Using data for good in a more connected world

It is estimated that as much as 90 per cent of the data in the world today has been created in the last two years alone. With this abundance of data available, an important question is how we can use it to make a positive difference in the world. To learn more, we caught up with Yuri Horvath, CTO of start-up accelerator 1776 and the brain behind their new global start-up platform, UNION.

As a business, data is not just your friend, it’s your everything. Whether it’s improving customer engagement, optimising operations or mapping revenue sources, data allows you to make informed decisions and address risks appropriately. As data has expanded exponentially in its velocity and variety over the last decade, making use of it has become more important than ever.

Maximising your use of data is exactly what Yuri Horvath’s background is in. As a self-confessed ‘data geek’, her career as a software developer has seen her work with media, government and financial services institutions to discover how data can improve the way our world works.

“There has definitely been a trend towards more transparency in data,” Yuri explains. “There is much more data in the public sphere that’s accessible through things like APIs (application programming interfaces) which then leaves it up to the masses to figure out how they can use this data for something more interesting.

“Let’s take the transportation industry. In a lot of cities they’re putting out data out like the bus schedules and the GPS coordinates of buses currently in use. But at the same time, you’ve got different cities putting this data out in different manners. As a result, you have companies working on standardising it across all different cities. They’re able to tell you that your next bus is coming in five minutes and the fastest and most cost-effective ways of getting to different places, all allowing you to make the right choices.”

This development has taken place for many reasons, but largely because it’s now much easier and cheaper to work through such large calculations. In essence, much less infrastructure is required to crunch numbers, and hence data is much more accessible. 

As an accelerator, 1776’s work focuses on helping start-ups across the world develop and grow to solve the world’s most critical challenges. Over recent years, the number of accelerators like 1776 has increased significantly. In fact, in the US alone this number increased from 16 in 2008 to 172 in 2015. The team at 1776 saw this expansion of accelerators alongside the growth in data as a major opportunity. UNION was born. 

UNION is a digital network and platform that catalyses innovation by uniting start-up ecosystems around the world. It connects different start-up incubators across the world and analyses the data held within each one. As Yuri explains in her recent medium post on UNION’s development, “By connecting these programs together, the whole becomes much greater than the sum of the parts. A fintech start-up in Nairobi can connect to a banking mentor in New York. An education start-up in Baltimore can connect with a charter school innovator in Austin. And UNION does this seamlessly based on data.”

UNION now has more than 4,000 start-ups and 1,000 mentors in the system. And it’s only just getting started. The reason why UNION is so effective is because data is unbiased. In real life, all sorts of externalities dictate why connections between different people happen. Whereas if you use data, you are matched with people on the basis of skillset and need. The latter represents a much more effective and efficient method of helping people work together. 

The data also allows for the discovery of different trends. “Let’s say there are different companies all making micro solar grids with technologies that are 90 per cent similar,” Yuri says. “They will then all have slightly different business models, methods of going to market, talent pools and company cultures.”

Using UNION, 1776 are able to use data from all these start-ups to find out what works beyond the technology that dictates which of these companies is most likely to take their business to the next level. The result is that these learnings can be shared publically, for the benefit of all. Take a read of 1776’s ‘Innovation that matters’ report as an example of their analysis of entrepreneurial cities across the US. 

But it’s not all plain sailing, there are hurdles. “Right now are bound to ecosystems where English is more prevalent,” Yuri explains. With products, courses and mentors that are all either written in English or English-speaking, this limits expansion. That said, Yuri explains that 1776 are currently working on translating their content and expertise with the aim of sharing skills and learning with more people worldwide.

Data security is another relevant issue. As the availability of data increases, those who hold that data become increasingly responsible for looking after it. “The reason why that’s really important is because people provide data and participate in systems that have data APIs because they think there’s a positive end to it and they’re getting something out of it. If there’s ever a negative impact of using these systems then people will start holding back,” Yuri explains.

But Yuri remains positive towards the future of data security for a couple of reasons. First, she predicts that our threshold for the information we hand over will naturally lower as we continue to see the benefits that access to this data provides. Secondly, the government’s role will be to restrict access to data that should not be available. “For small companies that are out there moving fast, it’s good to have hard lines that are non-negotiable and certain areas you can’t experiment around, like people’s medical history,” she says.

The future of data is undoubtedly exciting, characterised by increased accessibility with lower barriers to entry to make use of what’s available. As we give up more of our information, it’s important we stay up to date with experts like Yuri to make sure we stay ahead of the curve. 


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