Interview Preperation

Guesstimate

Category 1: Supply-Side Guesstimates (Bottleneck Method)

  1. Planes Taking Off from Delhi Airport (IGI) — Daily

Bottleneck: Runway capacity

Assumptions & Working:

  • Total runways: 4
  • Safe gap between movements (takeoff/landing): ~2 minutes
  • Slots per runway per hour = 30
  • Total theoretical slots per hour = 4 × 30 = 120
  • Assume:
    • 80% utilization for 16 peak hours
    • 40% utilization for 8 off-peak hours

Calculated Slots (All Movements):

  • Peak: 120 × 16 × 80% = 1,536
  • Off-peak: 120 × 8 × 40% = 384
  • Total movements ≈ 1,920/day

Since takeoffs ≈ 50% of movements:

Final Answer: ~960 takeoffs per day
(Reality check: official data ~1,200–1,500 total movements/day — very close)

  1. Cars Passing Through a Busy Toll Plaza (Sea Link) — Daily

Bottleneck: Toll booth processing time

Assumptions & Working:

  • Lanes (one direction): 8
  • FASTag processing time: ~5 seconds/car
  • Capacity per lane per hour = 720 cars
  • Total hourly capacity = 8 × 720 = 5,760 cars

Utilization:

  • Peak: 6 hours at 80%
  • Off-peak: 18 hours at 20%

Final Answer: ~48,000–50,000 cars per day (one way)

  1. Elevators Required for a 50-Storey Commercial Building

Bottleneck: Elevator cycle time vs. employee arrival rate

Assumptions & Working:

  • Employees per floor: ~100
  • Total employees = 5,000
  • Peak arrival window: 80% in 1 hour → 4,000 people
  • Elevator capacity: 15 people
  • Round trip time (50 floors + loading/unloading): ~5 minutes
  • One elevator trips per hour = 12
  • Capacity per elevator per hour = 180 people

Elevators Required:

  • 4,000 ÷ 180 ≈ 22 elevators

Final Answer: ~20–25 elevators
(Typically split into Low-Rise and High-Rise banks)

  1. Daily Revenue of a Busy Starbucks (South Delhi)

Bottleneck: Counter billing speed

Assumptions & Working:

  • Operating hours: 15
  • Billing counters: 2

Orders:

  • Peak (5 hrs): 1 order/min/counter → 600 orders
  • Off-peak (10 hrs): 1 order/5 mins/counter → 240 orders
  • Total orders ≈ 840

Average Order Value (AOV):

  • ₹500 (coffee + snack + tax)

Final Answer: ~₹4.2 lakh per day

  1. Daily Revenue of a Single Petrol Pump (Tier-1 City)

Bottleneck: Number of fuel nozzles

Assumptions & Working:

  • Fuel islands: 4
  • Nozzles per island: 2
  • Total nozzles = 8
  • Avg fill time: 3 minutes
  • Capacity per nozzle per day ≈ 480 vehicles
  • Total vehicles/day ≈ 3,840

Fuel Mix:

  • 60% bikes @ 5L
  • 40% cars @ 30L
  • Avg fuel per vehicle ≈ 9L

Total Fuel Sold:

  • ~345,000 liters/day
  • Fuel price: ₹100/L

Final Answer: ~₹34.5 lakh per day

  1. Daily Revenue of a 4-Screen Multiplex

Bottleneck: Seating capacity × show timings

Assumptions & Working:

  • Screens: 4
  • Seats per screen: 250
  • Shows per day: 5
  • Total seat inventory = 5,000
  • Avg occupancy: 40%
  • Tickets sold/day = 2,000

Revenue per person:

  • Ticket: ₹300
  • F&B: ₹200
  • Total: ₹500

Final Answer: ~₹10 lakh per day

  1. Number of Barbers in a Town

Logic: Demand–supply equilibrium

Assumptions & Working:

