Practice cases: Global
Four full cases with a global lens: electric city buses, electric mining trucks, hotel revenue, and choosing a first international market.
Key takeaways
- Worked case: Should a city switch to electric buses?
- Worked case: Electrifying a mine's haul trucks.
- Worked case: A hotel group's Southern Europe revenue fell.
- Worked case: Tallyfern: which international market first?
Four full cases with a global lens: electric city buses, electric mining trucks, hotel revenue, and choosing a first international market.
Cover the solution and run each case out loud, ideally with a partner playing the interviewer. Ask your own clarifying questions, state a hypothesis, build a structure, and do the math on paper before you look. Then compare your synthesis with the one given, and read the strong and weak candidate notes. Each case is labeled Starter, Standard, or Stretch.
Case 1: Should a city switch to electric buses?
Worked case
Standard: Should a city switch to electric buses?
The prompt
A large city plans to replace 1,000 diesel buses. An international development bank asks whether electric buses make financial sense. The exhibit compares costs per bus. What do you recommend?
Difficulty: Standard. Format: interviewer-led, with an exhibit. Industry: Public sector and transport. Region: Global (a large city in a middle-income country). Interview length: about 30 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- How many buses and over what life?Answer: 1,000 buses, each used for about 12 years.
- Who pays?Answer: The city, with a loan from an international development bank for the upfront cost.
- Is power available for charging?Answer: Yes, at the city's depots, with new charging equipment.
A hypothesis to say out loud: Electric buses cost more to buy but less to run. My hypothesis is that over 12 years they are cheaper in total, and the real problem is financing the higher upfront cost.
The structure
- Total cost of ownership over 12 years
- Purchase and charging equipment
- Energy or fuel and maintenance each year
- Key: Total cost per bus and for the fleet
- Upfront financing need
The exhibit
| Cost item | Diesel bus | Electric bus |
|---|---|---|
| Purchase price | 250 | 450 |
| Fuel or electricity a year | 50 | 20 |
| Maintenance a year | 20 | 12 |
| Charging equipment (one time) | 0 | 50 |
Working it through
1. Diesel bus over 12 years
Purchase plus 12 years of fuel and maintenance (USD thousands).
Diesel total (USD thousands):250 + 12 × (50 + 20) = 1,0902. Electric bus over 12 years
Purchase, charging equipment, and 12 years of power and maintenance.
Electric total (USD thousands):450 + 50 + 12 × (20 + 12) = 8843. Saving per bus
Diesel total minus electric total.
Saving per bus (USD thousands):(250 + 12 × (50 + 20)) - (450 + 50 + 12 × (20 + 12)) = 2064. Upfront gap for the fleet
Extra upfront cost per bus (purchase plus charging, minus the diesel price) for 1,000 buses, in USD million.
Extra upfront cost (USD million):1,000 × ((450 + 50) - 250) ÷ 1,000 = 2505. Payback of the extra upfront cost
The yearly running saving per bus is the difference in fuel and maintenance.
Payback (years):250 ÷ ((50 + 20) - (20 + 12)) = 6.586. Curveball: battery replacement
Interviewer: "Engineers expect each battery to need replacing once, in year 7, at about USD 100 thousand." The undiscounted saving falls to USD 106 thousand per bus, and payback of the extra spending becomes:
Payback including the battery (years):(250 + 100) ÷ ((50 + 20) - (20 + 12)) = 9.217. Discounted at 5 percent
Interviewer: "At 5 percent, USD 1 a year for 12 years is worth about 8.86 today, and USD 1 in year 7 about 0.71." Net present value per bus of switching:
NPV at 5 percent (USD thousands):38 × 8.86 - 250 - 100 × 0.71 = 15.688. Discounted at 8 percent
Interviewer: "At 8 percent, the factors are about 7.54 and 0.58." The year-7 battery now tips the answer negative:
NPV at 8 percent (USD thousands):38 × 7.54 - 250 - 100 × 0.58 = -21.48
What the exhibit shows
Electric buses cost USD 250 thousand more upfront including charging, but save USD 38 thousand a year to run.
The recommendation
I recommend switching to electric buses, but only with low-cost, long-term financing and battery protection. First, before discounting, an electric bus costs about USD 884 thousand over 12 years against USD 1,090 thousand for diesel. Second, one battery replacement cuts the saving to about USD 106 thousand per bus; at a 5 percent development-bank rate switching is worth about USD 16 thousand per bus, but at 8 percent about minus USD 21 thousand. Third, the USD 250 million extra upfront cost therefore needs a long, low-rate loan. Phase the switch depot by depot.
