Problem-solving questions come in three forms: behavioral ("tell me about a time you solved a difficult problem"), analytical ("how would you approach X situation?"), and case-based ("here's a business scenario, walk me through your thinking"). Each requires a different approach, but they share one thing: the interviewer cares more about your process than your answer.
What problem-solving questions test
Interviewers are watching for: do you define the problem before jumping to solutions, can you think in a structured way under pressure, can you make a decision with incomplete information, and can you learn from things that went wrong? A candidate who jumps straight to a solution without understanding the problem is a warning sign. A candidate who diagnoses first is far more credible.
How to approach any problem-solving question
For behavioral questions, use the STAR method and emphasise the Action and Result. For case or analytical questions, use this sequence: clarify the problem, break it into components, prioritise which to address first, propose a solution or hypothesis, and identify how you'd test it. Say your thinking out loud. Interviewers can't evaluate a process they can't see.
- Clarify: restate the problem and ask clarifying questions
- Structure: break it into components or hypotheses
- Prioritise: which component matters most? Start there.
- Solve: work through your primary hypothesis with logic or data
- Validate: how would you check whether your solution is right?
Behavioral problem-solving questions
"Tell me about a complex problem you solved at work"
S/T: "Our customer support ticket volume had grown 4x over 18 months while the team had only grown 1.5x. Average resolution time had gone from 4 hours to 22 hours. Customer satisfaction had dropped from 91% to 74%."
A: "Rather than just hiring more people, I started by categorising six months of tickets to understand the volume drivers. 43% of tickets were a single category: password reset and account access issues. These were fully solvable with self-service. I worked with the product team to build a self-service flow, which took six weeks. I also set up automated routing so the remaining high-complexity tickets went to senior agents first, cutting the time agents spent on misrouted tickets."
R: "Within 90 days, ticket volume dropped 38% from the self-service adoption alone. Average resolution time fell from 22 hours to 7 hours. CSAT recovered to 88%. We were able to handle the growth without any additional headcount."
Analytical and case questions
"If our app downloads dropped 20% last month, how would you investigate?" is a common analytical question. Don't jump to causes. Start with: is the data clean? If yes, segment the drop: platform, geography, channel, user type. Then look at what changed: app update, marketing spend, competitor activity, external events. Narrow from "something changed" to "this specific thing changed" before proposing a fix.
"How many golf balls fit in a school bus?" or similar estimation questions test whether you can structure reasoning from first principles. Break it into dimensions you can estimate, multiply through, and sanity-check the answer. Say every step aloud. The answer is far less important than the approach.