Structuring is a muscle. Below are ten prompts with a model MECE skeleton each. Cover the skeleton, give yourself two minutes per prompt to build your own tree aloud, then compare. Do not memorize these as templates. The point is to internalize the cuts (see MECE and the issue tree) so you can build a bespoke tree for any prompt. All companies synthetic.
D1: A bakery chain's profits are falling. Why? (algebraic cut) Profit = Revenue − Cost. Revenue = outlets × sales/outlet; sales/outlet = footfall × conversion × basket. Cost = variable (ingredients, packaging) + fixed (rent, staff, ovens). First test: is it revenue or cost, and is revenue volume or price?
D2: Should a US home-furniture retailer enter India? (market-entry cut) (1) Market attractiveness: size, growth, margins, fragmentation; (2) right to win: brand, supply chain, local sourcing, price point vs local rivals; (3) entry mode: own stores vs franchise vs online vs JV; (4) risks + go/no-go.
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D3: Should a cement maker shut its oldest plant? (decision cut) Compare keep vs close: incremental cash flows of keeping (contribution the plant still earns) vs costs avoided by closing (net of shutdown/severance/write-off costs) vs alternative uses of the site; plus strategic factors (regional capacity, customer coverage). Beware sunk costs: past capex is irrelevant to the decision.
D4: How can a subscription streaming service double revenue in three years? (lever tree) Revenue = subscribers × ARPU. Grow subscribers: reduce churn, acquire new (by geography, by segment), reactivate lapsed. Grow ARPU: raise price, upsell tiers, add ads, bundle. New revenue lines: licensing, live events. MECE by "more users" vs "more per user" vs "new streams."
D5: A telco is losing customers. Diagnose it. (funnel + segment cut) Where in the lifecycle? Acquisition (fewer joining) vs retention (more leaving). Segment the churn: by plan, tenure, geography, and reason (price, network quality, service, competitor offer). Test the biggest bucket first.
D6: How should a startup price a new project-management SaaS tool? (pricing cut) Floor = cost to serve per seat; reference = competitor per-seat pricing; ceiling = value (hours saved × loaded wage). Then choose model (per-seat vs usage vs tiered), test willingness-to-pay, and set price to capture a share of value above the competitive anchor.
D7: Should an auto-parts firm make a component in-house or buy it? (make-vs-buy cut) Cost (in-house total cost incl. capex, capacity utilization, learning curve vs supplier price) + strategic (IP/quality control, supply security, flexibility) + risk (demand volatility, supplier power). Quantify the cost cross-over volume; layer the strategic view on top.
D8: Should a hospital buy a second MRI machine? (investment cut) Incremental revenue (extra scans/day × price × utilization × days) vs incremental cost (machine amortization, technician, maintenance, space) → payback/NPV; plus capacity (is the current machine actually the bottleneck?) and strategic (patient wait times, referrals). Utilization is the swing variable.
D9: A diversified conglomerate wants to reshape its portfolio. (portfolio cut) Score each business on market attractiveness × competitive position → own/grow (strong-strong), fix or invest (strong market, weak position), harvest (weak market, strong position), exit/divest (weak-weak). Then reallocate capital from low-return to high-return units.
D10: An NGO wants to increase clean-water access per rupee donated. (non-profit / objective cut) Objective isn't profit; it's impact per rupee. Break into reach (people served) × effectiveness (per-person outcome) × cost efficiency (cost per person). Levers: cheaper delivery, higher-impact interventions, better targeting, reducing overhead. Be MECE on "more people," "better outcomes," "lower cost each." Shows the profit tree generalizes to any objective function.