In response to growing public safety concerns about food safety, the FDA’s Food Safety Modernization Act (FSMA) was signed into law on January 4, 2011. In its first phases, the FSMA focused on regulating food sources and the food supply chain; in 2014, its focus is broadening to the transport of food from producer to consumer.
What makes the FSMA interesting as a big data initiative is its acute sense of urgency. There are deadlines that food producers and transportation companies must meet, and a US public that sees one in six Americans (or 48 million people) get sick each year from eating the food that they buy. Of these victims, 128,000 are hospitalized, and 3,000 die annually, according to 2011 data from the Centers for Disease Control and Prevention.
To improve this situation and to ensure that they don’t fall under the microscope of government auditors, food producers and transporters are turning to sensor-based technologies and analytics that will inject big data into their supply chains and provide them with visibility that can be as granular as pegging a contaminated shipment to a particular farmer’s field.
Equally important is “track and trace” monitoring and visibility of food shipments during transport. This track and trace monitoring will use sensor- and RFID-based technologies that can follow food shipments from their points of origin through the logistics network and into warehouses, distribution centers, and retail outlets. If the foods are “cold chain” goods that require refrigeration or other types of strict environmental controls, such as maintenance of the goods in specific humidity ranges during transport, sensors for temperature and humidity will be expected in transport vehicles and in the containers that they carry. The sensor-based technology that controls the quality and safety of food in transport containers works in two ways: It can provide GPS data that delivers real-time information about the location of the transporter carrying the goods, and it can monitor the temperature and humidity parameters within food containers, immediately sending out automated alerts if a particular container’s environmentals begin to fail.
Data automation and a new “payload” of big data generated by sensors, scanners, and other mobile devices will also enable companies to plug the holes in the supply chain where there formerly was no visibility. One prime example is yard management (i.e., the controlling of trucks entering and leaving the yards of warehouses and distribution centers to drop off or load goods). Still using walkie-talkies and clipboards that are reminiscent of the mid-20th century, companies log arrivals and departures of trucks. It’s easy to get busy and to forget about the truck loaded with produce that sits in the yard for three weeks without activity while its cargo rots.
“The challenge is that there are many different vendors and many different scheduling requirements,” said Greg Braun, senior vice president sales and marketing for C3 Solutions, which provides dock scheduling and yard management solutions. “Yard transactions should be done electronically, yet they get done via email or through a highly manual process.”
Within the supply chain, less critical functions like yard management have never been priorities for many companies that instead have put effort into updating and automating warehouse and transportation management systems. However, with continuing food safety problems in the US (e.g., the E. coli beef outbreak in May 2014), public and governmental pressures will stay focused on companies to move to sensor-based technologies and big data monitoring and analytics that can collect machine-generated data for shipment track and tracing, and also for continuously in-transit monitoring of produce and other perishable foods as they travel from producers to consumers.