Quick commerce is the flavor of the season. And, it’s a delicate topic. The first question that comes up is, do we even need anything that urgently? When is the last time you wanted a toothpaste within 15 minutes? Well, there will be naysayers, but the entire quick commerce trend has something larger at play.
Role of artificial intelligence
When it comes to delivery and parcel management, a lot of the processes were heavily manual until a couple of years ago. Artificial intelligence (AI) and machine learning (ML) also seemed like buzzwords, but massive strides have been made in the industry in the last few years.
AI in the quick commerce use case is basically tracking billions of location data points and coming up with algorithms that account for several hundred variables to give the best possible delivery routes.
Imagine hundreds of orders pouring in from a gated community for various items ranging from furniture to toiletries. These orders are either placed on a super app or directly with the brand. With platform commissions rising, more and more brands prefer customers to buy directly from their website. And, when this happens, managing and optimizing driver capacity becomes critical to keep delivery costs low. This is where route planning and advanced route optimization along with auto allocation of orders to drivers comes into play. And, all of these technologies have their base in AI.
Use cases for AI and ML in delivery management
There are several areas where modern developments in AI and ML are being implemented to optimize and automate delivery management. Some of the key areas are:
1) Route planning and route optimization
There are thousands of orders and hundreds of possible routes that can be taken by numerous permutations and combinations of drivers (inhouse or third party). This is an incredibly complicated problem to solve for efficiency. And, this is where AI is implemented at scale to give brands the most efficient route plan for the best order management.
2) Visual inspection
AI is also an important element when it comes to in-scan and out-scan products, determining the type of product that is being packed or shipped, and also in use cases like 3D packing optimization. Information is read by a scanner or a camera and AI algorithms determine the next step to be taken for the organization in accordance with the pre-determined rules.
3) Analytics for dynamic pricing
When it comes to selecting the best carrier according to price and time, brokers are being replaced by automatic algorithms that help a company picks the best possible carrier for operational efficiency and reduced delivery costs.
4) Customer service chatbots
There are AI-driven chatbots being used across the supply chain communication funnel. For instance, there are several FAQs a customer might have with respect to an order which a brand can answer by using intelligent chatbots. There is also a communication channel usually in the form of an app between the driver and shipper. A lot of time can be saved with the use of AI.
The future of quick commerce
So, the real question to be asked here is not whether 15-minute deliveries should be given or not, but rather do we have a robust and flexible supply chain that can cater to such demands? Last-mile delivery is the most expensive leg of the delivery chain, and advancements in this field will basically help to drive enormous efficiency over here. The play with dark stores, parcel lockers for pickups and such are trends that point toward a future where there will be several hubs created in high-population density urban areas. These hubs, which are primarily a logistical exchange point or hub, will play a pivotal role in enabling the entire quick commerce trend. And, once we start moving toward this, 15-minute deliveries would be possible and may even become the norm.
The focus for the entire quick commerce depends on delivering value to the end customer and building systems that can handle situations like the pandemic. Enterprises across the globe are undergoing rapid digital transformation journeys and AI is playing a key role in building robust supply chains and delivery management systems at scale.
