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Antigravity Agent
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id: wiki-2026-0508-case-interviews
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title: Case Interviews (Consulting)
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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: [case interview, consulting interview, MBB, MECE, pyramid principle, hypothesis-driven]
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duplicate_of: none
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source_trust_level: B
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confidence_score: 0.88
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verification_status: applied
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tags: [career, consulting, mbb, case-interview, mece, problem-solving, structured-thinking, communication]
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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: career / soft skills
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applicable_to: [Consulting Recruitment, Structured Problem-Solving, Strategic Communication]
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---
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# Case Interviews
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## 📌 한 줄 통찰
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> **"매 logical reasoning 의 stress test"**. 매 ambiguous business problem + 매 limited info + 매 30 min. 매 MBB (McKinsey, BCG, Bain) 의 hiring filter. 매 modern AI 시대 의 consultant 의 still relevant — 매 LLM 의 augment 가, 매 structured thinking 의 require.
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## 📖 핵심
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### 매 case 의 type
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1. **Profitability**: 매 revenue / cost 의 분석.
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2. **Market sizing**: 매 estimate.
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3. **Market entry**: 매 strategic decision.
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4. **M&A**: 매 acquisition.
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5. **New product**: 매 launch decision.
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6. **Strategy**: 매 broad.
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7. **Operations**: 매 process improvement.
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### 매 framework
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#### MECE (Mutually Exclusive, Collectively Exhaustive)
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- 매 bucket 의 overlap X.
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- 매 exhaustive coverage.
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- 매 무 missing.
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#### Pyramid Principle (Minto)
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1. 매 conclusion 먼저.
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2. 매 supporting argument 의 grouping.
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3. 매 facts.
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#### 5R (closing)
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- **Recap**: 매 question.
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- **Recommend**: 매 answer.
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- **Reasons**: 매 supporting.
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- **Risk**: 매 consideration.
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- **Retention** (next step): 매 follow-up.
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#### Hypothesis-driven
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- 매 hypothesis 먼저.
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- 매 test with data.
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- 매 update or replace.
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### 매 process
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1. **Listen + restate**: 매 prompt 의 confirm.
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2. **Clarifying questions**: 매 scope 의 narrow.
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3. **Structure** (60 sec think): 매 framework.
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4. **Walk through**: 매 plan 의 explain.
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5. **Analyze**: 매 quantitative + qualitative.
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6. **Synthesize**: 매 insight.
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7. **Recommend**: 매 5R close.
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### 매 evaluation criteria
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- **Structure**: 매 MECE.
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- **Logic**: 매 sound reasoning.
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- **Quantitative**: 매 quick math.
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- **Communication**: 매 clear.
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- **Insight**: 매 non-trivial.
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- **Pressure**: 매 calm.
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- **Adaptability**: 매 framework 의 flex.
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### 매 common framework
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#### Profitability
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- 매 Revenue (price × volume) - 매 Cost (fixed + variable).
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- 매 segment-wise breakdown.
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#### 4P (Marketing)
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- Product, Price, Place, Promotion.
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#### 5C
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- Company, Customer, Competitor, Collaborator, Context.
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#### Porter's 5 Forces
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- 매 industry attractiveness.
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#### Value Chain
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- 매 inbound → operations → outbound → marketing → service.
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→ 매 모든 의 mechanical 적용 X. 매 problem 의 fit.
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### 매 modern (AI era)
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- 매 LLM 의 framework / data 의 augment.
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- 매 case 의 still 인간 의 final.
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- 매 structured thinking 의 increasingly valuable.
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- 매 AI 의 한계 (hallucination, judgment) 의 understand.
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### 매 prep resource
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- 매 "Case in Point" (Marc Cosentino).
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- 매 "Case Interview Secrets" (Victor Cheng).
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- 매 PrepLounge / Management Consulted (mock).
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- 매 firm 의 own case prep.
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### 매 anti-pattern
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- 매 framework 의 force.
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- 매 structure 없이 jump.
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- 매 silent thinking.
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- 매 panic on numbers.
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- 매 ignore interviewer 의 hint.
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## 💻 패턴 (응용)
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### Structured response template
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```
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[Listen + Restate]
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"매 understand 의 sure 의 — [restatement of the question]. Right?"
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[Clarify]
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"Before structuring, may I ask:
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1. What is the company's current state?
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2. Are we looking at a specific market / time horizon?
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3. How is success defined?"
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[Structure (after 60 sec think)]
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"I'd like to break this into [N] areas:
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1. [Bucket 1]: [why this matters]
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2. [Bucket 2]: ...
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3. [Bucket 3]: ...
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Let me start with [bucket 1] because [reasoning]."
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[Analyze each bucket]
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[Synthesize + 5R]
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"To summarize:
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- The question was [Recap].
