A cold chain is a supply chain in which goods must be temperature controlled. Cold chains are commonly associated with the pharmaceutical and food industries. According to a 2016 report by the International Trade Association, global food losses total $750 billion a year, largely due to cold chain issues. The same report reveals that $260 billion of annual biopharma sales are dependent on cold chain logistics.
Cold chain is big business and the stakes are high. The implications of a poorly maintained and monitored cold chain go far beyond monetary losses. Food or drugs that unknowingly fall outside of temperature tolerances can pose a hidden risk. They may become tainted with bacteria even though they may not be visibly spoiled. After finding their way into the hands of a consumer or patient, these tainted goods can cause serious illness or even death.
For this reason, pharmaceutical and food companies go to great lengths to establish cold chains that are tightly managed and traceable.
So what role does the digital supply chain play in bolstering cold chain safety and efficiency? One obvious contribution lies in temperature monitoring sensors. These relatively small GPS / GSM enabled sensors can be placed on a pallet or a box. They provide live temperature readings along the end-to-end journey of a case of frozen shrimp or a pallet of cancer fighting drugs from processing facility to grocery store or hospital.
At a minimum, tracking the real-time temperature of goods enables cold chain managers to identify shipments or SKUs that have fallen outside of temperature tolerances for a long enough period to be considered spoiled. Those goods can be removed from the supply chain once they reach an intermediary point or final destination, and destroyed before causing harm to a consumer.
Better yet, by receiving timely alerts about temperatures trending out of tolerance, a cold chain manager can quickly initiate remedial action that prevents spoilage altogether (e.g., direct a refrigerated truck with a broken AC unit to the closest truck depot where the unit can be fixed or the goods unloaded onto another truck).
Even armed with real-time alerts, however, a cold chain manager oftentimes cannot marshal the right resources quickly enough to remediate a cold chain issue once it starts going sideways. Shipments may be too remote to get to quickly enough, replacement equipment may not be available, etc.
For that reason, it’s important to be proactive rather than reactive in cold chain. This is where predictive analytics come into play. A digital supply chain solution, using predictive analytics, can peer forward along the scheduled route of a shipment to identify issues before they occur. By plotting the forecasted temperature along the predicted location of a conveyance over time, a digital supply chain solution can highlight shipments at risk before they even depart.
Knowing which drugs are on a palette or in a container, and understanding the temperature tolerances by duration, for every SKU, a digital supply chain solution can make prescriptive recommendations. One such recommendation could be to remove a single SKU that falls outside of predicted temperature tolerances from a palette and ship the rest of the palette ambient, knowing that the ambient temperatures along the route will be acceptable for the remaining SKUs.
A digital supply chain solution could also suggest a change to a route, where the predicted temperatures are more favorable than the original route.
Finally, digital supply chains deliver significant value to a cold chain by orchestrating timely handoffs between trading partners. The weakest link in any cold chain is typically at the transfer points, where goods change transportation modes or are staged to be offloaded at a manufacturing facility, warehouse or store.
When these transfers are not properly coordinated, goods end up sitting for long periods. And while no supply chain manager likes the idea of idle inventory, cold chain managers grind their teeth at the notion.
When goods are unloaded from a temperature controlled airplane or ocean vessel, for example, only to sit on a hot tarmac or dock for hours or days because a refrigerated dray carrier wasn’t waiting to pick it up, the goods spoil. Digital supply chains calculate predicted times of arrival at all transfer points and supply chain nodes, factoring learned behavior models and external events like weather and port congestion.
These predicted arrival times as significantly more accurate than carrier provided ETAs, and they enable cold chain managers to orchestrate just-in-time handoffs of temperature controlled goods.
Digital supply chains constantly model and learn about a company’s specific supply chain, highlighting choke points and risk areas within the cold chain.
These are just a few examples of how digital supply chains, leveraging real-time data, IoT devices and predictive analytics are benefiting cold chains.