Frameworks cheat sheet

Frameworks are a starting point, not a script

How to use these guides without sounding like you memorized them.

Interviewers have heard "the 4 Ps" and "the 3 Cs" hundreds of times. What they want to see is that you can build a structure for this client's problem — one that is complete, doesn't overlap, and points toward a decision.

Use the guides below as a mental checklist, then adapt:

1. Start from the question. Restate the objective in one sentence ("Should Halden enter Texas, and how?"). Every branch of your structure should help answer it.
2. Name branches in the client's language. "Patient volume" and "net price after rebates" beat "volume" and "price" in a pharma case.
3. Go one level deeper where the case is likely to be. If the prompt mentions a new competitor, make competition a full branch with sub-questions, not a bullet.
4. State a hypothesis. "I suspect the issue is on the cost side, because revenue is flat while profit fell — I'd like to start there."
5. Keep it to 3–4 top-level branches. More than that is hard to follow and usually overlaps.

A useful test: if you crossed out the case name, could your structure be used for any company? If yes, it isn't tailored enough.

Choosing your approach

Many real cases combine two: a market-entry case usually contains a sizing; an M&A case usually contains a profitability check of the target.

Market sizing

Turn a big, vague number into a few small, defensible ones.

Use it when

You're asked "how big is…", "how many…", or need a market size inside a larger case (entry, investment, capacity).

The core logic

Pick one of two directions and say which you chose and why:

• Demand side (top-down): population → share that has the need → share that buys → units per buyer → price. Good for consumer and patient markets.
• Supply side (bottom-up): number of sellers or sites → capacity or sales per site → utilization → price. Good when buyers are hard to count but suppliers aren't (cafés, factories, data centers).

Then segment wherever behavior differs a lot: by customer type, age, income, company size, or usage intensity. One average across very different groups is the most common source of a wrong answer.

Questions that unlock it

• Which geography, which year, units or value?
• Is this the whole market or only what our client can serve?
• Are repeat purchases or replacement cycles important (one-off vs. recurring)?

Adapt it

• Pharma & healthcare: patients → diagnosed → treated → on this type of therapy → doses per year → net price. Persistence (how long patients stay on therapy) often halves the answer.
• Energy: installed base × replacement rate, or new capacity added per year. Distinguish power (MW) from energy (MWh).
• Tech / SaaS: organizations × seats per organization × adoption × price per seat per month × 12.
• B2B / industrial: plants or sites × equipment per site ÷ equipment lifetime = annual replacement demand.

Traps

• Not saying your approach before calculating.
• Forgetting ×12 for monthly prices or ÷ lifetime for durable goods.
• Giving a number with no sanity check (compare with a known anchor, or size it a second way).
• Stopping at the number. Always say what it means for the client's decision.

See all 8 Market sizing cases →

Profitability

Find which part of the profit equation moved, then ask why.

Use it when

Profits, margins or returns are falling (or not growing as expected).

The core logic

• Profit = Revenue − Costs
  • Revenue = Volume × Price
    • Volume: market size × share — or customers × purchases per customer
    • Price: list price, discounts, mix of products or customers
  • Costs = Fixed + Variable
    • Variable: cost per unit × volume (materials, labor per unit, shipping, cloud usage)
    • Fixed: overhead, rent, salaries, sales force, R&D

Work quantitatively: get the numbers for two periods, find which line moved the most, then dig into that line. A simple profit bridge (volume effect + price effect + cost effects = total change) makes the answer crisp.

Questions that unlock it

• Is it just us or the whole industry? (Internal vs. external cause.)
• When did it start, and what changed then?
• Is it one product, region, channel or customer segment?

Adapt it

• Pharma: separate list price from net price — rebates, copay support and government discounts ("gross-to-net") often explain the whole story.
• Healthcare providers: revenue depends on payer mix (commercial vs. government vs. uninsured) and case mix, not just volume.
• Tech / SaaS: look at unit economics — customer acquisition cost vs. lifetime value, churn, and usage-driven costs such as AI inference.
• Industrial: high fixed costs mean volume drops hit profit hard (fixed-cost absorption); check aftermarket parts and service.
• Retail / consumer: product mix, promotions, waste/shrink and channel costs (e-commerce shipping, returns).

Traps

• Listing every possible cost before looking at data. Ask for the numbers first.
• Saying "price fell" when list price rose but net price fell.
• Fixing the symptom ("cut costs") without identifying the cause.
• Forgetting that some "unprofitable" units feed profit elsewhere (an ED that fills hospital beds; a razor that sells blades).

See all 7 Profitability cases →

Market entry

Answer whether to enter AND how — the second half is where most candidates stop short.

Use it when

A client is considering a new country, customer segment, product category or business model.

The core logic

1. Is the market attractive? Size, growth, profitability, how durable the profit pool is, regulation.
2. Can we win? Competitors and their reactions, customer needs, our capabilities and gaps, barriers to entry.
3. Does it pay? Revenue we could realistically capture, upfront investment, ongoing costs → break-even share, payback, or NPV vs. the client's hurdle.
4. How should we enter? Build ourselves, partner / license, joint venture, or acquire — and how fast.
5. What could go wrong? Key risks and how to test or mitigate them.

Questions that unlock it

• What is the client's goal (growth, diversification, using spare capacity) and its hurdle (payback, share, revenue)?
• What does the client already have that helps (brand, technology, channels, customers)?
• How have other entrants done?

