Structured analysis, financial modelling, and data-driven dashboards — the kind of thinking that sits behind every operational decision.
An Indian e-commerce platform plans aggressive expansion into Indore, Lucknow, and Jaipur. Evaluated financial viability across three scenarios — modelling revenue potential, COD fraud exposure, delivery costs, and CAC payback. Designed six operational levers and a phased rollout roadmap.
| Parameter | Tier-1 | Tier-2 Base | Tier-2 Best | Tier-2 Worst |
|---|---|---|---|---|
| Avg Order Value | ₹1,200 | ₹1,000 | ₹1,200 | ₹800 |
| Monthly Orders | 10M | 6M | 8M | 4M |
| COD Share | 40% | 70% | 50% | 90% |
| COD Fraud Rate | 2% | 5% | 3% | 8% |
| Delivery Cost / Order | ₹80 | ₹120 | ₹100 | ₹150 |
| CAC | ₹250 | ₹250 | ₹150 | ₹350 |
| Customer Retention | — | 6 months | 6 months | 6 months |
Yes, under Base and Best scenarios. Tier-2 delivers 80.3% contribution margin despite structurally higher delivery cost (₹120 vs ₹80 in Tier-1) and a 2.5× COD fraud rate. The Worst Case remains contribution-positive at 42.9% — meaning even in a downside scenario the unit economics hold. The critical risk is high COD share (90%) compressing margin through fraud. The mitigation priority must be fraud reduction before scale, not after.
Real-time risk model using pincode fraud history, device fingerprinting, address quality signals, and new vs. repeat customer behaviour. High-risk COD orders flagged for manual review or prepaid nudge.
Cap COD at ₹500 for first-time customers in high-fraud pincodes. Unlock progressively based on order completion history. Pair with ₹30–50 prepaid cashback to shift payment mix.
OTP-verified address for new COD customers. Google Maps + India Post API to validate deliverability. Reject unserviceable pincodes at order placement, not post-dispatch.
Dark store hubs in high-density Tier-2 zones — Vijay Nagar in Indore, Hazratganj in Lucknow. Last-mile from hub reduces delivery cost 20–30% vs. long-haul origin dispatch.
Volume-based agreements with regional 3PLs — Shadowfax, Dunzo, Blowhorn. Bundle delivery with D2C brands entering Tier-2 simultaneously to split fixed infrastructure costs.
Trust-score system — customers with 5+ successful deliveries and zero fraud get higher COD limits and faster dispatch SLA. Creates behavioural incentive for order completion.
A multi-sheet Excel performance system tracking 100 students across 10 mentors, 3 streams, and 5 cities. Weighted scoring, z-score relative grading, at-risk early warning, mentor effectiveness rankings, and admission channel correlation — built to drive academic interventions and mentor training decisions.
Final score = 0.8 × Academic Score + 0.2 × (Attendance% × 100). Academic component is a weighted average across 4 test types: Unit Test 1 ×0.25, Unit Test 2 ×0.25, Midterm ×0.50, Final ×0.50. Attendance is calculated as total days present ÷ (30 × active months).
Grades assigned by distance from cohort mean (μ) in standard deviations (σ): A = score > μ+σ, B = μ to μ+σ, C = μ−σ to μ, D = μ−2σ to μ−σ, F = below μ−2σ. Normalises performance across streams with different inherent difficulty — prevents grade inflation in easier cohorts.
A student is flagged At Risk if: Cumulative Score < 60 OR Attendance < 10%. Dual-trigger catches both academically struggling students and those disengaging — enabling two distinct interventions: academic support vs. reactivation outreach.
Effectiveness = 0.35 × (Avg Score/100) + 0.25 × Avg Attendance + 0.25 × (Satisfaction/100) + 0.15 × (1 − At-Risk%). The final term penalises mentors with high at-risk populations even if raw averages appear acceptable — revealing hidden performance gaps.
| Mentor | Students | Avg Score | At-Risk % | Satisfaction |
|---|---|---|---|---|
| M03 | 8 | 79.6 | 12.5% | 87% |
| M04 | 10 | 77.1 | 10.0% | 95% |
| M10 | 13 | 73.5 | 15.4% | 70% |
| M06 | 12 | 74.2 | 25.0% | 84% |
| M07 | 10 | 72.8 | 40.0% | 82% |
| M01 | 11 | 64.5 | 18.2% | 62% |
| Stream | Avg Score | Avg Attendance | At-Risk |
|---|---|---|---|
| Commerce | 74.2 | 78.4% | 7 |
| Science | 73.8 | 77.1% | 8 |
| Arts | 71.5 | 73.2% | 10 |
| ID | Mentor | Score | Attendance | Status |
|---|---|---|---|---|
| S065 | M04 | 69.2 | 0% | At Risk |
| S021 | M07 | 55.3 | 60% | At Risk |
| S035 | M07 | 49.5 | 53% | At Risk |
| S001 | M06 | 78.4 | 96.7% | Healthy |
| S052 | M02 | 91.7 | 90% | Healthy |
Referral is the highest-quality channel on both dimensions — top weighted scores and the lowest fee-default rate at 4.2%. Campus is the weakest — lowest scores and a 14.3% default rate, more than 3× Referral. This signals a misalignment between campus recruitment messaging and actual programme expectations. Recommendation: increase referral incentives, tighten Campus intake screening, and add a fee-commitment checkpoint at onboarding for Campus admits.