Risks: Electricity prices may rise; Charging depots need reliable grid supply; Staff need training to maintain electric buses.
Next steps: Run a pilot with 50 buses on two routes; Tender with battery warranties and service terms.
A strong candidate
Compared total cost over the life of the bus, found the upfront gap, and matched financing to the running savings.
A weak candidate
Compared purchase prices only and rejected electric buses as too expensive.
Case 2: Electrifying a mine's haul trucks
Worked case
Stretch: Electrifying a mine's haul trucks
The prompt
A global mining company is considering replacing its 50 diesel haul trucks at one mine with battery-electric trucks. Should it?
Difficulty: Stretch. Format: candidate-led, with interviewer dialogue. Industry: Mining and energy. Region: Global (a mine in Australia or South America). Interview length: about 40 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- How many trucks, and how long will the mine run?Answer: 50 haul trucks; the mine has about 15 years of life left.
- What does an electric truck cost and save?Answer: USD 3 million more per truck, plus USD 40 million of charging equipment for the site. It saves about USD 500,000 a year in energy and USD 100,000 in maintenance per truck.
- What carbon price applies?Answer: The company's internal carbon price of USD 50 per tonne; each diesel truck emits about 2,000 tonnes a year.
A hypothesis to say out loud: Electric haul trucks save fuel and carbon costs but need large upfront spending. My hypothesis is that payback is around five to six years, and that the source of electricity matters as much as the trucks.
The structure
- Upfront cost per truck versus yearly savings
- Upfront: extra truck cost plus a share of charging
- Key: Savings: energy, maintenance, carbon
- Payback versus mine life
- Where the electricity comes from
Working it through
1. Yearly saving per truck
Candidate: "Energy, plus carbon avoided at USD 50 per tonne, plus maintenance."
Saving (USD a year):500,000 + 2,000 × 50 + 100,000 = 700,0002. Upfront cost per truck
Extra truck cost plus one fiftieth of the charging equipment.
Upfront per truck (USD):3,000,000 + 40,000,000 ÷ 50 = 3,800,0003. Payback
Well inside the 15 years of mine life.
Payback (years):(3,000,000 + 40,000,000 ÷ 50) ÷ (500,000 + 2,000 × 50 + 100,000) = 5.434. Fleet upfront cost
50 trucks plus the charging equipment.
Fleet upfront (USD):50 × 3,000,000 + 40,000,000 = 190,000,0005. Curveball: diesel-generated power
Interviewer: "The mine is remote. Its electricity comes from diesel generators, so diesel use and emissions fall only about 30 percent, and the energy saving is only about USD 225,000 a truck." Candidate: "Then both savings shrink, and payback becomes:"
Payback with diesel power (years):3,800,000 ÷ (225,000 + 2,000 × 0.3 × 50 + 100,000) = 10.76. Adding a solar and battery plant
Interviewer: "A partner would build solar with storage and sell us power, raising the energy saving to USD 600,000 a truck and cutting emissions 80 percent." Candidate: "Payback becomes:"
Payback with solar power (years):3,800,000 ÷ (600,000 + 2,000 × 0.8 × 50 + 100,000) = 4.87
The recommendation
Electrify the trucks, together with a solar and storage power supply. First, on clean power each truck pays back in about 5.4 years, well within the mine's 15-year life. Second, on today's diesel-generated power most of the energy and carbon savings disappear and payback stretches to about 10.7 years, too close to the mine's remaining life, so a clean power supply is essential. Third, buying solar power through a partner raises energy savings and cuts emissions 80 percent, bringing payback under 5 years. Replace trucks as the diesel fleet reaches the end of its life rather than all at once, to spread the USD 190 million cost and learn from the first trucks.
Risks: Battery trucks are newer technology in mining; reliability must be proven; Carbon prices may change; Solar output varies, so storage and backup are needed.
Next steps: Run a trial with five electric trucks; Tender a long-term solar and storage power contract.
A strong candidate
Built the per-truck business case, compared payback with mine life, caught that diesel-generated power undermines the carbon benefit, and fixed the power source.
