Putting the AI in Inflation
When it comes to earnings reports, Apple and Amazon usually beat the Wall Street estimates. But this was not the case during the latest quarter. One of the main reasons: the escalating costs of the global supply chain.
In the case of Apple, the company reported a $6 billion revenue shortfall because of the delays with its iPhone and other products. And for Amazon, it spent an additional $2 billion to handle the challenges. Unfortunately, both companies indicated that the supply chain issues will continue into the all-important holiday quarter. And, of course, there are many other companies facing a similar predicament. In fact, companies like Hershey and Kimberly-Clark have slowed their advertising expenditures because they cannot adequately fulfill orders.
How did the global economy get to this point? What can be done? Perhaps technologies like artificial intelligence can help?
How the Economy has Impacted the Supply Chain
The Commerce Department’s latest report of the U.S. GDP (Gross Domestic Product) was a major disappointment. The annual growth rate came to 2%, while the consensus estimate was 2.8%. By comparison, in the prior quarter the GDP came in at 6.7%. According to the report, the deceleration in the growth was due primarily to disruptions and lower supply.
“There has been a lot of media coverage about the growing number of ships waiting to offload cargo in the port of Los Angeles,” said Sean Hughes, who is the AI Ecosystem Director at ServiceNow. “Increasing the number of available workers and shifts helps get containers onto the piers but moves the bottleneck somewhere else. Suddenly you need more forklifts, trucks, fuel, tires, drivers, mechanics, and storage facilities than existing suppliers can provide.”
The supply chain problems are likely not to be short term. In a survey from the Wall Street Journal, about 45% of economists believed that it would take until the second half of 2022 for there to be improvement.
“Over the foreseeable future, we will continue to battle with uncertainty introduced by the pandemic, potential geopolitical flare-ups in tariff and trade wars, and challenges related to climate and sustainability,” said Puneet Saxena, corporate vice president of supply chain planning, Blue Yonder.
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What is the Cause of the Supply Chain Woes?
The main catalyst for the supply-chain problems is the COVID-19 pandemic. The shutdowns made it extremely difficult for manufacturing as well as predicting demand. Then there were bouts of panic buying, which resulted in shortages of many consumer items like paper towels and toilet paper.
“Disruptions due to the pandemic severely broke software analytical models and made them unusable,” said Sri Ambati, CEO and founder, H2O.ai.
But there were certainly other events that worsened supply chain woes. In March, the Evergreen container ship ran aground in the Suez Canal and this blocked shipments for six days.
There have also been secular trends that have made the global supply chain vulnerable. “First, we moved our manufacturing sites to low-cost regions, often far away from the end consumers,”says Adam Kline, director of product management, Manhattan Associates. “Second, we took a very lean approach to inventory management—opting to analyze and forecast the exact amount of inventory needed to fulfill demand—to reduce overhead. Last, but certainly not least, we have seen a reduction of labor resources throughout the supply chain, as distribution centers and trucking companies struggle to fill their ranks.”
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Apply AI to the Supply Chain
AI, machine learning, and analytics are nothing new with the supply chain. “Artificial intelligence is already in use for predicting consumer demand better, predicting supply disruptions and prescribing corrective action even before the problem occurs,” says Saxena.
Yet there are inherent problems, such as the fragmentation of data. If artificial intelligence is to realize its potential, there will need to be much more integration and sharing.
“One way we’re advising clients to focus is on unified demand planning,” says Manish Sharma, group chief executive at Accenture Operations. “This integrates all of the available internal and external—and often real-time—data across every process and every function within an organization to completely transform the approach to forecasting and planning demand.
“As a result, companies are better positioned to meet demand, avoid being surprised by disruptions or changes in conditions, and even eliminate unnecessary shipments and, thus, fuel use and emissions.”
Historically, supply chain technologies have focused on mitigating costs. But this has actually exposed the system to risks. There really needs to be a broader approach to the supply chain.
“When a furniture factory shuts down in Vietnam, or a toy shipment is stuck in a closed port, you must have a ‘Plan B’ for your key products or components,” says Richard Howells, SAP’s Vice President of Digital Supply Chain.
He also recommends other actions, including enhancing visibility by using techniques like sentiment analysis—such as with social media—to forecast demand; incorporate inventory optimization across a company’s whole network; and be more responsive to changes in the planning cycle.
“By leveraging AI to help identify alternative sources of supply and network design to balance off-shore, near-shoring, and on-shore suppliers and contract manufacturers, you can significantly reduce the risk of disruption,” says Howells.
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