One-third of food produced is discarded

From production to consumption, food is one of the world’s biggest sources of waste. Staggeringly, it’s estimated that one-third of food produced is thrown away. Beyond its environmental impact, food waste exacerbates food insecurity and puts pressure on those who produce food—farmers, for example. At Datasparq, we’ve used AI to optimise supply chains and reduce food waste—helping clients achieve significant gains in both sustainability and profitability.

How AI helps

To illustrate how we approach the challenge here at Datasparq, I’ll use the example of a hotel restaurant. Restaurants are a key source of revenue for hotels, making profit margin optimisation crucial. Fresh food overstocking has historically impacted profitability due to the perishable nature of the products and limited repurposing options compared to supermarkets—a hotel restaurant can’t offer a “reduced price” food section, for example. This leads to lots of food items being thrown away—bad for people, the planet and profitability. To address this challenge, businesses must first collect data on customer behaviour and sales.

Once the data has been collected, it’s possible to implement a solution that predicts stock demand using regression modelling. The model is built using key performance indicators identified by the business, most often derived from sales data. While this approach is relatively straightforward—and can yield financial returns quickly—the model's performance and effectiveness hinge on data quality, model architecture and parameter tuning. A demand forecasting model offers the opportunity to optimise profits by either increasing sales or decreasing initial stock purchases. Beyond financial gains, using a demand forecasting model improves sustainability by reducing food waste and improving supply chain efficiency.

A 21% increase in profit by reducing food waste

Datasparq recently collaborated with a client in the airline industry on a similar predictive modelling use case. The results were positive, with a test period demonstrating a 21% profit increase and a 47% reduction in food waste. It was crucial for our model to include constraints to prevent item stockouts to maintain customer satisfaction. By incorporating these constraints, we were able to demonstrate the potential for significant profit growth through AI while addressing critical operational challenges.

Making it real for you

For businesses operating in industries such as hospitality and travel, AI is changing the way that fresh food produce is sold. Here at Datasparq, we’ve shown how reducing food waste not only helps sustainability efforts by cutting CO2 emissions—it has a significant impact on profitability, too. If you’re interested in finding out more, reach out via our website to find out how we could help your business on its journey to reduce food waste. Or, reach out to chat about the many ways that we can help you use AI to make your business more efficient.