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Improving Pandemic Preparedness

Recovery Diva

A significant strategic issue emerging from the pandemic seems to me to be this: In almost every country, the Covid pandemic required management skills and capacity beyond those available in ‘business as usual’ within the government structure.

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Four Questions About the Covid-19 Pandemic

Emergency Planning

What are, and have been, the key challenges in coping with the Covid-19 pandemic? Viral pandemics can have impacts that are as significant in the socio-economic field as they are in epidemiology and viral medicine. Hospitals need to develop very substantial surge capacity and greatly increase their infection control measures.

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Business, Interrupted: Peeling Back the Layers of Supply Chain Resilience

Castellan

While the pandemic certainly has shone a light on supply chain resilience issues, it’s not a new problem for the industry. That was a similar experience for others during the height of the pandemic in 2020 and into 2021 where container shipping was significantly impacted. The More Supply Chains Change, the Same Issues Pop Up.

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Navigating the Supply Chain Crisis

Risk Management Monitor

Extraordinary congestion at critical global ports, decreased availability of key raw materials and component parts, rising freight bills and an increasingly tight job market have all contributed to the need for companies to create an effective logistics risk management program.

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The Ukraine Invasion: What Are the Impacts on Supply Chain Dynamics?

Fusion Risk Management

Logistics Route and Capacity Constraints : Supply chain transportation and freight is already being impacted across the globe. These decisions will have a direct and immediate impact on the cost of logistics and freight-based travel. .

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Top 9 Considerations for Enterprise AI

Pure Storage

This is especially critical when there is data drift or concept drift, which was seen a lot during the pandemic era. Without traceable provenance and log analytics on such facets of data in the storage system, the enterprise AI/ML processes can slow to a crawl and/or decrease in accuracy. Consider data drift and concept drift.