Are You Data Economy Ready? You Can Only Control What You Can Measure

In theory, everything is "data-driven." Decisions, strategies, and the entire company. In practice, however, something essential is often missing: transparency. Real-time data. Trust. Instead Excel spreadsheets still dominate. Data is not an end in itself. It must create added value. British mathematician Clive Humby understood this in 2006 when he said that data is the new oil—but only if it has a purpose and is processed accordingly. Data only has added value if we understand it, link it, and contextualize it. Not every number provides insight. Not every statistic is true.

This concept is illustrated by the knowledge pyramid. The starting point is signals, symbols, and bits — that is, signs. Machines collect these and use them to create data that is of little significance on its own. Information, or details about facts and processes, is only created through their interpretation. Information is always purpose-oriented and preparatory to action. When information is combined, patterns and structures can be recognized. When enriched with context and experience, these patterns and structures lead to knowledge. Knowledge is power. We can derive concrete actions and solve problems from this totality of knowledge and skills. In its most structured form, knowledge is stored in databases and documents. Individual knowledge then becomes collective knowledge available to the entire company. Companies can take it a step further by sharing data with market participants, thereby creating a data economy. This can help optimize the supply chain, for example. However, only one-third of companies are currently "data economy ready."

Manage data efficiently

The catch is that companies often already have the data required to derive information. However, it is not possible to derive information from this data. Companies are "data rich but information poor" and still rely on gut feeling. There are many reasons for this: people are unaware of the data, its potential is misjudged, access is restricted, the ability to interpret the data is lacking, or the quality is insufficient. Surveys confirm that only one in three companies in Germany can manage data efficiently. While many companies store and process their data in a structured way, it subsequently remains unused—along with its potential.

 This phenomenon is particularly evident in the SAP cosmos. Data from ERP, CRM, HR, and logistics exist side by side, but are they connected? When we talk about AI and AI agents, we are talking about systems that rely on data. Specifically, they rely on qualitative data. Most companies are not well positioned in this area yet. Additionally, most companies do not manage to integrate data sources quickly enough. There is a lot of catching up to do.

One often underestimated factor is bias. No algorithm is neutral. No dataset is free from bias. Ignoring this would be negligent. Recognizing this is the first step toward making better decisions.

Yes, the future is data-driven. But, above all, it is consciously data-driven. It requires systems that not only store data but also understand it. It requires people who not only analyze but also question.

Away from Excel, towards clarity

Companies are doing themselves a favor by doing this. They are also fulfilling the requirements of the EU and the new data law, the EU Data Act. This law is based on certain principles and values. Access and transparency are clearly among them.

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