Combating food waste with AI-Driven food management techniques

The recently concluded G20 summit was a landmark moment for India and for the globe, not least because of a significant focus on the critical issue of global food security - with member nations pledging to work towards reducing food waste and loss across the value chain and building more sustainable food systems. 

In a world where 345 million people face high levels of food insecurity, one would hope that not a morsel of food gets wasted. And yet, a staggering 1.3 billion tons of food is wasted globally every year – about one-third of all food! This enormous wastage is unconscionable and addressing it should be a key priority not just for governments, but for individual organizations as well, particularly food service providers.  

If you visit a canteen at a school or college campus, office, or other institution, there’s a good chance you will see a sizable amount of leftover food. The sheer wastage is egregious enough – the fact that much of this food will end up in a landfill and release methane (25 times more harmful for the environment than carbon dioxide), exacerbating the impact of climate change, makes the situation that much worse. 

Much of this wastage occurs simply as a consequence of outdated, manual processes that leave food service providers unable to accurately forecast demand, optimally manage inventory, and avoid overproduction. AI-driven digital platforms, leveraging the power of predictive analytics, will go a long way towards addressing these gaps. Increased focus on the issue of food wastage by regulatory authorities, including the FSSAI (Food Safety and Standards Authority of India), places a strong impetus on the food service sector to embrace these technology-driven solutions, to facilitate more efficient, less wasteful and cost-effective food management.  

Forecasting Demand through Data 

A key underlying factor behind the wastage that occurs in food service operations is an inability to predict demand. For instance, in a college cafeteria, the kitchen staff often do not have an accurate count of how many students or faculty members will visit at a particular time and actually order food. This information gap causes a mismatch in demand and supply, leading to the over-preparation of food, which in turn leads to wastage. 

In addition to not knowing how much food to prepare, there’s also the issue of what to prepare. Due to shifting food preferences among students, the menu items offered by college cafeterias may no longer be in line with the expectations of their consumers. Students will simply not consume what is served if they don’t like it, making further wastage inevitable. 

Both of these challenges can be effectively addressed with AI-driven food management platforms, which empower cafeteria administrators to adopt a data-driven approach to forecasting consumer demand. Leveraging analytics, they can estimate footfalls at cafeterias during specific times of the day and get a fairly accurate estimate of how many people order specific meals. Moreover, they also gain insights into the food preferences and dietary patterns of their consumers. This enables them to adapt kitchen operations accordingly – planning menus that are in line with consumer preferences and preparing meals in quantities that do not exceed the estimated demand. 

Elevating Inventory Management 

Optimizing kitchen operations through predictive analytics can also contribute to better inventory management for food service providers. To return to our example of college cafeterias, more effective meal-planning, in line with current consumer (i.e. student and faculty) food preferences and forecasted demand, means that cafeteria administrators have a precise understanding of which food items and ingredients they need to keep in stock. This provides them with an opportunity to streamline supply chains, and to identify and purchase produce in a more cost-effective manner. 

Ineffective inventory management is a key source of food wastage, due to expiry of stock. This is another area where AI-driven solutions add value – enabling food service providers to track stocks by expiration date and ensure that ingredients are used in meal preparation before they start to degrade. 

Towards a New Paradigm of Food Management 

AI-powered digital platforms have a wide variety of applications for food service providers catering to a range of sectors. A digital solution can ensure better nutritional and allergen management in cafeteria operations. With AI-driven analysis of metagenomic data, it is even possible to pinpoint the impact of alterations to an individual’s diet on their well-being. These capabilities enable food management platforms to serve as an instrument of preventive health and optimize meal-planning, further contributing to food wastage reduction efforts. 

Bringing intelligent decision-making to cafeteria operations, AI-driven food management solutions empower food service providers to align offerings with consumer expectations, accurately forecast demand, streamline supply chains, and reduce costs – enabling them to create more robust and efficient business models, as well as to play their part in the global battle against food waste.  

In the years ahead, this digital revolution will undoubtedly become one of the lynchpins of our collective endeavor to build a world where no one, least of all a child, needs to go hungry. 

Rajesh Sinha

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Rajesh Sinha is Founder and Chairman of Fulcrum Digital.