Practice cases: Middle East
Six full cases set in the Gulf: an airline route, a government service center, a private-equity clinic deal, fiber broadband in Oman, hotel rooms for a new heritage destination in Saudi Arabia, and a public health screening programme in the UAE.
Key takeaways
- Where the structure comes from: it is built from the goal of this exact question (Route profit = seats x load factor x fare - seats x cost per seat), not taken from a list.
- Where the structure comes from: it is built from the goal of this exact question (Wait depends on arrivals and capacity), not taken from a list.
- Where the structure comes from: it is built from the goal of this exact question (Value today, value at exit, and the fund's return), not taken from a list.
Six full cases set in the Gulf: an airline route, a government service center, a private-equity clinic deal, fiber broadband in Oman, hotel rooms for a new heritage destination in Saudi Arabia, and a public health screening programme in the UAE.
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 from the maths of the goal (not from a memorised list), 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: Rimal Air: profit on the Dubai to London route has almost gone
Where the structure comes from: it is built from the goal of this exact question (Route profit = seats x load factor x fare - seats x cost per seat), not taken from a list. Each branch is one driver of that goal, and the hypothesis above says which branch to test first.
Worked case
Starter: Rimal Air: profit on the Dubai to London route has almost gone
The prompt
Rimal Air, a Gulf airline, made AED 80 million of profit on its Dubai to London route last year. This year the route made almost nothing. The exhibit shows the route's key figures. What happened, and what should Rimal Air do?
Difficulty: Starter. Format: interviewer-led, with an exhibit. Industry: Airlines. Region: UAE and UK. Interview length: about 25 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- Did the number of flights or the aircraft size change?Answer: No, the same schedule, about 400,000 seats a year.
- Did fares change?Answer: The average one-way fare was flat at AED 2,000.
- Did anything change in the market?Answer: A rival started a new daily flight on the route this year.
A hypothesis to say out loud: Seats and fares are flat, so my hypothesis is that fewer passengers per flight (a lower load factor), likely because of the rival's new flight, drove most of the fall, with some cost increase on top.
The structure
- Route profit = seats x load factor x fare - seats x cost per seat
- Key: Revenue: seats, load factor, fare
- Cost: cost per seat flown
- Market: the rival's new flight
The exhibit
| Measure | Last year | This year |
|---|---|---|
| Seats flown (a year) | 400,000 | 400,000 |
| Load factor (%) | 85 | 78 |
| Average one-way fare (AED) | 2,000 | 2,000 |
| Cost per seat flown (AED) | 1,500 | 1,550 |
Working it through
1. Revenue last year
400,000 seats, 85 percent full, AED 2,000 per passenger.
Revenue last year (AED):400,000 × 0.85 × 2,000 = 680,000,0002. Revenue this year
Same seats and fare, but only 78 percent full.
Revenue this year (AED):400,000 × 0.78 × 2,000 = 624,000,0003. Profit last year
Revenue minus 400,000 seats at AED 1,500 each.
Profit last year (AED):400,000 × 0.85 × 2,000 - 400,000 × 1,500 = 80,000,0004. Profit this year
Cost per seat rose to AED 1,550.
Profit this year (AED):400,000 × 0.78 × 2,000 - 400,000 × 1,550 = 4,000,0005. Revenue effect
The lower load factor alone.
Revenue effect (AED):(0.78 - 0.85) × 400,000 × 2,000 = -56,000,0006. Cost effect
The higher cost per seat alone. Together with the revenue effect, this explains the AED 76 million fall.
Extra cost (AED):(1,550 - 1,500) × 400,000 = 20,000,0007. Curveball: how close to a loss?
Interviewer: "The rival plans a second daily flight next year. How much room do we have?" The route breaks even when the share of seats filled equals cost per seat divided by fare.
Break-even load factor (%):1,550 ÷ 2,000 × 100 = 77.5
What the exhibit shows
Fares and seats did not change. Fewer seats were filled and each seat cost a little more to fly, which together wiped out the profit.
