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id: wiki-2026-0508-mece-pyramid-principle
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title: MECE + Pyramid Principle
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [MECE, Pyramid Principle, 미씨 + 피라미드, McKinsey Framework]
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duplicate_of: none
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source_trust_level: A
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confidence_score: 0.9
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verification_status: applied
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tags: [problem-solving, communication, structure, consulting, writing]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: methodology
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framework: mckinsey
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---
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# MECE + Pyramid Principle
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## 매 한 줄
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> **"매 MECE 는 thinking, Pyramid 는 communication"**. MECE (Mutually Exclusive, Collectively Exhaustive) 는 문제 분해 원칙, Pyramid Principle 은 결론-우선 communication structure. Barbara Minto (1973) 의 McKinsey 표준. 2026 LLM 시대에도 prompt structuring / report writing 의 backbone.
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## 매 핵심
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### 매 MECE
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- **Mutually Exclusive**: 각 카테고리 겹침 없음.
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- **Collectively Exhaustive**: 모든 가능성 포함.
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- 2x2 matrix, decision tree, issue tree 의 기본.
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### 매 Pyramid Principle
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- **Top**: governing thought / answer first.
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- **Middle**: 3-5 supporting arguments (MECE).
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- **Bottom**: data, evidence, examples.
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- **SCQA opener**: Situation → Complication → Question → Answer.
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### 매 응용
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1. Consulting deliverable / executive summary.
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2. Research paper structure.
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3. LLM prompt design (system + sections).
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4. Code review write-up.
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## 💻 패턴
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### Issue tree decomposition
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```python
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class Node:
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def __init__(self, q, children=None):
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self.q = q
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self.children = children or []
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# Profit decline 분석
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tree = Node("Why is profit declining?", [
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Node("Revenue down?", [
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Node("Volume down?"),
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Node("Price down?"),
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]),
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Node("Cost up?", [
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Node("COGS up?"),
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Node("OpEx up?"),
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]),
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])
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# 매 each level MECE
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```
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### MECE validator
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```python
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def is_mece(categories: list[set]) -> tuple[bool, bool]:
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universe = set.union(*categories)
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# ME: pairwise disjoint
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me = all(not (a & b) for i, a in enumerate(categories)
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for b in categories[i+1:])
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# CE: union covers universe
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ce = set.union(*categories) == universe
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return me, ce
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```
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### Pyramid outliner (LLM)
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```python
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def pyramid_outline(question: str) -> dict:
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prompt = f"""Structure as Pyramid Principle:
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1. Governing answer (1 sentence).
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2. 3 MECE supporting arguments.
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3. For each, 2-3 evidence bullets.
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Question: {question}
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Output JSON."""
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resp = client.messages.create(
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model="claude-opus-4-7",
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max_tokens=2048,
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messages=[{"role": "user", "content": prompt}],
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)
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return json.loads(resp.content[0].text)
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```
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### SCQA opener generator
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```python
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def scqa(situation, complication, question, answer):
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return (
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f"**Situation**: {situation}\n"
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f"**Complication**: {complication}\n"
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f"**Question**: {question}\n"
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f"**Answer**: {answer}"
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)
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```
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### 2x2 framework
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```python
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def matrix_2x2(items, axis_x, axis_y):
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quadrants = {"high-high": [], "high-low": [],
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"low-high": [], "low-low": []}
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for item in items:
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x = "high" if axis_x(item) else "low"
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y = "high" if axis_y(item) else "low"
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quadrants[f"{x}-{y}"].append(item)
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return quadrants
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```
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### Top-down report builder
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```python
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def build_report(answer, args: list[dict]):
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out = [f"# {answer}\n"]
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for i, arg in enumerate(args, 1):
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out.append(f"## {i}. {arg['claim']}")
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for ev in arg["evidence"]:
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out.append(f"- {ev}")
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return "\n".join(out)
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```
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## 매 결정 기준
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| 상황 | Approach |
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|---|---|
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| Problem decomposition | Issue tree (MECE at each level) |
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| Executive deck | Pyramid + SCQA + 3 args |
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| Categorization | 2x2 matrix or MECE list |
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| LLM task | Pyramid in system prompt |
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**기본값**: Issue tree 분석 → Pyramid 로 communicate.
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## 🔗 Graph
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- 부모: [[Problem Solving Process]]
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- 변형: [[Pyramid Principle]] · [[Issue Tree]]
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- 응용: [[Technical Writing]]
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- Adjacent: [[Hypothesis-Driven]]
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## 🤖 LLM 활용
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**언제**: report drafting, prompt structuring, decomposition assistance.
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**언제 X**: creative / divergent ideation — 매 over-constrains.
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## ❌ 안티패턴
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- **False MECE**: overlap 있는데 disjoint 라 가정.
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- **Bottom-up dump**: data 먼저 늘어놓고 conclusion 마지막 → executive 가 lost.
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- **Over-decomposition**: 7+ branches at one level → cognitive overload.
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- **Forced 3 categories**: 매 항상 3 으로 강제 → exhaustiveness 깨짐.
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## 🧪 검증 / 중복
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- Verified (Minto 1973 "The Pyramid Principle", McKinsey training docs, HBR 2019).
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- 신뢰도 A.
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — issue tree + SCQA + 2x2 패턴 |
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