Blockchain Analytics Firm Nansen Lays Off 30% of Its Staff

Blockchain Analytics Firm Nansen Lays Off 30% of Its Staff

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Alex Svanevik claimed the reduction will help “to create the right conditions for those who stay with <the company>.” 

Nansen, a prominent blockchain analytics platform, has confirmed a 30% reduction in its workforce.

The news was revealed by the company’s CEO, Alex Svanevik, via Twitter on May 30th, disclosing the company’s “extremely difficult decision to reduce the size of the Nansen team.”

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Svanevik pointed out two primary factors driving this significant team reduction. The first reason, named by Svanevik, was linked to Nansen’s rapid expansion during its initial operational years. According to Svanevik, the accelerated growth led the organization to venture into areas that deviated from Nansen’s core strategy.

The second factor, as pointed out by the CEO, was the turbulent market conditions. Svanevik stated that despite Nansen’s endeavors to diversify its revenue streams by catering to enterprise and institutional customers, the company’s cost base remained high in relation to its current status.

Svanevik also confirmed that employees affected by the layoffs would be provided with severance packages.

This news follows a trend in the crypto industry, which has seen several mass layoffs, although the rate of these job cuts has significantly decreased in recent months.

Earlier this year, Coinbase, a prominent cryptocurrency exchange, disclosed a 20% workforce reduction, equating to approximately 950 employees. The decision was attributed to Coinbase’s attempt to reduce operational costs by around 25% amidst an enduring crypto winter.

Similarly, a crypto venture capital firm Digital Currency Group (DCG), had to lay off more than 500 employees from its owned companies at the start of the year.

The decision of Nansen to cut down its workforce underlines the impact of volatile market conditions on the crypto industry. As companies like Nansen strive to adapt and build sustainable business models amidst these challenges, such decisions may become more common.


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