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Tough competition and difficult market conditions have led many organisations to downsize their business, then how is a 2011 established firm winning the market ? Big Basket’s prowess is the right strategy; market knowhow; customer centricity and yet another significant facet, “the right technology” points out Rakshit Daga, Vice President & CTO, Big Basket. “We have to understand that the market is absolutely massive and the overall Indian grocery market is US$ 500 billion, of which a couple of billion dollars are online right now.
There is a huge room for the market to grow in the online domain. And today the challenge is not really to grow the market, but doing it in a way which creates a sustainable business,” he adds.
A big tech basket
Algorithms and advanced analytics are manoeuvred well in the company for seamless operational efficiency. “We are re-architecting the whole supply chain and the platform for scale by leveraging some of the cutting-edge technologies. There is a conscious call to make a platform that is plug and play in nature. The emphasis is on the ability to experiment with different algorithms,” informs Daga.
At Big Basket, hefty investments are made to build solutions which allow possibilities like changing the routes for the delivery fleets. “A cart of the customer consists of various categories of products including high value, low value, or perishable products which are stored at different warehouses in a city or sometimes different cities altogether. The right way to assemble the cart is a combination of technology plus the individual worker on the ground who is actually putting the order together,” explains Daga.
In addition to this, there are investments on AI and ML, which are used aggressively for exercises like determining what should be recommended to the customers. “The technology helps to ensure that the quality of the recommendations is good and the potential of conversion with respect to the customers is better,” he says. “It also helps to understand how a delivery executive gets the best timings for a certain route, are done well with the aid of AI. However, even for AI and ML there is no one right answer, there are multiple possibilities and several new technologies keep emerging from time to time. So the best approach is to create a platform where you are able to rapidly explore all the possibilities to arrive at a conclusion on one solution that works best for the ecosystem,” Daga adds.
Hyper-personalisation helps to trace the buying pattern. It lends the ability to offer management right at the individual level. The company’s Smart basket feature uses AI and algorithms to understand the customer’s likeliness towards purchasing certain products and this accelerates the overall buying experience of the customer.
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“With Internet of Things, we track delivery of certain products such as ice-cream, whereby it is important to have the right temperature at the point of delivery. There are devices to server communication like location tracking in all the delivery routing that we do. There are pressure sensors deployed in vending machine which helps in estimating which products are sold and in what quantity,” he mentions.
Big business outcomes
“With the right technology deployment or the proper supply chain algorithm the best outcomes is that every time you want to experiment with the supply chain model, you do not have to actually write a new code or create a new technology. If you have a platform that is flexible and scalable you will be able to experiment with different supply chain models,” he says.
The platform that Daga and his team is envisioning would allow for faster go to market for different business needs, easier maintenance and lower cost of change. “This is of paramount importance since we have realised that this is one business where change and experimentation is a constant. So the technology platform has to really enable this. And then business as usual is a large part of the whole exercise, how do you keep running the platform in a stable and a scalable way as the business grows and as this problem is solved this helps in speeding up new feature roll outs, so all of this goes hand in hand,” he stresses.
Data centre
Storage essentially being an important part of the businesses is well leveraged. And referring to storage does not only mean the over 1800 varieties of products which Big Basket sells but also intelligent data, which is as valuable.
“We are completely running on a public cloud. It is working well as we do have to worry about the hardware,” says Daga.
“In our business, scaling up and down is very important; the required capacity during peak time can be 10 times the average capacity. Most of our infrastructure is based on our ability to scale up and down based on the demand; hence cloud is the better option,” he says, adding that for autoscaling, running Kubernetes is a key part of the strategy. Using Kubernetes helps scale seamlessly and all the microservices run on kubernetes.
Challenges
A big challenge was that as the company scaled up rapidly, the technology platform was not competent. “It was the so called monolithic architecture and we realised that we need to invest in an architecture which breaks up the various components of the technology platform into independent pieces. Thus, we did put in a lot of investments on the micro services stack. We also realised that as we grew to become the largest online grocery provider, we should invest in an asynchronous programming technology which allows processing more request but at the same hardware cost,” he emphasises.
Daga concludes by saying, “There is a major emphasis on creating an ecosystem that is keen to contribute to the industry forums and also bring back the leanings home.”
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