Learning objectives
By the end you can:
- State the four canonical case formats (profitability, market entry, pricing, M&A/growth/ops) and explain why profitability and market entry are taught first, every other format reuses their driver logic (CN2.04 extends it to the remaining two).
- Build the profit tree down through volume/price and variable/fixed, and extend it into a reconciling variance bridge that quantifies exactly how much of a profit change came from volume, price, variable cost, and fixed cost, with the arithmetic closing to the last rupee or dollar, not an approximate story.
- Split a multi-product or multi-segment volume effect into a quantity (yield) variance and a mix variance, and read what a mix shift is telling you about the business that the aggregate number hides entirely.
- Run the market-entry format as three separable gates (attractiveness, capability (right to win), and entry mode) and explain why collapsing them into one "good idea / bad idea" verdict is the single most common way this case format is cracked badly.
- Build and defend a weighted attractiveness scorecard and a qualitative capability / right-to-win checklist, keeping the two tests strictly apart even when the instinct is to average them into one feeling.
- Choose and quantify an entry mode (organic (greenfield) build, acquisition, joint venture, or licensing/franchise) against speed, control, capital intensity, risk, and reversibility, including a basic payback comparison between two modes.
- Read a real exhibit set fast: extract the one number that matters, spot a one-off or seasonal spike that would corrupt an unadjusted trend, and know precisely what to ask for next instead of computing on incomplete information.
- Turn either format's analysis into an answer-first recommendation carrying a named risk and a named mitigation for every supporting point, and correctly hand off the full synthesis mechanics (governing thought, pyramid, storyline) to CN1.03 rather than reinventing them here.
- (Productivity objective: R10 duality.) Use AI to accelerate exhibit drafting, reference-magnitude research, and first-pass scorecard scaffolding for either format, while keeping every number, every gate, and every "so what" owned, computed, and verified by you.
The duality, stated once (R10). Every module in this galaxy carries two objectives at once. The understanding objective (items 1–8) is what the mastery gate rewards: you earn the belt by building the bridge and running the three gates yourself, by hand, on a case you have not seen before. The productivity objective (item 9) is the payoff you keep afterward: knowing how to point an AI tool at the grunt work of a case (drafting an exhibit table, recalling a rough market-size anchor, sketching a first-pass scorecard skeleton) without ever letting it own the structure, the arithmetic, or the recommendation. A tool can never buy you a pass on the gate below.
Prerequisites & connections
Builds on. CN0.01 gave you the problem-solving cycle and the answer-first mindset, so you already know a case rewards structure before computation. CN1.01 gave you issue trees and MECE; every cut you make in a profit tree or an attractiveness scorecard is a MECE cut, tested here rather than taught here. CN1.02 gave you hypothesis-driven problem solving, and its day-one hypothesis and minimum-analysis discipline get drilled here against two specific, high-frequency formats. CN2.01–CN2.02 gave you case math and market sizing. You will run both inside these two formats without re-derivation: if a market-entry case needs a market size, CN2.02's top-down/bottom-up machinery is assumed, not repeated. If you have already run the Cycle-2 taster elective (E11.03, and its case CL-11.3, Kite Foods Profitability) you have met the profit tree and a four-block market-entry skeleton at introductory depth. This node is where that sketch becomes a professional instrument: quantified, segmented, and defended with a real reconciling bridge and a real weighted scorecard, not a memorized shape you recite and hope holds up under a follow-up question.