Adapt it

• Regulated markets (pharma, utilities, finance): approval timelines and reimbursement or licensing can matter more than demand.
• Consumer goods abroad: distribution and local partners are often the deciding factor; price points may need redesign.
• Energy / infrastructure: revenue durability (contracts vs. merchant prices) and grid or site access dominate.
• Tech: switching costs and incumbents' bundling power; partnering with a platform can beat building.

Traps

• Saying "yes, enter" without saying how.
• Using today's revenues when the market is about to get crowded.
• Ignoring the client's capabilities — an attractive market isn't automatically an attractive market for this client.
• No number: always compute a break-even share or payback and compare it with what's realistic.

See all 5 Market entry cases →

Pricing

Triangulate between cost, competitors and customer value — then design how the price is paid.

Use it when

A client is launching a product, changing prices, or designing tiers, bundles or payment models.

The core logic

Triangulate three views and explain where the price should sit between them:

• Cost-based (the floor): unit cost + target margin. Tells you the minimum, not the right answer.
• Competitor-based (the reference): prices of the closest alternatives, adjusted for differences in quality or features.
• Value-based (the ceiling): what the customer gains — money saved, revenue gained, health or time improved. Customers rarely pay all of it; you usually capture a share.

Then decide the structure: one price or tiers (good / better / best), per unit or subscription, upfront or over time, discounts by segment.

Questions that unlock it

• What is the objective — revenue, profit, market share, access or ridership?
• Who decides, who pays and who uses? (Often three different people in healthcare and B2B.)
• How price-sensitive are customers (elasticity), and how will competitors react?

Adapt it

• Pharma & gene therapies: value = avoided treatment costs + health gains; payers' budgets and risk drive structure (outcomes-based or annual payments).
• B2B software: price on a value metric that grows with the customer (seats, usage, transactions); fence tiers so customers don't trade down.
• Consumer subscriptions: anchor against the per-day or per-use cost; watch markup vs. margin confusion.
• Public sector: the objective may be ridership, equity or access, not revenue — design discounts for the groups you most want to serve.

Traps

• Stopping at cost-plus.
• Ignoring elasticity: a higher price can lose more volume than it gains in margin.
• Forgetting cannibalization when adding a cheaper tier.
• Confusing markup (on cost) with margin (on price): a 40% markup is only a 29% margin.

See all 4 Pricing cases →

M&A and investment

Is it a good business, is it worth more to us than we pay, and can we actually capture the value?

Use it when

A client is considering buying a company, investing in a business, or (for private equity) whether a deal will hit its return target.

The core logic

1. Why do the deal? Strategic rationale — growth, capabilities, filling a gap, scale. If there's no clear reason, stop here.
2. Is the target a good business on its own? Market, competitive position, profitability and its trend, risks.
3. What is it worth to us? Standalone value + synergies − integration costs. Compare with the price. The premium paid must be covered by synergies we can realistically capture.
4. Can we capture it? Integration difficulty, culture, key people, regulatory approval.
5. How should we structure it? Price, cash vs. shares, earn-outs or contingent payments that move risk to the seller.

Quick valuation tools for interviews

• Multiples: value ≈ EBITDA × a multiple typical for the industry.
• Risk-adjusted value (pipelines, projects): value if successful × probability of success.
• Private equity returns: exit value ÷ equity invested = MOIC (money multiple). Roughly, 2x in 5 years ≈ 15% a year; 3x in 5 years ≈ 25% a year.

Adapt it

• Pharma: value each drug by stage and probability; check patent life and whether the target fills a revenue gap.
• Private equity: returns come from EBITDA growth, multiple expansion and debt paydown — say which one the plan relies on.
• Energy transition deals: adjacent businesses (e.g. EV charging for a fuel retailer) may be worth more to this buyer than to anyone else — but don't pay the seller for value only you create.

Traps

• Valuing the target without asking about the price.
• Counting synergies that you'd have to pay away, or that take years to arrive.
• Ignoring the "do nothing" or "build instead" alternatives.

See all 3 M&A / investment cases →

Operations

Find the bottleneck, quantify the gap, and fix the cheapest constraint first.

Use it when

A client can't produce, process or deliver enough — or does so too slowly or too expensively.

The core logic

1. Map the process as a chain of steps (receive → inspect → process → pack → ship).
2. Find each step's capacity per day or week. The step with the lowest capacity is the bottleneck; the whole system can't go faster than it.
3. Compare with demand. Capacity below demand → a backlog that grows every day. Backlog ÷ (capacity − demand) = time to clear it once fixed.
4. Explain why the bottleneck is slow: not enough resources, downtime, changeovers, defects and rework, poor scheduling.
5. Prioritize fixes by impact and cost: cheaper process fixes usually come before new equipment or people.

For machines, overall equipment effectiveness (OEE) = availability × speed × quality. A line at 60% availability, 90% speed and 95% quality runs at about 51% of its theoretical output.

Questions that unlock it

• Is demand steady or peaky (seasonal, end of month)?
• Where does work pile up? (That's usually the bottleneck.)
• What does an extra unit of capacity cost at each step?

Adapt it

• Pharma manufacturing: changeovers and cleaning between batches, and quality release, often limit output more than machine speed.
• Warehouses and e-commerce: labor per step and shift patterns; returns flows are often an afterthought.
• Services (claims, call centers): people are the capacity; automation of simple cases frees experts for complex ones.

Traps

• Adding capacity everywhere instead of at the bottleneck.
• Forgetting that fixing one bottleneck moves it to the next step — say where it moves.
• Ignoring the cost of the backlog itself (lost sales, penalties, customer goodwill).

See all 3 Operations cases →