Speed is critical when removing unsafe food from the supply chain to prevent illness and save lives. Since the beginning of May alone, there have been eight food safety recall events in the US. According to the US Department of Agriculture, about 48 million episodes of foodborne illness and 3,000 deaths occur per year in the US. The most common foodborne pathogens cause an estimated annual burden of $14 billion to $36 billion.
iTradeNetwork (ITN), the global provider of supply chain management solutions and traceability for the food and beverage industry, has added new capabilities that instantly identify specific recalled products and simultaneously notify suppliers and buyers. These traceability tools help remove recalled products from the supply chain more quickly, whether they are in route from supplier to buyer, at a distribution center or at the final point-of-sale/consumption. These functions are unique in the industry and built on the strength of iTradeNetwork’s 8,000 customers and integrated FDA/CDC alerts.
“Food safety has never been more important,” said iTradeNetwork’s CEO Rhonda Bassett-Spiers. “Our new tools allow for instant and simultaneous notification about food recalls and provides the food’s exact location across the entire supply chain with surgical precision.”
iTradeNetwork’s new advanced traceability modules include:
FDA/CDC alert integration is a new standard for the industry, combining system-level monitoring with machine learning accessible online or through a mobile app. Growers/suppliers and retailers can be notified of a food safety incident the moment it is suspected and isolate affected products whether they are pre-shipment, in-transit or in-store. This allows for immediate action to protect consumers and brand integrity. Recalls can be issued within seconds.
For protein providers, suppliers of lower risk produce commodities and high-volume produce operations not currently using PTI or item labeling, this technology enables alerts, notifications and food safety incident management based on purchase order data, not labels.