Data economy: cultivating the true value of insights

Jun 19, 2022
  • IT
  • data

The ability to harness the power of data is the single greatest differentiator for businesses in the digital age. It helps them to plan more accurately, produce more efficiently, make better strategic decisions, and reduce waste. Yet, there’s more. Organizations that are at the very top of the ‘data maturity scale’ actively participate in the data economy. For them, data isn’t just a resource that allows them to improve their own business processes, but a product that can be bought, sold or shared beyond company borders. Here’s what that means.

Rest assured, most companies still have a lot of work to do – in terms of technology, culture, and governance – before they can leverage the value of their data internally, let alone produce data or insights that are of a quality level befitting the data economy. Becoming ‘data mature’ is a gradual process – a growth journey, if you will – which can be illustrated as follows:


Data mature illustrated as a growing plant

How to grow your data tree

In this model, organizations move beyond the outdated idea that ‘data is the new oil’ to instead regard data as the soil from which new insights, business process optimizations, and even entirely new business models can sprout. Along the way, several ‘nutrients’ are required to reach new stages in the development.

At the bottom are tools, technology and architecture, which are basic prerequisites for improving data maturity. The next steps, however, are less straightforward: set up a well-functioning data organization and governance framework, build knowledge and improve data literacy via communication campaigns, coaching and training, and establish a data community by exchanging insights and experiences. 

Many companies today have mastered the art of leveraging data to optimize internal processes – and sometimes even more than that.

On trust, sharing, and innovating

At the top of the ‘data maturity tree’ is full data democratization. This means that the whole organization has full confidence in the accuracy of its data, treats it like a product and an asset, and fully grasps its value. That is a prerequisite to participate in the data economy – along with a clear understanding of the organization’s activities and position within its sector. 

Some organizations have already reached this level of maturity. The city of Ghent, in Flanders, for example, makes its air quality records freely accessible to start-ups. And gas supplier Fluvius is making important moves to becoming a data broker – an effort for which it received an API award from Digitaal Vlaanderen. Petabytes of data from roughly 7 million digital meters will provide incredibly valuable insights that will allow the Belgian energy market innovate further. Because Fluvius is sharing its data with 26 other energy service providers, consumers can, for example, get personalized tips on how to lower their energy consumption. 

Data platforms: demolishing silos

But how do you get to that stage? Companies that want their data to move beyond a supporting role and deliver actionable insights require what’s called a modern data platform: an integrated technology solution that allows them to centralize and govern data located across a variety of silos and databases. Data platforms make it possible for users, applications and other technologies to access, combine and analyze this data for strategic purposes. 

To support companies in their quest to harness the power of data, these platforms consist of multiple components: from warehousing and architecture to analysis and security. Essentialy, the data platform is paramount for businesses to unify disparate data types and gain real-time insights in a cost-efficient and secure way. 

Clearing up the data mesh

Technology and architecture are just one step in the journey towards full data maturity. Taking part in the data economy requires a much more complex cultural and mental shift, which we’ve already hinted at above: regarding data as a product or an asset to be consumed. Not coincidentally, this is also one of the four central principles of the data mesh paradigm

In a data mesh, data is managed in a decentralized and democratized way, by the people and teams who are closest to it. To make this work universal interoperability is required, meaning everyone needs to adhere to the same syntax and standards of data governance. As you’ve probably guessed, this concept is central to enable the data economy as well. As companies share data with other organizations, industries need to make clear agreements. Evidently, APIs play a crucial role in this on a technical level. 

At the end of the day, the data economy isn’t so much about technology as it is about building business cases through data. In the long term, the goal is to make working with and sharing data as matter-of-fact as stepping into a car and driving – without knowing exactly how everything works, but being fully confident that you’ll reach your destination. 

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