Consulting Case Interview Questions

The case interview at MBB and tier-2 firms tests four things: structured thinking, business judgment, mental math under pressure, and the ability to deliver a recommendation that doesn't hedge. Most candidates over-prepare for frameworks and under-prepare for the math and the synthesis — and that's where rounds are decided.

Below are 8 representative cases — market sizing, profitability, market entry, M&A, cost reduction, pricing, and growth — with the structure, math, and recommendation for each. Each case is the kind of prompt you'd actually get in a McKinsey, BCG, or Bain final round.

If you'd rather work through these out loud against an AI interviewer that pushes on shaky math and demands a recommendation, run a consulting case mock.

1. Market sizing — How many electric vehicle charging stations does the US need by 2030?

Structure. Demand from EV stock × charging frequency × charging duration ÷ utilization target = stations needed. Then sanity-check vs. existing supply.

Math.

• US light-vehicle stock today ≈ 280M vehicles.
• Forecasts have EVs at 25–35% of new car sales by 2030, ~15% of stock by 2030.
• 280M × 15% ≈ 42M EVs in 2030.
• Average EV does ~12K miles/year, ~3.5 mi/kWh → ~3,400 kWh/year.
• Of that, assume 25% is charged at public stations (rest at home/workplace).
• 25% × 3,400 = 850 kWh public per car per year × 42M cars = 35.7B kWh/year.
• A Level-3 fast charger delivers ~50 kW. At 30% utilization (industry target), each charger delivers 50 × 0.3 × 8,760 = 131K kWh/year.
• Stations needed = 35.7B ÷ 131K ≈ 270K fast chargers.
• Today the US has 50K. Gap is **220K**, or ~30K new chargers/year for 7 years.

Recommendation. "The US needs to roughly 5× its DC fast-charging fleet by 2030 — about 30K new chargers per year. The constraint isn't capital; it's siting (real estate near highways), grid interconnection lead times, and utility coordination. The bottleneck a strategy here should solve is interconnection time, not station count."

Follow-ups. What if charger speed doubles? (Roughly halves the count needed, all else equal.) What if home charging share rises to 90%? (Public station count drops 60%.)

2. Profitability — A regional grocery chain's margin has dropped from 3.5% to 1.8% over 3 years. What's going on?

Structure. Profit = revenue − cost. Decompose each side.

• Revenue per store, store count, basket size, traffic.
• Cost: COGS, labor, rent, shrink, transportation.

Math + diagnosis.

• Revenue is flat (mentioned in the brief). So margin compression is on the cost side.
• COGS ratio: industry standard ~75% in groceries. If their COGS went from 75% to 78%, that's 3 percentage points of margin gone — explains most of the drop.
• Why might COGS rise without prices rising? Mix shift (customers trading down to lower-margin private-label without volume rising), input cost inflation absorbed instead of passed through, or shrink (stolen / spoiled inventory).
• Ask the interviewer for COGS broken down by category. They'll typically reveal that produce shrink doubled (2% → 4%) and meat margins compressed because the chain didn't raise prices in line with wholesale.

Recommendation. "Two-pronged: (1) Reduce produce shrink — automated ordering tied to actual sell-through data per SKU, second daily delivery on highest-shrink categories, ~150bps margin recovery in 12 months. (2) Reset meat-counter pricing to industry margin, with a value-perception campaign on the 15 SKUs that drive most of the foot traffic — recovers another ~100bps without losing the value position."

Follow-ups. What if competitors are also losing margin? (Then it's an industry shock — pass-through pricing is harder; private-label expansion is the better lever.) What if traffic is also down? (Different problem entirely — investigate competitive entry in the trade area.)

3. Market entry — Should a US streaming service enter India?

Structure. Market attractiveness × competitive position × entry economics.

• Attractiveness. Market size, growth, ARPU, willingness to pay.
• Competitive. Incumbent share, content moat, regulatory risk.
• Economics. CAC, content investment required, expected payback.

Math.

• India has ~1.4B people, ~600M with broadband / mobile data.
• Streaming penetration is high (~250M paying subscribers across all services).
• ARPU is ~$2/month — 10× lower than the US ARPU of ~$15.
• Local incumbents (JioHotstar, ZEE5, SonyLIV) own most of the cricket and Bollywood rights.
• US-style premium pricing wouldn't work; the unit economics need to clear at $2 ARPU.
• Content investment: Hollywood library is undervalued at $2 ARPU. Original local content is the only way to match incumbents on retention, but it's $2–5M per hour vs. $0.5M for incumbents.

Recommendation. "Don't enter as a standalone. The unit economics don't clear: at $2 ARPU and the content investment required to compete on retention, payback is north of 7 years even with optimistic assumptions on penetration. Instead, license the existing library to a local distributor (Reliance, Sony) for a flat fee — recover the content's marginal value without taking the operational risk. Revisit direct entry only if local ARPU rises above $5, which probably requires a ~3× rise in disposable income."

Follow-ups. What if the firm has a unique IP that India's incumbents don't have? (Different question — license the IP exclusively, take a revenue share rather than a flat fee.) What if regulatory rules change to require local-only operation? (Forces a JV; same answer — go via a partner, not direct.)

