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nw-jtbd-analysis

JTBD methodology for extracting real jobs behind feature requests — job statements, abstraction layers, first-principles extraction, ODI outcome sta…

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技能内容

JTBD Analysis

Core Principle

A job is the progress a person is trying to make in a particular circumstance. Jobs are stable over time — technology changes, jobs don't. People hire products to make progress; they fire them when they fail.

The trap: Feature requests describe a proposed solution, not the underlying job. Always extract the job first.


Job Statement Format

When [situation/trigger], I want to [motivation/action], so I can [expected outcome]

Examples (good):

  • "When I'm hosting a virtual networking event, I want to facilitate natural conversations between strangers, so I can create valuable connections that wouldn't happen otherwise."
  • "When I join an event as a participant, I want to quickly find relevant people to talk to, so I can maximize the value of my limited time."

Job Types — Extract All Three

| Type | Question | Example |

|------|----------|---------|

| Functional | What task is the user trying to accomplish? | Find someone with complementary expertise |

| Emotional | How does the user want to feel? | Feel confident approaching strangers |

| Social | How does the user want to be perceived? | Appear professional and well-connected |


Abstraction Layers — Navigate to the Real Job

Jobs usually live at strategic or physical level, not tactical.

| Layer | Question | Example |

|-------|----------|---------|

| Tactical | How do we improve this interaction? | Better drag-and-drop for notes |

| Operational | Why does this workflow exist? | Why do we need a facilitator? |

| Strategic | What decision is being pursued? | How do we reduce direction uncertainty? |

| Physical | What's the irreducible function? | Input → Synthesis → Convergence |

Navigation rules:

  • Use "why?" to move up layers
  • Use "how?" to move down layers
  • Stop when further "why?" produces a life-goal answer

First-Principles Extraction — 3-Step Inversion

When a feature request is presented as a job, apply this:

  1. Identify the Activity — What visible action is the user performing?
  • e.g., "User brainstorms on a whiteboard"
  1. Reject the Activity as the Job — Does anyone wake up wanting to do this activity?
  • "Nobody wakes up wanting to brainstorm" → the job is deeper
  1. Strip to Irreducible Function — What remains if all tools and methods are removed?
  • e.g., "Reduce uncertainty via input-synthesis-convergence"

Disruption check: Is there a higher-level job that would make this entire job unnecessary?


ODI Outcome Statements — Measurable Success Criteria

Format: [Direction] + [Metric] + [Object] + [Context]

Direction: Always "Minimize" (95% of time). "Maximize" only when more is genuinely better.

Metrics priority:

  1. the time it takes to — speed/efficiency (preferred)
  2. the likelihood of — avoiding occurrences
  3. the likelihood that — avoiding results
  4. the number of — quantity reduction
  5. the effort required to — ease

Good vs bad examples:

| Bad | Problem | Good |

|-----|---------|------|

| "I want easy video calls" | Ambiguous + solution | "Minimize the time it takes to start a conversation with a specific person" |

| "Manage my network effectively" | Vague verb + ambiguous | "Minimize the time it takes to identify who can help with a specific need" |

| "Use breakout rooms to talk privately" | Solution embedded | "Minimize the likelihood of conversations being overheard by unintended parties" |

| "Don't miss important people" | Negative framing | "Minimize the likelihood of failing to connect with relevant attendees" |

Forbidden words: easy, reliable, good, better, effective, efficient, manage, handle, deal with.

Forbidden patterns: solution references ("using AI", "via the app"), compound statements with "and"/"or", demographics.


Opportunity Scoring

Formula: Score = Importance + Max(0, Importance - Satisfaction)

Where Importance and Satisfaction are surveyed 1-10.

| Score | Interpretation |

|-------|---------------|

| > 12 | Under-served — high opportunity |

| 10-12 | Appropriately served — maintain |

| < 10 | Over-served — do not invest |

Output format per opportunity:

| Outcome | Importance | Satisfaction | Score | Status |
|---------|------------|--------------|-------|--------|
| Minimize time to find relevant attendees | 9.2 | 4.1 | 14.3 | Under-served |

DIVERGE Output for JTBD Phase

Produce docs/feature/{feature-id}/diverge/job-analysis.md with:

  1. Raw request — verbatim feature/problem statement received
  2. Job extraction — 5 Why chain from tactical to physical/strategic level
  3. Job statements — functional (required) + emotional + social (if identifiable)
  4. Disruption check — Is there a higher-level job this entire job is serving?
  5. Outcome statements — 3-6 measurable ODI-format statements
  6. Opportunity candidates — Which outcomes appear most under-served?

Gate: Job must be at strategic or physical abstraction level. Tactical-level jobs are not acceptable input for brainstorming — elevate first.

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同名技能的其他版本

有 2 个不同仓库或目录里都有叫 nw-jtbd-analysis 的技能。它们内容并不相同,别混用:

  • nWave-ai/nWave — JTBD methodology for extracting real jobs behind feature requests — job statements, abstra