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AI In The Supply Chain

Posted: May 22, 2018 8:28:00 AM

The globalization of supply chains has allowed trade to flourish, but added layers of complexity and cost. Companies are racing to find ways to operate more efficiently and affordably without undermining the integrity of the supply chain — and those who figure it out first will lead the industry. Artificial intelligence presents a huge opportunity to win that supply chain race for perfection, helping businesses save time and money with advanced machine learning.

What is AI?

In simple terms, artificial intelligence (AI) refers to activities performed by machines that mimic human work and behavior. Big data “powers” the artificial neural networks of these deep-learning machines, which can then perform a variety of tasks like reasoning, problem solving, learning, planning, and more.

At Gartner’s Supply Chain Executive Conference, Gartner analyst Noha Tohamy grouped AI into two categories:

  1. Augmentation: Assisting humans in daily tasks to reduce errors due to bias or fatigue
  2. Automation: Working completely autonomously in any task or activity, without human assistance

What’s important to remember is that any type of AI must be informed by a massive amount of up-to-date, accurate data to effectively improve supply chain operations.

The Need For AI in the Transportation Industry

McKinsey Global Institute’s report “Notes from the AI Frontier: Insights from Hundreds of Use Cases” states that AI, compared to other analytics techniques, can improve performance in the transportation and logistics industry by 89 percent. The McKinsey report also asserted that AI will create up to $500B in value for transport and logistics alone, which accounts for over 6 percent of industry revenues.

Additionally, MH&L found that the average U.S. business loses over $170K annually due to outdated payment processes (using manual systems, fixing errors, responding to suppliers, etc.) within the supply chain. A significant portion of these payment challenges could be improved, or eliminated, with AI and would save logistics businesses thousands.

Though there is a clear need in the transportation industry for AI technology, it’s equally as clear why most companies are not using it — deploying AI is complex and expensive. The volume of data needed to fuel AI systems requires companies to heavily invest in updating IT infrastructure, hire data scientists, and plan for wide-scale operational integration. Yet most experts agree that it’s only a matter of time — the global supply chain will continue to evolve, with more and more elements being run by intelligent machines.

Revolutionizing the Supply Chain With AI

As AI slowly eases its way into transportation and logistics companies, the wildest possibilities seem achievable with advanced machine intelligence. Here are a few examples of how AI can revolutionize supply chain operations:

  • Communications: Chatbots can handle purchasing requests, answer internal FAQs, manage templated documents, process payments, interface with suppliers, and much more. These AI communications functions will eliminate hours of mindless busy work and free up employees to focus on higher level, valuable functions.

  • Forecasting: Using internal data, advanced algorithms, online browsing statistics, social media activity, and more, AI can collate and analyze big data sets to predict and balance supply and demand. Forecasting becomes an exact science instead of a guessing game and businesses can make intelligent decisions that limit risk.

  • Delivery Routes: Logistics-based AI functions work to ensure prompt deliveries and lower costs. AI can predict heavy traffic and poor weather, advising trucks or planes to reroute to avoid delays. AI sensors on trucks can also monitor the vehicle and driver to collect data on how to maximize fuel efficiency and reduce maintenance.

  • Autonomous Vehicles: Already in beta tests, autonomous vehicles have the potential to drastically transform the entire supply chain. Because autonomous vehicles can be on the road 24 hours a day (compared to the 11 hours a day human drivers are legally allowed), the technology would effectively double the output of the U.S. transportation network at 25 percent of the cost.

  • Natural Language Processing: AI can be a supply chain translator. It can efficiently decipher data in foreign languages to build data sets that connect and optimize each segment of a global supply chain.

Ready or not, the logistics and transportation industry is careening toward supply chains powered by machine learning. AI can be a huge benefit to supply chain managers, but only if it is informed by solid data and smoothly integrated into existing operations.


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