4. M&A — Should a $5B specialty chemical company acquire a $1B competitor?

Structure. Strategic fit × valuation × integration risk × alternatives.

• Strategic. What's the rationale — scale, capability, geography, customer base?
• Valuation. Standalone DCF of target + synergies − integration cost.
• Integration. Likely realization rate of synergies, retention risk on key customers.
• Alternatives. Build vs. buy vs. partner.

Math.

• Target has $1B revenue, 12% EBITDA margin → $120M EBITDA.
• Acquirer offered 10× EBITDA = $1.2B.
• Cost synergies: 8% of combined cost base ≈ $60M/year (procurement consolidation, plant overhead, SG&A).
• Revenue synergies: cross-selling estimated at $40M extra revenue × 15% margin = $6M EBITDA. Be skeptical of revenue synergies; in M&A research, only ~30% of estimated revenue synergies materialize.
• Integration cost: ~$80M one-time over 18 months.
• Steady-state combined EBITDA = $120M (target) + $60M (cost syn) + $6M (rev syn × 30%) = $186M.
• Multiple expansion: combined entity at $186M × 10× = $1.86B value, $660M above purchase price.

Recommendation. "Yes, at $1.2B with explicit conditions. The cost synergies are credible because they're identifiable line items, not vague 'efficiency gains.' Bake them into the integration plan with named owners and quarterly milestones. Discount revenue synergies in the model. Walk away if the price moves above $1.4B (10×, plus a quarter turn for control)."

Follow-ups. What if the target's largest customer is also the acquirer's competitor? (Major retention risk — discount the customer's revenue or condition the deal on a long-term contract.) What's the right financing mix? (Depends on the acquirer's cost of capital and credit rating; usually 60/40 cash/stock for a deal this size.)

5. Cost reduction — A regional airline needs to cut $200M in annual costs. Where do you look?

Structure. Cost = variable + fixed. Variable: fuel, food, crew-hours, landing fees. Fixed: aircraft, facilities, IT, corporate.

Math.

• Airline runs at $4B annual cost. $200M = 5% reduction target.
• Cost mix: 30% fuel, 25% labor, 15% aircraft (lease + maintenance), 10% airport fees, 10% sales/distribution, 10% other.
• 5% across the board is unrealistic without service degradation. Better to find 10–15% on 1–2 categories.
• Fuel. Fleet renewal (newer aircraft are 15–20% more fuel efficient). $200M target is 17% of $1.2B fuel spend — achievable over 5 years through fleet rotation, not 1 year.
• Sales/distribution. Direct booking share at 35% (industry leader is 70%). Each percentage point of direct booking saves ~$1M in GDS fees + commission. Move to 60% over 18 months → $25M.
• Maintenance. Insourcing 30% of currently-outsourced heavy maintenance saves $40M/year, requires $80M one-time investment in hangar capacity.

Recommendation. "$200M in 12 months is unrealistic without service cuts that erode brand. Phase it: $100M in year 1 (direct booking + maintenance optimization + cabin product simplification), $200M run-rate by end of year 3 (fleet renewal + crew scheduling overhaul). The fastest win is direct-booking conversion — 12-month payback, no operational risk."

Follow-ups. What about labor? (Last lever to pull — has the highest morale cost. Touch only if board explicitly accepts brand risk.) Cabin densification? (Worth considering on long-haul; ~$40M/year per 5% capacity increase, but customer satisfaction costs are real.)

6. Pricing — A SaaS company is debating moving from per-seat pricing to usage-based pricing. Should they?

Structure. Customer segments × elasticity × revenue impact × competitive dynamics × operational complexity.

Math.

• Today: $20M ARR, average customer pays $400/month for 8 seats ($50/seat).
• Top 20% of customers (by seat count) pay 60% of revenue.
• Bottom 50% of customers use ~10% of total platform usage but pay 30% of revenue (over-paying).
• Move to usage-based at $0.10 per API call:
  • Top 20% currently average 50K calls/customer/month → $5K/month (vs. $1,500 today seat-based) → revenue 3× up on the heavy users.
  • Bottom 50% currently average 1K calls → $100/month (vs. $200 today) → revenue 50% down on light users.
• Net: top 20% gain ~$36M ARR, bottom 50% lose ~$3M ARR → +$33M ARR.
• But churn assumption: light users probably churn at 30% rather than rebuy. So actual gain is $33M − $1.5M churn revenue = +$31M ARR.

Recommendation. "Move to a hybrid: keep per-seat for the bottom 50% (with a higher floor), introduce usage-based for top 20%. Don't migrate the middle 30% until you've measured churn on the light tier — if it's worse than 30%, hybrid pricing protects the base. Roll out as opt-in for new customers first; force migration in 6 months once churn data is in."

Follow-ups. What if competitors all switch to usage-based? (Forces your hand — the elasticity argument flips because seat-based becomes the premium-priced incumbent.) What's the implementation cost? (Significant — usage instrumentation is a 6-month build, billing complexity goes up, customer success has to re-train. Bake into the timeline.)

