Download PDF
Case Studies > Quick Commerce Provider Automates Order Allocation to Scale 10 Mins Grocery Delivery Across Cities

Quick Commerce Provider Automates Order Allocation to Scale 10 Mins Grocery Delivery Across Cities

Technology Category
  • Functional Applications - Fleet Management Systems (FMS)
  • Analytics & Modeling - Predictive Analytics
Applicable Industries
  • Retail
  • E-Commerce
Applicable Functions
  • Logistics & Transportation
  • Warehouse & Inventory Management
Use Cases
  • Fleet Management
  • Predictive Maintenance
  • Real-Time Location System (RTLS)
Services
  • System Integration
  • Software Design & Engineering Services
  • Data Science Services
The Challenge
Due to rapid expansion and a growing customer base, this leading quick commerce provider faced challenges in managing massive order volumes. Additionally, growing dependency on manual processes posed scalability problems and impacted the visibility of financial transactions. The customer was facing the following challenges: Inability to rapidly scale delivery operations, Risk of system breakdown and availability when processing massive order volumes, Limitations in boosting (order) auto allocation volumes, Completely manual COD settlement, Inability to customize and configure driver payout operations, Lack of trust between managers and drivers regarding payouts.
About The Customer
Our customer is a leading quick commerce provider in India that is rapidly scaling its operations across Chennai, Bangalore, Mumbai, and Delhi NCR. It’s redefining on-demand deliveries by successfully executing 10-minute delivery of groceries. The customer operates out of 43 dark stores and is currently clocking 100,000 deliveries per month using its own fleet.
The Solution
We implemented a highly configurable and scalable on-demand delivery management solution. It enables delightful on-demand delivery experiences along with auto allocation of orders, driver shift management, dynamic en route order clubbing, live order tracking, driver app, and more that ensures efficient SLA management. Here are some key features of the solution: AI Enabled Auto Allocation Engine - Shipsy’s platform considers a pre-configured radius from a dark store while auto allocating tasks to drivers. The solution intelligently assigns deliveries to ensure equal distribution of tasks between drivers based on their existing workload. Driver App To Manage Deliveries - Shipsy’s driver app enables delivery executives to look into specific delivery-related customer preferences, calculate COD remittance, access the list of pending tasks, know when they logged, the number of hours they clocked, and do more. The application also ensures that a job is only assigned to drivers if their body temperature falls between the permissible limits. Also, Shipsy’s driver app is compatible with multiple old devices to ensure no delivery/driver-related data is ignored or missed. Driver Management - Shipsy’s helped the quick commerce delivery provider in optimizing its field force with driver profile enrichment, driver roster management, and shift and payout management capabilities. To ensure guaranteed minimum payment for delivery executives, Shipsy’s solution runs complex algorithms to determine a driver’s payout based on shift adherence during past weeks, days, peak hours, and more.
Operational Impact
  • Post-Shipsy’s implementation, the quick commerce provider successfully navigated its hyper-growth phase by automating core delivery processes and ensuring 10-minute deliveries across metro cities.
  • Proof-based and fair driver payout management.
  • Access to tracking the history of all orders for any period.
Quantitative Benefit
  • 99.7% of orders are being auto allocated.
  • Rapidly scaling on-demand delivery business by 25x in 6 months.

Related Case Studies.

Contact us

Let's talk!

* Required
* Required
* Required
* Invalid email address
By submitting this form, you agree that IoT ONE may contact you with insights and marketing messaging.
No thanks, I don't want to receive any marketing emails from IoT ONE.
Submit

Thank you for your message!
We will contact you soon.