git:20260712.2481042 to git:20260924.b016647

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description: Map an industry's supply / value chain as a directed graph — upstream to downstream — to locate a company's position, find chokepoints and margin pools, and surface second-order investment ideas

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# 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.

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 ⚠️ **Live data unavailable.** The following analysis uses training-data estimates which may be significantly out of date.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 existing skills. `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-screener` (rank the tickers at one layer), and `chart-master` / `report-generator` (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 `chart-master` for a richer HTML render or for a `report-generator` export.

**Mermaid flowchart (primary output):**

```mermaid

flowchart LR

MAT["Materials & Substrates<br/>(silicon, rare earths)"] --> EQ["Fab Equipment<br/>ASML · LRCX · AMAT"]

EQ --> FAB["Foundry / Fab<br/>TSMC · INTC · Samsung"]

FAB --> MEM["Memory<br/>MU · Hynix · Samsung"]

FAB --> GPU["GPU / Accelerators<br/>NVDA · AMD"]

MEM --> GPU

GPU --> NET["Networking / Interconnect<br/>AVGO · ANET"]

NET --> CSP["Cloud / CSP<br/>AMZN · MSFT · GOOGL"]

CSP --> LAB["Model Labs<br/>OpenAI · Anthropic"]

LAB --> APP["AI Software / Apps"]

APP --> USER["End Users<br/>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, or `competitor-analysis` to check each name's moat, or `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. Input Formats

```

# Map a full theme end-to-end

/industry-map "AI compute"

# Map the chain around a ticker, then locate it

/industry-map NVDA

# Focus on one layer + its neighbors

/industry-map semiconductors --layer memory

# Emphasize where value migrates next

/industry-map "electric vehicles" --focus value-migration

# Emit chart-ready graph spec for a report

/industry-map "GLP-1 drugs" --visual

```

---

## 11. Visualization Support

When `--visual` is used, provide graph specs ready for `chart-master` / `report-generator`:

### 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`

## 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.