Cloud kitchens: Can freight industry's hub-and-spoke model work for eat-in?

Topics kitchen | food | Freight

Cloud kitchens
For a long time, food delivery was a hyper local concept in the way it was perceived and managed, as the race was to serve warm food, tweaked to popular (and sometimes individual) preferences in the shortest possible time. But with the cloud kitchen model — that uses analytics to lower overhead costs, optimise real estate and other resources, and improve delivery time — gaining ground, many are hoping things will change for the better. But can a hub-and-spoke distribution model developed to transport passengers and freight and successfully applied to many manufacturing businesses be applied to the service industry? Specifically, will a centralised model of preparation and delivery work in a business like food that calls for a high degree of customisation? What is driving food aggregators like Swiggy and fast-food brands like KFC to jump on to the bandwagon? The answer boils down to one standout factor — cost.

“Cloud kitchens are nothing but restaurants without the frills involved,” says Ankur Pahwa, partner and national leader, ecommerce and consumer internet, EY. “The infrastructure requirements are bare in comparison to traditional dine-in restaurants. From an infrastructure standpoint the only thing that is required is some physical space and equipment for cooking. And some associated costs such as raw materials, chefs, and advertising.”

Data plays a key role in setting up the infrastructure and conducting the operations, which give the aggregators an early advantage. For instance, if an aggregator notices that the incidence of pasta ordering is higher in Greater Kailash in Delhi than anywhere else in the city, it might simply set up a kitchen on its own or by tying up with a brand without the latter having to set up a restaurant. “Let’s take the example of Fresh Menu or Rebel Foods. Rebel Food is a parent brand which operates multiple sub-brands such as Faasos and Behrouz Biryani. Say, in Delhi, they see demand coming in from all parts. So the first thing they would do is set up individual kitchens across multiple locations in the city,” says Ankit Mehrotra, CEO and co-founder, Dineout, explaining the procedure. Dineout has a software called Torqus which has a supply chain management module used by all the major cloud kitchens in India.

On the procedures, Mehrotra adds, “As a trend, biryani will sell more in some areas, rolls or Chinese would sell more in others. They have one centralised purchasing unit that acts as a store room and that store room distributes supplies to all the kitchens in the city. Now if you have to make biryani, the key ingredients would be rice and meat. So you purchase 100 kg each of the two items to produce 200-250 kg of the finished product which has to be distributed from various locations.”

As billing keeps happening at different locations, the software keeps subtracting that quantity from the central unit and once it reaches a certain threshold, say 20-30 kg, they know that they have to make another batch of biryani. “But it is possible that to make another batch, they fall short of ingredients. But our software also tracks the supplies in the kitchen in real time and it is connected with the vendor at the backend. For example, we have an integration with Amazon B2B. As soon as they spot the shortfall in supplies, they can order directly from the Amazon B2B dashboard,” says Mehrotra.  

In a restaurant chain, one has to keep records manually and call up vendors individually; here those processes are automated and can be performed simultaneously, he adds.  

The rise of cloud kitchens is also a result of the fact that franchisee-owned kitchen models haven’t been very successful locally. The reason, says Mehrotra, is that restaurant brands want uniformity which is difficult to achieve with Indian foods, across multiple locations.

Flirtation with the cloud kitchen model was started in a way by brands with a storefront model such as McDonald’s and Domino’s that serviced a large area with a few outlets serving as the kitchens. As the model evolved and improved, more players decided to take a bite.

Anil Talreja, partner, Deloitte India, says in the cloud-based model that one can foresee demand. This ensures wastage, a problem with many restaurants that sometimes prepare extra food but aren’t able to create demand, is minimised. “The cloud kitchen works primarily on the principle of bringing the consumer to the food and hence is more effective,” he sums up. For a brand or a small restaurant, opening a cloud kitchen on its own won’t make much sense even if it has some idea about the demand. “That opens up the possibility of cannibalism — if one ties up with an aggregator and the aggregator knows the demand trends, it would displace the restaurant in no time,” says Mehrotra. In other words, delivery has to be under its own control.

The low capital expenditure means the potential of profitability from each kitchen is more. In a blog post published in August, Jaydeep Barman, co-founder and CEO, Rebel Foods, claimed that revenues from restaurants grew 4X over the past 24 months, while the kitchen footprint only grew by 20 per cent over the same period. “Our kitchens are becoming profitable within three months and our investment (capex) in them is paid back in less than 12 months,” the post added.


  • Simply put, a cloud kitchen is a kitchen which helps branch out distribution without setting up a dine-in restaurant that has considerable overheads, rentals and labour costs
  • Rise is primarily attributed to online delivery aggregators and more millennials entering the consumer mix 
  • India’s online food delivery market is expected to touch $5 billion by 2023 and nearly a fifth can come from cloud kitchen led deliveries, say recent reports
  • There are two kinds of cloud kitchens: Those who do not have any storefronts but are known since they serve the customer directly, say a Faasos or InnerChef, or anonymous ones run by the aggregators themselves or leased out to third parties

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