Big Data can help reduce food recalls, if companies can harness it. Karl Deily, president of Food Care at Sealed Air, comments
Food recalls can have a major impact on the balance sheet. On average, a food recall can cost a company US$10 million in direct costs, not including lost future sales from the damaged reputation. When you factor in medical expenses, productivity loss and mortality, food recalls across the industry cost the United States alone an estimated $56 billion each year.1-2
Despite increased regulation, the number of food recalls has continued to rise. In 2016, 764 food recalls were announced in the US and Canada, up 22% from the year before. According to a survey by the Grocery Manufacturers Association, 58% of food companies have been affected by recalls in the past five years.3
Food safety becomes especially important as the global and complex food supply chain grows. Regulation has a role to play, but preventing future recalls requires improved traceability throughout the food supply chain. Predictive analytics and remote tracking technology can allow food companies to track production and operations, improve food traceability and prevent contamination.
The Internet of Things (IoT) allows food companies to collect data through sensors embedded within the advanced food packaging. Smart packaging provides real-time monitoring and management of food products from farm to table. With the right data, companies can stop contaminated products and prevent recalls altogether.
With all the data that companies can capture, separating the signal from the noise can be a challenge. Simple spreadsheets are not enough to tackle this. Sealed Air, for example, has developed specialised tools to capture and analyse multiple sources of data.
Food companies should not focus on just collecting data but collecting the right data to drive results. Real-time temperature tracking has been of particular interest to the industry. At favourable temperatures, bacteria can grow rapidly to the point where they can cause illness.
As the cold supply chain has expanded in recent years, so have the opportunities for errors in maintaining the proper temperature. Contamination can occur at any stage in the food supply chain.
Smart packaging sensors allow companies to track food temperature beyond their own operations. This data can help identify temperature fluctuations within the supply chain, whether on a truck or on the retailer shelf and predict potential contamination issues.
As we continue to apply IoT to food safety applications, we will need to work more closely than before with suppliers and customers across the supply chain to address contamination issues. If we can pinpoint temperature fluctuations, it becomes easier to apply preventative measures to resolve the issue quickly and minimise the disruption.
Of course, remote monitoring and predictive analytics require an investment in building a strong supporting infrastructure. This is more than offset by the cost savings from the efficiencies it will drive and potentially fewer recalls. Researchers have found that improving traceability could cut the cost of recalls by nearly 90% for businesses and would save $260 million in 10 years for large-scale beef production plants. And that analysis does not even include the reputation and cost benefit.4
Making the business case for preventing and reducing recalls is not always easy, but leading companies know how valuable prevention is. They work with experienced partners to conduct detailed, technical assessments and help strengthen the business case for their organisation.
The food industry has always been reliant upon technology to feed the world’s ever-growing population and today is no different. To counter the rise of food recalls, business leaders in the food industry must continue to drive change and invest in remote monitoring and predictive analytics to improve traceability.