This lesson teaches how to form, test, and update hypotheses in a case interview so your analysis stays focused.
Cases are usually too broad to analyze in a completely open-ended way.
If you try to investigate everything equally, you waste time and often look passive.
Hypothesis-driven thinking helps because it gives your analysis direction.
Instead of asking:
“What could possibly be happening?”
you ask:
“What do I currently think is most likely happening, and how can I test it quickly?”
A hypothesis is a working belief, not a final conclusion.
It is your current best guess based on:
Good candidates form hypotheses early, test them, and update them honestly.
They do not pretend certainty where none exists.
After presenting a structure, use your hypothesis to decide:
The hypothesis should create motion.
Use the prompt and business logic.
Example:
“Since occupancy is stable but profits are down, I suspect margin pressure may be coming from cost inflation or customer mix deterioration rather than traffic decline.”
You do not need to sound dramatic.
You can say:
Ask for the data that helps you learn quickly.
If the data disproves your first view, change course.
A hypothesis is useful because it helps you prioritize.
Prompt:
“A regional retailer’s profits are down.”
A candidate may hypothesize:
“Because profits have fallen in a regional retail business, I would initially suspect either lower traffic or margin compression from discounting or input cost increases. I would want to start by comparing revenue and gross margin trends.”
That is a good hypothesis because it is:
A strong candidate:
A weaker candidate often:
You are not claiming certainty. You are choosing where to investigate first.
If it cannot guide action, it is not useful.
The whole value of a hypothesis-driven approach is that it adapts to evidence.
Do not say “my hypothesis is” if the rest of your behavior shows no prioritization.
Take this prompt:
“A budget airline’s profits are down, but passenger volume is up.”
Write one reasonable initial hypothesis and one piece of data you would ask for first to test it.
A strong phrasing might sound like this:
My initial hypothesis is that the issue may be margin pressure rather than demand weakness, because passenger volume is growing. I would start by comparing ticket yield, ancillary revenue, and major cost categories to see whether pricing or cost inflation is driving the decline.
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