A weak candidate
Assumed electric trucks remove all emissions without asking where the electricity comes from.
Case 3: A hotel group's Southern Europe revenue fell
Worked case
Starter: A hotel group's Southern Europe revenue fell
The prompt
A global hotel group, which reports in US dollars, saw room revenue fall in its Southern Europe hotels after raising prices. The exhibit shows the figures. What happened, and what should it do?
Difficulty: Starter. Format: interviewer-led, with an exhibit. Industry: Travel and hotels. Region: Global (Southern Europe portfolio). Interview length: about 25 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- How is hotel revenue measured?Answer: Revenue per available room (RevPAR): occupancy times the average daily rate.
- Did the number of rooms change?Answer: No, about 10,000 rooms.
- What changed in pricing?Answer: The group raised its average rate this year.
A hypothesis to say out loud: The group raised rates, so my hypothesis is that occupancy fell by more than the rate gain, lowering RevPAR.
The structure
- Room revenue = rooms x 365 x occupancy x average daily rate
- Key: Occupancy
- Average daily rate
- RevPAR and revenue
The exhibit
| Measure | Last year | This year |
|---|---|---|
| Occupancy (%) | 80 | 72 |
| Average daily rate (USD) | 150 | 160 |
| Rooms | 10,000 | 10,000 |
Working it through
1. RevPAR last year
80 percent occupancy at USD 150.
RevPAR last year (USD):0.8 × 150 = 1202. RevPAR this year
72 percent at USD 160.
RevPAR this year (USD):0.72 × 160 = 1153. Change in yearly revenue
RevPAR change times 10,000 rooms times 365 nights.
Revenue change (USD a year):(0.72 × 160 - 0.8 × 150) × 10,000 × 365 = -17,520,0004. Occupancy effect
Lower occupancy at last year's rate.
Occupancy effect (USD a year):(0.72 - 0.8) × 150 × 10,000 × 365 = -43,800,0005. Rate effect
Higher rate at this year's occupancy. Together with the occupancy effect, this gives the total change.
Rate effect (USD a year):(160 - 150) × 0.72 × 10,000 × 365 = 26,280,0006. Curveball: short-term rentals
Interviewer: "Short-term rental apartments grew fast in these cities. If we return to USD 150, we expect occupancy to recover only to 78 percent." RevPAR would be:
RevPAR at USD 150 and 78 percent (USD):0.78 × 150 = 117
What the exhibit shows
The rate rose about 7 percent but occupancy fell 8 points, so revenue per room fell.
The recommendation
Revenue fell about USD 17.5 million because the price rise cost more occupancy than it gained in rate. First, lower occupancy cost about USD 43.8 million, while the higher rate added about USD 26.3 million. Second, short-term rentals have taken part of the market for now, so returning to USD 150 recovers occupancy only to 78 percent and RevPAR to about USD 117, still below last year. Third, a blanket rate rise across all days and segments was the wrong tool: use revenue management that charges more at peak times and for business travelers, and less on quiet days and for longer stays, where rentals compete most.
Risks: Rentals may keep growing; Discounts on quiet days can spread to busy days.
Next steps: Analyze occupancy by day of week and guest type; Launch longer-stay offers in the three most affected cities.
A strong candidate
Used RevPAR, split the change into occupancy and rate effects, and used the curveball to see that the market had changed.
A weak candidate
Said the price rise "worked" because the average rate went up, ignoring occupancy.
Case 4: Tallyfern: which international market first?
Worked case
Stretch: Tallyfern: which international market first?
The prompt
Written case: Tallyfern, a software company selling accounting subscriptions to small businesses, must choose its first international market among Germany, the UAE, and India. Using the data pack below, write a one-page recommendation.
Difficulty: Stretch. Format: written case, with a data pack. Industry: Technology (software). Region: Global (Germany, UAE, India). Interview length: about 45 minutes. The company is fictional and all figures are illustrative. Lead with the recommendation, then show a short table of the numbers that support it.
Clarifying questions, with the interviewer's answers
- What does the company sell?Answer: Accounting software for small businesses, sold by monthly subscription, with an 80 percent gross margin everywhere.
- What is the goal?Answer: Pick one market to enter first, based on revenue in year three and customer economics.
- Are there local requirements?Answer: Each market needs tax and invoicing localization: Germany (e-invoicing and GoBD bookkeeping rules), the UAE (VAT and planned e-invoicing), and India (GST e-invoicing), about USD 0.5 million one time each (illustrative). Many German customers also prefer their data stored in Germany.
