CASE STUDY

Your approach to Digital Transformation is described as being centered on process and data before technology. Could you elaborate on how this philosophy is applied at MET Group and what kind of measurable value it has delivered?

Too many transformations fail because they start with technology. At MET, we always start with people. Then we design the process, define the data and only after that do we bring in the technology. While people are the foundation – requiring governance, alignment and shared goals-the core of transformation lies in clearly designing and improving processes. Most transformations adapt existing, often undocumented, workflows into more transparent and efficient ones.

Processes must be clearly structured to connect old ways of working with new ones, enabling real change. Data then fuels these processes, not only by enabling functionality but also by establishing shared definitions, in other words, a common language across teams. Without well-defined data, collaboration and effective decision-making are compromised.

Only after aligning people, refining processes and structuring data should technology be introduced – as an optimizer, not the driver. Technology enhances productivity but must be built on clarity about who does what, how and with which data. optimization and scalable processes. As transaction volumes surged, traditional methods could no longer keep pace. Digital Transformation initiatives – focusing on process redesign, data management and technology – were essential in enabling this growth.

A critical use case is the daily revaluation of trading positions, crucial for understanding performance and managing risk. Given the scale and speed required, this demands high-quality, timely data. To meet these needs, MET built a robust cloudbased data lakehouse as a core enabler, integrating millions of data points from trades, sales and market price feeds.

This system allows for accurate tracking of positions, risk exposures and margin generation within a 24-hour cycle. The data engineering backbone, combined with clearly defined processes and capable teams, ensures that all transactions are aggregated, transformed and made available for decision-making every day.

With a focus on risk management, what specific data-driven strategies have you implemented to help MET Group navigate the dynamic and often volatile European energy market?

MET Group’ s risk management relies heavily on transparency and timely access to accurate information. In-house quantitative analysts develop advanced data science models to assess market risk and guide hedging decisions. A major focus has been restructuring data collection and harmonization processes across all sales subsidiaries to provide a unified, comparable view of complex sales contracts, which carry inherent market risks.

The core value of the project was defined by the Group CEO’ s desire for real-time visibility into the organization – access to key information without relying on calls or intermediaries. As MET has grown in complexity, the transformation also supports better alignment and dependency management between teams, ensuring decisions are not only correct but also understood, justified and scalable across functions.

MET Group has significantly increased its traded volume of natural gas and power. How have your Digital Transformation initiatives, particularly in real-time data usage and trading efficiency, directly supported this rapid growth?

MET Group’ s rapid growth in traded natural gas and power volumes created a need for real-time

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