While in some ways obtaining supply chain visibility has gotten more difficult over the years, due to globalization, outsourcing, product proliferation, and other factors, in other ways it has gotten easier thanks to advancements in technology. One area, for example, is trading partner and system integration. How are today’s technologies helping in this area?
“You have to think of the integration, first and foremost, as a network problem,” said Rich Katz, Chief Technology Officer at Elemica in a recent episode of Talking Logistics. “What that means is because your supply chain networks are so fluid, every time you have to add another trading partner, whether it’s a shipper, customer, or logistics service provider, you don’t want to constantly have to make point-to-point connections; you want to be able to leverage [the connections that already exist in the network]. Today’s new technologies approach integration as a network problem so you get reusability.”
Katz also discussed the importance having the right kind of data model in order to link all of the disparate data formats out there:
“In order to link different transactions [such as purchase orders, sales orders, and shipments], you have to ensure that the data model speaks the same language, uses a common semantic framework. Today’s technologies are built around a proper canonical that is agnostic, not tied to a particular standard, and can handle different formats — such as flat files, idocs, X12 — and actually puts that data in a format where you can link the purchase order to the sales order to the booking to the status messages and provide that clear visibility to what’s happening in the supply chain.”
We’re also seeing an explosion of data sources, everything from mobile devices to sensors. Of course, the problem with more data is that you might end up with more poor quality data, which I view as the Achilles’ heel of supply chain visibility. Are there better ways for companies to manage and improve data quality? The short answer is yes, as Katz discusses in the short clip below:
“When you can do it, it’s always best to address a data quality issue at the system of record,” says Katz. “But in many cases, that’s going to be a challenge because you’re dealing with a lot of things [and systems] that are beyond your control….[Today’s technologies enables us] to deal with data inconsistencies at the point we see them and we’re able to reuse the logic we put in place to clean up data in real time.”
I encourage you to watch the rest of my conversation with Rich for additional insights and advice on this topic, including the role that mobile technologies, artificial intelligence and machine learning are playing in improving supply chain visibility. Then post a question or comment and keep the conversation going!
