Fishbone

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Focused Fishbone Mode

You are running in focused-fishbone mode. Execute only the procedure below and produce only its canonical output sections — do not run the full 5-phase first-principles analysis. Skip Step 0 technique selection; the user has already chosen this technique by invoking the slash command directly.

When to reach for this

Use a fishbone diagram when the problem has multiple interacting causes with no single traceable causal chain — you need breadth across the cause space, not depth into one chain.

Good fit: multiple plausible contributing factors exist across different areas; the problem recurs despite surface fixes and the cause is unclear; you need a structured way to ensure no category of cause is overlooked before narrowing focus.

Not a good fit: the problem has a single traceable causal chain and you need to drill to the root cause — that calls for a 5-Whys analysis instead, which is a depth-first root-cause drill down one causal chain rather than a breadth-first map across categories.

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Cause categories

The category set is chosen once, before brainstorming begins. Two paths: use the domain-neutral default set, or select a named preset that matches your domain. The decision rule below maps domain signals to the recommended choice.

Default category set

The domain-neutral default covers most situations cleanly. Use it when no preset row in the table below clearly matches your domain.

Category	What it covers
People	Human contributors — skills, behaviours, training, workload, decision-making
Process	Methods, procedures, workflows, sequences of steps
Technology & Tools	Equipment, software, instruments, physical tools, infrastructure
Environment	Physical surroundings, conditions, constraints imposed by the setting
Information	Data quality, availability, communication, documentation, reporting
Resources	Materials, budget, time, capacity, supply inputs

Named presets

Use a named preset when your domain maps cleanly to an established category vocabulary. Each preset's category list is fixed — do not rename or merge categories mid-analysis.

6M (manufacturing / operations): Machine, Method, Material, Measurement, Man (People), Mother Nature (Environment). Use when analysing a production or operations process with physical machinery and materials at the centre.

8P (service / marketing): Product, Price, Place, Promotion, People, Process, Physical Evidence, Productivity. Use when the problem sits inside a service delivery or marketing context where the customer experience and offer design are the relevant axes.

4S (service delivery): Surroundings, Suppliers, Systems, Skills. Use when the problem is a service-delivery failure and a compact four-category lens is sufficient — typically a narrower operational scope than 8P.

Decision rule

Domain signal	Recommended category set	Note
Physical production line, factory floor, ops process with equipment	6M	Machine and Measurement categories capture equipment and process-quality causes that the default set folds into Technology & Tools and Process
Service business — customer offer, channel, pricing, marketing mix	8P	Covers the full service-marketing mix; too broad for narrowly scoped delivery failures
Service delivery operation — narrow scope, no marketing mix needed	4S	Compact; suited to front-line service failures where offer design is not in scope
Software, knowledge work, cross-functional teams, research	Default (six categories)	Domain-neutral labels avoid manufacturing jargon; Technology & Tools and Information handle the technical axes cleanly
Unclear domain, or no preset row fits cleanly	Default (six categories)	The default set is always a valid fallback — prefer it over forcing a preset that does not fit

The default set is always a valid fallback when no preset row clearly matches your situation. Choosing a preset that does not fit the domain produces misleading category labels and blank branches.

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Procedure

1. Define the effect. One sentence naming the observable problem to be explained — what is happening, not why. Do not name a suspected cause.

2. Choose categories. Pick the set by domain signal: 6M (Machine, Method, Material, Measurement, Man, Mother Nature) for a physical production line; 8P (Product, Price, Place, Promotion, People, Process, Physical Evidence, Productivity) for a service business with a marketing mix; 4S (Surroundings, Suppliers, Systems, Skills) for a narrow-scope service-delivery operation; the default six-category set (People, Process, Technology and Tools, Environment, Information, Resources) for software, knowledge work, or when no preset fits cleanly — always a valid fallback. Lock the set now. Do not add, rename, or remove categories once brainstorming begins.

3. Brainstorm causes. For each category, generate candidate causes that could plausibly contribute to the effect, one category at a time. Do not evaluate or discard causes during this step — record everything.

4. Identify sub-causes. For any cause that is itself explained by a deeper cause, add a sub-cause beneath it. Two levels of nesting are typically enough; go deeper only where the extra depth changes what action is possible.

5. Prioritise and verify. Review the completed map, identify the branches most likely contributing based on available evidence, and mark unverified candidate causes explicitly. Select the highest-priority branches for evidence gathering or further depth analysis.

Read fishbone-detail.md when you need:

• a worked example of this technique
• the failure modes and how to avoid them
• handoff guidance to another technique

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If a fuller analysis is needed afterward, invoke the main first-principles agent with this output as Known ground truths.