Share data, create added value: When is data sharing worthwhile for companies

What does data sharing mean in practice?

Data sharing describes making your own data available to others — whether within the company or for external partners. It is not about uncontrolled approval, but about structured, rule-based exchange with a clear purpose.

In principle, two forms can be distinguished. With internal data sharing, data is shared between departments, locations, or business areas. Sales, marketing and product development access the same customer data. Production receives real-time data from the warehouse. Controlling works with the same figures as management. Sounds obvious, but it often isn't: Many companies are still struggling with data silos in which valuable information is isolated.

With external data sharing, data is shared with suppliers, customers, partners or even competitors — under defined conditions. This could be the joint use of production data along the supply chain, the exchange of market data in industry associations or the provision of anonymized usage data for research purposes. So-called clean rooms are used for particularly sensitive data — protected environments in which data can be analyzed without the raw data leaving the company.

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What is the added value of data sharing?

The benefits are manifold and go far beyond pure efficiency gains. One ZEW study among 1,400 German companies identified three key benefit dimensions: the optimization of joint work processes, the development of new business models and the ability to monetize collected data on the market.

In practice, the added value is particularly evident in the supply chain. When companies share their data with suppliers and logistics partners, transparency and planning security are created. More efficient processes, faster decisions, cost reductions and improved adherence to schedules are the most common benefits that companies report.

The effect goes beyond operational improvements. Data sharing makes it possible to recognize patterns that remain invisible in your own data set. Anyone who links production data with maintenance data can plan ahead. If you combine sales data with external data sets, you make better decisions. And anyone who systematically shares customer feedback with product development builds better products. Our show how companies actually implement this data-based decision making Articles on the topic.

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Why are so many companies hesitating?

Despite the benefits, data sharing remains the exception in Germany: Less than half of companies in industry and industry-related services actively share data. The majority do not share data with other companies.

The reasons are understandable. Legal uncertainties come first. Many companies do not know exactly which data they can share and under which conditions. Data protection concerns, unclear liability issues and concerns about unauthorised access by third parties are slowing down preparedness.

There is also a strategic dilemma: data is seen as a competitive advantage. Anyone who shares their data may reveal insights into cost structures, production processes or customer relationships. This reluctance is understandable — but it also prevents companies from benefiting from others' data.

A third obstacle is uncertainty about the benefits. Many companies are unable to estimate what they would gain from data sharing. Without clear use cases and measurable goals, the effort remains difficult to justify.

Find out how other SMEs have overcome these hurdles on the Mittelstands Stage at the data:unplugged festival 2026 on March 26 & 27 in Münster. There, companies share their specific experiences with data sharing projects — from initial steps to scaling.

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When is data sharing really worthwhile?

Not every company needs to develop a comprehensive data sharing strategy right away. But there are clear indicators of when it's worth getting started.

Data sharing makes sense when information asymmetries cause problems. The classic example is the supply chain: When suppliers don't know when to order and customers don't know when they can deliver, there are buffers, delays and costs. Transparency through data exchange solves this problem.

It is also worthwhile if data remains unused in your own company. Many companies collect data that has only limited value for themselves — but could be highly relevant for others. Anonymized usage data, aggregated market information, or technical performance data can be valuable for partners, research institutions or industry associations. This creates potential for new business models.

And finally, data sharing makes sense when regulatory requirements require it. With the Supply Chain Due Diligence Act (LkSG for short), the EU taxonomy and upcoming regulations such as the Digital Product Passport, there is increasing pressure to make data transparent along the value chain. Companies that adapt to structured data exchange at an early stage have an advantage here.

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What is needed for successful data sharing?

The ZEW study identifies three factors that motivate companies to release and share data: legal certainty, reciprocity and financial compensation.

Legal security means that it is clearly defined who can use which data and under which conditions. This includes contracts that regulate rights of use, liability issues and deletion obligations. Solid data governance — i.e. clear rules for data access and use — is the basis. Sample contracts, guidelines and examples of best practice can help here — and are increasingly being provided by industry associations and public authorities.

