Practice cases: US and Canada
Four full cases set in North America: a pet-food price rise, software growth quality, a private-equity buy-and-build, and urgent-care clinics.
Key takeaways
- Worked case: Prairie Pet Foods: should it raise prices 10 percent?
- Worked case: Bluegrass HR: how safe is its growth?
- Worked case: Corvane Home Comfort: a buy-and-build in home services.
- Worked case: A health system considers urgent-care clinics.
Four full cases set in North America: a pet-food price rise, software growth quality, a private-equity buy-and-build, and urgent-care clinics.
Cover the solution and run each case out loud, ideally with a partner playing the interviewer. Ask your own clarifying questions, state a hypothesis, build a structure, and do the math on paper before you look. Then compare your synthesis with the one given, and read the strong and weak candidate notes. Each case is labeled Starter, Standard, or Stretch.
Case 1: Prairie Pet Foods: should it raise prices 10 percent?
Worked case
Starter: Prairie Pet Foods: should it raise prices 10 percent?
The prompt
Prairie Pet Foods sells premium dog food in Canada. It is considering a 10 percent price rise. The exhibit shows results from test markets. Should it go ahead?
Difficulty: Starter. Format: interviewer-led, with an exhibit. Industry: Consumer goods. Region: Canada. Interview length: about 25 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- What are the price, cost, and volume?Answer: CAD 50 per bag, variable cost CAD 30, about 2 million bags a year.
- What is proposed?Answer: A 10 percent price rise, to CAD 55.
- Do we have evidence on customer response?Answer: Yes, two test markets and a control market.
A hypothesis to say out loud: Premium pet food buyers are loyal, and the product has a healthy contribution. My hypothesis is that the price rise pays unless volume falls by a lot.
The structure
- Price rise versus the volume it can afford to lose
- Contribution per bag before and after
- Key: Break-even volume loss
- Evidence from test markets
- Retailer response
The exhibit
| Market | Price change (%) | Volume change (%) |
|---|---|---|
| Test market A | 10 | -5 |
| Test market B | 10 | -7 |
| Control market | 0 | 0 |
Working it through
1. Contribution now
Price minus variable cost.
Contribution now (CAD per bag):50 - 30 = 202. Contribution after the rise
At CAD 55.
Contribution after (CAD per bag):55 - 30 = 253. Break-even volume loss
Price rise divided by (contribution plus the rise).
Break-even volume loss (%):5 ÷ (20 + 5) × 100 = 204. Average test result
The two test markets lost 5 and 7 percent of volume.
Average volume loss (%):(5 + 7) ÷ 2 = 65. Yearly contribution now
2 million bags at CAD 20.
Contribution now (CAD a year):2,000,000 × 20 = 40,000,0006. Yearly contribution after
6 percent fewer bags at CAD 25.
Contribution after (CAD a year):2,000,000 × 0.94 × 25 = 47,000,0007. Curveball: the largest retailer wants a share
Interviewer: "Our largest retailer says it will ask for an extra 3 percent discount if we raise prices." Contribution after the rise and the discount (conservatively applied to all volume):
Contribution with the discount (CAD a year):2,000,000 × 0.94 × (55 × 0.97 - 30) = 43,898,000
What the exhibit shows
Volume fell 5 to 7 percent after a 10 percent price rise, far less than the 20 percent the company could afford to lose.
The recommendation
Raise the price. First, the company could lose up to 20 percent of volume before profit falls, and tests show only about 6 percent. Second, contribution rises from about CAD 40 million to about CAD 47 million a year. Third, even if the largest retailer takes an extra 3 percent discount, contribution is still about CAD 43.9 million, above today. Roll out region by region, watch volume monthly, and offer the retailer joint promotions instead of a permanent discount.
Risks: Long-term volume loss may exceed a three-month test; Rivals may hold prices to win share.
Next steps: Roll out in two regions first; Prepare the retailer negotiation with the test data.
A strong candidate
Found the break-even volume loss, compared it with the tests, and tested the retailer curveball.
A weak candidate
Worried that customers would leave and rejected the rise without checking how many could leave.
Case 2: Bluegrass HR: how safe is its growth?
Worked case
Standard: Bluegrass HR: how safe is its growth?
The prompt
Bluegrass HR sells payroll and HR software to mid-sized US companies, priced per employee (per seat). Its board asks how healthy its growth is. What would you tell them?
Difficulty: Standard. Format: candidate-led, with interviewer dialogue. Industry: Technology (software). Region: US. Interview length: about 30 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- How big is the business?Answer: USD 50 million of annual recurring revenue (ARR) at the start of the year.
- What happened to existing customers over the year?Answer: 8 percent of ARR churned, 2 percent downgraded, and existing customers added 15 percent through more seats.
- How much came from new customers?Answer: About USD 12 million of new ARR.
A hypothesis to say out loud: Software growth depends a lot on existing customers growing. My hypothesis is that growth relies on customers adding seats, which makes it exposed to a hiring slowdown.