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- I recommend [Recommend].
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- Because [Reasons 1-3].
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- Risks include [Risk 1-2].
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- Next steps would be [Retention]."
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```
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### Profitability framework
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```
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Profit = Revenue - Cost
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Revenue = Volume × Price
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Volume:
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Market size × Market share × Customer frequency
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By segment / channel / geography
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Price:
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By segment / channel
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Trend / mix shift
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Cost = Fixed + Variable
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Fixed: rent, salaries, depreciation
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Variable: COGS (materials, labor), marketing, distribution
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By cost driver
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```
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### Market sizing (Fermi estimation)
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```
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"How many tennis balls fit in a Boeing 747?"
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1. Plane volume: ~875 cubic meters (interior, after subtracting walls/seats).
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2. Tennis ball volume: ~0.0001 m³ (4πr³/3 with r=3.4cm).
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3. Packing efficiency: ~70% (FCC packing).
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= 875 / 0.0001 × 0.7 ≈ 6.1 million tennis balls.
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Sanity check: 매 reasonable order of magnitude.
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```
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### Mock interview prompt
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```python
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MOCK_PROMPTS = [
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"Our client is a regional grocery chain. Profits dropped 15% last year. Why?",
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"Should our pharma client enter the African market?",
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"How would you size the global market for electric toothbrushes?",
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"A streaming service is losing subscribers. What would you investigate?",
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"Our manufacturing client has 30% scrap rate. How to reduce?",
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]
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def practice_session():
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import random
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prompt = random.choice(MOCK_PROMPTS)
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print(f'PROMPT: {prompt}')
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print('You have 60 seconds to structure...')
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# 매 record voice + 매 transcribe + 매 LLM critique
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```
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### LLM-assisted prep
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```python
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def case_critique(transcript):
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return llm.generate(f"""You are a McKinsey case interview coach. Evaluate this case response transcript on:
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1. Structure (MECE? clear buckets?)
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2. Logic (sound reasoning? cause-effect?)
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3. Math (correct? clear?)
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4. Communication (concise? confident?)
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5. Insight (non-trivial conclusions?)
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For each, give:
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- Score 1-5
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- Specific evidence from transcript
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- One concrete improvement
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Transcript:
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{transcript}""")
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```
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### Common math drill
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```
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- 매 Mental: 17 × 24 = ?
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Trick: (20-3)(24) = 480 - 72 = 408
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- 매 Percentage: $4.5M is 36% of total revenue. What's revenue?
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$4.5 / 0.36 = $12.5M
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- 매 Growth: 5% per year for 10 years = ~63% (rule of 72: 14 yr to double)
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- 매 Breakeven: Fixed $1M, contribution margin $5/unit. Breakeven volume?
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1M / 5 = 200K units
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```
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## 🤔 결정 기준
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| 상황 | Framework |
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|---|---|
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| Profit declining | Profitability tree |
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| Market entry | Market attractiveness + Capability fit |
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| New product | 4P + go-to-market |
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| Pricing | Cost-based / value-based / competitor-based |
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| Cost reduction | Cost driver decomposition |
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| M&A | Strategic fit + financial + integration |
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| Estimation | Top-down + bottom-up |
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**기본값**: 매 problem 의 listen + 매 framework 의 fit (force X).
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## 🔗 Graph
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- 부모: [[Problem_Solving|Problem-Solving]]
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- 변형: [[MECE]] · [[Pyramid Principle]] · [[Hypothesis-Driven]]
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- Adjacent: [[Articulateness]] · [[Be-Detailed]] · [[Beliefs]] · [[Bounded_Rationality|Bounded-Rationality]]
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## 🤖 LLM 활용
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**언제**: 매 consulting prep. 매 structured thinking exercise. 매 mock practice. 매 critique.
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**언제 X**: 매 final interview substitute. 매 framework 의 mechanical 적용.
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## ❌ 안티패턴
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- **Force framework**: 매 problem 의 fit X.
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- **Silent thinking**: 매 interviewer 의 see X.
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- **Skip structure**: 매 jump 의 chaos.
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- **Ignore hint**: 매 interviewer 의 lead 의 follow X.
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- **Panic on math**: 매 estimate first.
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- **No 5R close**: 매 hanging finish.
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- **Memorize 의 manual answer**: 매 surface 의 lose.
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## 🧪 검증 / 중복
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- Verified (Cosentino "Case in Point", Cheng's "Case Interview Secrets", MBB own materials).
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- 신뢰도 B.
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- Related: [[Articulateness]] · [[Be-Detailed]] · [[Bounded_Rationality|Bounded-Rationality]] · [[Pyramid Principle]].
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-04-27 | Auto-mapped |
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — type + framework + 5R + 매 mock / critique / Fermi code |
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