Smart kitchens: How AI is revolutionising food waste management in restaurants

When it comes to food waste, it has been a long-standing global issue for years. Commercial food waste is a significant global issue, impacting both the environment and economic efficiency. Food waste occurs at multiple nodes in a food lifecycle, right from farms to wholesale stores, retails store to fine dine restaurants and cafeterias. This article is focussed on restaurants and cafeterias.

Food waste is increasingly becoming a problem for restaurants, costly in both financial and environmental terms. First let us understand the challenges with the restaurants business with respect to food wastage. The fundamental challenge is to adhere to the standardised process and protocols for food management at restaurants. There are various factors which contribute to this food waste including overproduction, improper supply chain co-ordination, improper storage causing spoilage, inefficient inventory management, lack of know-how to re-purpose food ingredients and inaccurate demand forecasting.

With Artificial Intelligence (AI) impacting every industry, AI has also opened new opportunities for restaurants to reduce their food waste and contribute to environmental sustainability. In this article we will explore how AI is set to revolutionize food waste management in specifically restaurants.

In first place, it is important to understand the factors affecting overall food lifecycle, the restaurants should consider analyzing the historic data for the following aspects:

• Customers preferred food type and food portion size

• Seasonal food items and its likeliness among the customers

• Long weekends

• Festive months

• Weather / seasons

• National events including sports, elections

AI is emerging as an innovative solution to cater the food waste management. Restaurants could leverage AI technologies in the following three phases:

Past - Analyse the past data such as customer preferences for specific food category, seasonal performance, volume of customers incoming / ordering on festive days, long weekends or during national events such as sports, politics, etc.

Present - Real-time monitoring capabilities of AI help businesses to quickly recognize and address issues as they arise. For eg cameras and sensors installed in food kitchen helps in real time monitoring of the inventory and suggest for dynamic pricing of the food dishes, offer less popular dishes at offers, suggesting customers for dishes with seasonal food items to minimise the wastage. AI systems can be implemented to appropriately size recipes and automate menu item rotation both helping in utilising excess ingredients used.

Future – Predictive analytics algorithms could be used to predict future trends and events which, in turn, will help the restaurants to forecast the future inventory needs. AI algorithm could be trained on past data of including the customers purchasing style, events, most preferred food category, seasonal requirements, thus forecasting a restaurant’s need accurately.

To cater for this space, many start-ups have emerged offering innovative solutions to the industry including Foodsi, GreenBytes, Freshflow, Positive Carbon, among others worldwide. Large companies like Yum Brands, the parent company of Taco Bell, Pizza Hut, KFC, and Habit Burger Grill, have already integrated “AI-powered” future for its fast-food operations to enhance every aspect of its restaurant operations. Another use case is of IKEA deploying the AI tool developed by Winnow across its 23 stores in the UK and Ireland.

In my opinion, adoption of AI will have major contribution to larger hoteliers working on franchise model and it will be very effective in inventory management. By collecting and analyzing the data from individual restaurants of these large hoteliers can help in identifying broader trends in food consumption, this information when shared with the food suppliers, in turn helps in optimising production and distribution processes, further minimising waste throughout the food supply chain.

For deploying the AI technologies, initial investments are significantly high, which seems difficult to come from smaller established restaurants. I see that the outlook with the integration of these technologies in the existing workflow will be contributing to the industry both financially and environmentally.