Case Code-X | IIM Calcutta x Indore | Quick Commerce Profitability Strategy

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1. About the Case Competition

Case Code-X is a prestigious analytical case competition jointly hosted by the Analytics Club of IIM Calcutta, Analytica (IIM Indore’s Data Science Society), and Infinit-I (IIM Indore’s Data Analytics Club), making it one of the most rigorous data-driven case competitions on the B-school circuit. Team Pitch Perfect from IIM Rohtak. secured the 2nd runners-up position. The case sits squarely in the unit economics, financial analytics, and operations strategy domain.

2. Problem Statement Overview

A quick commerce food delivery operation is bleeding ₹1,51,72,545 annually despite strong order volumes, with a per-order loss of ₹16.3 and a QC channel margin of -13.75%, while the dine-in channel runs a healthy 12.43% margin. The gap is structural: a ₹45 fixed delivery cost unique to QC, platform commissions averaging 22% of revenue, and blanket discounting running 8–15% higher than other channels together create a “margin scissors” effect that no volume increase can solve. The problem compounds across geographies, metro cities and food court formats post the worst numbers, and across time bands, with late-night slots dropping to margins as low as -20.3%. The deck’s core thesis: this is a structural failure, not an operational one, and it requires five simultaneous interventions rather than incremental tweaks.

3. What This Winning Deck Covers

The deck opens with an unusually rigorous cost anatomy, breaking down the ₹1 earned in QC into 31.9p COGS, 28p store operating cost, 20.1p platform fee, 19p delivery cost, and 1p CAC, before introducing the central insight: the 41-paise gap between QC (loss of 14.6p per rupee) and dine-in (profit of 28.3p per rupee) is entirely driven by delivery and commission costs that COGS cannot absorb. The segmentation across city tiers, store formats, and time bands adds analytical granularity that elevates this well above standard profitability decks.

The data integrity section is the deck’s most distinctive contribution to the analytical case competition genre. Rather than treating the dataset as clean, the team systematically identifies five data imperfections: aggregation and scale bias, city-level heterogeneity, incomplete CAC allocation, outlier events, and discount attribution ambiguity, and runs a full sensitivity analysis across conservative, base case, and optimistic assumptions for each. The conclusion is analytically robust: under every assumption set, QC margins remain negative, confirming the structural thesis. This kind of assumption-testing rigour is also central to the approach in The Data Conclave – IIM Rohtak.

The outlier analysis maps nine specific 2024 events, from IPL season to gig worker strikes to peak monsoon, against their individual impacts on margin, order volume, and cost, then argues for a “stress scenario lens” where outliers are excluded from baseline strategy but retained separately for operational resilience planning. The five-lever recommendation roadmap follows a tight sequencing logic: Stop the Bleed (Month 0–1) via ₹300 MOV and ₹30 small order fee; Recovering Revenue (Month 1–3) via dynamic discounting with sub-5% discounts during peak hours; Aligning Product (Month 3–6) via a QC-specific menu eliminating the bottom 20% low-margin items; Sustainable Structuring (Month 6–12) via renegotiating platform commissions from 22% to tiered rates; and Retention and Stability (Month 12–18) via discount-free order frequency improvement. Each lever carries a risk mitigation matrix and a KPI target. Similar phased profitability and pricing strategy design is explored in Airtel iCreate 2025 – 1st Year B-School Track.

Key Takeaways:

  • Decomposing per-rupee economics (not just total P&L) is the sharpest way to isolate structural vs. operational losses in multi-channel businesses
  • Sensitivity analysis across data imperfections, not just financial assumptions, is a competition differentiator that signals consultant-grade analytical confidence
  • Sequencing recommendations by time horizon (stop the bleed → recover revenue → restructure) is more persuasive than presenting all levers simultaneously
  • Outlier event mapping builds operational credibility and prevents judges from poking holes in baseline assumptions
  • KPI-per-lever accountability (combo attachment rate, discount ROI, churn rate during surge) converts recommendations into measurable commitments

4. The Numbers

Annual QC loss stands at ₹1,51,72,545 (monthly ₹12,64,378; daily ₹41,620; per order ₹16.3). QC channel margin is -13.75% versus dine-in at 12.43% and takeaway at 12.32%, a 41-paise structural gap per rupee earned. The current average QC order value is ₹216; the MOV intervention targets ₹303. Platform commissions average 22%; the recommendation targets an 18% rate for orders above ₹500 and 10% plus ₹10 fixed for orders below ₹500, reducing per-order cost by ₹8. The MOV and small order fee together are projected to lift the average profit margin from -13.7% to 0.04%. The surge pricing standard fee of ₹20 is projected to improve profitability by 3–5%.

5. Who Should Study This Deck

This deck is essential for MBA students preparing for analytical and data-driven case competitions, particularly those involving unit economics, multi-channel profitability, or quick commerce mandates. Students targeting consulting or strategy roles will find the sensitivity analysis framework and per-lever KPI structure directly replicable across any profitability case. Anyone building decks for IIM analytics clubs or data conclave formats will gain a strong template for handling messy datasets with intellectual honesty. For more winning frameworks across analytics, unit economics, and strategy, explore CaseBuzz, India’s leading case competition resource platform.

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