The recommendation
Profit fell by AED 76 million, mostly because the route now fills fewer seats. First, the load factor fell from 85 to 78 percent after the rival's new flight, costing AED 56 million of revenue. Second, cost per seat rose AED 50, costing AED 20 million. Third, the route now breaks even at 77.5 percent full, so a second rival flight could push it into a loss. Rimal Air should fly smaller aircraft on quieter days to fill a higher share of seats, sharpen revenue management with more fare levels for early and late bookers, feed the route with connecting passengers from its network, and review fuel hedging and airport costs.
Risks: Smaller aircraft may lose premium-cabin revenue; The rival may cut fares, forcing a price response.
Next steps: Check load factor by day of week and cabin; Model a smaller aircraft on the four quietest days.
A strong candidate
Split profit into revenue and cost, sized both effects, and used the break-even load factor to show how exposed the route is before the curveball.
A weak candidate
Suggested cutting fares to win back passengers, without checking that the route is already close to a loss.
Case 2: Cutting waiting times at a government service center
Where the structure comes from: it is built from the goal of this exact question (Wait depends on arrivals and capacity), not taken from a list. Each branch is one driver of that goal, and the hypothesis above says which branch to test first.
Worked case
Standard: Cutting waiting times at a government service center
The prompt
A Saudi government agency wants to cut the average wait at its main service center from about 90 minutes to under 30 minutes, without a big rise in running costs. How would you approach this?
Difficulty: Standard. Format: candidate-led, with interviewer dialogue. Industry: Public sector. Region: Saudi Arabia. Interview length: about 30 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- Is the 90-minute wait an average across the day?Answer: Yes, an average.
- How many visitors come, and how long does a visit take at the counter?Answer: About 480 visitors in an 8-hour day; about 15 minutes per visit, with 15 counters open.
- Are there limits?Answer: The agency prefers not to add permanent staff; a digital channel would cost about SAR 2 million one time.
A hypothesis to say out loud: If the counters are almost always busy, even small changes in arrivals create long queues. My hypothesis is that the center runs close to full capacity, and the best lever is fewer avoidable visits rather than more counters.
The structure
- Wait depends on arrivals and capacity
- Key: Arrivals per hour, and how many are avoidable
- Service capacity (counters x visits per hour)
- Utilization and the queue (Little's Law)
- Levers: fewer avoidable visits, online services, more counters
Working it through
1. Arrivals per hour
Candidate: "480 visitors over 8 hours is:"
Arrivals per hour:480 ÷ 8 = 602. Capacity per hour
Candidate: "Each counter serves 4 visitors an hour at 15 minutes each, so 15 counters serve:"
Visitors served per hour:15 × 60 ÷ 15 = 603. Utilization
Candidate: "Arrivals equal capacity, so counters are busy all the time. At 100 percent a queue is unstable: any delay builds it up, and at peaks it only clears after closing."
Utilization (%):(480 ÷ 8) ÷ (15 × 60 ÷ 15) × 100 = 1004. People waiting
Candidate: "By Little's Law, people waiting equals arrivals per hour times the wait in hours."
Average number waiting:60 × 1.5 = 905. Counters needed at 80 percent utilization
Candidate: "Queues stay short when counters are busy about 80 percent of the time or less."
Counters needed:60 × 15 ÷ 60 ÷ 0.8 = 18.756. Cost of adding counters
Interviewer: "Each extra counter costs about SAR 300,000 a year in staff." Four more counters would cost:
Yearly cost (SAR):(19 - 15) × 300,000 = 1,200,0007. Curveball: avoidable visits
Interviewer: "One more fact: about 20 percent of visits are repeat visits, because applicants forgot a document the first time." Candidate: "Then fixing that alone cuts arrivals to:"
Arrivals per hour without repeat visits:60 × (1 - 0.2) = 488. Adding online services
Candidate: "If 30 percent of the remaining visits move online, utilization of today's 15 counters becomes:"
Utilization after both changes (%):60 × (1 - 0.2) × (1 - 0.3) ÷ 60 × 100 = 56
The recommendation
Cut avoidable visits first, then move simple services online, rather than adding counters. First, the center runs at 100 percent utilization, which is why about 90 people are waiting on average. Second, a document checklist sent before the visit, plus an online pre-check, targets the 20 percent of repeat visits at very low cost; the 56 percent figure that follows assumes it removes nearly all of them. Third, moving 30 percent of simple services online for about SAR 2 million one time brings utilization to about 56 percent with today's 15 counters, well below the 80 percent level where queues stay short; at 80 percent or lower with 15 counters, the average wait should fall to a few minutes, well under the 30-minute goal. Four extra counters, by contrast, would cost SAR 1.2 million every year. Track average wait, first-visit resolution, and the share of services completed online each week.
