Data has long been more than just an IT topic – it is a business model. Companies that generate added economic value from their data grow faster, are more resilient – and achieve significantly higher valuations on the market. Data-driven business models are transforming entire industries: they create recurring revenue, new product logics and open up economies of scale beyond traditional production capacities.

But how exactly do you actually earn money with data? The answers are varied – and often surprisingly tangible:

• Usage-based pricing: TRUMPF enables usage-based billing with networked laser machines – customers only pay when they use the machine.
• Predictive services: KONE offers predictive maintenance via its networked elevators. This reduces downtime and saves service costs.
• Data sales & partnerships: Deutsche Bahn makes anonymized movement data available to third parties – for example for traffic planning in cities.
• Smart bundles & AI recommendations: At Siemens MindSphere, industrial customers can have their machine data analyzed – for a fee, as a scalable platform business.

A young Berlin-based FinTech is leading the way: Pliant impressively demonstrates how a scalable business model can be developed from modern technology and the smart use of data analysis and artificial intelligence. The company has won over investors with its platform for the intelligent management of business payments – 36 million euros in growth capital is flowing into its further expansion. A strong signal for the innovative power of digital financial solutions “Made in Berlin”.

These models are also increasingly gaining ground in traditional industrial sectors. Companies such as Bosch, Schindler, Rolls-Royce (with “Power by the hour”) and John Deere (with smart farming data services) have shown how to turn a physical product into a digital service ecosystem – with data as the core value.

From cost block to source of capital

Many companies have been collecting data for years – such as sensor values, customer processes or maintenance logs. But they hardly use it. The opportunity lies in developing an active business model from this reactive treasure trove of data.

And it often only takes a small piece of hardware to get started. A networked sensor, an edge device, an IoT module. Example: Vaillant has started to equip heating systems with sensors to enable remote maintenance and energy optimization. The real benefit here is not in the hardware – but in the services it enables.

In a world where hardware comes cheaply from the Far East, the real added value is not in the device, but in the data model, software and service. Companies that recognize this are building smart business logic around small devices – and transforming themselves from product companies to platform companies.

Strategic data monetization: from insight to revenue

The economic benefit of data arises from clear monetization strategies:

• Internally: savings through automation, error minimization, energy optimization – such as at Heidelberg Materials, which controls cement plants based on data.
• External: Pay-per-use at Kaeser Kompressoren, which offers “compressed air as a service”.
• Ecosystems: Connected services at Bosch Smart Home or Airbus Skywise, where partners access aggregated fleet data.

Data is no longer a by-product – it is a product in itself.

From old building to smart building – and to the transaction

A traditional manufacturing company with a stagnating margin was transformed from an “analog old building” into a “digital smart building” through a targeted data strategy. The highlight: it was not new products that made the difference, but the refinement of the company’s own database.

Digital services, license models and data-based business processes – from energy management to usage-based billing – were created by evaluating operating data collected over the years. The business model changed fundamentally within just a few years.

This transformation did not go unnoticed on the market: a private equity investor recognized the potential and got on board – with the aim of scaling the data-based model internationally. The company not only became viable – it became strategically valuable.

Data as a lever in M&A – and as a lifeline

Data-based business models are more sustainable, have higher margins and are easier to integrate. Their importance in the transaction environment is correspondingly high:

• Scalability without production limits
• Less dependence on material costs or suppliers
• Faster integration through cloud-native architectures

In the USA, data-driven SaaS companies often achieve higher sales multiples than in Europe. While top performers such as Snowflake or Palantir have at times achieved double-digit multiples, the valuations of most companies are lower. In Europe, multiples are usually lower, but data-ready companies such as Celonis or UiPath show that a “data-driven premium” is also possible here.

“Data readiness” – a new KPI

Demand is increasing in the M&A context:

• How structured is the data?
• Is there an API strategy?
• What about data protection & ownership?
• Can data be used operationally AND strategically?

Those who respond convincingly here not only increase their company value – but also their future viability.

Conclusion: Data is not a department. It is a strategy.

Data-driven business models are not a gimmick for start-ups, but survival principles for established companies. Those who use data correctly can open up completely new growth paths from existing structures – and even breathe new life into industries that were thought to be dead.
M&A is not the goal, but the means to accelerate this change.