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Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-20 23:52:15 +09:00

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MECE
Pyramid Principle
미씨 + 피라미드
McKinsey Framework
none A 0.9 applied
problem-solving
communication
structure
consulting
writing
2026-05-10 pending
language framework
methodology mckinsey

MECE + Pyramid Principle

매 한 줄

"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.

매 핵심

매 MECE

  • Mutually Exclusive: 각 카테고리 겹침 없음.
  • Collectively Exhaustive: 모든 가능성 포함.
  • 2x2 matrix, decision tree, issue tree 의 기본.

매 Pyramid Principle

  • Top: governing thought / answer first.
  • Middle: 3-5 supporting arguments (MECE).
  • Bottom: data, evidence, examples.
  • SCQA opener: Situation → Complication → Question → Answer.

매 응용

  1. Consulting deliverable / executive summary.
  2. Research paper structure.
  3. LLM prompt design (system + sections).
  4. Code review write-up.

💻 패턴

Issue tree decomposition

class Node:
    def __init__(self, q, children=None):
        self.q = q
        self.children = children or []

# Profit decline 분석
tree = Node("Why is profit declining?", [
    Node("Revenue down?", [
        Node("Volume down?"),
        Node("Price down?"),
    ]),
    Node("Cost up?", [
        Node("COGS up?"),
        Node("OpEx up?"),
    ]),
])
# 매 each level MECE

MECE validator

def is_mece(categories: list[set]) -> tuple[bool, bool]:
    universe = set.union(*categories)
    # ME: pairwise disjoint
    me = all(not (a & b) for i, a in enumerate(categories)
                          for b in categories[i+1:])
    # CE: union covers universe
    ce = set.union(*categories) == universe
    return me, ce

Pyramid outliner (LLM)

def pyramid_outline(question: str) -> dict:
    prompt = f"""Structure as Pyramid Principle:
1. Governing answer (1 sentence).
2. 3 MECE supporting arguments.
3. For each, 2-3 evidence bullets.

Question: {question}
Output JSON."""
    resp = client.messages.create(
        model="claude-opus-4-7",
        max_tokens=2048,
        messages=[{"role": "user", "content": prompt}],
    )
    return json.loads(resp.content[0].text)

SCQA opener generator

def scqa(situation, complication, question, answer):
    return (
        f"**Situation**: {situation}\n"
        f"**Complication**: {complication}\n"
        f"**Question**: {question}\n"
        f"**Answer**: {answer}"
    )

2x2 framework

def matrix_2x2(items, axis_x, axis_y):
    quadrants = {"high-high": [], "high-low": [],
                 "low-high": [], "low-low": []}
    for item in items:
        x = "high" if axis_x(item) else "low"
        y = "high" if axis_y(item) else "low"
        quadrants[f"{x}-{y}"].append(item)
    return quadrants

Top-down report builder

def build_report(answer, args: list[dict]):
    out = [f"# {answer}\n"]
    for i, arg in enumerate(args, 1):
        out.append(f"## {i}. {arg['claim']}")
        for ev in arg["evidence"]:
            out.append(f"- {ev}")
    return "\n".join(out)

매 결정 기준

상황 Approach
Problem decomposition Issue tree (MECE at each level)
Executive deck Pyramid + SCQA + 3 args
Categorization 2x2 matrix or MECE list
LLM task Pyramid in system prompt

기본값: Issue tree 분석 → Pyramid 로 communicate.

🔗 Graph

🤖 LLM 활용

언제: report drafting, prompt structuring, decomposition assistance. 언제 X: creative / divergent ideation — 매 over-constrains.

안티패턴

  • False MECE: overlap 있는데 disjoint 라 가정.
  • Bottom-up dump: data 먼저 늘어놓고 conclusion 마지막 → executive 가 lost.
  • Over-decomposition: 7+ branches at one level → cognitive overload.
  • Forced 3 categories: 매 항상 3 으로 강제 → exhaustiveness 깨짐.

🧪 검증 / 중복

  • Verified (Minto 1973 "The Pyramid Principle", McKinsey training docs, HBR 2019).
  • 신뢰도 A.

🕓 Changelog

날짜 변경
2026-05-08 Phase 1
2026-05-10 Manual cleanup — issue tree + SCQA + 2x2 패턴