<img height="1" width="1" style="display:none" src="https://www.facebook.com/tr?id=233424683662236&amp;ev=PageView&amp;noscript=1">
Quick Service Restaurant Case Study Book
Quick Service Restaurant Case Study Text

ON-DEMAND DELIVERY MANAGEMENT

One of the largest quick service restaurant chains with sales of more than $24 billion from more than 15000 restaurants across the world looks to establish dominance in their on-demand delivery management module with expert delivery route planning and optimization.
 

A CASE STUDY ON ON-DEMAND DELIVERY SERVICE

On-Demand Delivery Management through Mobile Field Service Optimization

The client handles upwards of 15 million orders a day, 4.5 million of which are delivered to the customers, using around 75,000 delivery personnel daily. The company is one of the largest Quick Service Restaurants (QSR) in the world. They function in the Fast Food Hamburger Restaurant (FFHR) section of the QSR segment. They want to strengthen their mobile field service to ensure on-time food deliveries.

The client wants to expand its customer base by creating a dependable on-demand delivery management system. Their business model requires daily iteration and planning to stay ahead of the demand, even factoring in situational spikes in sales.

With LogiNext on-demand delivery management software, the client could attain their primary growth targets with a clear boost in customer retention ratios.

Download Case Study

  • Route Planning Software

    Leveraging machine learning to decipher historical movement and plan future routes better with more accurate Estimated Time of Deliveries (ETAs).
  • Delivery Route Optimization

    Optimizing delivery routes for on-field field service management to bring down the reaction time for the restaurant managers, in the case of delays.
  • Mobile Field Service Management

    Effectively manage the mobile field service to understand movement potential of all resource personnel and fleets and track their deliverables.
  • Automated Resource Allocation

    Effectively solve the problem of low decision times by automating the process of resource allocation across branches and mobile field workforce.
  • Service Time Optimization

    Optimize service time to precision to ensure a balance between quality and speed while managing the multitude of on-demand deliveries.
  • Dynamic ETA Calculation

    Effective delivery route optimization enabled real-time calculation of the estimated time of arrival (ETA) visible to the client and the customer.