Risks: Some citizens may prefer or need in-person service; Online services need good design, or they create new calls and visits.
Next steps: Launch a document checklist by text message before appointments; Pick the five simplest services to move online first.
A strong candidate
Used utilization and Little's Law to explain the queue, found the avoidable demand through a good question, and compared one-time and yearly costs.
A weak candidate
Recommended hiring more staff straight away, missing the repeat visits and the cheaper online option.
Case 3: Should a fund buy Qasr Clinics?
Where the structure comes from: it is built from the goal of this exact question (Value today, value at exit, and the fund's return), not taken from a list. Each branch is one driver of that goal, and the hypothesis above says which branch to test first.
Worked case
Stretch: Should a fund buy Qasr Clinics?
The prompt
Written case: a Gulf private-equity fund is considering buying Qasr Clinics, a chain of 20 outpatient clinics in the UAE. Using the data pack below, prepare a three-slide answer: is the deal attractive at the asking price, what are the main risks, and what should the fund offer?
Difficulty: Stretch. Format: written case, with a data pack. Industry: Private equity and healthcare. Region: UAE. Interview length: about 45 minutes. The company is fictional and all figures are illustrative. In a written case you usually get 30 to 60 minutes with a data pack, then present your slides and answer questions.
Clarifying questions, with the interviewer's answers
- What return does the fund need?Answer: About 20 percent a year over five years.
- How are clinics paid?Answer: Mostly by private health insurers, at agreed tariffs per visit.
- How will new clinics be funded?Answer: From the company's own cash flow; the data pack shows debt at exit after paydown.
A hypothesis to say out loud: Clinic chains grow by opening sites, and the price looks close to what such businesses sell for. My hypothesis is that the plan gives a return near, but below, the fund's target, and that insurer tariffs are the key risk.
The structure
- Value today, value at exit, and the fund's return
- Revenue and EBITDA today
- Entry price as a multiple of EBITDA
- Key: Growth plan, exit value, MOIC, and IRR
- Risk: insurer tariffs
The exhibit
| Item | Value |
|---|---|
| Clinics today | 20 |
| Visits per clinic per day | 125 |
| Days open a year | 360 |
| Average revenue per visit (AED) | 400 |
| EBITDA margin (%) | 20 |
| Asking enterprise value (AED million) | 576 |
| Debt available at entry (AED million) | 288 |
| New clinics planned over 5 years | 10 |
| EBITDA per mature new clinic (AED million a year) | 3 |
| Debt at exit after paydown (AED million) | 188 |
| Expected exit multiple (EV/EBITDA) | 8 |
Working it through
1. Revenue today
20 clinics x 125 visits a day x 360 days x AED 400 per visit.
Revenue (AED a year):20 × 125 × 360 × 400 = 360,000,0002. EBITDA today
At a 20 percent EBITDA margin. The asking price of AED 576 million is 8 times this EBITDA.
EBITDA (AED a year):20 × 125 × 360 × 400 × 0.2 = 72,000,0003. Exit value
Ten new clinics each add AED 3 million of EBITDA once mature, giving AED 102 million in year five, sold at 8 times.
Exit EV (AED million):(72 + 10 × 3) × 8 = 8164. MOIC
Equity at exit (exit value minus AED 188 million of remaining debt) divided by equity invested (AED 576 million minus AED 288 million of debt).
MOIC:(816 - 188) ÷ (576 - 288) = 2.185. IRR check
About 2.2 times in five years is roughly 17 percent a year, below the 20 percent target.
1.17 to the power of 5:1.17 × 1.17 × 1.17 × 1.17 × 1.17 = 2.196. Price that meets the target
For 2.5 times the money (about 20 percent a year), equity invested must be AED 628 million divided by 2.5, plus the AED 288 million of debt.
