Are companies really "seeing" their supply chains? Adam Compain, founder and chief executive officer of ClearMetal Inc., traces the progress of supply-chain visibility.

Q: Why aren't shippers getting the visibility that they need?

Compain: Because the underlying data is flawed. How can you answer questions about visibility in transit if the data about where the cargo is is incorrect, inaccurate, latent, and incomplete?

Q: In the era of big data, I would have thought that availability of data isn’t the problem — making sense of it is. Are you saying that shippers actually do lack critical data at certain times?

Compain: It’s both of those. Most of the data is out there and available, but it's often misleading or incorrect, and it can be latent and even missing. The challenge comes both from accessing the data and making sense of it in a way that creates visibility.

Q: Are there gaps in the supply chain where you typically cannot get the data on a timely basis?

Compain: Parts of the supply chain are more difficult than others. People often struggle with visibility going inland or inside the terminal. But it doesn't require all parties necessarily to cooperate, although we want that in the industry. It's possible to get great gains just by working with either an independent software company or just a few parties. Think about door-to-door moves going in a shipping container. A lot of that data is passed back through the carrier, and if you can pair it with IoT [Internet of Things] or satellite data, you can see a pretty complete picture.

Q: Would you argue that the importance of visibility in the supply chain has increased in urgency? And if so, why?

Compain: Absolutely, for a few reasons. First, the Amazon effect has bubbled up to the point where suppliers are needing to perform much better in regard to on-time service to consignees or customers. The other thing is that we solved a lot of problems in this industry in the past by using brute force or physical economies of scale. After trade started slowing a bit, and with challenges today in the macro environment, it's more important to be efficient, rather than big. We need new ways to create efficiency and competitive advantage, instead of through larger store footprints or megaships.

Q: The dream over the years has been that data replaces physical inventory. Is that happening?

Compain: Interesting question. I think not fully, but potentially. It’s impossible to do efficient things with your physical inventory unless you master and make sense of the underlying data. The two have to be paired. You need the ability to sell inventory on the water, or optimize inventory across the D.C. network.

Q: You would think if you had better intelligence at the consumer demand end, you wouldn’t need as much safety stock further up the chain. Is that happening?

Compain: It is happening. Amazon is probably the best example of being able to make sense of the actual market and consumer demand, and trickle that through the rest of the supply chain. But Amazon aside, we're seeing a lot of retailers and manufacturers do exactly as you say. If you figure out what the data is saying, you can make much smarter decisions about lead time and buffer stock, and improve exception management.

A good example is sending a dray provider to the port when the container is actually available for pick up, rather than waiting a few days, incurring D&D [demurrage and detention] charges, and having things get to the warehouse and on the shelves later. Throughout the supply chain, there are a lot of buffer areas that are getting reduced through better control of data.

Q: One might think of basic freight status information as “dumb data.” How do you use data to make real analytical decisions, and plan throughout your supply chain? Is artificial intelligence a factor?

Compain: Absolutely. We’re seeing that quite a bit. A lot of people mistakenly believe that A.I. is only a futuristic capability. We're actually seeing a big use of A.I. today, to clean and make sense of the data. Simple things like taking in data, cutting out errors and preventing a shipper from ever seeing the [incorrect] information.

I’ll give you two practical examples. If you're able to predict the likelihood of a shipment's arrival before time of booking, depending on a certain origin and destination pair and carrier schedule, you can make different procurement decisions. Like staying on the ocean versus shipping by air, or choosing different carriers on the spot market.

Downstream, we're seeing the possibility of taking real-time satellite data and pairing it with real locations, to identify when a vessel has actually berthed. If a shipper knows that cargo has arrived, then you're able to predict its availability for pickup at the out gate for the dray provider or a rail carrier. You’re using A.I. not just to learn where your stuff is, but when's it going to be where it needs to get. Then you can execute decisions accordingly. That's all happening today.

Q: How do you see the potential of blockchain as a means of improving visibility?

Compain: Having irrefutable pieces of information that follow on a chain is a powerful technology. Also using machine intelligence to constantly learn, as opposed to just using static, fixed algorithms. It’s a fundamentally different kind of computing.

Q: In the meantime, there’s EDI [electronic data interchange], which gives us sufficient communication standards.

Compain: I totally agree. The industry is built off of EDI, and the ability to make sense of information in that format is paramount, if you're trying not only to survive, but thrive today.