2nd/10_Wiki/Topics/AI_and_ML/Case Interviews.md

---
id: wiki-2026-0508-case-interviews
title: Case Interviews (Consulting)
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: [case interview, consulting interview, MBB, MECE, pyramid principle, hypothesis-driven]
duplicate_of: none
source_trust_level: B
confidence_score: 0.88
verification_status: applied
tags: [career, consulting, mbb, case-interview, mece, problem-solving, structured-thinking, communication]
raw_sources: []
last_reinforced: 2026-05-10
github_commit: pending
tech_stack:
  language: career / soft skills
  applicable_to: [Consulting Recruitment, Structured Problem-Solving, Strategic Communication]
---

# Case Interviews

## 📌 한 줄 통찰
> **"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.

## 📖 핵심

### 매 case 의 type
1. **Profitability**: 매 revenue / cost 의 분석.
2. **Market sizing**: 매 estimate.
3. **Market entry**: 매 strategic decision.
4. **M&A**: 매 acquisition.
5. **New product**: 매 launch decision.
6. **Strategy**: 매 broad.
7. **Operations**: 매 process improvement.

### 매 framework

#### MECE (Mutually Exclusive, Collectively Exhaustive)
- 매 bucket 의 overlap X.
- 매 exhaustive coverage.
- 매 무 missing.

#### Pyramid Principle (Minto)
1. 매 conclusion 먼저.
2. 매 supporting argument 의 grouping.
3. 매 facts.

#### 5R (closing)
- **Recap**: 매 question.
- **Recommend**: 매 answer.
- **Reasons**: 매 supporting.
- **Risk**: 매 consideration.
- **Retention** (next step): 매 follow-up.

#### Hypothesis-driven
- 매 hypothesis 먼저.
- 매 test with data.
- 매 update or replace.

### 매 process
1. **Listen + restate**: 매 prompt 의 confirm.
2. **Clarifying questions**: 매 scope 의 narrow.
3. **Structure** (60 sec think): 매 framework.
4. **Walk through**: 매 plan 의 explain.
5. **Analyze**: 매 quantitative + qualitative.
6. **Synthesize**: 매 insight.
7. **Recommend**: 매 5R close.

### 매 evaluation criteria
- **Structure**: 매 MECE.
- **Logic**: 매 sound reasoning.
- **Quantitative**: 매 quick math.
- **Communication**: 매 clear.
- **Insight**: 매 non-trivial.
- **Pressure**: 매 calm.
- **Adaptability**: 매 framework 의 flex.

### 매 common framework

#### Profitability
- 매 Revenue (price × volume) - 매 Cost (fixed + variable).
- 매 segment-wise breakdown.

#### 4P (Marketing)
- Product, Price, Place, Promotion.

#### 5C
- Company, Customer, Competitor, Collaborator, Context.

#### Porter's 5 Forces
- 매 industry attractiveness.

#### Value Chain
- 매 inbound → operations → outbound → marketing → service.

→ 매 모든 의 mechanical 적용 X. 매 problem 의 fit.

### 매 modern (AI era)
- 매 LLM 의 framework / data 의 augment.
- 매 case 의 still 인간 의 final.
- 매 structured thinking 의 increasingly valuable.
- 매 AI 의 한계 (hallucination, judgment) 의 understand.

### 매 prep resource
- 매 "Case in Point" (Marc Cosentino).
- 매 "Case Interview Secrets" (Victor Cheng).
- 매 PrepLounge / Management Consulted (mock).
- 매 firm 의 own case prep.

### 매 anti-pattern
- 매 framework 의 force.
- 매 structure 없이 jump.
- 매 silent thinking.
- 매 panic on numbers.
- 매 ignore interviewer 의 hint.

## 💻 패턴 (응용)

### Structured response template
```
[Listen + Restate]
"매 understand 의 sure 의 — [restatement of the question]. Right?"

[Clarify]
"Before structuring, may I ask:
1. What is the company's current state?
2. Are we looking at a specific market / time horizon?
3. How is success defined?"

[Structure (after 60 sec think)]
"I'd like to break this into [N] areas:
1. [Bucket 1]: [why this matters]
2. [Bucket 2]: ...
3. [Bucket 3]: ...

Let me start with [bucket 1] because [reasoning]."

[Analyze each bucket]

[Synthesize + 5R]
"To summarize:
- The question was [Recap].
- I recommend [Recommend].
- Because [Reasons 1-3].
- Risks include [Risk 1-2].
- Next steps would be [Retention]."
```