The structure
- Growth = existing customers (net revenue retention) + new customers
- Churn and downgrades
- Key: Expansion from more seats
- New customers
Working it through
1. ARR lost to churn
Candidate: "8 percent of USD 50 million."
Churned ARR (USD):50,000,000 × 0.08 = 4,000,0002. Net revenue retention
Candidate: "Start, minus churn and downgrades, plus expansion, divided by start."
Net revenue retention (%):(50,000,000 - 50,000,000 × 0.08 - 50,000,000 × 0.02 + 50,000,000 × 0.15) ÷ 50,000,000 × 100 = 1053. ARR at year end
Existing customers at 105 percent, plus USD 12 million of new ARR.
Ending ARR (USD):50,000,000 × 1.05 + 12,000,000 = 64,500,0004. Growth
Change over the starting ARR.
Growth (%):(64,500,000 - 50,000,000) ÷ 50,000,000 × 100 = 295. Curveball: hiring slows
Interviewer: "Our customers are slowing hiring. Expansion could halve." Candidate: "Net revenue retention would be:"
Net revenue retention (%):(1 - 0.08 - 0.02 + 0.075) × 100 = 97.56. Growth in that case
Same new ARR.
Growth (%):(50,000,000 × 0.975 + 12,000,000 - 50,000,000) ÷ 50,000,000 × 100 = 21.57. A lever not tied to seats
Interviewer: "We could sell an analytics module." Candidate: "If 20 percent of customers buy it at 10 percent of their current spend:"
Extra ARR (USD):50,000,000 × 0.2 × 0.1 = 1,000,000
The recommendation
Growth is healthy today but depends too much on customers hiring. First, the business grew 29 percent, with existing customers growing 5 percent net (105 percent retention). Second, most of that expansion comes from added seats, so a hiring slowdown that halves expansion drops retention below 100 percent and growth to about 21.5 percent. Third, 8 percent churn is the largest single loss and worth reducing. Reduce churn with better onboarding, and add revenue not tied to seats, such as an analytics module worth about USD 1 million of ARR at 20 percent take-up.
Risks: A deeper hiring slowdown; Module take-up may be lower than 20 percent.
Next steps: Find which customer groups churn most, and why; Test the analytics module with 50 customers.
A strong candidate
Split growth into retention and new sales, calculated net revenue retention, and tested its dependence on hiring.
A weak candidate
Reported 29 percent growth as strong and stopped, without asking where it came from.
Case 3: Corvane Home Comfort: a buy-and-build in home services
Worked case
Stretch: Corvane Home Comfort: a buy-and-build in home services
The prompt
A US private-equity fund plans to build Corvane Home Comfort, a heating and air-conditioning services group in the Midwest, by buying a platform company and five add-ons. The exhibit shows the deal pieces. What return could the fund earn, and what could go wrong?
Difficulty: Stretch. Format: interviewer-led, with an exhibit. Industry: Private equity and home services. Region: US. Interview length: about 40 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- What is the strategy?Answer: Buy one larger heating and air-conditioning services company (the platform), then buy five small local companies (add-ons) and combine them.
- How is it financed?Answer: 60 percent debt; debt falls to USD 134 million by exit.
- What growth and exit?Answer: About 5 percent a year EBITDA growth for five years; the fund expects to sell at 10 times EBITDA.
A hypothesis to say out loud: Small companies sell for lower multiples than large ones, so combining them can create value. My hypothesis is that the return depends heavily on the exit multiple.
The structure
- Entry cost, exit value, and the fund's return
- Total price and blended entry multiple
- EBITDA growth to exit
- Key: Exit value, MOIC, and IRR
- Risk: a lower exit multiple
The exhibit
| Item | Platform | Each add-on |
|---|---|---|
| EBITDA (USD million a year) | 20 | 3 |
| Purchase multiple (EV/EBITDA) | 10 | 6 |
| Number of companies | 1 | 5 |
Working it through
1. Total price
Platform at 10 times USD 20 million, plus five add-ons at 6 times USD 3 million each (USD million).
Total price (USD million):20 × 10 + 5 × 3 × 6 = 2902. Combined EBITDA
Platform plus add-ons.
Combined EBITDA (USD million):20 + 5 × 3 = 353. Blended entry multiple
Below the 10 times paid for the platform alone.
Blended EV/EBITDA:290 ÷ 35 = 8.294. Equity invested
40 percent of the total price.
Equity (USD million):290 × 0.4 = 1165. Exit value
EBITDA grows 5 percent a year for five years and sells at 10 times.
Exit EV (USD million):35 × 1.05 × 1.05 × 1.05 × 1.05 × 1.05 × 10 = 4476. MOIC
Exit value minus USD 134 million of remaining debt, divided by equity.
MOIC:(35 × 1.05 × 1.05 × 1.05 × 1.05 × 1.05 × 10 - 134) ÷ 116 = 2.77. IRR check
About 2.7 times in five years is roughly 22 percent a year.
