Studies conducted by Juniper Research have found that blockchain’s ability to trace food across the supply chain, will enable food fraud savings amounting to USD$31 billion (AUD$49) by 2024.
Food fraud savings will begin to be unlocked in 2021, and by 2024, the use of blockchain and Internet of Things (IoT) technology (a system of interrelated computing devices which transfer data over a network) could reduce food compliance costs for businesses by up to 30 per cent.
The use of blockchain technology to trace food across supply chains have been widespread amongst some of the largest retail food stores this year, with examples such as Topco Associates piloting Mastercard’s blockchain blockchain-based Provenance Solution, Walmart China started tracking food through VeChain’s Thor blockchain in June, and Migros, Switzerland’s largest supermarket chain and retailer, announcing that it would use TE-Food’s blockchain-based food traceability system for its products.
According to the study, blockchain and the IoT would need to work in tandem, with IoT technology feeding data via tracking sensors and temperature monitors into a secure Blockchain supply chain which is both tamper-proof and accessible to other actors in that chain.
Juniper Research author Dr Morgane Kimmich stated:
Blockchain and the IoT provide an immutable, shared platform for all actors in the supply chain to track and trace assets; saving time, resources and reducing fraud.
From our experience, the greatest resistance to adoption blockchain in supply chain has been from the end participants, who may be reluctant to give up more data to their customers for fear of it being used against them. Supply chain systems which properly consult and create buy-in, showing the value which can come back to participants, are likely to dominate the market. Those which amount to a centralised party requiring more data and compliance from suppliers are more likely to be treated like current supply chain systems, a necessary evil.
Once a sufficient bank of standardized data is available within Blockchain supply chains (assuming they are carefully designed), even more interesting machine learning opportunities arise for the analysis of those data sets.