSFT · GOOGL"] CSP --> LAB["Model Labs
OpenAI · Anthropic"] LAB --> APP["AI Software / Apps"] APP --> USER["End Users
enterprise · consumer"] ``` **ASCII fallback:** ``` Materials ─► Fab Equipment ─► Foundry ─┬─► Memory ──┐ (ASML,LRCX,AMAT) (TSMC,INTC) │ ▼ └─► GPU/Accel (NVDA,AMD) ─► Networking (AVGO,ANET) │ End Users ◄─ AI Software ◄─ Model Labs ◄─ Cloud/CSP (AMZN,MSFT) ◄────┘ (enterprise, (OpenAI, (GOOGL) consumer) Anthropic) ``` **Chain map table** — accompany the graph with a table so the data is machine-readable and feeds the later steps: ``` Layer Position Key Tickers Concentration Value Capture (now) ────────────────────────────────────────────────────────────────────────────────────────── Materials/Substrates Upstream SHECY, SUMCF Fragmented Low Fab Equipment Upstream ASML, LRCX, AMAT Oligopoly/Monopoly High ◄ chokepoint Foundry Midstream TSMC, INTC Oligopoly High Memory Midstream MU, Hynix, Samsung Oligopoly Cyclical GPU / Accelerators Midstream NVDA, AMD Near-monopoly Very High ◄ chokepoint Networking Midstream AVGO, ANET Oligopoly High Cloud / CSP Downstream AMZN, MSFT, GOOGL Oligopoly Medium (capex heavy) Model Labs Downstream OpenAI, Anthropic Fragmenting Negative→? AI Software / Apps Downstream many Fragmented Emerging End Users Demand — — — ``` --- ## 4. Step 3 — Position Locator If the user supplied a ticker, pin it precisely: - **Which node** does it occupy? (a company may span several — e.g. Amazon is both CSP and end-market retailer) - **Its upstream dependencies**: who must it buy from, and how substitutable are they? (single-source dependency = risk) - **Its downstream customers**: who buys from it, how concentrated are they, and can they build it in-house or switch? - **Direction of pricing power**: does value flow *toward* this node (it can raise prices) or *away* (it is squeezed between a strong supplier and a strong buyer)? State the one-line takeaway: *"[Ticker] sits [upstream/mid/down] at the [layer] node; it depends on [supplier layer] and sells into [customer layer]; pricing power currently favors [node]."* --- ## 5. Step 4 — Chokepoint & Bottleneck Analysis This is where the alpha usually is. Walk the chain and score each layer for **bottleneck power** — the ability to hold up the entire chain: ``` Bottleneck Score (per layer, 0–10) = average of these four factors, each scored 0–10: - Supplier scarcity (fewer credible suppliers = higher) - Substitutability (no viable alternative = higher) - Switching cost / lead (longer to qualify a new supplier = higher) - Demand inelasticity (chain cannot proceed without it = higher) ``` Layers scoring high are **toll collectors**: they capture value regardless of who wins downstream. Classic examples to reason by analogy from: ASML (sole EUV supplier), TSMC (leading-edge foundry), NVDA + CUDA (accelerator + software lock-in). Explicitly flag: - **Where the bottleneck is today** - **Whether it is durable** or being competed / engineered away (second sources, in-housing, new architectures) - **The "arms dealer" thesis**: a bottleneck layer often wins no matter which downstream competitor prevails --- ## 6. Step 5 — Value-Pool & Margin Migration The profit pool is dynamic. Map where margin sits **now** and build a thesis for where it goes **next**: - **Current margin map**: which layer earns the fat gross/operating margins, and which is a thin-margin commodity pass-through? - **Scarcity shift**: today's bottleneck gets competed away or over-built; a new one forms elsewhere. (e.g. compute scarcity today → energy/power and data scarcity next; hardware margins → software/services over time.) - **Value migration direction**: is value moving **downstream** (toward platforms and apps as hardware commoditizes) or **upstream** (toward whoever controls the newly scarce input)? - **What to expect in the future**: name the layer likely to capture incremental value over the next 1–3 years and the *trigger* that would confirm it (capacity coming online, a standard emerging, an input going scarce). This is the section that turns a static picture into a forward-looking investment view. --- ## 7. Step 6 — Concentration & Supply-Chain Risk A chain view exposes fragility that a single-stock view misses: - **Single-source / single-region chokepoints** (e.g. Taiwan foundry concentration, rare-earth processing in one country) - **Geopolitical exposure**: export controls, tariffs, sanctions that could sever an edge in the graph - **Cascade risk**: if one upstream node fails, how far downstream does the disruption propagate? - **Inventory / bullwhip dynamics**: demand signals amplifying up the chain (over-ordering, then a glut) — especially in memory and components - **Customer concentration at each node**: a layer selling >30% to one downstream buyer inherits that buyer's fate --- ## 8. Step 7 — Investment Idea Generation Turn the map into a ranked idea list, organized by layer: ``` Layer Best-positioned names Rationale Idea type ──────────────────────────────────────────────────────────────────────────────────────── Bottleneck [tickers] Durable toll on the whole theme Core / "arms dealer" Direct winner [tickers] Obvious primary