unifided-project
🍽️ SkyCity Auckland — Multi-Channel Restaurant Profitability Analysis
📌 Project Overview
This project delivers a comprehensive multi-channel profitability analysis of SkyCity Auckland’s Restaurants & Bars portfolio. It examines the financial performance of 1,696 restaurant branches across four service channels — In-Store Dining, Uber Eats, DoorDash, and Self-Delivery — across four Auckland subregions.
Core Finding: Uber Eats generates 39.6% of total revenue ($30.8M) yet delivers only $152/month average net profit per restaurant (1.1% margin). In-Store Dining generates 26.9% margin — nearly 25× higher. 538 restaurants (31.7%) are actively losing money on both aggregator platforms.
🔗 Project Links
| Resource | Link |
|---|---|
| 🌐 Live Dashboard | https://rahulgoudk.github.io/unifided-project/ |
| 📁 GitHub Repository | https://github.com/Rahulgoudk/unifided-project |
| 📄 Research Paper | View in Repo |
📊 Dashboard Features
The interactive HTML dashboard (index.html) includes:
- 4 KPI Cards — Avg net profit and margin % per channel at a glance
- Channel Profit & Margin Charts — Side-by-side bar charts comparing all 4 channels
- Revenue Distribution Donut — Showing the revenue vs profit paradox visually
- Loss-Making Restaurant Counter — 538 restaurants losing money on aggregators
- Tabbed Cuisine / Segment / Subregion Analysis — Grouped bar charts + data tables
- Revenue Waterfall — Cost decomposition per $100 of revenue per channel
- What-If Scenario Modeler — Slide commission rate and delivery cost to see profit impact in real time
- Strategic Recommendations Table — Channel matrix with risk levels and actions
📂 Repository Structure
unifided-project/
│
├── index.html # Interactive dashboard
├── SkyCity_Auckland_Channel_Profitability_Research_Paper.docx # Full research paper
├── 1774164201722_SkyCity_Auckland_Restaurants___Bars.csv # Source dataset
└── README.md # This file
📈 Key Findings
| Channel | Avg Net Profit/Month | Net Margin | Loss-Making Restaurants |
|---|---|---|---|
| 🟢 In-Store Dining | $2,257 | 26.9% | 0% |
| 🔵 Self-Delivery | $2,139 | 22.9% | 0% |
| 🟠 Uber Eats | $152 | 1.1% | 31.7% |
| 🔴 DoorDash | $89 | 1.1% | 31.7% |
By Business Segment
| Segment | In-Store | Uber Eats | DoorDash | Self-Delivery |
|---|---|---|---|---|
| Cafe | $3,127 | $1,113 | $610 | $2,632 |
| QSR | $2,401 | $1,058 | $577 | $2,620 |
| Ghost Kitchen | $1,148 | $2,781 | $1,529 | $3,593 |
| Full-service | $1,599 | –$3,152 | –$1,706 | $379 |
🧠 Methodology
- Profit Calculation Validation — Verified net profit formulas across all channels
- Channel Margin Analysis — Computed absolute profit and margin % per channel
- Cost Component Decomposition — Broke down COGS, OPEX, Commission, and Delivery costs
- Commission Sensitivity Analysis — Modelled profit at commission rates from 15%–45%
- Cuisine & Segment Analysis — Identified margin-resilient vs margin-fragile categories
- Profit Volatility Assessment — Flagged loss-prone channel strategies
Profit Formulas
In-Store Net Profit = Revenue × (1 – COGSRate – OPEXRate)
Uber Eats Net Profit = Revenue × (1 – COGSRate – OPEXRate – CommissionRate)
DoorDash Net Profit = Revenue × (1 – COGSRate – OPEXRate – CommissionRate)
Self-Delivery Net Profit = Revenue × (1 – COGSRate – OPEXRate) – SD_DeliveryTotalCost
🗂️ Dataset Description
| Column | Description |
|---|---|
| RestaurantID | Unique branch identifier |
| CuisineType | Food category (Burgers, Pizza, Chinese, Indian, Japanese, Thai, Chicken, Kebabs) |
| Segment | Business model: Cafe, QSR, Full-service, Ghost Kitchen |
| Subregion | CBD, North Shore, South Auckland, West Auckland |
| AOV | Average Order Value ($29.79–$47.23) |
| COGSRate | Cost of Goods Sold % (20%–40%) |
| OPEXRate | Operating expenses % (20%–55%) |
| CommissionRate | Aggregator commission (avg 30%) |
| DeliveryCostPerOrder | Self-delivery cost per order ($0.89–$5.31) |
| InStoreNetProfit | Net profit from in-store dining |
| UberEatsNetProfit | Net profit from Uber Eats orders |
| DoorDashNetProfit | Net profit from DoorDash orders |
| SelfDeliveryNetProfit | Net profit from self-managed delivery |
Total Records: 1,696 restaurant branches
Total Revenue (all channels): $77.7M
Subregions: CBD, North Shore, South Auckland, West Auckland
💡 Strategic Recommendations
- Scale In-Store & Self-Delivery — Both channels produce 0% loss rate and 22–27% margins
- Renegotiate Aggregator Commissions — Reducing commission from 30% → 25% adds ~$458/month per restaurant ($9.3M portfolio-wide annually)
- Segment-Specific Strategies — Full-service restaurants should exit aggregator channels; Ghost Kitchens should lean into them
- Cuisine-Level Optimisation — Chicken Dishes and Kebabs/Mediterranean need menu price adjustments to offset commission drag
- Implement KPI Monitoring — Track Net Profit per Order, Channel Margin %, and Commission Drag Index monthly
🛠️ Tech Stack
- Dashboard: Vanilla HTML, CSS, JavaScript + Chart.js
- Analysis: Python (data processing), statistical aggregation
- Document: Microsoft Word (.docx)
- Deployment: GitHub Pages
👤 Author
Rahul Goud K
Project submitted to: SkyCity Auckland · Government Stakeholders
Dataset: SkyCity Auckland Restaurants & Bars (2024)
High order volume is not a proxy for profitability. True business sustainability depends on unit economics, margin discipline, and channel governance — not sales growth alone.