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Case Code: LDEN148
Case Length: 13 Pages 
Period: 2014-2019   
Pub Date: 2019
Teaching Note: Available
Price: Rs.300
Organization : Swiggy
Industry :Foodservice
Countries : India
Themes: Entrepreneurship/ Business Models
Case Studies  
Business Strategy
Human Resource Management
IT and Systems
Leadership & Entrepreneurship

Swiggy`s Delivery Model

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In order to ensure that food was delivered on time, Swiggy introduced live-order tracking. Like other on-demand delivery startups, Swiggy too integrated the Google Maps application program interface (API) which let the customers know where their order was and how much time it would take for the order to be delivered. That allowed them to track the DE’s current location with accuracy.

Swiggy aimed to offer an integrated ordering solution by deploying multiple proprietary applications, including a vendor management application provided to restaurant partners and a delivery application powered by routing algorithms, provided to driver partners. When a consumer placed an order with Swiggy through the iOS or Android applications or website, the order was immediately transmitted to the merchant and the DE, based on availability and distance from the restaurant...

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Swiggy earned some part of its revenues from commissions. It charged a 15% – 25% commission on the order bill amount received by the restaurant. This commission was calculated on the full bill amount which was inclusive of the Goods and Service Tax (GST) charged over and above the menu price. However, the company often aimed to get restaurants to be available on Swiggy exclusively. For this it gave certain benefits to the restaurants like greater visibility (with the restaurants appearing on the application more number of times) and its commissions sometimes being cut by 2-3%...


While creating an exhaustive and hassle free delivery model, Swiggy faced challenges on a daily basis from the DEs and restaurant partners. The first kind of challenge for Swiggy was to fix the problem of restaurant listing and the delivery time promise. Whenever a customer opened the Swiggy application, a query was sent to the delivery system regarding the serviceability of restaurants to the customer and the expected time of the order from the potential restaurant. But the expected time was difficult for many of the restaurants to estimate due to their geographical locations...


However, Swiggy cracked the delivery challenges and brought changes in its existing environment by taking certain measures. To ascertain and resolve the problem of delivery timing, Swiggy brought in the technique of Just in Time (JIT) Assignment (a way to minimize the time spent by the Delivery Executive at the restaurant waiting for the food to be prepared” ). Through JIT, Swiggy earmarked the DE available nearest the restaurant to pick up the order and service its customers. The engineers at Swiggy came out with a new model. Under this model, when the order was received, rather than dispatching the DE immediately to the restaurant, Swiggy earmarked him for the delivery...


In FY 2018, Swiggy’s revenues rose to Rs 4.42 billion up from Rs 1.33 billion in FY 2017, as it continuously expanded its geographic footprint across the country. Swiggy had expanded its operations from seven cities in March 2017 to 12 by March 2018, even as order volumes had increased by three times during the period. Swiggy ended September 2017 with more than 21 million orders in absolute terms. ..


In June 2019, Swiggy announced its entry into the home chef space with the launch of a new venture, 'Swiggy Daily', an application to give consumers access to a variety of simple home style meals prepared by home chefs, tiffin service providers, and organized vendors. “Swiggy Daily” was expected to list over 30 options for every meal. The platform would include meal options from a mix of organized vendors like Homely,...


As of 2019, Swiggy was looking to further strengthen its tech efforts and focus on an AI driven delivery platform for hyperlocal and on-demand delivery. According to Dale Vaz (Vaz), Head of Engineering and Data Science at Swiggy, “The first big tech challenge was moving from a food tech stack to a platform in the hyperlocal category. Today, even though we support food, we should able to do the same for other things like buying medicines, grocery, pet food, etc. With our AI-first approach, we are looking at how can we replace and rethink Swiggy products, and replace some of our hard-coded system assumptions with intelligent AI-based systems. We are doing this across the board to look at how Swiggy can become an AI-first product. Last year, we hired multiple PhDs from international universities, and tenured people from places like IBM and GE Research as senior scientists.” ...