  • Town population: 100,000
  • Males: 50,000
  • Haircut frequency: Once every 30 days
  • Daily demand = ~1,670 haircuts
  • One barber:
    • 1 haircut / 30 mins
    • 10-hour day → 20 haircuts/day

Barbers Required:

  • 1,670 ÷ 20 ≈ 84

Final Answer: ~80–90 barbers

  1. Security Counters for an IPL Match

Bottleneck: Entry time window

Assumptions & Working:

  • Stadium capacity: 50,000
  • Entry window: Last 2 hours
  • Required throughput = 25,000 people/hour
  • One guard checks:
    • 1 person / 15 seconds
    • 240 people/hour

Counters Required:

  • 25,000 ÷ 240 ≈ 104

Final Answer: ~100–110 security counters

 

Category 2: Demand-Side Guesstimates (Market Sizing via Income Pyramid)

  1. Annual Market Size of Sanitary Pads in India

Segmentation: Menstruating population

Assumptions & Working:

  • Total population: 4B

  • Females: 700M

  • Age 12–50 (~60%): 420M

Penetration:

  • Urban females: 140M × 80% = 112M

  • Rural females: 280M × 40% = 112M

  • Total users = 224M

Consumption:

  • 8 pads/cycle × 12 cycles ≈ 100 pads/year

Market Value:

  • 224M × 100 × ₹8

Final Answer: ~₹17,920 Crores annually

  1. Total Number of iPhone Users in India

Segmentation: Affordability + aspiration

Assumptions & Working:

  • Smartphone users: 800M

  • Top 5% households can afford ₹60k+ phones → ~40M

  • Apple share in premium segment: ~50%

  • Core premium users: 20M

  • Secondary/refurbished market: +20%

Final Answer: ~24 Million active iPhone users

  1. Total Number of Two-Wheelers in Bangalore

Segmentation: Household-based, bottom-up

Assumptions & Working:

  • Population: 13M

  • Avg family size: 4

  • Households: ~3.25M

Tier-wise Ownership:

  • Upper Class (10%): 2 cars, ~0 bikes
  • Middle Class (60%): 1.5 bikes/household → ~3.0M

  • Lower Class (30%): 1 bike per 2 households → ~0.5M

Final Answer: ~3.5 Million two-wheelers

  1. Annual Sales of Washing Machines in India

Segmentation: Replacement vs. first-time buyers

Assumptions & Working:

  • Total households: 300M

  • Penetration: ~15%

  • Installed base: 45M

Replacement Demand:

  • Lifespan: ~10 years
  • 45M ÷ 10 = 5M units/year

New Buyers:

  • Non-owners: 255M
  • 1% adoption/year = 5M units

Final Answer: ~7 Million units per year

  1. Market Size of Luxury Watches (₹50k+) in India

Segmentation: High Net Worth + aspirational buyers

Assumptions & Working:

  • UHNIs: ~800,000

  • Purchase rate: 1 watch every 2 years → 400,000/year

Aspirational Segment:

  • Upper management / weddings: 1M people

  • Purchase rate: 1 watch every 5 years → 200,000/year

Total Units Sold:

  • 400k + 200k = 600,000

Avg Price: ₹1,00,000

Final Answer: ~₹6,000 Crores annually

  1. Annual Spend on Wedding Cards in India

Segmentation: Cultural event volume (urban vs rural)

Assumptions & Working:

  • Weddings per year: 10M

Rural (7M weddings):

  • 50% use simple cards
  • 5M × 200 cards × ₹10 = ₹700 Cr

Urban (3M weddings):

  • 80% use fancy cards
  • 4M × 300 cards × ₹50 = ₹3,600 Cr

Final Answer: ~₹4,300 Crores annually

  1. Smart TVs Sold During a Diwali Sale

Segmentation: Time-bound e-commerce demand

Assumptions & Working:

