Artificial Intelligence In Supply Chain – While the challenges of the past few years have exposed many problems with the company’s supply chain processes, efforts to address them have been plagued by current thinking rather than forward thinking.
In the mid-2020 Supply & Demand Chain Executive, I had the pleasure of chatting with Editor-in-Chief Brielle Jaekel about Emerging Technologies Claiming to Help Companies in the Supply Chain. In that talk, I mentioned the evolving role of artificial intelligence (AI) and machine learning (ML):
Artificial Intelligence In Supply Chain
“In the near future, supply chain AI will start migrating to machine learning. Currently, supply chain AI has developers writing business rules that tell the computer what to look for and what to do when it encounters these situations, but as humans Intelligence migrates to machine learning and it will start to think for itself. As machine learning becomes more advanced, technology will increasingly be able to record repeated situations and past experiences to start learning and making recommendations on its own. Technologies like this are already in Widely deployed in other industries, it has the potential to rapidly automate and improve a wide range of supply chain processes.”
Artificial Intelligence In Supply Chain Management
After a year and a half, it’s time to revisit how companies have adopted these technologies to optimize their supply chain processes and determine how they can continue to evolve.
Over the past few years, supply chain challenges posed by global pandemics, extreme weather events, Brexit and labor shortages have prompted many companies to review their strategies and invest in technology to help bypass disruptive bottlenecks. According to the Wall Street Journal:
“Transportation bottlenecks and shortages of everything from semiconductors to chicken wings are drawing more attention to technologies aimed at streamlining supply chains and making distribution networks more efficient. Companies are also looking to automation and software to help curb rising logistics costs , and meet the growing demand for e-commerce and delivery services.”
As Harvard Business Review reported in September 2021, enterprise adoption of AI has skyrocketed since the start of the pandemic, but adoption for supply chain issues is still in its infancy:
Leading Businesses Are Incorporating Ai Into Their Supply Chain Processes To Gain A Leading Edge
“AI-driven supply chains are still in their early stages, with a survey released by the U.S. Center for Productivity and Quality finding that only 13% of executives expect AI or cognitive computing to have a significant impact in the coming year. Another 17% Humans are expected to have a modest impact. Businesses still rely on manual methods to monitor their supply chains – and those that adopt AI in the coming months and years will realize significant competitive differentiation.”
While the challenges of the past few years have exposed many problems with the company’s supply chain processes, efforts to address them have been plagued by current thinking rather than forward thinking. Investments in technologies that solve specific pressing problems often replace investments in technologies that prevent future problems. In some ways this makes sense: plug the holes that let water into the boat before worrying about pushing it ashore. Problems come when companies only focus on solving immediate problems. Once the holes in the boat are plugged to prevent it from sinking, rowing against the current results in slow progress and is easily overtaken by competitors with outboard motors.
As Harvard Business Review points out, “Those companies that adopt AI in the months and years ahead will achieve significant competitive differentiation.” As AI becomes ML, it can do so in ways that manual processes cannot. way to optimize supply chain operations. By ingesting vast amounts of data, ML can quickly spot trends and make recommendations for immediate improvements, whether or not global supply chains are still stuck in bottlenecks. It learns, optimizes, informs, simplifies, validates, and scales, all in a more time- and cost-effective manner.
Every organization creates vast amounts of data with every supply purchase, manufacturing order, warehouse and retail point replenishment, customer interaction, sale, order shipment and return. Even a small part of it—such as an order shipment—generates a lot of data, including:
Reducing Supply Chain Costs With Artificial Intelligence
For organizations that ship thousands, tens, or even hundreds of thousands of packages a day, the volume of data can easily overwhelm and bog down human analysis. Add data from every other point in the supply chain, and it becomes clear that optimization opportunities can easily go unnoticed. Machine learning can reduce this possibility and reduce the burden on employees.
If the analysis of the Harvard Business Review report is as expected, fewer than 30 percent of executives foresee AI and ML having any impact in the near future. It’s a huge flashing red light that indicates a significant advantage to forward-thinking organizations. Investment in supply chain technology has boomed, but it’s focused on short-term needs. When these organizations invest only in plugging the holes in their ships, they are likely to find that the competition has left them behind.
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Benefits Of Artificial Intelligence In Supply Chain Management
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