How AI Can Help Minimize Food Waste in Commercial Kitchens

KEY TAKEAWAYS

Commercial kitchens encounter substantial challenges due to food wastage, leading to significant economic and environmental repercussions. Traditional manual methods to address the issue have proven insufficient. However, the integration of AI technologies offers great promise in efficiently and sustainably reducing food waste. By implementing AI solutions, commercial kitchens can effectively combat the problem of food wastage and mitigate its adverse impacts.

Commercial kitchens catering to paying customers have long grappled with the issue of food waste, a problem that holds significant implications from various angles. From a financial perspective, restaurants in the United States alone generate a staggering 22-33 billion pounds of food waste annually, with associated costs amounting to a substantial $218 billion per year. From an environmental standpoint, the disposal of this food waste in landfills leads to the emission of toxic methane gas, which is 86 times more harmful than carbon dioxide.

Presently, commercial kitchens attempt to address this challenge through manual means, such as tracking ordered dishes, monitoring food quantities ordered and consumed, and analyzing costs. However, these efforts prove inadequate and unsustainable in curbing the waste effectively.

To make substantial progress, commercial kitchens urgently require smarter approaches, and although artificial intelligence (AI) has already been deployed to some extent, its implementation remains below its potential.

By leveraging AI, commercial kitchens can unlock numerous use cases that enable them to combat the scourge of food waste more effectively.

Causes of Food Waste at Restaurants

Restaurants of all sizes tend to waste food due to the following reasons:

  • Disproportionate purchase of stock or raw materials: Restaurants often overbuy supplies. During festive seasons especially, they tend to miscalculate the demand for certain dishes, leading to food waste.
  • Poor storage: Stock, particularly fresh produce, requires appropriate storage conditions encompassing space, temperature, and packaging. While larger restaurants possess the financial resources to procure and maintain ideal storage conditions and provide staff training, relatively smaller restaurants often lack such means, resulting in inadequate storage practices and increased stock waste.
  • Portion control: Portioning is the default quantity of food served after an order. Unfortunately, many restaurants do not adhere to the best practices, and the lack of standardization in portioning is a prevalent issue. Chefs or cooks often rely on their experience and approximation to determine portion sizes, which may not be inherently wrong but can be insufficient in effectively minimizing food waste.

All the Ways AI Can Help Minimize Food Waste

Numerous AI tools and practices are now available to help minimize food waste in commercial kitchens:

Advertisements
  • Manual tracking and data collection of food items has always been cumbersome and inefficient. However, AI has revolutionized this process by learning to identify food items through human inputs, thus monitoring the entire workflow from storage to waste disposal. In the interim, it records the types of food items prepared and the amount wasted, optimizing its identification capabilities over time. This automation frees up personnel involved in the storage-to-disposal workflow, allowing them to focus on other tasks while AI collects and processes data.
  • AI’s data processing abilities allow it to generate interactive, visual dashboards for human operators in commercial kitchens. By integrating with other software applications, AI can also automate the export of data into report forms. Commercial kitchen managers can then view these reports to objectively identify errors and omissions in the workflow, as well as discern the proportion of food items being consumed or wasted. Consequently, commercial kitchens can take measures to prevent overproduction or excessive procurement.
  • AI aids managers in identifying seasonal and perishable food items, empowering them to make data-backed decisions on rationalizing or optimizing the procurement of fresh produce.
  • AI can provide valuable inputs to enhance storage conditions, allowing raw items to last longer and stay fresh, ultimately contributing to reduced waste and improved efficiency in commercial kitchens.

A Success Case: How IKEA Has Been Minimizing Food Waste with AI?

IKEA UK&IE has been using Winnow, which develops AI tools to minimize food shortages for a few years to cut food shortage by 50%. Hege Sæbjørnsen, the Country Sustainability Manager at IKEA UK&IE, said:

“Sustainability is at the heart of everything we do at IKEA and a part of our DNA. We have set ourselves an ambitious target to cut our food waste by 50% across our operations before the end of August 2020, and our partnership with Winnow is critical to realizing that goal.”

In 2018, IKEA demonstrated significant progress in addressing food waste and achieving cost savings. The company successfully saved £1.4 million in expenses while also managing to save 800,000 meals that would have otherwise gone to waste. Additionally, the company achieved a 37% reduction in food waste across all its stores.

Such AI tools operate similarly to those employed in autonomous vehicles. They are initially trained with human assistance to recognize various food items, and over time, they become capable of doing so independently. These intelligent cameras installed in the kitchen collect data on the prepared food items and those disposed of in the garbage, allowing the AI to continually improve and provide valuable insights on parameters like food types, waste patterns, and preparation times.

The AI tool developed by Winnow has been successfully deployed across all 23 IKEA stores in the UK and Ireland. Lorena Lourido, the Country Food Manager for IKEA UK & Ireland, emphasized IKEA’s commitment to inspiring and enabling people to change their behavior regarding food waste, starting with their own operations.

“The feedback from the IKEA Food teams running our restaurant kitchens has been extremely positive so far.”

The Bottom Line

AI holds significant promise in tackling food waste, but its implementation faces challenges. While established commercial kitchens, such as those in big hotels, are already adopting AI solutions, smaller eateries lag behind due to limited awareness. Consequently, these eateries persist in using manual processes, contributing substantially to overall food waste.

However, contrary to popular belief, AI doesn’t have to be expensive – cost-effective and customized solutions are available. Kitchen managers play a crucial role in identifying suitable AI solutions and training their staff accordingly.

The first step, though, is acknowledging the problem of food waste.

Advertisements

Related Reading

Related Terms

Advertisements
Kaushik Pal

Kaushik is a technical architect and software consultant with over 23 years of experience in software analysis, development, architecture, design, testing and training. He has an interest in new technologies and areas of innovation. He focuses on web architecture, web technologies, Java/J2EE, open source software, WebRTC, big data and semantic technologies. He has demonstrated expertise in requirements analysis, architectural design and implementation, technical use cases and software development. His experience has covered various industries such as insurance, banking, airlines, shipping, document management and product development, etc. He has worked on a wide range of technologies ranging from large scale (IBM…