Interviewer view · keep this screen to yourself
Starter: A hotel group's Southern Europe revenue fell
You run the case. Read the prompt, answer questions from the notes below, and share data only when the candidate asks for it or gets stuck. Score at the end.
Case timer
00:00
1. Read the prompt aloud
Read it slowly, then pause. Let the candidate ask questions before they structure.
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?
Format note: 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.
2. Answers to clarifying questions
Give these answers only if the candidate asks. If they ask something not listed, give a sensible answer or say it does not matter here.
If asked: How is hotel revenue measured?
Answer: Revenue per available room (RevPAR): occupancy times the average daily rate.
If asked: Did the number of rooms change?
Answer: No, about 10,000 rooms.
If asked: What changed in pricing?
Answer: The group raised its average rate this year.
3. The hypothesis a strong candidate states
Listen for an early, testable guess like this one. It does not need to match word for word.
The group raised rates, so my hypothesis is that occupancy fell by more than the rate gain, lowering RevPAR.
4. A model structure
Compare the candidate's structure with this one. A different split can be just as good if it is clean and fits the problem.
- Room revenue = rooms x 365 x occupancy x average daily rate
- Key: Occupancy
- Average daily rate
- RevPAR and revenue
Exhibit 1
Reveal to candidate: when they ask for this data, say "Open Exhibit 1" (they press "Show exhibit 1" on their screen).
| Measure | Last year | This year |
|---|---|---|
| Occupancy (%) | 80 | 72 |
| Average daily rate (USD) | 150 | 160 |
| Rooms | 10,000 | 10,000 |
So-what
The rate rose about 7 percent but occupancy fell 8 points, so revenue per room fell.
5. The working, step by step
Each step shows how a strong candidate works it out. Share a new fact from it only when the candidate asks or is stuck, and let them do the math: the result in the dark box is what they should reach.
Step 1: RevPAR last year
What a strong candidate does: 80 percent occupancy at USD 150.
RevPAR last year (USD): 0.8 × 150 = 120
Step 2: RevPAR this year
What a strong candidate does: 72 percent at USD 160.
RevPAR this year (USD): 0.72 × 160 = 115
Step 3: Change in yearly revenue
What a strong candidate does: RevPAR change times 10,000 rooms times 365 nights.
Revenue change (USD a year): (0.72 × 160 - 0.8 × 150) × 10,000 × 365 = -17,520,000
Step 4: Occupancy effect
What a strong candidate does: Lower occupancy at last year's rate.
Occupancy effect (USD a year): (0.72 - 0.8) × 150 × 10,000 × 365 = -43,800,000
Step 5: Rate effect
What a strong candidate does: 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 = 26,280,000
Step 6: Curveball: short-term rentals
What a strong candidate does: 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
The recommendation to listen for
At the end, say: "The CEO walks in. What is your 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 a strong answer names: 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.
Strong versus weak
A strong answer
Used RevPAR, split the change into occupancy and rate effects, and used the curveball to see that the market had changed.
A weak answer
Said the price rise "worked" because the average rate went up, ignoring occupancy.
Score the candidate
Score each criterion from 1 to 5. A 2 or a 4 sits between the descriptions.
Total
0 out of 25
Score all five criteria to see the band and the feedback template.