Revisiting AI in the supply chain

October 16, 2019 Matt Vermeulen

We’ve talked in the past about machine learning and artificial intelligence, and since last we looked, companies have continued to use it in innovative ways to bring value to their supply chains. 

The power of artificial intelligence and machine learning is far more extensive than faux-robot chatbots. The true potential these twin technologies have is in their ability to make you improve relationships with core stakeholders and help you make smarter decisions without having to second guess your actions. 

Data rich, intelligence poor

Most companies today are data rich but intelligence poor. They’re positively swimming in data. We have more data on every purchase probably than we’ve ever had. In fact, at last count, there’s 2.5 quintillion bytes of data created each day. And if data leads to insight, then that’s the cat’s pajamas! But the problem is, few companies have the ability to turn this data into usable insight. We just don’t have the human capacity and hours to sort through so much information. 

That’s where the twin potential of machine learning and AI comes in. They can sort that data, look for patterns, learn from them, complete tasks for your or offer suggestions to make smarter suggestions. Just in the context of accounts payable, AI has the potential to help you with assisted coding: offering automatic coding suggestions, automatic coding: actually coding it without bothering you to check it. AI can automate your processes, solve problems faster, and massively increase straight-through processing, all using that wealth of data. That insight and intelligence helps accounts payable work more closely with other departments (like treasury and procurement) to better strategize cash management and improve working relationships within the whole finance team. 

But where else can artificial intelligence and machine learning play a role in the B2B world? It can often be hard to conceptualize where new groundbreaking technology can play a role until you see it in practice. Let’s take a look at how a couple of companies from different industries are using them to reimagine how work gets done. 

Unilever makes the theoretical practical with AI factories

For AI in the supply chain and logistics, Unilever revealed they’re building virtual versions of physical factories. They’re equipping their machines with sensors so they can create digital models to track physical conditions and test operational changes. 

They’re capitalizing on AI and machine learning to make use of the “Internet of Things” devices embedded into factory equipment. The technology embedded in their warehouse machines tracks the performance of the machines and the conditions in the factories. That in turn lets Unilever make instant changes to optimize their factory output and make a more streamlined process out of their supply chain. 

And it’s already working. According to the Wall Street Journal, the project has already saved about $2.8 million at the site they’re testing it at, and they’ve rolled the project out to eight more plants in North America. And they can start using the analytics to provide insight into how to design and make management decisions, helping teams collaborate more efficiently across the whole organization.

Big River Steel uses AI to make steel production ultramodern

From a manufacturing standpoint, both AI and machine learning technologies are playing a role in metal production. United States Steel Corp. recently bought a $700 dollar stake in Big River Steel LLC to gain access to “ultramodern technology, including machine learning.” 

Big River calls themselves “a technology company that just happens to make steel,” and is focused on improving the entire manufacturing process. Big River’s factory uses an AI system to use machine learning and neural networks to continually train algorithms on the data captured by thousands of sensors. Sound familiar? It’s the same sort of tag team technology approach that Unilever is using: take advantage of a wealth of data by giving it to artificial intelligence technology to sort and learn. This lets the steel mill operators spot problems, sequence production, and conserve energy. And all this insight allows Big River Steel to help the plant avoid downtime like a traditional mill would see. According to Big River’s Chief Executive David Stickler, “Pretty soon you get an extra three weeks of operation a year.” And that extra operation time means extra profit. And that holds similar implications for the finance world — it’s safe to say that the time-saving potential of AI and machine learning can massively increase your productivity. 

Their innovations in steel production have led to concrete partnerships. According to their website, they’re the only steel producer to be invited to become a member of the Center for Collision and Safety Analysis (CCSA), and they partner with academic researchers to explore the potential of modern technology to improve production and relationships across the entire manufacturing industry. That’s the sort of intelligence AI can bring: the ability to improve partnerships that can lead to greater innovations. 

Both are great test cases to see how the Power of AI and machine learning can make sense of the wealth of data you have right now. Companies that learn how to apply the potential of these technologies can not only keep their enterprises adaptive, but can play a role in innovating the whole industry. That’s change worth pursuing. 

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About the Author

Matt Vermeulen

Matt Vermeulen writes about B2B commerce for Tradeshift. Whether he's writing about Accounts Payable best practices or debunking AI myths, Matt enjoys making complex topics easy to understand and fun to read.

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