Maximum EV to meet the target (AED million):(816 - 188) ÷ 2.5 + 288 = 5397. Curveball: insurers cut tariffs 5 percent
The fund hears that insurers, backed by a revised regulator price list, plan to cut clinic tariffs by 5 percent. With costs unchanged, EBITDA falls by 5 percent of AED 360 million of revenue, and the value of today's business at 8 times becomes:
Value after a 5 percent tariff cut (AED million):(72 - 360 × 0.05) × 8 = 4328. Price that still meets the target after the cut
With the cut, year-five EBITDA is at most AED 84 million (54 plus 30 from new clinics). This generously keeps AED 3 million per new clinic; new clinics are paid by the same insurers, so their EBITDA would fall too and the true price is lower still. With the same AED 288 million of debt, the price that still returns 2.5 times is:
Maximum EV after a tariff cut (AED million):((72 - 360 × 0.05 + 10 × 3) × 8 - 188) ÷ 2.5 + 288 = 482
What the exhibit shows
The price is 8 times EBITDA, and the plan adds about 40 percent more EBITDA through new clinics. Whether that clears a 20 percent return depends on the price paid and on insurer tariffs.
The recommendation
Slide 1, the answer: the fund should not pay the asking price of AED 576 million, but the deal works at about AED 540 million with protection against tariff cuts. Today the 20 clinics earn AED 360 million of revenue and AED 72 million of EBITDA, so the asking price is 8 times EBITDA. With ten new clinics adding AED 3 million each, year-five EBITDA reaches AED 102 million and the exit value at 8 times is AED 816 million. After debt falls to AED 188 million, the fund gets about 2.2 times its AED 288 million of equity, roughly 17 percent a year, below its 20 percent target. Slide 2, the reasons and risks: first, the entry and exit multiples are both 8, so all the return must come from new clinics and debt paydown; second, the plan depends on opening ten clinics on time; third, a 5 percent tariff cut by insurers would cut today's value to about AED 432 million, because costs do not fall with tariffs. Doctors leaving after the sale is a further risk. Slide 3, the offer: bid about AED 540 million, the price at which the plan returns about 2.5 times, but only with protection against tariff cuts, such as a price adjustment or an earn-out tied to tariffs. If a 5 percent cut looks likely, the price that still returns about 2.5 times falls to at most about AED 480 million (lower if the new clinics also earn less), with the same AED 288 million of debt. As a next step, review the top five insurer contracts and the pipeline of clinic sites before signing.
Risks: Insurer tariff cuts; Delays in opening new clinics; Doctors leaving after the sale.
Next steps: Review the terms and renewal dates of the top five insurer contracts; Visit the planned clinic sites and check licensing timelines; Plan retention for senior doctors.
A strong candidate
Built value from the data pack step by step, compared the return with the fund's target, found the price that works, and tested the tariff risk. The slides led with the answer.
A weak candidate
Summarized the data pack line by line and ended with "the deal looks attractive because the market is growing," with no return calculation.
Case 4: Wadi Telecom: size the home fiber market, then build or rent?
Where the structure comes from: it is built from the goal of this exact question (Size the market, then compare build with rent), not taken from a list. Each branch is one driver of that goal, and the hypothesis above says which branch to test first.
Worked case
Standard: Wadi Telecom: size the home fiber market, then build or rent?
The prompt
First, estimate how many homes in Oman have fiber broadband. Then: Wadi Telecom, an Omani operator, can extend fiber to 100,000 more homes at OMR 300 per home passed. It expects 40 percent of those homes to sign up, paying OMR 25 a month, with a 60 percent contribution margin. Should it build?
Difficulty: Standard. Format: market-sizing opener, then a business question. Industry: Telecom. Region: Oman. Interview length: about 30 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- Homes only, or businesses too?Answer: Homes only.
- How many households are there, and how many can get fiber today?Answer: Use about 1,000,000 households, rounded and illustrative; about 70 percent can get fiber.
- Where fiber is available, how many homes take it?Answer: About half.
