Dr. Heiner Lütjen from RheinEnergie on data strategic work

“We now have a fixed order and structure. ”

For a company like RheinEnergie, with an annual turnover of 4.07 billion euros in 2023, which already has numerous data initiatives in 15 divisions, developing a cross-divisional data strategy is a central task. Together with taod, the Cologne-based company plans to speed up data practice through a dedicated strategic orientation. In an interview, strategy and business developer Dr. Heiner Lütjen from RheinEnergie and Ben Köhler, senior data consultant at taod, talk about how theoretical work with data can ensure practical business success.

Heiner, what role does data play in your everyday life?

Heiner Lütjen: Of course, I deal a lot with data & AI in a professional context. RheinEnergie also gives me the opportunity to participate in the ada fellowship program, where I am currently working with managers from other companies on a joint project to implement and use an AI chatbot. In my private life, the topic of digitization also accompanies me in my voluntary work. I support senior citizens in acquiring digital skills. This requires patient guidance, simple explanations and appropriate exercise options that are tailored to the needs and level of knowledge of senior women. In particular, the simple and addressee oriented communication there helps me to communicate complex things more easily, even in everyday working life.

Ben, do you spend a lot of time with data in your private life?

Benedikt Köhler: I'm not a hyperdigital person, but of course, it's hard to escape from the world of data in private today. I'm only really active with financial data — I like to dig into that and use Power BI for my analyses.

The value-creating use of data is a very important issue in companies. What are the relevant drivers at RheinEnergie to deal with data?

Heiner: At RheinEnergie, we have several drivers for working intensively with data. One major factor is certainly the increasing transformation pressure for energy suppliers. Particularly in the direction of our various customer segments, due to increasing competition, we must communicate in a more targeted manner and test new products and services more quickly in order to also be able to meet new customer expectations.

However, in order to be able to do this, we also need improved data quality in our processes. Good data quality is essential for successful data use, as it ensures that the information and insights obtained are reliable and usable. If the data quality is not right, this can lead to incorrect decisions that can have potentially significant financial and strategic consequences for our business.

It should not be forgotten that we want to support our employees in expanding their data literacy with suitable training formats and tools. These are a selection of internal and external drivers that suggest that we will continue to focus a lot on the topic of data in the future.

You are already well positioned in this area, have various data initiatives, and are tackling the topics. But you can also hear that you are not yet completely sorted everywhere and that you also lack competencies here and there.

Heiner: Which company would now say that we are already “on the top” everywhere. Of course, we will have to make many adjustments in the future. Like many other companies, we face the challenge of collecting, managing and then using consistent, complete data accordingly. These often come from different systems, which are not always linked together, which makes it difficult to integrate data into a uniform database. As a company with many different areas of expertise, it also requires clarity as to who has which roles and responsibilities. There is a need for central data governance that sets standards and processes for data quality, but also defines clear responsibilities for the various roles and should identify the interfaces between centralized and decentralized areas.

Another challenge for us is to take our employees with their different areas of focus on the transformation journey and to shape the development of competencies accordingly. Against this background, it was clear to us that we needed well-thought-out data strategy planning and close cross-functional cooperation between IT department, strategy and specialist departments.

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What is the status quo in other companies, Ben?

ben: So on an abstract level, I can already see that the challenges are the same in many places. Data quality is of course always an issue, especially when you're thinking about AI. We get very different inquiries about this. And the vast majority of companies operate here in the brownfield — meaning they have to deal with legacy issues and drive forward development instead of just relying on detached new initiatives. The topic of data strategy usually only pops up when you realize that too many independent initiatives mean that the fields of action are becoming too broad. Then you ask yourself which direction you actually want to go or what the overarching problems are, within a corporate structure, for example.

What role does company size play at this stage?

ben: There is a clear difference between creating a data strategy for a medium-sized company and being able to depend much more specifically on the core business, or whether, as with RheinEnergie, it is about working out a denominator. Because here we had very independent decentralized areas and wanted to see what synergies we could exploit. We had a lot of very different tasks and content there. A small company can change faster, can define completely different types of goals and also has to pick up fewer people.

Heiner: That's right.

ben: With such large companies, a lot of internal politics and communication is required to change the course for this tanker by just five degrees.

How do you go about that?

ben: It really depends on the size and how specific the tasks are. When it comes to organizational development, the inquiries are usually very specific, according to the motto: “We need a data team, can you help us set it up?” In a purely strategic project, we must first understand the company's situation and the value creation processes so that we can deduce what role data must play in the future in order to deliver actual added value.
Sometimes we also have to question the customer's request first and see whether we might need to downstate specific target formulations in order to then take smaller strategic steps.

