Delivery Workflow Automation
The first step towards BYOC efficiency
Introduction: History and Background
Burgerbar + UberEats - BYOC Project
December - Project Pilot
Store crashed under orders. No driver time tracking, low efficiency. Poor bag selection and route planning sent drivers to opposite sides of the map in single trips. Uber app underutilized, causing excessive store calls.
Orders canceled, satisfaction and ratings declined.
Second Week Until Now
Increased drivers based on traffic. Limited to 2 bags per ride. Address-based bag selection minimizes trip times. Route planning before departure. Paper tracking implemented. Uber app usage increased, reducing store pressure.
Store handles more orders, increased revenue, improved customer satisfaction.
The Problem
Bag Selection
Manual selection leads to suboptimal groupings and wasted time.
Route Planning
Drivers copy addresses one by one, creating inefficient routes across opposite sides of the map.
Paper Records
Manual tracking prone to errors, loss, and difficult to analyze.
Time Estimates
Manual estimation without data-driven insights leads to inaccurate delivery windows.
Additional Burden
Floor employees are pulled away from primary responsibilities to help with dispatch, creating bottlenecks.
The Solution
Intelligent Batching
Algorithm-based batching considers geographic proximity, delivery windows, and route optimization.
Automated Route Planning
Optimized routes and Google Maps navigation links eliminate manual address copying.
Digital Tracking
Automatic digital tracking provides real-time visibility and audit trails.
Data-Driven Time Estimates
Automated estimation based on historical data and real-time conditions improves accuracy.
Result
Floor employees are freed from dispatch tasks, drivers work efficiently with optimized routes, and the process becomes scalable and error-free.
Development Overview
Development organized into logical sections. Total estimated time: 119-153 hours (~3-4 weeks full-time).
| Section | Estimated Hours | Complexity | Key Deliverables |
|---|---|---|---|
| Database Foundation & Schema | 11-14 hours | Medium | Database schema, migrations, type-safe models |
| Uber API Integration & Webhooks | 17-21 hours | High | Webhook endpoints, authentication, order ingestion |
| Batch Management System | 21-25 hours | High | Batch creation algorithm, order assignment logic |
| Driver Management & Pickup Workflow | 14-17 hours | Medium | Driver system, pickup flow, QR codes |
| Order Status Tracking | 11-14 hours | Medium | Status updates, webhook handlers, state management |
| Special States Handling | 8-11 hours | Low-Medium | Special states UI, workflow handling |
| UI/UX Enhancements | 11-14 hours | Medium | UI improvements, responsive design, error handling |
| Testing & Quality Assurance | 11-14 hours | Medium | Test suite, bug fixes, performance optimization |
| Deployment & Infrastructure | 8-11 hours | Medium | Production deployment, server setup, monitoring |
| Documentation | 6-8 hours | Low | API docs, user guides, deployment guides |
Total Estimated Time: 119-153 hours (~3-4 weeks full-time)
Numbers: Costs and ROI
Current workflow inefficiencies cost significant time and money. Automation eliminates these costs.
Time Savings Analysis
Manual process takes 5-10 min/hour (lower) to 10-30 min/hour (upper) per driver on: bag selection, route planning, paper records, time estimates, and floor employee assistance.
Per Location - Lower Range
Per Location - Upper Range
Multiple Locations (3 Locations Example)
Lower Range
Upper Range
Key Assumptions
Wage rate €20.00/hour, 6-hour shifts, 2-3 drivers per shift. Costs represent the price per location for the workflow that automation eliminates.