I think time management is one of the places we have invested a lot in technology and AI over the last two years. What happens is when orders come in, you have a fixed number of orders but you also have a finite number of drivers so the real challenge is how do you decide which driver should be fulfilling which order. At a point there could be one order coming in for food, the other order is for Swiggy stores and yet another one for Swiggy go, so the problem space is basically what we call an assignment problem, where you have to assign a certain amount of work to a certain number of resources and you have to do it in the way in which you optimize on constraints. These constraints could be one, that you have to deliver the order within the time customer was promised, two, you also have to find the most cost-effective way of delivering and three, you also have to figure out whether there are certain rules by which you cannot assign a particular order; for example, I don’t want to assign somebody sitting in Kormangala an order that’s in Malleshwaram, because the driver has to travel across the city. So, you are also figuring out different constraints that go into an assignment. You get reduced to this basic problem which is essentially a mathematical one that states if I have a set of resources and I have a set of orders what is that unique combination that will optimize this set. We have built this technology which is a combination of AI-based models and optimization research (OR) based on math functions that run algorithms every two minutes in any given zone, it looks at all the orders that have come in, looks at all the drivers that are available and then start to predict which driver will become free in the next few minutes and which driver is actually available to take up a new order. Based on these predictions it will then match the set of items to the drivers, it will also include things like the driver’s skill, is a particular driver capable of delivering a package or Swiggy package pickup, and so on. All of this is happening at the moment as we speak, that’s the secret sauce. That algorithm is running and making sure that across India millions of orders are being fulfilled and customers are getting their dishes and products on time.
When it comes to voice texts, we believe long-term customers will move away from typing to interact with the devices in a more natural way just like we are speaking right now at some point in the future. Maybe in the coming times, there will be a virtual bot running this podcast and a virtual me answering; as long as we program the bots with questions and answers we don’t need to physically be present. I personally feel that technology will at some point fade away into the background and you will interact with the devices without really understanding its technology. Today, you take out your phone off your pocket and you physically have to type on it with your fingers which is natural, but if you see a kid using technology especially when I look at my kids, my daughter when she was 4 years old she was able to speak to Alexa and just commanded her to do stuff. For her, that was very natural versus having to go find a character on the screen and they type on it even though she knows how to read and write she just finds it difficult to go find letters and match them. But if given a complex situation, she will be able to do it better with Alexa. So, I think yes, the future is going to be about interactions like voice, maybe touch or maybe even physical presence, for example as you walk into the room the system detects you and the lights dim, the temperature sets to a certain value; in that world, you can imagine food delivery and convenience also being redefined. For example, you could be in a world wherein when you wake up Alexa will ask you, “you want me to reorder your food, your favourite breakfast from Swiggy?” You may say yes and then you go for a bath and then you come out from the shower, your food is ready, and it’s delivered via Swiggy. We do want to get into this place where we can understand voice. The challenge with India is that there are different levels of dialect and huge language differences, so from that perspective, it is a very hard and unsolved problem at the moment. We have begun a very early stage pilot within Swiggy trying out to understand voice calls that customers are making into our customer services and as we build that capability over time maybe we will get more sophisticated features like voice ordering.
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