- For the business question, how long does fiber last and what discount rate should I use?Answer: Fiber lasts 20 years or more; use 8 percent. At 8 percent, OMR 1 a year is worth about OMR 9.82 today over 20 years, and about OMR 5.75 over 8 years.
A hypothesis to say out loud: Fiber take-up is limited by where the network reaches. My hypothesis is that the market is several hundred thousand lines, and that for a new area building pays off only if enough homes sign up.
The structure
- Size the market, then compare build with rent
- Households x share with fiber available x take-up
- Key: Build: capital cost versus yearly contribution
- Rent: use the open-access network instead
Working it through
1. Homes with fiber
About 70 percent of about 1,000,000 households can get fiber, and about half of those take it.
Fiber lines:1,000,000 × 0.7 × 0.5 = 350,0002. Yearly contribution if Wadi builds
40,000 subscribers at OMR 25 a month and a 60 percent margin.
Contribution (OMR a year):100,000 × 0.4 × 25 × 12 × 0.6 = 7,200,0003. Payback
Building costs OMR 30 million (100,000 homes at OMR 300 each).
Payback (years):100,000 × 300 ÷ (100,000 × 0.4 × 25 × 12 × 0.6) = 4.174. Curveball: rent from the open-access network
Interviewer: "Oman's national open-access fiber network offers to rent Wadi access to the same homes for OMR 10 per subscriber a month, with no build cost." When renting, Wadi also avoids network running costs, so its margin before rent would be higher than 60 percent; keep 60 percent to be conservative. Yearly contribution if Wadi rents:
Contribution when renting (OMR a year):100,000 × 0.4 × (25 × 0.6 - 10) × 12 = 2,400,0005. Build over the asset life
Net present value over 20 years at 8 percent: yearly contribution times 9.82, minus the build cost.
Build NPV (OMR):7,200,000 × 9.82 - 30,000,000 = 40,704,0006. Rent over the same period
No build cost.
Rent NPV (OMR):2,400,000 × 9.82 = 23,568,0007. On a short horizon
Over only 8 years (factor 5.75), building minus renting is negative, so renting wins on a short view.
Build minus rent over 8 years (OMR):(7,200,000 - 2,400,000) × 5.75 - 30,000,000 = -2,400,0008. Break-even take-up
Each subscriber earns OMR 15 a month of contribution when Wadi builds, against OMR 5 when it rents. Building wins over 20 years if those extra OMR 10 a month cover the build cost, which needs this take-up:
Break-even take-up (%):30,000,000 ÷ (10 × 12 × 9.82) ÷ 100,000 × 100 = 25.46
The recommendation
Oman has roughly 350,000 homes on fiber. Wadi should build where it is confident take-up will be well above about 25 percent, and rent elsewhere. First, over fiber's 20-year life and at 8 percent, building is worth about OMR 40.7 million today against about OMR 23.6 million for renting, and it pays back in about 4.2 years. Second, on a short 8-year view renting comes out ahead, so the case for building rests on the long asset life. Third, building beats renting only if take-up exceeds about 25 percent; the expected 40 percent gives a margin of safety in dense neighborhoods, while in areas with uncertain demand Wadi should rent from the open-access network first and build later if take-up proves high.
Risks: Take-up below 40 percent would stretch the build payback; Rival price cuts could lower the OMR 25 monthly price.
Next steps: Map expected take-up by neighborhood; Negotiate rental terms with the open-access network as a fallback.
A strong candidate
Built a clean sizing chain, compared build and rent over the asset life with discounting, found the break-even take-up, and tied the choice to take-up by area.
A weak candidate
Sized the market with no stated assumptions, then said "build, because owning the network is strategic," without numbers.
Case 5: Sahra Heritage: how many hotel rooms for a new destination?
Where the structure comes from: it is built from the goal of this exact question (Rooms needed = room nights demanded / (365 x target occupancy)), not taken from a list. Each branch is one driver of that goal, and the hypothesis above says which branch to test first.
Worked case
Standard: Sahra Heritage: how many hotel rooms for a new destination?
The prompt
Sahra Heritage, a government-backed developer in Saudi Arabia, is opening a desert heritage site to visitors. It must decide how many hotel rooms to have ready by the third year. The exhibit shows the plan. How many rooms should it plan for, and how should it add them?