### Profitability framework
```
Profit = Revenue - Cost

Revenue = Volume × Price
  Volume:
    Market size × Market share × Customer frequency
    By segment / channel / geography
  Price:
    By segment / channel
    Trend / mix shift

Cost = Fixed + Variable
  Fixed: rent, salaries, depreciation
  Variable: COGS (materials, labor), marketing, distribution
  By cost driver
```

### Market sizing (Fermi estimation)
```
"How many tennis balls fit in a Boeing 747?"

1. Plane volume: ~875 cubic meters (interior, after subtracting walls/seats).
2. Tennis ball volume: ~0.0001 m³ (4πr³/3 with r=3.4cm).
3. Packing efficiency: ~70% (FCC packing).

= 875 / 0.0001 × 0.7 ≈ 6.1 million tennis balls.

Sanity check: 매 reasonable order of magnitude.
```

### Mock interview prompt
```python
MOCK_PROMPTS = [
    "Our client is a regional grocery chain. Profits dropped 15% last year. Why?",
    "Should our pharma client enter the African market?",
    "How would you size the global market for electric toothbrushes?",
    "A streaming service is losing subscribers. What would you investigate?",
    "Our manufacturing client has 30% scrap rate. How to reduce?",
]

def practice_session():
    import random
    prompt = random.choice(MOCK_PROMPTS)
    print(f'PROMPT: {prompt}')
    print('You have 60 seconds to structure...')
    # 매 record voice + 매 transcribe + 매 LLM critique
```

### LLM-assisted prep
```python
def case_critique(transcript):
    return llm.generate(f"""You are a McKinsey case interview coach. Evaluate this case response transcript on:

1. Structure (MECE? clear buckets?)
2. Logic (sound reasoning? cause-effect?)
3. Math (correct? clear?)
4. Communication (concise? confident?)
5. Insight (non-trivial conclusions?)

For each, give:
- Score 1-5
- Specific evidence from transcript
- One concrete improvement

Transcript:
{transcript}""")
```

### Common math drill
```
- 매 Mental: 17 × 24 = ?
  Trick: (20-3)(24) = 480 - 72 = 408
  
- 매 Percentage: $4.5M is 36% of total revenue. What's revenue?
  $4.5 / 0.36 = $12.5M
  
- 매 Growth: 5% per year for 10 years = ~63% (rule of 72: 14 yr to double)
  
- 매 Breakeven: Fixed $1M, contribution margin $5/unit. Breakeven volume?
  1M / 5 = 200K units
```

## 🤔 결정 기준
| 상황 | Framework |
|---|---|
| Profit declining | Profitability tree |
| Market entry | Market attractiveness + Capability fit |
| New product | 4P + go-to-market |
| Pricing | Cost-based / value-based / competitor-based |
| Cost reduction | Cost driver decomposition |
| M&A | Strategic fit + financial + integration |
| Estimation | Top-down + bottom-up |

**기본값**: 매 problem 의 listen + 매 framework 의 fit (force X).

## 🔗 Graph
- 부모: [[Problem_Solving|Problem-Solving]]
- 변형: [[MECE]] · [[Pyramid Principle]] · [[Hypothesis-Driven]]
- Adjacent: [[Articulateness]] · [[Be-Detailed]] · [[Beliefs]] · [[Bounded_Rationality|Bounded-Rationality]]

## 🤖 LLM 활용
**언제**: 매 consulting prep. 매 structured thinking exercise. 매 mock practice. 매 critique.
**언제 X**: 매 final interview substitute. 매 framework 의 mechanical 적용.

## ❌ 안티패턴
- **Force framework**: 매 problem 의 fit X.
- **Silent thinking**: 매 interviewer 의 see X.
- **Skip structure**: 매 jump 의 chaos.
- **Ignore hint**: 매 interviewer 의 lead 의 follow X.
- **Panic on math**: 매 estimate first.
- **No 5R close**: 매 hanging finish.
- **Memorize 의 manual answer**: 매 surface 의 lose.

## 🧪 검증 / 중복
- Verified (Cosentino "Case in Point", Cheng's "Case Interview Secrets", MBB own materials).
- 신뢰도 B.
- Related: [[Articulateness]] · [[Be-Detailed]] · [[Bounded_Rationality|Bounded-Rationality]] · [[Pyramid Principle]].

## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-04-27 | Auto-mapped |
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — type + framework + 5R + 매 mock / critique / Fermi code |