Beyond visibility: Decision intelligence in the supply chain

Visibility has long been the Holy Grail of supply chain management technology. RFID tags, IoT sensors, and software linked seamlessly across companies and continents would communicate the status of every part of the supply chain in real time.

But be careful what you wish for. Some observers say supply chain visibility has turned out to be too much of a good thing. Logistics managers are swamped with more data than they can handle. What's really needed is AI-driven "decision intelligence" that sorts through analytics dashboards, emails and alerts to identify problems while there's still time to change course. Even better would be agentic AI that can make decisions and act with little or no human involvement.

In this episode of Enterprise Apps Unpacked, Jett McCandless, founder and CEO of project44, explains how the company's decision intelligence platform works, where it fits within the ecosystem of ERP and logistics software, and how AI could soon make supply chains more responsive and autonomous.

Why supply chain visibility is not enough

McCandless has spent 27 years on the logistics side of supply chain management, starting out in freight brokerage for a shipping company before moving to a third-party logistics provider (3PL) and eventually founding a logistics software development and consulting firm. He started project44 in 2014 and began building the logistics network that became the foundation for today's AI-native platform that tracks 1.5 billion shipments annually across more than 190 countries.

"Visibility is a bit of a passive technology," McCandless said. "That doesn't mean it's not valuable. In fact, it's extremely valuable." After all, reliable visibility tells managers what's happening in their supply chains and inspires confidence in the data they need to make decisions.

"I can tell you that something's going to be late, and I can tell you why it's going to be late," he said. "The next logical thing is what are you going to do about it?"

People will want to know whether it makes sense to expedite the order or take the item off the shelves. They might wonder if a different distributor can move a good closer to its destination. Thinking further ahead, they might consider building in more lead time or keeping more inventory on hand.

Now, with AI embedded throughout the platform, those decisions can be handled either by human or digital workers (AI agents), according to McCandless. "We can lift this information up to where a human can make a decision, or it can be outsourced to a digital worker," he said. The two can also work in tandem, with the agent attempting a fix before the human steps in to make the final call.

Other topics discussed in the podcast include the following:

• How the AI knows which data to prioritize.
• Advice on overcoming challenges in implementing decision intelligence.
• Examples of companies that use project44.
• Areas where supply chain visibility remains challenging.

David Essex is an industry editor who creates in-depth content on enterprise applications, emerging technology and market trends for several Informa TechTarget websites.