  • Online shoppers: 100M

  • Electronics intenders during sale: 10% → 10M

  • TV-specific conversion: 15% → 1.5M

  • Large-appliance purchases heavily skewed to sale periods

Final Answer: ~1.5–2 Million Smart TVs

  1. Total Active Gym Memberships in a Metro City

Segmentation: Age × income × lifestyle

Assumptions & Working:

  • Metro population: 10M

  • Age 18–40: 40% → 4M

  • Top income/time segment: 20% → 800k

  • Actual paid conversion: 15%

Final Answer: ~120,000 active gym memberships

Category 3: Digital, Habits & Usage Guesstimates

  1. Total WhatsApp Messages Sent in India (Daily)

Segmentation: User intensity

Assumptions & Working:

  • WhatsApp users in India: ~850M

User Buckets:

  • Heavy (20%): Students, professionals, forwards
    • 170M × 100 msgs/day = 17B

  • Medium (50%): Casual daily users
    • 425M × 30 msgs/day = 75B

  • Light (30%): Elderly/occasional users
    • 255M × 5 msgs/day = 25B

Total Messages:

  • ~31 Billion/day

Sanity Check:
 Global WhatsApp traffic ≈ 140B/day → India contributing ~22% is logical.

Final Answer: ~30–35 Billion messages per day

  1. Zomato / Swiggy Deliveries in a Metro City (Daily)

Segmentation: Geography + time-of-day peaks

Assumptions & Working:

  • Zomato orders in Delhi NCR (annual): ~4.2 Crore

  • Zomato + Swiggy combined: ~8 Crore/year

  • Daily average: 80M ÷ 365 ≈ 220,000 orders/day

Sanity Check:

  • Peak dinner minute (8:25 PM): ~18 Lakh orders nationwide
  • Top metros contribute ~60% of national volume

Final Answer: ~2.5–3 Lakh orders per day per metro

  1. UPI Transactions at Tea / Chai Stalls (Daily, India)

Segmentation: Micro-merchant penetration

Assumptions & Working:

  • Total UPI transactions/day (2026): ~700M

  • P2M share: ~60% → 420M

  • Tea stalls in India: ~10M

  • QR-enabled stalls: ~50% → 5M

  • Avg UPI txns per stall/day: ~40

Calculation:

  • 5M × 40 = 200M transactions/day

Final Answer: ~200 Million UPI transactions per day

  1. Concurrent OTT Viewers for India vs Pakistan Match

Segmentation: Peak-event engagement

Assumptions & Working:

  • Peak concurrency in recent (2025–26) tournaments on platforms like JioHotstar: ~60 Crore

  • Smartphone users: ~800M

  • During final overs / winning moment:
    • ~75% of active mobile users tune in simultaneously

Final Answer: ~600 Million peak concurrent viewers

  1. Annual Revenue of Netflix India

Segmentation: Subscribers × ARPU

Assumptions & Working:

  • Paid subscribers: ~10M

  • Avg revenue/user/month: ₹400

  • Annual revenue:
    • 10M × ₹400 × 12 = ₹4,800 Cr

Growth Overlay:

  • ~30% YoY growth → rounds to ₹5,000 Cr

Final Answer: ~₹5,000 Crores annually (~$600M)

  1. Data Consumed in a Mumbai Local Train (Peak Hour)

Segmentation: Ultra-dense usage environment

Assumptions & Working:

  • 12-coach train peak load: ~4,500 people

  • Active phone users: 80% → 3,600

Usage Mix:

  • 40% video users:

    • 1,440 × 0.5 GB/hr = 720 GB

  • 60% light users (chat/scroll):

    • 2,160 × 0.05 GB/hr = 108 GB

Total Data Consumption:

  • ~828 GB per train per hour

Final Answer: ~800 GB to 1 TB per train per peak hour

 

 

Category 4: Oddball / Structural Guesstimates

  1. Number of Tennis Balls in a Boeing 747

Logic: Volume of a cylinder × packing efficiency

Assumptions & Working:

