As sea lice plagues the Scottish salmon industry, markets should turn to AI
A case for a predictive supply chain
Scottish salmon accounts for less than a tenth of global production, but it’s a premium product — it’s the first fish and first non-French product to be awarded France’s selective Label Rouge quality mark. As a result, it’s in high demand everywhere from the US to China. Salmon is the biggest food export from Scotland and, in 2014, it became the biggest food export in the United Kingdom. [1]
But last year, production hit a major snag in Scotland. The problem was sea lice — parasites that attach to salmon and make them unsuitable to eat. [2]
“Sea lice is costing over a billion dollars [USD] a year in global loss of salmon,” Ian Bricknell, a professor of aquaculture biology at the University of Maine, told IBM.
While major salmon producers the world over have issues with the tiny crustaceans, Scotland’s dilemma is the worst of all. As a result of last year’s outbreak, supplies of Scottish salmon fell 5 percent. [3] This created a ripple effect that sent prices surging in key markets. One English smoked salmon curer, which supplies several major supermarkets, said he was forced to increase prices three times last year after the cost of Scottish salmon went up as much as 100 percent. [4]
Learn about IBM’s supply chain solutions
“The supply of many products and especially fresh food products such as salmon are heavily dependent on a number of external factors that are largely uncontrollable, such as weather, ground and water conditions, and disease,” said IBM retail client executive James Lovell. “While growers and farmers take many measures to mitigate against the risk of these external factors, there is not a 100 percent reliable way of controlling them.”
Salmon producers spend millions annually fighting sea lice and other marine pests. While they’ve had some success, there is still no permanent solution, and as a result fluctuations in supply will persist.
“Salmon was domesticated relatively recently, and large scale production is even more recent. Fish veterinarians did not exist at all before the 1980s,” marine economist Frank Asche told IBM.
While retailers and distributers can’t prevent fluctuations in availability, they can respond to them. With artificial intelligence and machine learning, they could predict and identify patterns and trends impacting production that humans and traditional processes cannot. By measuring supply and demand globally with precision and speed, they could better determine how much salmon to order from various salmon producers. Retailers that use this technology for fresh food replenishment have seen reductions in out-of-stock rates of up to 80 percent. [5]
“Artificial intelligence is able to process the vast amounts of data required to do this much quicker and more accurately than any other process,” Lovell said.
Learn more about IBM’s supply chain management solutions and see how the ripple effect impacts your business.
