To understand data is to understand technology. Data is at the heart of today’s tech-driven world. There is more of it than ever before and it is growing fast. By 2025, there is expected to be 463 exabytes of data created every day around the world – the equivalent of 212,765,957 DVDs per day. Businesses are increasingly prioritizing putting data at the heart of everything they do: one recent survey found 83% CEOs want a data-driven organization.
The data economy is, in the words of IBM, built on the premise that “while data has no inherent value, its use does.” The data economy today is still mainly understood as the value exchange that occurs when users give their data to access digital services, which companies then monetize that data through advertising - a good chunk of available capital is still invested here today. We are now entering a new era where businesses are pushing to improve and broaden how they manage, analyze, and ultimately extract value from their data. This will expand both the definition and market potential of the new data economy, and as such there is a major opportunity for start-ups to capitalise on this moment, building the hardware and software that will enable such a paradigm shift in the enterprise.
Opportunities for growth
The size of this market opportunity is significant. The European Commission estimated that the value of the data economy of the EU27 was around €325 billion in 2019. By 2025 it is predicted to be more than €550 billion.
Beyond just user data monetization through ads and commerce, the modern utility of data extends across a range of different sectors and market segments in business. Automation is one such key area, with businesses particularly focused on ‘intelligent enterprise automation’: the use of intelligent automation technologies like AI, process mining, RPA, and document automation, to optimize and streamline processes such as customer service and many others all across the enterprise. There are already several trailblazers in this space, notably UiPath. Its business automation platform has transformed how businesses can free up workers from repetitive tasks, and focus on the work that delivers impact for the organization. In its fiscal year 2023 financial results, UiPath hit $1.204 billion in annual recurring revenue.
In the face of once-in-a-generation supply chain disruption, industrial users are also investing significant capital in using data to ensure a smooth and transparent journey for products from factory floor to the customer. German start-up Operations1 tackles this problem with its connected worker platform, built with data analytics at its core. Its success has been built on giving manufacturers a full view of processes, helping them see how tasks are being carried out, and empowering them to make data-driven decisions to optimize, streamline, and ultimately future-proof their operations.
Data also flows into building and enabling transformative technologies upon which the data economy is built: like AI, quantum, and API infrastructures. AI is attracting huge interest at the moment with the launch of GPT-4 and Google’s Bard. The opportunity for start-ups amidst all this noise is to help make AI, which requires special skills and often extensive programmes to implement, workable for enterprises. Swiss-based Latticeflow, for example, auto-diagnoses problems with machine learning models to ensure ML is trusted and continually optimized to deliver for the business.
And of course, there remains a massive opportunity to leverage data to create category-defining software. Start-ups have a crucial role to play as the connective tissue for businesses, providing them with the tools to start utilizing their data for competitive advantage and delivering an exceptional experience for customers.
Trust and transparency
As it is with consumers using digital services, building trust is at the heart of realizing the potential of the different areas of the data economy. Without it, businesses will be deprived of the data that many of them rely on to advance new use cases. Many current AI models, for example, could not be trained and advanced without access to large data sets. Transparency needs to be put at the heart of this process. Before any data is shared, users should be crystal clear about how their data will be used, stored, and safeguarded when they give it away.
There are plenty of both well-established and new and emerging approaches in this space to help address trust and transparency. One shift we are seeing is a push toward creating AI that runs using high-quality, accurate data - rather than focusing on data quantity and sourcing large datasets. Federated learning is widely seen as one of the most feasible, shorter-term ways to deliver this data quality-first strategy. It (in essence) sees algorithms run on data locally, and only the results of the training are shared centrally. This approach could prove particularly fruitful for industries such as banking, healthcare, and education where data security and privacy are paramount.
The role of the regulator
Europe has a particularly important global role to play in setting the standards for how the data economy will function. The 2020 EU Data Strategy prioritized the importance of finding a “European way, balancing the flow and wide use of data while preserving high privacy, security, safety, and ethical standards”. Globally our region’s ‘superpower’ comes from finding a more pragmatic middle ground between the private sector-first approach in the US and the significant state controls in China.
Start-ups need to engage in the continuous development of these rules. They should also work closely with regulators to ensure that governance meets their needs. Government action should not exist in a vacuum, and start-ups have a critical role to play as a voice from the frontlines, ensuring that regulators are clear-eyed on what start-ups need to continue growing and innovating to push forward the data economy.
Data is the defining feature of our tech-driven world. It has the potential to revolutionize and disrupt how different industries operate and connect with customers. Whether it is harnessing data to automate and optimize processes in a manufacturing plant, or aggregating marketing data to build memorable and personalized experiences for customers - the opportunities are significant. Europe has a particular opening to lead the way here, building on the region’s world-class universities, engineering talent, and reasonable regulators to build the next generation of category-defining software and businesses in the new and expanding data economy.
Lead image: Federico Respini
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