How I'd recruit for a BizOps role in 2026 (Pt. 3)

Dec 18, 2025

If you've been following along, we've covered getting interviews (Pt. 1) and nailing behaviorals (Pt. 2).​

Today we're covering case interviews.

This is like the final boss of interviews because it most closely mimics the job.

If I give you a problem that I have run into - one that has real stakes, how would you respond?

Do you get flustered and start spewing nonsense or do you lock in and problem solve?

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The Two Types of Cases:

1. Consulting-style cases (market sizing, profitability) You might see these occasionally. But they’re not the main event and there are more qualified people out there to speak on this so I'm focusing on 2.
2. Business problem cases (the main boss)
   • Diagnostic: e.g. Engagement dropped 20%. What would you do?
   • Trade-off: e.g. Should we invest in Product A or B?
   • Hypothesis-driven: e.g. We think our issue is X. How would you test that?
   • Take-home: Given a dataset and a prompt what insights or recommendation can you come up with?

Since diagnostics are the most common, I'll focus on those. If you want to see how I’d approach the other cases, reply and let me know! I’ll write those up if you'd find it helpful.

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The Key Mindset Shift - How to Approach a Case

Think about the last time you went to the doctor with a vague symptom - maybe your knee hurt after a run (totally not something I'm dealing with and 100% hypothetical ...)

What did they do? They started with questions.

• Where exactly does it hurt?
• When did it start?
• Does it hurt when you walk, or only when you run?

Then they thought about what else you might need, maybe an MRI, maybe just a referral.

They tested hypotheses. Ruled things out.

Then they prescribed treatment.

BizOps cases work the same way.

Strategists are just doctors, but for businesses.

My old team literally ran a weekly report called Health of the Business with red-green color coding for parts that were healthy vs. unhealthy.

TLDR: just remember this diagram.

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Let's walkthrough a case together

Ex: Instagrams' user engagement is down 20% Y/Y. What would you do?

Step 0: Clarify what they even mean

Someone saying "engagement dropped" is like saying "my leg hurts."

Okay... what do you mean by leg? Your knee? Shin? Hamstring? Muscle or joint?

Same thing here. Before you can diagnose WHERE or WHY, you need to know WHAT we're even talking about.

• When we say engagement - are we talking about daily active users, time spent in app, or specific feature usage?
• What's the metric we care most about here? (This is your north star metric)

Let's say you ask and the interviewer says time spent on the app has decreased by 20% YoY.

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Step 1: Figure out where it hurts

Now that you know WHAT metric dropped, you need to know WHERE the pain is.

A doctor doesn't just hear "knee hurts" and immediately order an MRI. They press on different spots. They test your range of motion. They're trying to isolate WHERE the problem actually is.

You do the same:

Ask things like:

• Is it across all regions, or concentrated somewhere? US vs. international?
• Is it all user types, or specific segments? New users, certain age groups, etc?
• Is it specific to certain use cases? Less time spent on reels vs. stories vs. DMs

Half the work of a good strategist is just asking the right questions

Let's say, existing users in the US are spending 30% less time on reels.

IRL you'd get even more specific and segment further (think heat map across age group, region, content type, or time series by month, etc..) but for the sake of brevity let's move on.

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Step 2: Diagnose why it's happening

Here's where you begin thinking of solutions.

The key to this section is thinking out loud and framing your thoughts as hypotheses.

This might sound like:

• My initial hypothesis is that something changed in the product experience that's frustrating existing users.
• To test this, I'd check our release calendar and see if we shipped any UX changes recently and if that correlates to when we see ? Did we change navigation or moved features around?
• To further validate, I'd also dig into support tickets and user feedback around the timing of that change.
• For example, maybe we changed how users navigate to reels. If they were used to swiping right to get to messages, but now it takes them to reels instead, that could disrupt their habits and make the feature feel harder to access.

Remember there's no one perfect answer here. We're trying to find a reasonable hypothesis based on the data, not the "right" answer.

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Step 3: Recommend a course of action

Only after you know WHERE and WHY do you prescribe treatment.

Let's say the data validated our initial hypotheses - the decrease in engagement coincided directly with a UX change.

A good recommendation shows three things:

1. How you'd test your solution
2. What trade-offs exist
3. What you'd measure to know if it worked

For this case, a tempting first answer might be to roll-back the change completely.

But that's like trying to sledgehammer a nail. We need more precision first.

Because what if users just need time to adjust to the new pattern?

What if the new design actually IS better for discovering content, but existing users hate the change because it breaks their muscle memory?

You need to test before you fully commit.

• A better approach would be a phased rollback. Revert 30% of users to the old version while keeping the new version for the rest. Run that for 2-4 weeks and track if engagement recovers.
• If engagement recovers in the rollback group, you know the change was the issue. If it doesn't, you've saved yourself from making it worse.

You might also look at how different user segments respond. Maybe heavy users who message constantly are most disrupted, while casual users adapt fine.

That helps you understand the trade-off - are we optimizing for power users who drive engagement, or making the app easier for everyone else?

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Final Note & Reminders:

Don't obsess over the perfect answer. Intellectual flexibility matters more than solving for the perfect equation.

Cases mimic real life, and in real life you almost never have perfect information or time to validate everything. You're making the best guess with what you have. And it's just that - a guess. A well-informed, logical one, hopefully. But still a guess.

Frame your thinking as hypotheses, not certainties. That's why good strategists say things like:

• "My initial hypothesis is..."
• "My current thinking is..."
• "To validate this, I'd want to check..."

If a business problem is a big murky cloud, your role is to shine a flashlight through it and pinpoint where someone should look.

Pay attention to your interviewer's responses. If the interviewer seems skeptical or pushes back, take that in. They're guiding you somewhere. Don't steamroll ahead with your original plan. Adapt. Show you can take feedback and course-correct in real time.

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Alright that's the series!

• ​Pt. 1: Getting interviews (networking strategy)
• ​Pt. 2: Behaviorals (connection over STAR)
• Pt. 3: Cases (diagnose like a doctor)

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P.S. Which part of this 3-part series was most helpful? I'm thinking about what to write next. Just hit reply and let me know!

Until then
Jacky "diagnose before you prescribe" Ye