A hypothesis to say out loud: Large markets are not always the best first choice. My hypothesis is that the market with the best customer economics (lifetime value against acquisition cost) should go first, even if it is not the biggest.
The structure
- Year-3 revenue and customer economics by market
- Customers and ARR in year 3
- Key: LTV/CAC
- Local costs and requirements
The exhibit
| Market | Target small businesses | Expected share by year 3 (%) | Price (USD a month) | CAC (USD) | Monthly churn (%) |
|---|---|---|---|---|---|
| Germany | 400,000 | 2 | 60 | 900 | 1.5 |
| UAE | 80,000 | 4 | 50 | 600 | 2.5 |
| India | 1,500,000 | 1 | 15 | 150 | 4 |
Working it through
1. Germany: year-3 ARR
2 percent of 400,000 businesses at USD 60 a month.
ARR (USD):400,000 × 0.02 × 60 × 12 = 5,760,0002. UAE: year-3 ARR
4 percent of 80,000 at USD 50 a month.
ARR (USD):80,000 × 0.04 × 50 × 12 = 1,920,0003. India: year-3 ARR
1 percent of 1,500,000 at USD 15 a month.
ARR (USD):1,500,000 × 0.01 × 15 × 12 = 2,700,0004. Germany: LTV/CAC
Monthly contribution divided by monthly churn, then divided by CAC.
LTV/CAC:(60 × 0.8 ÷ 0.015) ÷ 900 = 3.565. UAE: LTV/CAC
Same method.
LTV/CAC:(50 × 0.8 ÷ 0.025) ÷ 600 = 2.676. India: LTV/CAC
Same method.
LTV/CAC:(15 × 0.8 ÷ 0.04) ÷ 150 = 27. Curveball: local data hosting in Germany
Interviewer: "Many German customers prefer data stored in Germany, and hosting it there would cost about USD 1 million a year." Germany's year-3 contribution after that cost:
Germany contribution (USD a year):400,000 × 0.02 × 60 × 12 × 0.8 - 1,000,000 = 3,608,0008. Germany LTV/CAC after hosting
Spread over 8,000 German customers, hosting costs about USD 10.4 per customer a month (USD 1,000,000 / 8,000 / 12), lowering monthly contribution:
LTV/CAC after hosting:((60 × 0.8 - 1,000,000 ÷ 8,000 ÷ 12) ÷ 0.015) ÷ 900 = 2.78
What the exhibit shows
India has the most businesses but the lowest price and highest churn; Germany has fewer businesses but the best customer economics.
The recommendation
I recommend that Tallyfern enter Germany first, plan the UAE as its second market, and approach India later with a different product. First, Germany gives the highest year-3 recurring revenue: 2 percent of 400,000 businesses at USD 60 a month is about USD 5.8 million, against USD 2.7 million in India and USD 1.9 million in the UAE. Second, it has the best customer economics. With 1.5 percent monthly churn and a CAC of USD 900, its LTV/CAC is about 3.6, against about 2.7 in the UAE and 2 in India, where a USD 15 price and 4 percent churn leave little room to pay for acquisition. Third, the choice survives the main local cost. Hosting data in Germany would cost about USD 1 million a year, which lowers LTV/CAC to about 2.8, still above both other markets, and leaves a year-3 contribution of about USD 3.6 million, the largest of the three. The UAE is a sound second step: a small market, but a 4 percent share and an LTV/CAC of about 2.7 make it a good base for the Gulf. India has the most businesses, but at its price it needs a lower-cost product and sales model first. The main risk is that the 2 percent share proves optimistic, since German customers may expect local-language support and accounting features. As a next step, confirm hosting and data rules with German customers and test pricing with 50 German accounting firms that advise small businesses.
Risks: German customers may expect local-language support and accounting features; Share assumptions may be optimistic in a crowded market.
Next steps: Confirm hosting and data rules with German customers; Test pricing with 50 German accounting firms that advise small businesses.
A strong candidate
Led with a clear choice, compared markets on both revenue and customer economics, and tested the German hosting cost.
A weak candidate
Chose India because it has the most businesses, without checking price, churn, or acquisition cost.
Sources for this lesson (1)
- Recognized public explanations of case-interview concepts and frameworks
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