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2020-03-06
As the global supply chain faces turmoil from COVID-19, shipping analytics software is helping companies adapt to unprecedented disruption. Shippers, container lines, and forwarders are now embracing predictive analytics for logistics to align capacity, demand, and delivery in real time. These digital tools are reshaping how global trade responds to crises.
Singapore-based startup Portcast has become one of the leading names in container shipping technology. Its predictive analytics platform enables carriers to adjust operations dynamically. According to Portcast, nearly 950,000 TEU of capacity was withdrawn from China to Europe during February 2020, combining the Lunar New Year shutdown with COVID-19-related blank sailings.
This removal caused a 75–80% drop in container demand, a level unseen in years. CEO Nidhi Gupta emphasized that while COVID-19 was unpredictable, the technology can still quantify demand fluctuations in real time, minimizing lost revenue from low vessel utilization.
Portcast’s subscription-based logistics analytics platform helps both carriers and forwarders optimize schedules. It analyzes internal shipment data and external risks to forecast utilization six to eight weeks ahead. With these insights, shipping lines can decide whether to skip ports or add blank sailings, maximizing their load factor and improving operational visibility.
“Dynamic capacity planning allows companies to shift supply where demand exists,” Gupta noted. “Even during the COVID-19 supply chain disruption, real-time adjustments improve efficiency and protect profits.”
While capacity reduction was the first challenge, demand decline soon became more severe. China’s Purchasing Managers Index (PMI) dropped to a ten-year low of 35.7, signaling a deep manufacturing slowdown. New orders, raw material inventory, and employment indexes all showed sharp decreases.
These numbers were worse than those seen during the 2008–09 financial crisis. Gupta pointed out that additional blank sailings in March further affected global flow, with over 250,000 TEU removed from China-Europe routes. Remaining capacity was used mainly for delayed shipments, not new production.
German startup xChange supported these findings, reporting an imbalance in container availability — surpluses in China but shortages in Europe and the U.S. Such mismatches underline the value of real-time logistics visibility offered by predictive platforms.
By processing carrier schedules, vessel positions, and port performance data, Portcast’s algorithms identify when disruptions, missed sailings, or weather delays may occur. This predictive capacity helps carriers mitigate 3–5% revenue losses during volatile conditions.
Carriers often change schedules 2.5 times per voyage, complicating coordination. Portcast integrates directly with forwarders’ transport management systems (TMS) and control tower solutions, giving users live shipment visibility. These integrations ensure transparency across complex supply networks.
Gupta explained that using AI-driven insights, forwarders can communicate accurate delivery times and adjust bookings proactively. The result is a stronger, data-driven response to uncertainty.
San Francisco-based ClearMetal offers another layer of innovation. Its predictive analytics for supply chains focuses on improving customer service and delivery accuracy. CEO Adam Compain described how shippers use data to predict when containers may be delayed, rolled, or transshipped.
Traditional logistics models rely on averages and static rules, but those fail under volatile conditions. “You can’t solve an evolving crisis with static systems,” Compain said. “Predictive analytics transforms data into dynamic insight, keeping customers informed.”
ClearMetal’s clients, including major beneficial cargo owners (BCOs), use the system to anticipate problems and maintain their service-level agreements during the pandemic.
Compain described a four-part “playbook” for data-driven logistics operations.
First, shippers identify regions most at risk — such as outbound lanes from China — and apply live filters for updates across thousands of containers. Second, they assess lead times and customer promise dates, determining which routes or carriers remain reliable.
Third, ClearMetal integrates with ERP and CRM systems through APIs, automatically updating delivery commitments. Finally, the company provides dashboards and customer portals to improve transparency for all stakeholders.
These systems don’t control the situation but enable companies to act as better partners. The result is faster communication, better allocation of resources, and stronger relationships with customers.
The COVID-19 pandemic exposed weaknesses in global logistics systems, but it also accelerated the adoption of digital technologies. Companies now see predictive analytics for logistics as essential, not optional. Real-time visibility tools enable shipping lines, freight forwarders, and BCOs to manage uncertainty effectively.
Predictive models help organizations shift from reactive decisions to proactive strategies. By continuously analyzing demand and risk, logistics providers can reallocate capacity and reduce delays before they escalate.
Furthermore, these tools foster collaboration across the entire container shipping technology ecosystem. When data flows seamlessly between ports, carriers, and customers, supply chains gain resilience.
The COVID-19 supply chain disruption revealed the limits of traditional planning. Yet, it also proved the value of shipping analytics software and predictive logistics solutions. Companies like Portcast and ClearMetal have shown that technology can turn uncertainty into foresight.
As industries recover, real-time logistics visibility and dynamic decision-making will remain vital. Those who adopt these digital strategies will not only survive disruptions but thrive beyond them. Predictive analytics is no longer a competitive edge—it is the foundation of the modern supply chain.
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