How to Handle an Excel Case Study in an Interview

An Excel case study interview gives you a realistic data set and a business question, and asks you to analyze it and explain what you found. The method that works: read the brief and every question, check the data, answer each question with formulas that point to input cells, sanity-check the results, and finish with a short set of findings. This guide is for anyone facing a case study for an analyst, operations, finance or graduate role.

What an Excel case study interview involves#

A case study is different from a formula test. A test asks "what is the total for Sales?"; a case study asks "which region should we invest in, and why?" You still calculate, but you also decide what to calculate and explain what it means.

Typical case studies use one realistic table, such as home listings, hospital admissions, sales orders or survey results. You might get:

• 4 to 8 questions, some precise ("average stay in Ward B") and some open ("what stands out?").
• A time limit in the interview, or a take-home workbook.
• A short presentation or discussion afterwards.

Our overview of what employers test in Excel assessments describes how these fit alongside other formats.

Step 1: Read the brief and every question first#

Spend the first few minutes reading, not typing. Note:

• The goal. What decision is the business trying to make?
• The inputs. Is there a cell the interviewer will change, such as the area or month to study?
• The order of questions. Later questions often build on earlier ones, such as an average used as a threshold.
• What a good answer looks like. A number, a list, a label or a recommendation.

If something is unclear, ask. In a live interview, a clarifying question shows good judgment.

Step 2: Check the data before you analyze it#

Real case data often has a deliberate problem in it. Look for these before calculating anything:

The hospital case in our lessons is a good example: one patient has no discharge date yet, so their length of stay must be excluded rather than calculated as a huge negative number. Say what you found and how you handled it.

Step 3: Set up inputs and helper columns#

Keep the raw data untouched, and add what you need beside it:

• Input cells: if the brief names an area, month or threshold, put it in a labelled cell and point every formula at it.
• Helper columns: add calculated columns such as price per square foot (=C2/D2) or length of stay (=E2-D2), and fill them down.
• An answers area: a block of labelled cells to one side, one per question.

This structure means the interviewer can change an input and watch every answer update, which is often exactly what they test.

Step 4: Answer each question with formulas#

Here is a mini case on six home listings, with the area to study, Riverside, in I1:

Change I1 to Hillcrest and the first three answers update to 2, 815,000 and 407,500. The SUMIFS function guide and the XLOOKUP function guide explain both functions in full.

Step 5: Sanity-check your answers#

Before you present, check that each number makes sense:

• Does the summary add back to the data? The totals per area should add up to the SUM of the whole Price column.
• Is the average between the smallest and largest value? If not, a blank or text value has crept in.
• Does the answer change when the input changes? Try another area in I1.
• Average of ratios vs ratio of totals. Riverside's total price divided by its total square feet is 1,324,000 / 4,550 = 291.0, but the average of its price-per-square-foot column is 291.2. Both are valid, but they answer different questions. Big and small homes count equally in the average, while the ratio of totals weights by size. Interviewers like to ask about this, so be ready to explain which you used and why.

Step 6: Present your findings#

End with what the numbers mean. A simple structure is answer, evidence, next step:

1. "Riverside has the highest prices: an average asking price of 441,333 across 3 listings."
2. "It's also the most expensive per square foot, at about 291, against 271 in Hillcrest."
3. "If the client wants value, I'd look at Hillcrest first, and I'd want more listings before drawing a firm conclusion."

Note the limits honestly. Six listings is a tiny sample, and saying so shows judgment. Keep the formulas visible so you can walk the interviewer through any number.

Common case study mistakes#

These cost the most marks:

• Typing results as numbers instead of formulas, so nothing updates.
• Typing the input ("Riverside") into formulas instead of pointing to I1.
• Ignoring data problems you were meant to find.
• Overwriting the raw data while cleaning it.
• Running out of time on one hard question. Our guide to managing your time in a timed Excel test has a plan for this.
• Giving numbers with no conclusion.

For targeted practice before the day, work through these 10 Excel practice tasks to do before your test. If you're early in your career, the Excel skills every fresh graduate should have list the foundations, and the guide to passing an Excel test for a job interview covers shorter formula tests.

Practise it#

The best preparation is a full case under realistic conditions. Work through Case study: real estate listings for price per square foot, averages by area and a filtered list of good-value homes, then Case study: hospital admissions, which includes a missing date you have to handle. The exercise on this page is one case question: find the top listing with a formula that updates.