Difficulty: Standard. Format: interviewer-led, with an exhibit. Industry: Tourism and hospitality. Region: Saudi Arabia. Interview length: about 30 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- Is the visitor target for one year?Answer: Yes, 600,000 visitors in the third year after opening (illustrative).
- Do all visitors stay the night?Answer: No, about 60 percent stay, for 2 nights on average; the rest are day trips from the nearest city.
- Is demand even through the year?Answer: I will tell you more about that later.
A hypothesis to say out loud: Hotel rooms depend on overnight guests, not total visitors, so my hypothesis is that the destination needs a bit over twice the rooms it has today, and that seasonality could change the answer.
The structure
- Rooms needed = room nights demanded / (365 x target occupancy)
- Key: Visitors staying overnight, and nights per visitor
- Guests per room, giving room nights
- Target occupancy and rooms already open
- Seasonality: peak and off-peak demand
The exhibit
| Item | Value |
|---|---|
| Visitors a year | 600,000 |
| Share staying overnight (%) | 60 |
| Nights per overnight visitor | 2 |
| Guests per room | 1.8 |
| Rooms open today | 600 |
| Average room rate (SAR a night) | 900 |
Working it through
1. Overnight visitors
600,000 visitors, of whom 60 percent stay the night.
Overnight visitors a year:600,000 × 0.6 = 360,0002. Guest nights
Each overnight visitor stays 2 nights.
Guest nights a year:600,000 × 0.6 × 2 = 720,0003. Room nights
On average 1.8 guests share a room.
Room nights a year:600,000 × 0.6 × 2 ÷ 1.8 = 400,0004. Rooms needed
Planning for rooms to be 70 percent full on average across the year.
Rooms needed at 70 percent occupancy (rooms):400,000 ÷ (365 × 0.7) = 1,5665. Rooms to add
Rounded up to 1,570 rooms, with 600 rooms open today.
New rooms to add (rooms):1,570 - 600 = 9706. Curveball: the cool season
Interviewer: "About 70 percent of room nights fall in the 182 cooler days from October to March, and hotels cannot be fuller than about 90 percent on busy nights." Rooms needed to meet peak demand:
Rooms needed in the peak season (rooms):400,000 × 0.7 ÷ 182 ÷ 0.9 = 1,7097. Off-season occupancy
If Sahra built 1,710 permanent rooms, the other 30 percent of room nights would spread over the 183 hot days.
Off-season occupancy with 1,710 rooms (%):400,000 × 0.3 ÷ (183 × 1,710) × 100 = 38.358. Room revenue
At an average room rate of SAR 900 a night.
Room revenue (SAR a year):400,000 × 900 = 360,000,000
What the exhibit shows
Only overnight guests need rooms, so the room count starts from 400,000 room nights, not from 600,000 visitors.
The recommendation
Plan for about 1,570 permanent rooms by year three, which means adding about 970, and meet the cool-season peak with about 140 seasonal units rather than more hotels. First, 600,000 visitors become 400,000 room nights, which need about 1,566 rooms at 70 percent occupancy. Second, demand is seasonal: the cool months alone need about 1,710 rooms, but building that many permanently would leave hotels about 38 percent full in the hot months. Third, the rooms earn about SAR 360 million a year at SAR 900 a night, so the plan should protect the room rate rather than chase volume. Build in two phases, with the second phase released only when the first reaches its occupancy target, and use desert camps or other seasonal units for the peak.
Risks: The visitor target may not be reached, leaving new rooms empty; Seasonal units may not meet the quality the destination promises.
Next steps: Test the visitor forecast against bookings from the first year; Ask operators for offers on seasonal units for the cool months.
A strong candidate
Converted visitors into room nights before counting rooms, used occupancy, and saw that seasonality changes the build plan.
A weak candidate
Divided 600,000 visitors by 365 and said about 1,600 rooms, missing day visitors, shared rooms and the seasonal peak.
Case 6: Should a health department run a diabetes screening programme?
Where the structure comes from: it is built from the goal of this exact question (Five-year value = savings from early diagnosis - cost of screening), not taken from a list. Each branch is one driver of that goal, and the hypothesis above says which branch to test first.
