Can Artificial Intelligence Save America From The Global Supply Chain Disaster?
The issue facing the world today is not simply “THE supply chain,” the issue is that nearly every single link in the supply chain is compromised. Human talent is less available and manufacturers fear this will become a permanent reality, even after the pandemic. Extreme weather events occur every month and the ongoing pandemic is also causing shortages of direct and indirect materials. In turn, shipping costs have risen sharply. The status of sheet metal, computer chips and all food ingredients are up in the air. Constraints on the supply of raw materials, including those needed for semiconductors, PPE and various plastics, have led to factory shutdowns. A chronic lack of truck drivers has every neighborhood filled empty store shelves staring back at its citizens. And, to no surprise, Inflation was just reported at 5.4%, which is a 13 year high.
Now consider that only 4% of supply chain leaders believe their operations are future ready. We are at the precipice of either complete disaster, or a brave new world.
How we got here has been hashed out and rehashed again and again. Yes, studies do need to be conducted on where every breakdown was, who should be held accountable and how. But, for the sake of my work here, I will focus on a solution moving forward to our current crises and prevention of the next supply chain catastrophe.
AI as the Solution
Per Infoholic Research, AI in the logistics and supply chain market is predicted to grow at a CAGR of 42.9% over 2017-2023 to reach USD 6.5 billion by 2023. Leveraging AI to its maximum potential in supply chain technology is paramount in our race to solve the crises of the day. We can use AI to drive scale and efficiency through new distribution models including direct to consumer, click and collect and subscription, harnessing the automation in the full supply chain ecosystem by improving interconnectivity across customers, partners and suppliers.
Cognitive automation
Forecasting for Process Optimization
Predictive insights driven companies predict, prepare and see issues that may disrupt their abilities to deliver products enough time in advance to make necessary adjustments to their processes to prevent disruption. They also possess advanced planning solutions to better sense changes in demand and supply to accelerate the ability to respond. These companies are also predicting delivery routes by enhancing communication between a multitude of global supply chain participants to efficiently transport, pick up and deliver shipments. Not to mention often overlooked disruptors to the supply chain such as forecasting wear and tear of machinery and improving the overall equipment effectiveness index and predicting fuel usage for fleet optimization.
Supply Chain Resilience
AI technology will be used to learn and then show how to handle massive shocks to the supply chain. Through this a ‘self-healing’ supply chain dataset will emerge, using AI to help identify and correct data issues in real-time. This then leads to agility and flexibility and end-to-end control to enable real-time visibility of supply chain performance, risks, opportunities and events and allow leadership teams to make better informed end-to-end decisions
AI assistance with skills shortage
Machines will be working closely with Humans assisting in all stages of production, from checking the quality of our ingredients and parts all the way to final assembly and shipping of products to end consumers including automated driving . Some have said the “weakest link" in the global supply chain may be the shortage of truck drivers. Through automation of driving and automation of recruitment and vetting of human truck driving job candidates weeks if not months of delay in hiring qualified and certified truckers around the globe will be removed.
8 Examples to Monitor and Model
Walmart teams up with Ford
Wal-Mart Ford and Argo AI to deliver goods to customers' homes via self-driving vehicles. Initial pilot programs will run in Miami, Washington, D.C. and Austin, Texas and then expand once deemed successful.
DHL created a machine learning-based tool for predicting air freight delays
The machine analyzes 58 different data points and predicts daily delays or speedups up to a week in advance while simultaneously pinpointing the main reasons for delays.
FedEx SameDay Bot
The SameDay Bot combines Lidar and standard cameras to bring packages the last mile. These are tested and proven to avoid collisions and increase efficiency.
Fizyr created software products for automated picking and placing in harsh logistics environments
Fizyr’s software integrates with any camera, robot, and end-effector so businesses can choose what best works for their needs. There are over 100 grasp poses each second through their algorithm and there are different classifications so it knows how to handle different kinds of objects.
Nuro’s Delivery Robots
Nuro makes R-1 robots that can carry products onto ships or trucks, cross sidewalks, and climb stairs to make deliveries. They are very slim making them a safe alternative to other robotics.
Robby Technologies’ autonomous vehicle
Powered by advanced AI their vehicles can navigate roads, sidewalks, pedestrians, and rail crossings. It also featured conversational AI for increased human-machine interaction.
DigitalGlobe’s satellite imagery for ride-sharing
Their satellite images provide the input for the creation of advanced mapping tools. This allows for increases in precision of pick up, navigation, and drop off. Their satellites detect new road-surface markings, lane information and street-scale changes to traffic patterns.
Alloy.ai’s Point of Sale Based Predictions
Alloy.AI has designed a machine learning platform that continuously monitors incoming data from Point-of-Sales and several other sources. It then takes this data to map all sales to better predict demand in the future. This allows companies to better plan ahead what they will need and when, thus decreasing bottlenecks and shortage of goods.
AI to Predict the Next Pandemic
The above solutions are all incredibly valuable to correcting our supply chain issues in the present, and increasing efficiencies going forward. But, the genesis of our current crisis is the Covid-19 Global Pandemic. Though you often hear people say, “There was no way to predict something like this” that may no longer be the case.
Researchers from the University of Glasgow used viral and human genome Trusted Source sequence features to develop machine learning models to predict the likelihood of an animal virus possibly jumping humans. The ability to predict this movement is a huge win for the world. If scientists and governments know which virus to track they can then hone in on infections before they become outbreaks to stop the spread.
In Germany, a new global data hub to detect emerging pandemic threats is being created. This will be the WHO Hub for Pandemic and Epidemic Intelligence and will quickly analyze data to predict, prevent, detect, prepare for and respond to risks worldwide. Research from places like the University of Glasgow being fed into the WHO Hub is exactly the kind of collaboration we need to ensure that A) we prevent a global health crisis that then B) turns into a global economic crisis that C) cripples the global supply chain that will D) lead to the elongation of the global pandemic.
The global pandemic will push more companies across the U.S. to explore their options to add AI to their supply-chain management platforms. Big wins will help companies around the world to build more resilient, agile supply chains that thrive in any business condition. Now is the time for businesses across the U.S. to fully embrace the power of AI for the good of not only their company, but every company in every link of the global supply chain.
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