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AI to cut causes of waste in food supply chain

supply chain

AI technology can tackle waste across the supply chain to meet customer needs and cut carbon footprints.

According to the Environmental Protection Agency, food waste is responsible for up to eight per cent of global greenhouse gas emissions. Identifying and tackling the cause of food waste across the supply chain is crucial in order to reduce the impact food waste has on the environment.

However, in order to do this, organisations need to be able to gain a better understanding of supply and demand data and establish greater cooperation between suppliers, says Svante Göthe, head of sustainability at RELEX .

RELEX has identified the top causes of waste across the food supply chain and believes that AI is the solution.

Store ordering is often handled locally by managers who base their buying decisions entirely on manual observations and records, leading to unnecessary food waste. This decentralised approach sidesteps fully integrated and intelligent data that could be analysed by technology implemented at the store’s headquarters, leading to over-ordering of goods that the store may not need and unnecessary waste.

There is an underlying perception that customers do not want to buy bruised or over-ripened fruits and vegetables. Poultry and fish nearing their sell-by date are often rejected in favour of food that will last longer, with some supermarkets opting to remove sell-by dates from fresh products altogether.

This puts supermarkets in a cycle of waste. Stores have a constant supply of new products coming in to ensure aisles are appealing, but this doesn’t mean the food is selling at the same rate. Leftovers, caused by overstocking, are thrown away in favour of more visually appealing food. 

Grocery stores are often frozen by manual processes, unable to adapt to radically and rapidly shifting circumstances. Individual stores are only ordering based on their recent data and lack the technology to pivot if conditions are to change. Failing to prepare by leveraging demand data creates an environment ripe for food waste – stores are ordering too many of the wrong or too few of the right products to address the demand swing. 

“Food waste across supply chains is most likely occurring due to inefficient ordering processes,” Göthe said. “When managed manually at the store level and without a deeper understanding of sales and trends data, it’s not possible to have optimal stock levels. This inefficiency has led to unnecessary added work for restocking teams. Simply put, technology is the answer.

“Machine learning-based supply chain solutions can help food retailers to reduce waste by transforming how they order and manage fresh goods. These tools provide deeper insight into both macro and micro demand trends to ensure the right amount of product is ordered to each store, driving higher availability without unnecessary waste. This includes a high level of visibility into fresh inventory stock, batch expiration dates and enabling planners to make timely markdown decisions clearing fresh goods before they spoil.

“Grocery stores can reduce food waste by connecting their ordering and replenishment processes with their demand data. Technology is making this approach easier than ever. Cutting-edge tools are available to provide deeper visibility throughout the supply chain, and there’s never been a better time to strive to reduce food waste.”

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