Every Friday, Talking Logistics shares news headlines related to supply chain and logistics. What if we fed these news headlines into a generating AI engine to create an image? What would they look like?
Over the past two weeks, SAP (sponsor of Talking Logistics) has used AI and human artists to “transform the day’s biggest business and technology stories into a single image that represents what the day needs to be prepared for.” I’ve been All images created can be found on the ‘Be Ready’ website. This is my favorite article, born out of stories of supply his chain quietly exiting, floating homes coming, new his VPN ransomware, baristas unionizing and more.
Sure, it’s a fun and creative example of human-AI collaboration, but how does it move from creating art to delivering business value, especially in supply chain management?
You have one chance here. It feeds a generative AI engine with supply chain data, allowing companies to generate visual maps of their supply chains.
What is Supply Chain Mapping? A graphical representation of where your suppliers (and their suppliers’) manufacturing/production facilities are physically located and what parts and materials are manufactured/produced at each location. To do.
Supply chain mapping is a key component of supply chain risk management, Hidden suppliers determine business success or failure (Harvard Business Review, May 2015) stated, “As supply chains grow in size and complexity, companies face the daunting task of identifying critical nodes hidden within vast supply networks. We do.”
Getting supply chain mapping right takes time, money and resources. Unfortunately, many companies lack him all three (as well as support for leaders), which is why it’s still not implemented.
In a March 2020 survey we conducted among members of the Indago supply chain research community (consisting of supply chain and logistics executives from leading manufacturing, retail and distribution companies), 91% of members answered that they know where all or most of There is one supplier facility. However, only 17% said they knew where all or most of their Tier 3 supplier facilities were located..
Similarly, when it comes to knowing what parts and materials are being produced at each supplier facility, Tier 1 suppliers have the best visibility (61% know what is being produced at every Tier 1 facility). I’m here. Only 9% know what all Tier 3 facilities produce).
Lack of visibility beyond Tier 1 suppliers not only exposes companies to greater supply chain risk, but also impedes the ability to measure and manage Scope 3 greenhouse gas emissions, which are associated with forced labor in the supply chain. It contributes to ongoing problems.
But what if you embedded generative AI capabilities within your business network?
Business networks use cloud-based software applications to connect large communities of trading partners. They give you more timely, accurate, and complete visibility into purchase orders, shipments, inventory, deliveries, invoices, status updates, and many other supply chain processes and events. This enhanced visibility is achieved, in part, by enabling a “long tail” of small suppliers, customers, logistics service providers and other trading partners to electronically connect and transact ( Using APIs, web services and mobile devices, e.g. instead of relying on emailed spreadsheets or faxes.
For example, at last week’s SAP Sapphire conference, SAP announced it was building an industry-specific network that will initially focus on consumer products, high-tech, industrial manufacturing, and life sciences. Across these four industries, he already has over 800,000 trading partners on his network, processing more than $700 billion in commerce annually.
Instead of news headlines, we generate data from purchase orders, advance shipment notices, invoices, bills of lading, status updates, proof of delivery, and other transactions that flow between trading partners on your business network and feed them into our AI engine. What if you could generate a graphical supply chain map?
I believe so.
Maps will never be perfect or complete. Just as it takes a human artist to perfect a SAP image, it can require validation and fine-tuning by Supply He Chain Analysts. However, AI engines certainly reduce the time, cost, and effort required to create maps. And because the supply chain network is constantly changing, the generative AI engine (with the help of analysts) continuously updates the map, so the benefits continue.
Have you arrived yet? No, but it’s part of the future of AI and business networks, and in the words of great Ferris his Buehler, “The future is moving pretty fast. Sometimes if you don’t stop and look around, you’ll miss it.” I might lose it.”
Don’t miss the future. Please be prepared.