  • Fuselage ≈ cylinder
  • Length ≈ 70 m
  • Radius ≈ 3 m

Total Volume:

  • π × r² × h ≈ ~1,980 m³

Usable Volume:

  • Subtract ~30% for cockpit, seats, cargo bays
  • Net volume ≈ 1,386 m³

Tennis Ball:

  • Diameter ≈ 6.7 cm → Volume ≈ 160 cm³
  • Convert aircraft volume to cm³

Packing Efficiency:

  • Spheres pack at ~70%

Final Answer: ~6.1 Million tennis balls

  1. Number of Tennis Balls in a Standard Swimming Pool

Logic: Simple volume displacement

Assumptions & Working:

  • Pool size: 25 m × 10 m × 2 m
  • Total volume = 500 m³
  • Apply 70% packing efficiency

Calculation:

  • Effective volume ≈ 350 m³
  • Divide by volume of one tennis ball

Final Answer: ~2.3 Million tennis balls

  1. Weight of the Taj Mahal Hotel (Mumbai)

Logic: Volume × density × solid fraction

Assumptions & Working:

  • Footprint ≈ 150 m × 100 m
  • Height ≈ 40 m
  • Total volume ≈ 600,000 m³

Hollow Factor:

  • Only ~15% is solid material
  • Solid volume ≈ 90,000 m³

Material Density:

  • Concrete/stone ≈ 2,000 kg/m³

Weight:

  • 90,000 × 2,000 = 180,000,000 kg

Final Answer: ~180,000 tonnes

  1. Quantity of Paint Required for an Airbus A320

Logic: Surface area estimation

Assumptions & Working:

  • Fuselage ≈ cylinder
    • Length ≈ 37 m
    • Radius ≈ 2 m
  • Surface area ≈ 465 m²
  • Wings + tail ≈ ~400 m²

Total Area: ~850–900 m²

Paint Coverage:

  • Industrial aviation paint ≈ 6–8 m² per liter

Final Answer: ~120–150 liters of paint

  1. Number of Street Lights in Chandigarh

Logic: Road length × spacing

Assumptions & Working:

  • City area ≈ 110 km²
  • Major grid roads:
    • ~22 main roads × 10 km each = 220 km
  • Poles every 25 m, both sides
    • 80 poles per km

Main Roads:

  • 220 × 80 ≈ 17,600 poles

Internal Roads Buffer:

  • Add ~50%

Final Answer: ~25,000–30,000 street lights

  1. Weight of Garbage Generated by Delhi (Daily)

Logic: Per-capita waste generation

Assumptions & Working:

  • Population: 32 Million
  • Waste/person/day ≈ 4 kg

Domestic Waste:

  • 32M × 0.4 = 12,800 tonnes/day

Commercial + Industrial Buffer:

  • Add ~20%

Final Answer: ~15,000 tonnes per day

  1. Total Gold Held by Indian Households

Logic: Cultural asset allocation

Assumptions & Working:

  • Total households: 300M

Rural:

  • 200M households
  • 70% own gold
  • Avg holding: 30 g
  • ≈ 4,200 tonnes

Urban:

  • 100M households
  • 80% ownership
  • Avg holding: 150 g
  • ≈ 12,000 tonnes

Top 1% Wealth Concentration:

  • High accumulation ≈ ~5,000 tonnes

Final Answer: ~22,000–25,000 tonnes
(Matches World Gold Council estimates)

  1. Square Inches of Pizza Consumed in India (Daily)

Logic: Market volume × geometric area

Assumptions & Working:

  • Pizzas sold/day ≈ 1 Million
    • (Domino’s alone ~4 lakh/day)
  • Avg pizza diameter: 10 inches

Area per Pizza:

  • π × r² = π × 25 ≈ 5 sq inches

Total Area:

  • 1M × 78.5

Final Answer: ~78.5 Million square inches per day

 

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