Interviewer view · keep this screen to yourself

Beds or shorter stays at an Indian private hospital

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

Target length:

1. Read the prompt aloud

Read it slowly, then pause. Let the candidate ask questions before they structure.

A private hospital in Bengaluru has 320 beds and its emergency department is often full, with patients waiting for beds. Should it add beds?

Format note: Candidate-led: you drive; the interviewer answers what you ask.

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 many admissions a day, and how long do patients stay?
Answer: About 60 admissions a day, with an average stay of 5 days.
If asked: How is the hospital paid?
Answer: Most admissions are paid a fixed package price per procedure by insurers, not per day.
If asked: What does a bed cost to add, and what does a bed-day cost to run?
Answer: About INR 12 million (1.2 crore) per new bed; about INR 8,000 per bed-day in variable costs.

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.

With package prices, shorter stays cost less without lowering revenue. My hypothesis is that shortening stays is cheaper and faster than building beds.

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.

Occupied beds = admissions x length of stay
- Occupancy today versus an 85 percent target
- Option A: add beds
- Key: Option B: shorten stays

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: Occupied beds
What a strong candidate does: Candidate: "By Little's Law, average occupied beds are admissions per day times length of stay."
Average occupied beds: 60 × 5 = 300
Step 2: Occupancy today
What a strong candidate does: Candidate: "That is about 94 percent of 320 beds, well above the 85 percent that leaves room for peaks. That explains the emergency waits."
Occupancy (%): 60 × 5 ÷ 320 × 100 = 93.75
Step 3: Beds needed at 85 percent
What a strong candidate does: Candidate: "To bring occupancy to 85 percent with today's stays, the hospital needs:"
Beds needed: 60 × 5 ÷ 0.85 = 353
Step 4: Cost of option A
What a strong candidate does: About 33 more beds at INR 12 million each.
Cost of new beds (INR): (353 - 320) × 12,000,000 = 396,000,000
Step 5: Option B: shorter stays
What a strong candidate does: Interviewer: "Faster discharge planning could cut the average stay to 4.5 days." Candidate: "Then occupancy becomes:"
Occupancy at 4.5 days (%): 60 × 4.5 ÷ 320 × 100 = 84.38
Step 6: Money effect of option B
What a strong candidate does: Candidate: "With package prices, revenue per patient stays the same. Each patient stays half a day less, and each bed-day avoided saves INR 8,000 of variable cost: 60 x 365 x 0.5 x 8,000."
Yearly cost saved (INR): 60 × 365 × 0.5 × 8,000 = 87,600,000

The recommendation to listen for

At the end, say: "The CEO walks in. What is your recommendation?"

Shorten stays before adding beds. First, the problem is occupancy of about 94 percent, and cutting the average stay from 5 to 4.5 days brings it to about 84 percent, within the 85 percent target, with no construction. Second, because insurers pay a fixed package per procedure, shorter stays do not reduce revenue and save about INR 8.8 crore a year in running costs. Third, adding beds would cost about INR 40 crore and take years. Keep a bed expansion plan ready if admissions keep growing.

Risks a strong answer names: Discharging too early could raise readmissions and harm patients; Admissions may grow faster than expected.

Next steps: Introduce daily discharge planning and weekend discharges; Track length of stay, readmissions, and emergency waiting times weekly.

Strong versus weak

A strong answer

Used Little's Law to find the occupancy problem, asked how the hospital is paid, and chose the faster, cheaper lever while watching patient safety.

A weak answer

Recommended building beds because the hospital "is full," without checking length of stay or the payment model.

Score the candidate

Score each criterion from 1 to 5. A 2 or a 4 sits between the descriptions.

This case has no exhibit. Score Exhibit reading on how the candidate used the data you gave them: did they pick out the number that matters and say what it means?

Structuring

1: No clear structure, or a memorized framework that does not fit the problem.
3: A sensible structure, but with some overlap, a gap, or no clear priority.
5: A structure built for this problem, with no overlap and no gaps, a stated hypothesis, and a clear first step.

Math

1: Frequent errors, no units, or needed heavy help to finish.
3: Right answers but slow or messy working, or one error caught late.
5: Accurate and clearly narrated, with units, a sense check, and what the number means.

Exhibit reading

1: Read the chart aloud without finding the number that matters.
3: Found the key number but gave only part of the so-what.
5: Pulled the right number quickly and said what it means for the case.

Synthesis

1: Summarized what was done, with no clear answer.
3: Gave an answer, but with weak reasons or no next step.
5: Answer first, then two or three reasons with numbers, the main risk, and next steps.

Communication

1: Hard to follow: long silences, no signposting.
3: Clear most of the time, with some rambling.
5: Calm and concise, signposted each step, and checked in with the interviewer.

Total

0 out of 25

Score all five criteria to see the band and the feedback template.