The upward mobility and evolving expectations of customers especially Gen Z expect their orders to be delivered in less than 30 minutes. This has put immense pressure on Quick-Service Restaurant (QSR) chains, driving them to enhance their operations as traditional manual processes for driver allocation and logistics planning are proving insufficient in the face of these evolving customer demands.
The global Last-Mile Delivery market, estimated at $32 billion in 2020, is projected to reach $53.4 billion by 2027 due to the boost in online food and grocery delivery.
As this demand intensifies, QSR chains find themselves struggling to fulfill these heightened expectations, leading to delayed deliveries. The consequence of delayed deliveries has led to a notable increase in wasted food, with approximately 15% of prepared foods being discarded due to poor temperature control and delayed dispatch. Traditional approaches are no longer sufficient, prompting the industry to explore innovative solutions.
To navigate these challenges, the QSR industry is turning to AI-enabled delivery technology as a solution. Automated order assignment/auto-allocation and First-In-First-Out (FIFO) order assignment – features in logistics planning, have become crucial elements for QSRs trying to change how they operate.
Automated order assignment, driven by AI, streamlines the allocation of delivery tasks by intelligently assigning orders to delivery agents based on factors such as proximity, availability, and capacity. This not only ensures optimized delivery routes but also expedites order fulfillment, thereby elevating customer satisfaction.
Furthermore, when integrated with FIFO order assignment, automated order assignment becomes even more powerful. FIFO ensures that the oldest orders are delivered first, reducing the risk of food spoilage and ensuring that customers receive their meals fresh and hot. By combining these two features, QSR chains can significantly improve their overall operational efficiency while guaranteeing freshness.
But how exactly do these AI-enabled technologies elevate customer experience and ensure food freshness? Let’s break it down.
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Real-time Data Analysis:
AI-driven technology enables QSR chains to analyze real-time data, such as weather conditions, traffic patterns, and order volumes. This information assists in dynamic route planning and ensures that deliveries are made under optimal conditions, preserving food quality.
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Predictive Analytics:
By leveraging predictive analytics, QSR chains can anticipate peak hours, allowing them to allocate additional resources during busy periods. This proactive approach ensures that even during high-demand times, deliveries are made promptly, maintaining the freshness of the food.
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Customer Preferences:
AI-enabled systems can analyze customer preferences and behavior, facilitating personalized delivery experiences. This includes considering factors like preferred delivery time slots and customizing delivery routes accordingly, ensuring that customers receive their orders at their convenience.
McDonald’s, KFC, Pizza Hut, Starbucks, Burger King, among others, have leveraged AI-enabled delivery technology across North America, South America, Europe, the Middle East, and Southeast Asia. By implementing AI-driven solutions, these brands have not only met the challenge of reducing delivery times by 35% but have also positioned themselves as leaders in operational excellence. The system’s ability to make decisions regarding the use of the current fleet or external carriers further enhances flexibility and efficiency in delivery logistics. This ensures that QSR chains can adapt to varying demand levels and dynamically allocate resources, optimizing their operations and minimizing delivery times.
The Article was written by Dhaval Thanki, EVP- LogiNext
