Investing for growth in the data economy

Money makes the world go around and this has never been more true when it comes to the data economy as innovative start-ups seek investment to achieve their ambitions and unlock their potential. Led by insight from Atomico and Realm, this piece - the fifth in our data economy series - will look at the data economy from an investment perspective - what traits do they look for in data-driven companies? How are start-ups approaching it? These are the questions this piece will answer. You can find the earlier pieces in this series here

If money makes the world go around, then data is the axis on which it rotates. Since the first wire money transfer, conducted in 1871, money and data have been indistinguishable.

Today, more than 150 years later, the connection between the two is stronger than ever, for one, simple reason - user data has become the most in-demand commodity of the twenty-first century.

Building empires with user data

Understanding who users are, what they do, and how they interact is the driving force behind today’s businesses. It’s what the likes of Meta, Amazon and Netflix have built their empires on. But behind those businesses, away from the product innovations and branding-razamataz are the early stage investors. The financial backers that see the potential in data-based companies long before they become the hugely influential businesses we see today.

It’s their commitment to invest in businesses rooted in data that is fuelling the data economy we see today. Despite some challenging and well-publicized macroeconomic issues in recent times, the European investment landscape remains reasonably positive, attracting more than $5bn in the first quarter of this year alone - much of it into data-driven companies. A point made by Luca Eisenstecken, Partner, Atomico, who recently told us,

We love data-driven businesses at Atomico and, as matter of fact, we’re a data driven VC ourselves so we understand how important that is. And at this point in time, it is paramount and table stakes for any company to be data driven.

VC’s back innovation, but they also need to keep innovating themselves to stay competitive and that’s why we are seeing more funds investing in data and research teams to make sense of it. According to this report, more than a third (35%) of VCs globally say data tools are responsible for sourcing at least half of their deals. It also found 190 ‘data-driven’ VC firms — all of which have at least one engineer on their team, and have developed at least one piece of internal tooling.

This isn’t bandwagon jumping either. Its clear data delivers the types of numbers VCs like Atomico crave. A McKinsey study found that data-driven organizations are 23 times more likely to acquire customers, six times more likely to retain customers, and 19 times more likely to be profitable.

Countries on a technology mission

Investing in the data economy isn’t confined to forward-thinking investment firms. Nations, too, are getting in on the act in order to best position themselves for competitiveness in the future. Only a matter of weeks ago, four major tech firms based in the US committed to the UK as the place to invest in data centers, fueling Britain’s economic growth and spurring on AI development. Indeed, the UK is in the middle of a ‘technology mission’ that will see it invest £250 million to enable new and existing capabilities and capacity in artificial intelligence (AI), quantum technologies and engineering biology by the end of next year.

This type of financial backing is happening all over the world. For instance, Finland has a specific Data Economy program designed to encourage Finnish companies to develop international businesses based on the utilization and sharing of data with the backing of a €135 million pot.

New companies creating category-defining software

This kind of backing is why we’re seeing data-based start-ups become so influential. These companies are providing category-defining software rooted in the power of data. They are agile and able to flex to the data they have and the demands of the economy they’re operating in. By doing so, they’re filling a considerable gap that enterprises of the early part of the century created and are now too cumbersome to fill.

As we start to see some early entrants into the data economy mature and become established businesses, these organizations are keen to avoid the oversight of their predecessors. It’s why almost all the major technology companies have programmes specifically designed to cultivate the next-generation of start-up. Amazon and Google are two of the more famous ones but there are many others.

They are ecosystems designed to give back. Where big companies give the helping hand to start-ups that they wanted but never had. It’s also a mechanic to bring different elements, skills and backgrounds together in the hope that better and more productive companies are created. As explained by Andra Nuta, manager of Aiven’s Cluster Startup Program which offers qualifying start-ups credits to use on any of its services,

There are so many different parts to the data economy ecosystem. However, what happens is new start-ups emerge that connect multiple different elements and make them all work better for increased and shared benefits.

The ironic edge of data

Today’s start-ups have data at their core. They are all data-based businesses and are making it their mission to make the world ‘work’ better through the products and services they are creating. As explained by Miika Huttunen, founder of conversational AI start-up, Realm, which is part of Aiven’s Cluster startup program, who said,

In the world of AI and large language models, documentation and data produced in the universe has a huge value. Companies that have a strong documentation culture in place and are rigorous about how they handle data will have an edge in the future.

There is an irony to the fact that companies, investors and countries are looking for data to give them an edge. This is because the environment in which this is happening is as circular as they come - data needs investment, investment needs data, data produces money, money produces investment, and around we go.