The global business landscape is once again grappling with the repercussions of supply chain disruptions, this time attributed to ongoing Covid-19 lockdowns in China. The impact of these lockdowns has been felt acutely in the Port of Shanghai, a key hub for global trade.
Since March, container dwell times have surged, leading to delayed or even canceled cargo deliveries to and from the Port of Shanghai and other Chinese ports. In fact, the number of container vessels awaiting clearance outside Chinese ports has skyrocketed by 195% compared to February figures.
The Port of Shanghai, responsible for handling approximately a fifth of China’s export containers, has seen a dramatic decline in shipment volumes, with reductions of up to 85%. Consequently, businesses worldwide are grappling with substantial delays in their supply chains, with waiting times at Shanghai marine terminals soaring by almost 75% since the onset of the lockdowns. As a result, ships have diverted to alternative ports like Ningbo and Yangshan, but these too are experiencing congestion.
This disruption is poised to have far-reaching repercussions on global shipping schedules throughout the upcoming summer and fall seasons. Companies heavily reliant on freight transportation are feeling the pressure to expedite supply chain bookings in anticipation of worsening congestion in the weeks to come. Simultaneously, businesses are bracing themselves for potential inflationary conditions due to product shortages, occurring in tandem with rising inflation rates in the United States.
It is evident that such supply chain disturbances, like the one witnessed in Shanghai, are likely to recur periodically. Regrettably, many businesses, including retailers and consumer packaged goods (CPG) firms, are inadequately prepared to manage global-scale disruptions. The persistence of global supply chain interruptions, coupled with inflationary pressures and the emergence of new COVID-19 variants, has consistently disrupted essential functions such as demand forecasting.
In light of these challenges, it is incumbent upon businesses to proactively plan for disruptions by harnessing the power of artificial intelligence (AI) in conjunction with third-party and first-party data. This enables them to monitor rapidly evolving conditions in real-time and adapt their processes, particularly in the realm of demand forecasting.
Third-party data sources, such as weather forecasts and satellite imagery depicting port traffic, offer companies an up-to-the-minute overview of factors that can impact supply chain operations. For instance, insights from third-party data can help a U.S.-based retailer gain more precise visibility into how congestion might affect cargo ships en route to U.S. ports over the span of several weeks. Armed with this data, the retailer can make more accurate projections about supply disruptions, cost implications, and pricing strategies.
Furthermore, businesses can enhance their decision-making by amalgamating third-party shipping and weather data with consumer-generated data, such as Google search trends, to align supply with demand at regional levels. This is crucial since the impact of a supply chain crisis varies across different regions in the United States. For instance, a shortage of rain-repellent clothing will have a more significant impact on retailers in Seattle during the summer than on retailers in Phoenix.
The sheer scale of data involved in this process is beyond human capacity to monitor, assimilate, and analyze effectively. Therefore, machine learning, a form of AI, is indispensable. Machine learning algorithms can sift through vast amounts of third-party data to uncover patterns and associations that would elude manual analysis, especially those nonlinear connections crucial for demand forecasting, such as search behavior where purchase intent isn’t always apparent.
The synergy between machine learning and real-time data can be a potent combination. By applying machine learning to real-time third-party and first-party data, businesses can:
- Prepare for impending disruptions through scenario planning. CPG firms and retailers can conduct “what-if” analyses using computer simulations, allowing them to anticipate the impact of potential disruptions and formulate corrective actions well in advance. They can also assess the ripple effects of disruptions, considering factors like product shortages and fluctuating fuel prices across different regions.
- Gain real-time visibility into inventory status throughout the supply chain. This includes tracking the precise locations of trucks that may be unable to deliver goods to critical ports. This level of visibility empowers retailers to adapt their in-store sales strategies for major seasonal events effectively.
In conclusion, amidst global uncertainties, including conflicts, ongoing pandemics, inflationary pressures, and fuel shortages, businesses must embrace a new paradigm. By combining AI with machine learning, they have a powerful toolkit at their disposal, enabling them to achieve more predictable outcomes regardless of the market disruptions that lie ahead.
Your source for supply chain report news updates: The Supply Chain Report. For international trade insights and tools, head to ADAMftd.com.
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