Read an industry's structure through Porter's Five Forces with documented signals per rating, ending at the profit pool. Use when weighing market entry or when margins erode and nobody can say why.
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[industry or segment, and the decision it supports]
description
Read an industry's structure through Porter's Five Forces with documented signals per rating, ending at the profit pool. Use when weighing market entry or when margins erode and nobody can say why.
intent
An evidence-cited five-forces read: rivalry, new entrants, substitutes (with AI-driven substitution named explicitly), buyer power, and supplier power โ each force rated weak/moderate/strong with the documented signals that justify the rating, closing with where the profit pool sits and who is squeezing it.
type
workflow
theme
market-intelligence
best_for
["Pressure-testing a market-entry decision against the industry's actual structure","Explaining margin erosion structurally instead of blaming execution","Grounding strategy debates in rated forces with evidence, not vibes"]
scenarios
["We're considering entering the clinical-data-management space โ what does its structure do to everyone who plays?","Our margins keep compressing and every explanation is tactical; give me the structural read"]
estimated_time
25-40 min per run
Porter's Five Forces (Evidence-Cited)
Purpose
Read an industry's structure through Porter's Five Forces, with evidence: search plan โ
force-by-force ratings with signals โ profit-pool implication โ next-step options. Each force โ
competitive rivalry, threat of new entrants, threat of substitutes, buyer power, supplier power โ is
rated weak/moderate/strong and justified with documented signals, because a rating without signals is
vibes. The analysis closes where it should have been aiming all along: where the profit pool sits
and who is squeezing it. Five forces is an argument about where margin goes, not a diagram for
slide four.
Input
Works best with: the industry or segment, named as precisely as you can ("clinical data
management SaaS," not "healthcare"), and the decision this analysis should support.
Also useful: a geographic boundary if the structure differs by region, and a
market-landscape-scan in session โ the forces read builds on
it and searches only gaps.
Input supplied inline with the invocation โ text after the skill name, a pasted context dump, or an
appended ARGUMENTS: line โ counts as answers already given. Use it against the question budget;
don't re-ask.
Arriving empty-handed? That works too. The skill opens with at most 3 questions (segment,
decision, boundary) and proceeds on labeled assumptions if they go unanswered.
Example invocation:Five forces on mid-market field-service management software, North America โ decision: whether we enter or partner.
Key Concepts
Governing protocol: honors the autonomous-investigation
contract โ question budget of 3, search-plan gate, Fact/Inference/Assumption labels, Just Enough
Mode (2-4 signals per force), stable schema, 4-option Final Step. Disciplines: FININT
(concentration, margins, filings) + OSINT (analyst coverage, trade press) per
intelligence-collection-disciplines.
The framework (Porter, 1979): industry profitability is determined by five structural forces,
not by how hard incumbents work. Rivalry sets the intensity of margin competition; entry threat
caps pricing; substitutes cap value; buyer power extracts margin downstream; supplier power
extracts it upstream. Structure explains what negotiation skill cannot:
pricing power is
structural.
Ratings must survive "how do you know?" Each weak/moderate/strong rating stands on documented
signals โ concentration data, switching costs, entry examples and how they fared, substitute
adoption curves, margin trends. Forces-with-signals is the difference between naming a framework
and using one.
AI-driven substitution is a named candidate, always. In most knowledge industries it is now
the substitute threat; assess it explicitly in the substitutes force rather than letting the
analysis pretend it's 2015. Supplier power gets the same modern read: cloud, model, and platform
dependencies are supplier concentration.
Industry, not player: this reads what the structure does to everyone who plays.
swot-analysis reads one company's position within it.
When NOT to use: nascent categories with no stable structure โ the forces are still forming;
run the landscape scan and revisit.
Credit inline context, then ask only the unanswered questions (max 3):
Which industry or segment, precisely?
What decision should this support?
Any geographic boundary?
Show the 3-bullet search plan โ what you'll search per force, source types (filings, analyst
coverage, trade press, pricing pages, funding databases), fact/inference separation. Continue
unless revised. If a landscape scan is in session, build on it; search only gaps.
