The effect of war on global supply chain sentiment –

The effect of war on global supply chain sentiment


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The Effect of War on Global Supply Chain Sentiment: Summary

As we approach week four of the Ukrainian crisis, we present our initial findings on the effect of war on global supply chain management.

Following Russian troops across international borders on Feb 24 has seen a major impact on global supply chains in particular in US, UK and Germany. We are seeing the biggest network effects on global supply chain management in the banking system, oil and gas and mining.

Key stats on the effect of war on the global supply chain:

  • 200+ global listed companies with direct partnership links to the 5 key Russian state assets (Gazprom, Sberbank, Rosneft, Aeroflot, VTB Bank).
  • 3000+ listed companies will be next impacted.
  • Sberbank Ad Banka Luka, Royal Dutch Shell, Equinor Asa, Yandex NV and Mastercard amongst the most affected companies.
effect of war on global supply chain

Highlights By Sector

Banks: Amongst the biggest sectors hit is the international banking sector, while European bank stocks have lost than a fifth of their value amid the Ukraine crisis, the main damage to banks are the threats to the world economic outlook and prospect of higher interest rates and loan defaults.

Oil & Gas: Shell, BP and Norway’s Equinor have all announced termination of ties with the Russian oil industry – a move requiring substantial balance sheet write-offs. 

Defence: Airbus pulls of it’s support services agreeements with Russia

Automobile: France’s Renault has major export dependency into Russian market will lose close to $5bn in revenue, should they terminate the deal.

effect of war on global supply chain

The Future Effect Of War On Global Supply Chain Management

We anticipate more supply chain effect data in the coming months. Permutable scans over 55 million extract data points from over 23,000 sources around the world covering over 120 countries of reporting.  

The analysis was produced by our RnD team specialising in natural language processing (NLP) and in particular name entity recognition (NER / GENRE). 

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