skills/industry-competition/references/modules/M031-industry-structure-mapping.md

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<!-- Module: 031 | Title: Industry Structure Mapping -->

## PART VII - INDUSTRY AND COMPETITIVE ANALYSIS | MODULE 031

# Industry Structure Mapping

> Mission. Map value chains, profit pools, bottlenecks, substitutes, regulators, and bargaining power.

## Decision output

Objective: Map value chains, profit pools, bottlenecks, substitutes, regulators, and bargaining power. The completed work product must be reproducible from evidence, show the downstream financial or decision effect when material, state the strongest contrary case, and define a dated update rule.

## Explicit operating procedure

1. Draw the full value chain from raw input/capital to end customer, including suppliers, manufacturers/service providers, distributors, platforms, regulators, complements, and substitutes.

1. Estimate revenue and profit pools by layer and identify where bargaining power causes economics to migrate over time.

1. Map concentration, switching costs, capacity, cost curves, contract terms, standards, regulation, and customer procurement to determine the marginal price setter.

1. Identify bottlenecks and scarce complements that can capture disproportionate value even when the visible end market grows rapidly.

1. Separate structural industry economics from the current cycle by showing what changes when capacity is tight versus abundant.

1. Update the map when technology, vertical integration, new regulation, or business-model innovation changes who controls the customer or critical resource.

## Required evidence and model bridge

- Primary-source set: peer filings, industry data, regulator data, channel evidence, technology roadmaps. Preserve exact document/version, date, period, and source location for every material factual input used in industry structure mapping.

- For each key concept - value chain, profit pools, marginal producer, customer/supplier power, capacity, bottlenecks - state whether it is a reported fact, analyst calculation, management claim, external estimate, or judgment. Quantitative concepts must retain raw components and units; qualitative concepts must retain the specific evidence and counterevidence.

- Map only economically relevant findings into the model or decision record. Process-control modules such as industry structure mapping may have no direct valuation line; in that case document the downstream error or governance risk the control prevents.

## Metrics and calculation controls

| Metric / concept | Construction | Required validation |
| --- | --- | --- |
| profit-pool share | Company operating profit or economic profit divided by total estimated industry/value-chain profit pool for the same scope and period. | profit-pool share: Recalculate from same-scope numerator and denominator; confirm period, units, cohort/geography, and issuer definition; reconcile material differences to filings or operating data. |
| demand/capacity | Expected demand units divided by effective industry capacity units after utilization, downtime, yields, and committed additions; track forward by period. | demand/capacity: Tie physical/operating units to company disclosures or source-system data; reconcile beginning/ending populations where applicable and test scope, ownership, and period consistency. |
| concentration | Top-customer, supplier, geography, product, or channel exposure divided by the relevant total; report top-1, top-5, and HHI when data permit. | concentration: Recalculate from same-scope numerator and denominator; confirm period, units, cohort/geography, and issuer definition; reconcile material differences to filings or operating data. |



## Worked application

> Case: the bottleneck in AI infrastructure moves from chips to power equipment.

- Reconstruct the relevant reported fact from primary evidence before interpreting the case. For industry structure mapping, show the raw components rather than only the resulting ratio or narrative.

- Build the causal chain through value chain, profit pools, marginal producer, customer/supplier power, then identify which link is directly observed and which link remains an assumption.

- Calculate profit-pool share, demand/capacity, concentration from sourced components under the reported/base interpretation and at least one skeptical alternative interpretation.

- Translate the difference between cases into the variable that matters for industry structure mapping: evidence quality, revenue, operating profit/NOPAT, free cash flow, invested capital, financing/dilution, risk, or valuation. Mark non-applicable links instead of inventing them.

- Expert consistency test: track where the constraint moves because that is where incremental economics can migrate.

- Precommit the specific future filing, KPI, customer/supplier observation, regulator action, or market input that would materially invalidate the industry structure mapping conclusion.

## Failure tests

- FAIL if value chain cannot be defined and reproduced from the source pack.

- FAIL if the value-chain map omits a layer that controls a material bottleneck, standard, customer relationship, input, or profit pool.

- FAIL if the industry structure mapping conclusion depends on an unstated assumption, unreconciled definition, or evidence that cannot be traced to its source/version.

- FAIL if evidence materially inconsistent with the industry structure mapping conclusion is omitted, reclassified, or dismissed without a documented definition, materiality, causal, timing, and source-quality analysis.

## Completion test

A senior reviewer must be able to reproduce the industry structure mapping conclusion, vary the most sensitive assumption independently, trace the change through the model, understand the strongest opposing case, and identify the next evidence that would force an update. If any link is missing, the module remains open.