Worked case
Standard: Should a health department run a diabetes screening programme?
The prompt
The health department of an emirate in the UAE is considering a free screening programme for undiagnosed diabetes in adults. It asks you: is the programme worth its cost over five years, and how should it be designed?
Difficulty: Standard. Format: candidate-led, with interviewer dialogue. Industry: Public sector and healthcare. Region: UAE. Interview length: about 30 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- Who would be screened?Answer: Adults aged 30 to 65, about 1,200,000 people, and we expect half of them to take part (illustrative).
- What does a screening cost, and what does it find?Answer: About AED 60 per person, including the test and follow-up; about 4 percent of those screened are found to have diabetes they did not know about (illustrative).
- What does finding it early change?Answer: Each person found early avoids about AED 8,000 of treatment for complications over five years, but early treatment costs about AED 1,000 a year (illustrative).
A hypothesis to say out loud: Screening pays off when enough people come and enough cases are found. My hypothesis is that the programme saves more than it costs over five years, but that low participation could make it marginal.
The structure
- Five-year value = savings from early diagnosis - cost of screening
- Key: Reach: people eligible x participation
- Yield: share of those screened found with diabetes
- Cost per person screened and per case found
- Savings per case found, net of early treatment
Working it through
1. People screened
Candidate: "1,200,000 eligible adults, and half take part."
People screened:1,200,000 × 0.5 = 600,0002. Programme cost
Candidate: "AED 60 per person screened."
Programme cost (AED):1,200,000 × 0.5 × 60 = 36,000,0003. Cases found
Candidate: "4 percent of those screened."
Cases found:1,200,000 × 0.5 × 0.04 = 24,0004. Cost per case found
Candidate: "The cost of one screening divided by the share that finds a case."
Cost per case found (AED):60 ÷ 0.04 = 1,5005. Net saving per case
Candidate: "AED 8,000 of avoided complications, minus five years of early treatment at AED 1,000 a year."
Net saving per case over five years (AED):8,000 - 1,000 × 5 = 3,0006. Total net saving
Candidate: "Across every case found."
Total net saving over five years (AED):1,200,000 × 0.5 × 0.04 × (8,000 - 1,000 × 5) = 72,000,0007. Benefit for each dirham spent
Candidate: "Total net saving divided by the programme cost."
Benefit to cost ratio:(1,200,000 × 0.5 × 0.04 × (8,000 - 1,000 × 5)) ÷ (1,200,000 × 0.5 × 60) = 28. Curveball: fewer and healthier people come
Interviewer: "Pilots elsewhere suggest only 30 percent take part, and those who come are healthier, so only 3 percent are found." Candidate: "The saving minus the cost becomes:"
Net value at 30 percent participation (AED):1,200,000 × 0.3 × (0.03 × 3,000 - 60) = 10,800,0009. Benefit ratio in the pessimistic case
Candidate: "Per person screened, AED 90 of saving against AED 60 of cost."
Benefit to cost ratio, pessimistic case:(0.03 × 3,000) ÷ 60 = 1.5
The recommendation
Run the programme, but design it to reach the people least likely to come on their own. First, at 50 percent participation it costs about AED 36 million and saves about AED 72 million over five years, two dirhams for every dirham spent. Second, each case found costs about AED 1,500 to find and saves about AED 3,000 net, so the yield of each screening matters most. Third, even if only 30 percent take part and only 3 percent are found, it still returns about 1.5 times its cost, but the margin is much thinner. Screen where people already are, such as workplaces, pharmacies and community centres, focus invitations on groups with higher risk, and track cases found per 1,000 screened each month.
Risks: People found may not stay on treatment, which cuts the savings; Savings arrive over years while the cost comes first.
Next steps: Pilot workplace screening with three large employers; Agree with clinics how people found are followed up within a month.
A strong candidate
Built reach, yield, cost per case and net saving per case, compared value with cost, and tested the answer with lower participation.
A weak candidate
Said screening is always good for public health and recommended screening everyone, with no cost or yield estimate.
Sources for this lesson (1)
- Recognized public explanations of case-interview concepts and terms
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