Chris Striffler Interview on the Evolution of eCommerce with Logistics Management
March 3, 2020 | Durham, NC
Supply Chain Services Leader, Chris Striffer was interviewed on the evolution of eCommerce by Logistics Management. An excerpt from the interview and a link to the full article from Logistics Management are included below.
AI’s Many Uses
Today, it seems that AI is on everyone’s lips. The reason: AI is a technology with broad scope, explains Chris Striffler, a senior manager with Clarkston Consulting. “AI and machine learning [ML] have broad applicability, so we’re seeing a lot of traction around those,” he says. “By contrast, blockchain has strong potential in areas including traceability and contract management, but it doesn’t have the broad applicability that AI has.”
Within some larger enterprises, there’s a centralized analytics group working on AI projects and other projects that tap emerging technologies. These enterprises tend to be quite forward thinking about AI, but small to mid-sized companies can also work with consultants to rapidly deploy AI within “proof for value” projects, says Striffler. “Frankly, logistics and freight are a great place to start with a use case,” he says. “That said, it’s smart to view AI not just as a tool for point solutions, but as part of a larger strategy.”
When it comes to all of the details involved in moving goods across borders and recording changes to chain of custody over goods, blockchain is seen as an ideal technology. That’s because it’s a digital ledger that lives in the Cloud where partners can access information easily without corrupting it. These characteristics make blockchain ideal for traceability, storing cold chain data, proof of delivery, or contract details involved with global trade, says Striffler.
Blockchain has various pilot projects or consortiums working to prove its supply chain value, including Walmart’s program to trace green leafy produce supplies, and the Blockchain in Transport Alliance (BiTA). A bit more time and broader participation is needed for blockchain to really take off, says Striffler. “Organizations are starting to dip their toes into the water with blockchain, but it needs that critical mass to be fully effective. We might be a couple of years away from that point.”
Ultimately, how various emerging technologies can help with the challenge of e-commerce is more than deploying each one as an isolated technology. They tend to overlap in a good way. IoT needs predictive analytics and AI, while AI and ML are also baked into AMRs and autonomous trucks.
You don’t to pick and choose from a list of emerging technologies—you might blend ML with IoT to understand the operational implications of massive data sets, Striffler points out. “There can be strong synergies from implementing these technologies together,” he adds.
Read the full article here.