Technology, customer experience, and a streamlined supply chain are the key differentiations for a delivery kitchen to thrive or lose its foothold in a crowded space
Cloud kitchen model also reduced the cost of starting up a food brand, and many first-time restaurateurs embraced the model. However, only a few managed to survive and scale with the model during the period
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The way we eat from restaurants has fundamentally changed in the last couple of years, and that has thrown up a lot of questions for the industry. Earlier, most restaurants would see a small part of their business coming from delivery. Today, most of the established restaurants see an increasingly higher share—even the majority share in many cases—coming from customers ordering in. In the new normal, the Indian foodservice delivery market is expected to double in value to $13 billion by 2025 (according to a RedSeer report), growing over 30 percent CAGR between 2021-26 (according to a report by Motilal Oswal Financial Services), growing much faster than the overall industry (including dine-in). This changing trend has also led to the rise of ‘cloud kitchens’. According to a report by RedSeer Management Consulting, cloud kitchens are set to be a $2 billion industry in India by 2024, up from $400 million in 2019.
The answer lies in technology. Smart cloud kitchens utilise technology to solve the above issues and help create memorable brands. There are many aspects that can leverage tech—culinary innovation and product consistency, kitchen management technology, and supply chain. At Rebel Foods as well, we’ve been focusing on building the ‘Operating System’ which allows brand-partners to not just scale up fast, but scale up smart through a tech-enabled network.
Similarly, Machine Learning (ML) and open data are key tools that restaurants could use to enable access to real-time and aggregated data visibility, which further helps to make faster decisions in real-time such as order throttling, inventory/stock management, product availability, minimising order delays, etc. and many other elements which are important to great customer experience. This should be empowered with constant improvement and finetuning the recommended models, thereby ensuring customers find relevant products faster and saving their precious time. Working with various ML models like demand/supply forecasting, recommendation & RFM segmentation for enhanced customer experiences, feedback analysis to improve CX, storefront design for faster discovery, rider auto-allocation to bring cost efficiency, delivery predictions to enhance CX, etc. will help solve varied data science problems, some of which are very specific.
There is little doubt that customers are moving towards ‘ordering in’ than ‘going out’ quickly, and this trend will only accelerate in the future. While cloud kitchens can help in enabling this trend from the supply-side efficiency perspective, they don’t necessarily solve many other challenges. To build strong food brands with a consistent experience, it is critical to utilize technology across various operational aspects. It may be prudent to focus on making it smart before making it large.
The writer is a co-founder at Rebel Foods