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How Distributed Teams Help Solve Some of the Problems Facing Europe's Startups As a whole, Europe's tech scene lags behind the U.S. and China.

By Jan Erik Solem Edited by Dan Bova

Opinions expressed by Entrepreneur contributors are their own.

You're reading Entrepreneur Europe, an international franchise of Entrepreneur Media.


European tech continues to rise. A May Tech Nation report shows that the U.K. tech sector raised almost twice as much venture capital in 2017 as it did in 2016, attracting more investment than France, Germany and Sweden combined. This is particularly remarkable as France alone raised 31 percent more venture capital in 2017 than it did the year before, and Sweden continues to punch way above its weight on the global tech scene.

Related: How Being on the Fringes of Europe Gives Our Company a Global Edge

In spite of all this, there's little doubt that Europe as a whole is lagging behind both Silicon Valley and China, and no wonder -- European tech companies don't have the immediate market size that both American and Chinese startups do. This means two things. First, thinking globally from Day One is crucial for any European startup that wants to succeed. Second, you need an internationally diverse team to help get you there.

Other than startups needing diverse teams, the need for, for instance, machine learning engineers has gone up by 485 percent between 2014 and 2017 in the U.K. alone. Limiting hiring to one or a few locations where you have physical offices means you have to compromise based on the talent distribution in that location, and the more specific your position is, the worse this problem becomes. You might have to compete aggressively for sought-after positions, or have a very small pool to recruit from locally. And to make matters worse, local hiring in Europe also often means low diversity.

So, what can European startups do to ensure that they think globally, have access to a global talent pool and hire a diverse team? At Mapillary, we're over 40 people across seven different time zones. We only hire the best of the best, and let them work from wherever they want -- usually where they live, or in rare cases, where they've always wanted to go and visit for a longer period of time. Working with online tools like GitHub, Slack, Google Drive and Hangouts allows us to remain a closely knit organization, even though some of us are thousands of miles apart.

Related: My Italy-Born Company Opened an U.K. Office So We Could Be Global From the Start. Here's What We Learned Scaling Internationally.

Operating a fully distributed team solves several issues that European startups are currently facing -- it means that you have a global talent pool, local networks and insights into several different markets, and, of course, a diverse team. And from a worker's perspective, we know that retention and worker satisfaction tend to be higher where there's more flexibility. Mapillary's retention rate of 97 percent, calculated over the course of the four years since we started, testifies to this. Considering how poor staff retention rates tend to be in the tech sector, this is a remarkable number -- and I'm sure our distributed approach plays a role in this.

There's another huge competitive advantage that is rarely spoken of when it comes to operating distributed teams -- radical transparency. If you're fully distributed, all your communication needs to happen in the open to make sure that people keep tabs of what other teams are working on. Roughly 85 percent of all our conversations at Mapillary happen in open channels, available for anyone in the company to see. The importance of transparency shouldn't be underestimated in maintaining an inclusive culture. While European entrepreneurs should look toward Silicon Valley for extraordinary growth stories, they should also learn from Silicon Valley's mistakes. Operating a distributed team taps into both.

Jan Erik Solem

CEO of Mapillary

Jan Erik Solem is the co-founder and CEO of Mapillary, a street-level imagery platform that uses computer vision to extract map data at scale. Solem is a computer vision specialist and a former math professor, and has authored several books on computer vision.
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