beneficiary Consensus long 2nd-order [tickers] Sells picks-and-shovels to winners Under-covered Squeezed [tickers] Caught between strong up/down Avoid / short candidate Optionality [tickers] Cheap exposure if value migrates Speculative ``` Flag the **non-obvious** node — the second-order supplier the market under-covers because it isn't a pure-play on the theme. Hand the shortlist to `stock-screener` to rank, to `competitor-analysis` to check each name's moat, or to `bear-case` to stress-test the consensus winner. --- ## 9. Worked Example — AI Compute Stack Reading the map above: - **Chokepoints**: Fab Equipment (ASML EUV monopoly) and GPU/Accelerators (NVDA + CUDA). These are the durable toll collectors today. - **Value pool now**: concentrated at the GPU and foundry layers; CSPs are absorbing heavy capex; model labs are largely unprofitable. - **Migration thesis**: as accelerator supply catches up, incremental scarcity shifts toward **power/energy and networking**, and value accrues to **software/inference** that monetizes the installed base. Watch for the trigger: accelerator lead times normalizing. - **Idea shape**: core = the bottleneck arms dealers; 2nd-order = power, cooling, interconnect, and HBM memory suppliers the market under-weights; avoid = undifferentiated app-layer names with no data moat. --- ## 10. How to Invoke Provide a theme, a ticker, or a layer, and (optionally) a focus: - **Map a full theme end-to-end** — "Map the AI compute supply chain." - **Map the chain around a ticker, then locate it** — "Where does NVDA sit in its value chain, upstream to downstream?" - **Focus on one layer + its neighbors** — "Map the semiconductor chain, focused on the memory layer." - **Emphasize where value migrates next** — "Map the EV value chain and tell me where the profit pool moves next." - **Emit a chart-ready graph spec** — "Map the GLP-1 drug supply chain and give me a diagram for a report." --- ## 11. Visualization Support When a visual is requested, provide graph specs ready for a charting / report-generation step: ### Chain Graph **Chart type**: Directed graph (Mermaid `flowchart LR` primary, ASCII fallback, graphviz/HTML for rich export). Nodes = layers with representative tickers; edges = supplier→customer flow. ### Value-Capture-by-Layer Bar **Chart type**: Horizontal bar — estimated gross/operating margin (or a 0–10 value-capture score) per layer, to show where the profit pool sits. ``` Layer Value-capture score (0–10) Fab Equipment [value] Foundry [value] GPU / Accelerators [value] Cloud / CSP [value] Model Labs [value] ``` ### Bottleneck Heat Row **Chart type**: Scorecard / heat row — bottleneck score per layer, highlighting the chokepoints. --- ## Output Provide an industry-map report with: - Executive Summary (scope, where value sits today, migration thesis — 3 sentences) - The Chain Map (directed graph + chain-map table) - Position Locator (if a ticker was given) - Chokepoint & Bottleneck Analysis (scored, with the durable toll-collectors named) - Value-Pool & Margin Migration (now → next, with the confirming trigger) - Concentration & Supply-Chain Risk - Investment Ideas by layer (core / 2nd-order / avoid) - Investment Implications and how this feeds `competitor-analysis` / `stock-screener` / `bear-case` work ## Standard Signal Output All analysis concludes with this standardized block: ``` ## Thesis Invalidation After delivering the analysis signal, specify what would reverse it: **If signal is BULLISH — thesis breaks if:** - Price closes below the MA200 / key support level identified in this analysis on above-average volume - the mapped chokepoint is broken (credible second source qualifies, or a customer in-sources) OR value migrates away from the node you favored - Macro regime shift: Fed pivots hawkish unexpectedly, recession probability >60% **If signal is BEARISH — thesis breaks if:** - Price closes above key resistance / MA200 level with volume confirmation - the node re-establishes a durable bottleneck OR a new scarce input forms in its favor - Fundamental improvement: surprise earnings beat >20% with guidance raise **Re-run this analysis when:** - [ ] Next earnings release - [ ] Price moves ±15% from current level - [ ] 60 days have elapsed - [ ] Material news event (acquisition, leadership change, regulatory decision) ╔══════════════════════════════════════════════╗ ║ INVESTMENT SIGNAL ║ ╠══════════════════════════════════════════════╣ ║ Signal: BULLISH / NEUTRAL / BEARISH ║ ║ Confidence: HIGH / MEDIUM / LOW ║ ║ Horizon: SHORT / MEDIUM / LONG-TERM ║ ║ Score: X.X / 10 ║ ╠══════════════════════════════════════════════╣ ║ Action: BUY / HOLD / SELL ║ ║ Conviction: STRONG / MODERATE / WEAK ║ ╚══════════════════════════════════════════════╝ ``` Score Guide: 8.0–10.0 Strongly Bullish | 6.0–7.9 Moderately Bullish | 4.0–5.9 Neutral | 2.0–3.9 Moderately Bearish | 0.0–1.9 Strongly Bearish Confidence: HIGH (strong data, clear signals) | MEDIUM (mixed signals) | LOW (limited data, conflicting signals) Horizon: SHORT-TERM (1 week–3 months) | MEDIUM-TERM (3 months–1 year) | LONG-TERM (1+ years) **Disclaimer:** Educational analysis only. Not financial advice.