1.22 to the power of 5:1.22 × 1.22 × 1.22 × 1.22 × 1.22 = 2.78. Curveball: exit multiples fall
Interviewer: "If buyers pay only 8 times at exit, what happens?"
MOIC at an 8 times exit:(35 × 1.05 × 1.05 × 1.05 × 1.05 × 1.05 × 8 - 134) ÷ 116 = 1.93
What the exhibit shows
Add-ons cost 6 times EBITDA against 10 for the platform, so combining them lowers the average price paid.
The recommendation
The plan could return about 2.7 times the fund's money, roughly 22 percent a year, but much of that depends on the exit multiple. First, buying add-ons at 6 times lowers the blended entry multiple to about 8.3 times. Second, selling the combined group at 10 times turns that gap into value, alongside 5 percent yearly EBITDA growth and debt paydown. Third, if the exit multiple is only 8 times, MOIC falls to about 1.9 times, below a typical target. So only proceed if the group becomes a real, integrated business that deserves a higher multiple: shared booking, purchasing, and technician training, not just a collection of local firms.
Risks: Add-on owners and key technicians may leave after the sale; Integration may fail, so the group does not earn a higher multiple; Higher interest rates increase debt costs.
Next steps: Build an integration plan for booking, purchasing, and training; Agree retention terms with add-on owners.
A strong candidate
Calculated the blended entry multiple, exit value, MOIC, and IRR, and identified the exit multiple as the main risk.
A weak candidate
Added up EBITDA and said the deal is good because the market is fragmented, without calculating the return.
Case 4: A health system considers urgent-care clinics
Worked case
Standard: A health system considers urgent-care clinics
The prompt
First, estimate how many urgent-care visits a year happen in a US metro area of 3 million people. Then: a local health system wants to open urgent-care clinics. How many, and will they make money?
Difficulty: Standard. Format: market-sizing opener, then a business question. Industry: Healthcare. Region: US. Interview length: about 30 minutes. The company is fictional and all figures are illustrative.
Clarifying questions, with the interviewer's answers
- What area?Answer: A US metro area of about 3 million people.
- How often do people use urgent care?Answer: About 0.4 visits per person a year.
- What share could our system win?Answer: About 10 percent; a clinic handles about 15,000 visits a year.
- For the business question, what does a clinic cost and earn?Answer: About USD 1.2 million of fixed costs a year per clinic. A visit earns about USD 150 from commercial insurers and costs about USD 60 in variable costs.
A hypothesis to say out loud: Urgent care is a volume business with high fixed costs per clinic. My hypothesis is that the market supports several clinics, but payer mix decides whether each clinic makes money.
The structure
- Size the visits, then test one clinic's economics
- People x visits per person x our share
- Clinics = our visits / visits per clinic
- Key: Break-even visits per clinic
- Payer mix
Working it through
1. Visits in the metro area
3 million people at 0.4 visits a year.
Visits a year:3,000,000 × 0.4 = 1,200,0002. Our visits
A 10 percent share.
Our visits a year:3,000,000 × 0.4 × 0.1 = 120,0003. Number of clinics
At 15,000 visits each.
Clinics:120,000 ÷ 15,000 = 84. Break-even visits
Each clinic has about USD 1.2 million of fixed costs a year; a visit earns USD 150 and costs USD 60.
Break-even visits a year:1,200,000 ÷ (150 - 60) = 13,3335. Curveball: payer mix
Interviewer: "About 30 percent of visits would be covered by Medicaid, which pays about USD 80." Blended revenue per visit:
Blended revenue per visit (USD):0.7 × 150 + 0.3 × 80 = 1296. New break-even
Fixed cost divided by the new contribution per visit.
Break-even visits a year:1,200,000 ÷ (0.7 × 150 + 0.3 × 80 - 60) = 17,3917. Profit per clinic at 15,000 visits
With the blended revenue.
Profit per clinic (USD a year):15,000 × (129 - 60) - 1,200,000 = -165,000
The recommendation
The metro area has about 1.2 million urgent-care visits a year, enough for about eight clinics at a 10 percent share, but not all of them would make money. First, at USD 150 per visit a clinic breaks even at about 13,300 visits. Second, with 30 percent Medicaid patients paying USD 80, break-even rises to about 17,400 visits, so a clinic at 15,000 visits loses about USD 165,000 a year. Third, the fix is better economics, not avoiding patients: choose sites on unmet demand and access, accept all payers, and close the gap through better Medicaid managed-care contracts, lower-cost staffing (nurse practitioners and physician assistants), evening hours to raise visits, and telehealth for simple cases.
Risks: Payer mix may differ by site; Retail clinics and telehealth rivals may take share.
Next steps: Map payer mix and competition by neighborhood; Model three clinics first, with evening hours.
A strong candidate
Sized the market cleanly, then showed how payer mix moves break-even and shaped the plan around it.
A weak candidate
Opened eight clinics because the market supports eight, without checking whether each one makes money.
Sources for this lesson (1)
- Recognized public explanations of case-interview concepts and frameworks
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