Jewelers Mutual Group has a vested interest in ensuring that high-value items get from point A to B in a supply chain in which there is between $2 billion and $8 billion worth of cargo in transit at any one time.
“In fact it’s so important for us to understand where everything is at that we acquired our own shipping company a couple of years back,” said Benjamin DeBoer, the company’s director of corporate innovation, speaking Friday as part of a supply chain visibility panel during FreightWaves LIVE @HOME.
However, the challenge for a company like Jewelers Mutual – the largest insurer of retail jewelers in the U.S. and Canada – has been obtaining real-time cargo visibility so that it can more efficiently handle and mitigate insurance claim risk.
“I consider the jewelry industry a sleeper industry,” said Ilya Preston, co-founder and CEO of startup PAXAFE, an artificial intelligence (AI)-enabled Internet of Things (IoT) platform that contextualizes supply chain data to help “de-risk” cargo insurance. Speaking on the same panel, Preston said that the insurance industry is deceivingly large – $90 billion in the U.S. alone – “but it’s sometimes shielded from tech disruption and innovation.”
DeBoer conceded that, as an industry, the domestic and international jewelry business does not yet fully trust IoT. “There are too many solutions out there, and everybody wants to create a proprietary technology that nobody else can play with,” he said. “And they just provide tons of raw data without exposing the ‘calls to action’ that really need to be there.”
To help the jewelry industry and other supply chain sectors get more control over cargo insurance visibility, Preston said his company gathers – and importantly, puts into context – data that addresses three core areas: intervention, resolution and prediction.
“That third part, being able to accurately predict an event that can lead to an insurance claim, is probably the most important but is likely the most underserved as well, meaning nobody has really gotten there yet,” Preston acknowledged.
“We don’t have to look too far past the industry loss ratios in cargo insurance to understand just how difficult it is to price shipment risk. Our take is, if you can’t use data to understand how or why something happened in the supply chain, it’s very difficult to then properly classify an adverse event. If you can’t properly classify it, you can’t accurately contextualize it. And if you don’t have that level of contextualization you can’t really drive accurate risk models off that.”
DeBoer believes that the jewelry industry will eventually embrace IoT as it relates to insuring shipments – “maybe not 2021, but I think IoT is going to get there,” he said.
He also believes that predictive analytics can change carrier performance.
“With our shipping solution [called TransGuardian], one of my utopian dreams is for our customers to not even be aware of solutions that we put in place that uses predictive modeling that says, for example, shipping with a particular carrier is going to have a high likelihood of some kind of damage or loss – so we’re not even going to offer up that option for the customer in the first place.
“That opens opportunities to have conversations with the carriers themselves to talk about what isn’t working. I’d like to have all that visibility and context that can help drive prices lower and improve service, which will make it a win-win for everybody.”