Reciprocity means that companies are more likely to share data if they receive data themselves in return. Unilateral models in which only one party benefits rarely work in the long term. Successful data sharing initiatives therefore rely on equal exchange.

Financial compensation can be an additional incentive — but it is not always necessary. Sometimes the value lies in access to information that would not be available otherwise. Sometimes in increasing efficiency, which allows both sides to benefit. And sometimes in meeting regulatory requirements. For companies that want to market data as a product, data marketplaces also offer new sources of income.

Technical infrastructure is also required. Data must be available in formats that can be exchanged. Interfaces must be defined, access rights regulated and security standards must be met. With modern cloud technology and standardized interfaces, this is much easier today than just a few years ago.

In the master classes at the data:unplugged festival, experts work together with participants on specific data sharing strategies — from technical implementation to legal protection. You can find out which speakers are there at here.

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Practical examples: Where data sharing is already working

Data sharing has long been established in some industries. The pharmaceutical industry, for example, uses joint distribution structures to supply pharmacies several times a day. Various pharmaceutical companies share logistics data and coordinate their deliveries — a model that creates efficiency without jeopardizing competitive advantages.

Similar approaches can be found in the dairy sector, where there are comparable requirements for cooling and delivery frequency. Here, too, the exchange of data between actually competing companies enables joint distribution structures and cost savings.

Cross-sector data rooms are currently being created at European level. The project Manufacturing-X For example, promotes secure data exchange in industry — with the aim of improving transparency, sustainability and AI applications along the supply chain. In the healthcare sector, he works European Health Data Space on the joint use of health data for research and care.

These examples show that data sharing works best where there is a common interest in transparency, clear rules structure exchange and cooperation is based on trust.

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Getting started: How companies can get started

If you want to consider data sharing as a strategic option, you don't have to immediately invest in large infrastructure projects. You can get started pragmatically.

An internal inventory is a useful first step: What data does the company collect? Where are they located? Who uses them — and who could use them in addition? This often shows that there is already untapped potential within the company. Departments work with different sets of data, information is recorded twice, valuable insights remain stuck in silos.

The second step is to identify specific use cases. Don't ask abstractly whether data sharing would make sense — but in concrete terms: Which decision would be better if we had access to specific data? Which process would run more efficiently? Which problem would be solved? Anyone who finds concrete answers here has the basis for a pilot project.

The third step is talking to potential partners. It often turns out that the other side is also interested in sharing data — but no one has taken the first step. Suppliers, customers or industry colleagues can be valuable partners for long-term cooperation if interest is symmetrical.

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Data sharing as part of the data strategy

Data sharing is not an end in itself. It is a tool that can add significant value under the right conditions. The decision as to whether and how a company should share data depends on the individual situation: the industry, the position in the value chain, the existing data and the strategic goals.

What can be said in general: Companies that actively shape data sharing have more control than those that just react. They can define conditions, select partners, and set standards. They can benefit from others' data while using their own strategically.

Regulatory requirements are increasing, customers expect transparency, and companies that use data sharing are becoming more efficient and faster. Anyone who knows the risks and actively manages them can take advantage of the benefits.

Find out how to develop a data strategy that also takes data sharing into account in our guide to Data analysis in medium-sized companies.

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Conclusion: Approach data sharing strategically

Data sharing offers companies the opportunity to create more value from existing data — through more efficient processes, better decisions and new business models. The key lies in a structured approach: identify clear use cases, create a legal framework and work with the right partners.

You can find out how other SMEs are successfully implementing data sharing at the data:unplugged festival 2026 on March 26 & 27 in Münster. On the SME stage and in interactive master classes, companies share their experiences: What data do they share? With whom? For what reason? In which structure? And what added value did it bring?

Data sharing affects all areas of the company — from IT to purchasing to management. For successful implementation, it is important to involve and qualify key people. data:unplugged stands for practical transfer of knowledge — from which the entire team benefits. Get your ticket now!