In order to keep its own competitiveness fit for the future in a volatile market environment, in particular with regard to emerging technological innovations combined with artificial intelligence, RheinEnergie strives for a very high speed of data-related work. RheinEnergie relies on external support for rapid results and thus a significant increase in its own speed of action. In order to jointly develop a structure or roadmap with appropriate fields of action, RheinEnergie is looking for a sparring partner in developing a data strategy.
How can data be used efficiently as a strategic resource?
How are decentralized data landscapes developed into an integrated structure?
What framework conditions must the data strategy meet?
In this phase, the current state of data practice at RheinEnergie is analysed. This includes data maturity interviews to assess the level of maturity and a strategy assessment to align with the corporate strategy. The Data Thinking Workshop creates data-driven ideas and concrete use cases. The architecture assessment tests the existing IT and data architecture for its future viability.
After analyzing the status quo, taod's Strategy Consultants bundle all findings and derive central, comprehensive conclusions. The results form the basis for clear goals and prioritized areas of action. This includes strengthening innovation management or setting up structured enablement structures. A common understanding of roles also improves cross-divisional cooperation within the company.
We develop a roadmap with clearly defined fields of action and responsibilities. An open implementation approach is chosen to keep the degree of centralization flexible. Individual topics will initially be piloted on a small scale with selected market areas. The result is a blueprint that enables rapid progress without having to involve all 15 areas at the same time.
As a result, RheinEnergie receives a compact strategy paper that reflects the logical structure of the data strategy, including concrete action plans, from vision to implementation. The Next Steps planned together with RheinEnergie are shown with specific time plans. The new data strategy centralizes RheinEnergie's strategic projects, underpins existing data initiatives and opens up individualized opportunities for the department-compliant value creation of data.
RheinEnergie wanted to develop a central data strategy that would involve decentralized stakeholders from different areas of the company. The aim was to improve operational processes, accelerate data-related work and at the same time create conditions for future use cases.
Prior to the project, RheinEnergie worked with decentralized data landscapes and was looking for a structure or roadmap with clear areas of action. At the same time, the data strategy had to be structured in such a way that it strengthens competitiveness in a volatile market environment and takes technological innovations, including those related to artificial intelligence, into account.
Together with RheinEnergie, taod developed a central data strategy and a compact strategy paper with specific action plans. For this purpose, data maturity interviews, a strategy assessment, a data thinking workshop and an architecture assessment were used to systematically assess the maturity level, corporate strategy, use cases and future viability of the IT and data architecture.
Development began with an analysis phase of the status quo. The identified findings were then bundled, prioritized fields of action derived and a roadmap with responsibilities developed. The implementation approach was deliberately kept open so that individual topics can initially be piloted in selected market areas without involving all 15 areas at the same time.
RheinEnergie received a compact strategy paper that describes the logical structure of the data strategy from vision to implementation and contains concrete next steps with time planning. In the project, 13 central data challenges were analysed, four workshop formats were carried out with a total of 26 participants and three specific project goals were achieved: the positioning of the status quo and the level of maturity, a strategy concept including a target image and a list of measures with a clear focus on execution.
Let us answer your questions during a non-binding initial consultation.
Your data strategy as a starting point for successful data management.
.webp)
In an interview, Benedikt Köhler, data consultant at taod, and Dr. Heiner Lütjen, business and strategy developer at RheinEnergie, talk about working with data.
Our white paper explains important strategic principles that are essential for building a data team.