Rate each force with signals, then emit the schema below exactly.
Output schema (do not reorder)
# Five Forces: [Industry / Segment]**As-of date:** | **Boundary:** | **Decision supported:**## 1. Competitive Rivalry โ [weak / moderate / strong]- Signals: [concentration, growth rate, differentiation, exit barriers โ each with URL + label]
- What it means here: [one sentence]
## 2. Threat of New Entrants โ [weak / moderate / strong]- Signals: [entry barriers, capital needs, recent entrants and how they fared, regulation โ each with URL + label]
- What it means here: [one sentence]
## 3. Threat of Substitutes โ [weak / moderate / strong]- Signals: [substitute adoption, price-performance trajectory, switching evidence โ each with URL + label]
- AI-driven substitution, named and assessed: [labeled]
- What it means here: [one sentence]
## 4. Buyer Power โ [weak / moderate / strong]- Signals: [buyer concentration, switching costs, price transparency, backward-integration examples โ URL + label]
- What it means here: [one sentence]
## 5. Supplier Power โ [weak / moderate / strong]- Signals: [supplier concentration (including cloud/model/platform dependencies), input differentiation โ URL + label]
- What it means here: [one sentence]
## 6. The Profit Pool (the "so what")- Where margin sits today, and the force squeezing it: [labeled]
- Structure trend: [tightening / loosening, on what evidence]
- For your decision: [2 sentences tying structure to the decision named above]
### Assumptions to Validate- [Assumption 1] / [Assumption 2] / [Assumption 3]
A copy/paste fill-in version of this schema, with quality checks, lives in template.md.
Final Step (offer exactly 4 options)
Trace the strongest force into your strategy's exposed assumptions
Feed the profit-pool read into an Ansoff growth-options analysis (ansoff-matrix)
Schedule-ready version: which force signals should a re-run watch?
Accept 1, 2, 3, 4, 1 and 3, Verbose Mode, or a custom path.
Examples
A rating that survives "how do you know?" (fictional):
4. Buyer Power โ strong
Signals: top 10 buyers account for ~60% of segment spend โ Fact ([trade association data,
URL]); three publicized incumbent-to-rival switches in 18 months with no reported penalty โ
Fact ([press coverage, URLs]); public rate cards make pricing fully transparent โ Fact
([vendor pricing pages]); one major buyer built the capability in-house โ Fact ([their
engineering blog, URL])
What it means here: buyers can credibly threaten to leave or build, so list-price integrity is
an illusion in this segment โ discounting pressure is structural, not a sales-discipline problem.
The profit-pool close doing its job: rivalry moderate, entrants weak, substitutes strong (AI
agents absorbing the low-complexity tier), buyers strong, suppliers moderate. The pool sits in the
regulated high-complexity tier โ the only place two strong forces don't reach โ Inference. For
the entry decision: enter only via the regulated tier; the volume tier's margin is already spoken
for by buyers below and AI substitution above.
See examples/sample.md for a complete worked five-forces read (fictional
FSM-software market) that builds on the market-landscape-scan example and lands at a profit-pool
close that changes the decision. examples/sample-industrial.md
shows the forces inverting in an industrial market โ read both to see the framework adapt instead
of recite.
Common Pitfalls
Ratings as vibes. "Rivalry: strong" because it feels crowded. Every rating stands on signals
with URLs, or the whole exercise is a diagram.
Skipping the AI substitute. Assessing substitutes as adjacent products while an AI workflow
eats the category's low end. Name it and rate it, even when the rating is "weak โ for now."
Confusing competitors with structure. Listing who plays (that's the landscape scan) instead of
what the structure does to everyone who plays. The forces are about margin physics, not rosters.
No profit-pool close. Five rated forces and no answer to "where does margin go?" The close is
the analysis; everything above it is evidence assembly.
Forcing structure onto a nascent category. Rating forces that haven't formed yet produces
confident noise. Say "still forming," scan the landscape, revisit in two quarters.