7. Growth — A boutique fitness chain is at $80M revenue. CEO wants to triple revenue in 3 years. How?

Structure. Growth = same-store growth + new stores + new offerings.

• Same-store: traffic, frequency, spend per visit.
• New stores: how many, where, what payback.
• New offerings: adjacencies (apparel, nutrition, virtual classes).

Math.

• Today: 50 studios × $1.6M/studio = $80M.
• Target: $240M in 3 years.
• Same-store growth at industry typical 4%/year → 50 studios × $1.8M = $90M (12% growth, not 200%).
• New studios: each new studio costs $400K to build, takes 18 months to ramp, then $1.6M revenue at maturity. To add $130M, need 80 new studios. At 30 studios/year build pace, achievable in 3 years.
• New offerings: virtual class subscription at $30/month × 100K subscribers = $36M ARR. CAC at $80 / LTV at $720 → 9-month payback.
• Combined target: $90M (same-store) + $130M (new studios) + $36M (virtual) ≈ $256M. Tracks.

Recommendation. "Doable but capital-intensive. Three workstreams in parallel: (1) Open 80 new studios in next-tier cities at $32M one-time capex over 3 years, (2) launch virtual subscription off existing content for $5M build, (3) raise prices 5%/year on the existing book to fund (1) and (2). The risk is the 80-studio build pace — operational capacity to find sites, hire instructors, and maintain quality is the binding constraint. Stress-test with the COO on whether 30/year is realistic."

Follow-ups. What about acquiring competitors? (Adds a fourth lever — tuck-in acquisitions of small chains at 1–2× revenue can buy the studio count faster, but cultural fit kills most of these.) What if the macro turns? (Studio model is recession-sensitive; the virtual subscription is the recession hedge — push it harder.)

8. Brain teaser — A pharmaceutical company's blockbuster drug goes generic in 18 months. They have $4B/year of revenue at risk. What do you do in the next 18 months?

Structure. Pre-LOE (loss of exclusivity) revenue defense + post-LOE strategy + reinvest the brand value before it dies.

Math.

• $4B revenue today, ~70% gross margin → $2.8B gross profit.
• Standard generic erosion curve: 80% volume loss within 12 months of LOE, with another 10–15% in years 2–3.
• 18 months pre-LOE: maximize cash extraction.
• Steps:
  • Authorized generic. Launch your own generic at LOE-day-1, capture 30–40% of generic share at lower margin. Retains ~$400M/year for 2 years.
  • Lifecycle. Reformulate as extended-release (12-hour dosing); file new patent. Can extend exclusivity 3–5 years on the new formulation. Industry success rate: ~40%.
  • Indication expansion. New approved indications get separate exclusivity for the indication. Run two pivotal trials in parallel.
  • Pricing. Don't cut price pre-LOE — the channel discount preserves nothing once generics are listed. Hold price, accept volume erosion.
  • OTC switch. If the drug is a candidate, file for OTC. OTC launch can preserve $300–500M/year for many years post-Rx LOE.

Recommendation. "Run all five plays in parallel. Most blockbusters use a portfolio approach because no single play is high-confidence. Expected value of the package is $1.5–2B/year preserved at 24 months post-LOE — half of pre-LOE revenue, but a significantly better outcome than pure cliff. Critical bottleneck is the lifecycle reformulation; it has to be filed in the next 9 months to get a 6-month FDA review before the cliff."

Follow-ups. What if it's a biologic, not a small molecule? (Biosimilar erosion is slower — ~50% volume loss over 3 years vs. 80% in 12 months for small molecules. Different urgency.) What if the company's pipeline is weak? (More aggressive on lifecycle and OTC; consider M&A of late-stage assets to refill the pipeline before the cash flow drops.)

FAQ

How long should each part of a case take?

Typical 30-minute case: 5 min clarification + framework, 15 min analysis + math, 5 min recommendation, 5 min follow-ups. Most candidates over-spend on framework and under-spend on the recommendation. The interviewer remembers the recommendation, not the framework.

Do interviewers care which framework I use?

No. They care that you customized the framework to the case. Walking in with "profitability cases use 4P + Porter's" gets a low score; walking in with "let me start by decomposing revenue and cost, then dig into whichever side the data tells me to" gets a high one.

How important is the math?

Critical at MBB. Senior interviewers grade arithmetic specifically — if you can't multiply two-digit numbers under pressure or compute percentages without writing them down, the round is over even if your structure is excellent. Drill mental math.

What's the right way to recover from a math mistake?

Acknowledge it directly, redo the calculation, move on. Don't apologize or explain. The interviewer is grading recovery, not perfection — a candidate who notices their own mistake and fixes it is signaling exactly the right behavior.

How do I deliver the recommendation strongly?

Lead with the answer, then the rationale. "I would acquire the target at $1.2B. The synergies are credible at $60M cost-side, the integration risk is manageable, and the multiple expansion alone clears the cost of capital. The two conditions are X and Y." That's a senior consultant's voice; that's what the interviewer is grading for.