Selling groceries and fast-moving consumer goods (FMCG) online can be a daunting task in India. But there is one startup which has cracked it and set the bar. It has succeeded at what was earlier thought to be a near impossible feat. Yes, we are talking about Bigbasket, which has emerged as one of India’s biggest online food and grocery companies. Eight years down the line, the grocer is known for variety, value, punctuality and amicable staff.
The march to the top has been led by a mishmash of technology, strategy and leadership, points out Rakshit Daga, Vice President and Chief Technology Officer (CTO) at Big Basket. He says that due to the nature of business, they always have a lot of interesting business problems to solve such as perishable inventory management, fleet management, delivery route optimization, building a web and application platform for scale, fraud detection, etc. For all this, there has to be a robust technology infrastructure ably supported by the backend platform.
“The role of technology has to be to facilitate easy experimentation. For this, the backend platform has to be agile and responsive. It should be easy to experiment with as there can be different approaches to solving a problem,” he says.
He informs dynamicCIO that the company is doing a lot as far as building an agile backend is concerned. When I ask about the specific optimization problems that he is looking to solve with the help of technology, he talks about how he is currently looking to improve on the picking process in the company’s warehouses. He enumerates the challenges that such a problem poses.
“When a customer order comes in, there is a specific cost in terms of time and manpower. Moreover, there are many other questions that have to be addressed. Do you pick one customer’s order at a time? Do you pick multiple orders at a time? How much does a picker need to walk within a warehouse? Is he in a healthy working environment? Is he completely tired with a lot of manual work? What kind of automation needs to be there? There are multiple algorithms that would potentially do the job but which one to use and where to use can be crucial for the business. We use technology to solve them,” he explains.
The tech team, under his leadership, has made the core decision to create a platform on which they are able to switch algorithms quickly.
“In our business, we want to experiment with a number of ways of doing deliveries, picking, storing in a warehouse, etc. There is no right answer. We have different answers to different optimization problems. We are making a conscious choice to invest in a platform where switching around solutions is not so hard. It is built in such a way that it is not hard coded into the system. Otherwise, any change that happens will mean a lot of work,” says Daga.
The company is also investing in a deep supply chain where procurement is directly made from the farmers and delivered directly to customers. The algorithms analyze data and help in ensuring that the delivery is made within the slated time frame while keeping costs to the bare minimum.
“We will continue investing in a lot of areas. We are driven by the fact that we always want to solve problems by leveraging technology. In case solutions already exist then we try to further optimize them,” concludes Daga.