“Sometimes we also have to question the customer's request.”

I hear from both of you that companies are already in the middle of setting up data initiatives and buying and using technologies. At some point, however, they seem to get into the situation where they say: “We're not getting anywhere here, we need help.” Heiner, at what point did you realize that looking from outside could help you, so that you advertised the topic of data strategy?

Heiner: For us, there were three main reasons for this: speed, objectivity and external expertise. It was clear to us from the start that we wanted to strongly involve our specialist areas in order to achieve a high level of commitment to the results. The many interviews and workshops with the departments were time-consuming, but with great added value in terms of content for a sustainable end result. Ben has just mentioned it: In a company with 2,500 employees, you have to pick up many employees and managers at different hierarchical levels so that you create commitment and conduct good stakeholder management. We decided that we would not be able to implement this quickly enough on our own, but now we want to have a result as soon as possible, with which the divisions can continue working.

And the other reasons?

Heiner: We also wanted an external perspective, an unbiased perspective, in order to identify blind spots and established patterns in the company that might be a hindrance. At the beginning of the project, we carried out a status quo analysis. It was also good to see how we are actually doing in competition and what are our pain points. Is that just the image we're making up right now or is that also what other companies feel the same way? In order to develop a structure or roadmap together, with appropriate fields of action, we were looking for sparring.

And, of course, data strategies require in-depth expertise in data architecture, data management, analytics, AI, and legal frameworks. Here, we also wanted to obtain specialized expertise through external advice.

“At the start of the project, we sharpened the content focus and also adjusted the content of the project goals.”

What goals did you want to achieve with an overarching strategy?

Heiner: Yes, that was very interesting. Ben also noticed: At the start of the project, we sharpened the content focus and also adjusted the content of the project goals. In the beginning, my idea was actually that we could work on content topics more intensively. For example, discuss a data governance model with colleagues. Or perhaps to take the <a href="https://www.taod.de/services/data-engineering-consulting" data-webtrackingID="blog_content_link" >first steps to evaluate future data infrastructures</a>. The colleagues from taod had already presented this with their data mesh concept.

But?

Heiner: The longer we are in discussion with the departments and also with the sponsors (Budget provider of the strategy project, editor's note), all the sooner we realized that the first step is actually about setting central premises for RheinEnergie. For example, to define that data is an entrepreneurial value for us, and we want to align our corporate strategy with this in the future. We also wanted to anchor the topic of data more firmly in the corporate culture in order to enable data-based decision-making and continuous testing & learning. With such premises, we have created clarity and a common understanding.

The second main goal, which we have just recognized, was to bring a certain order and structure to the topics that we want to implement. In other words, to define a kind of roadmap of fields of action, and then to fill them with responsibilities. At the end of the day, these were also the two key results, the premises and the fields of action with responsibilities that we are now implementing.

That sounds like questioning your original requirements, as Ben just mentioned.

Heiner: At the beginning, my expectation was that we would get more involved in discussing the content of our fields of action. It was about building competencies in the respective areas, about data infrastructure, and we have already talked about many topics, such as data quality and governance. But in the strategy project, we did not get too much into the technical design of the fields of action.

ben: I felt the same way you describe it. I think that was also part of the process of discovery. Because no one, neither you nor we, would refuse to press ahead with specific content. But that wasn't that easy because a lot of stakeholder management was required and there were so many different status quo in the areas involved. For example, some had already developed data governance, others had not yet.

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It sounds like a big challenge to me to bring existing data work to an early, abstract level.

ben: If we had said in January that we are now doing central governance, then some areas would have pointed out that they already have one, others would have asked about the costs and the next would have thought they didn't need any. With the data strategy, we have resolved a great deal of organizational discussion. As a result, everyone was involved and the size of the project became all the more obvious. A project that has been approved by the Executive Board and which three major areas are already involved in.

“I see it as a strength of the strategy that it is also a bit abstract.”

The data strategy — and that's straight out of a textbook — enables existing corporate goals. I see it as a strength of the strategy that it is also a bit abstract and that you can deduce the doing from it. It is a success for RheinEnergie that everyone is now pulling together when it comes to data issues. Without this project, this would have been far from being achieved.

Heiner: I see what you describe as abstract as strength and weakness at the same time. Of course, many employees have the understandable desire that a data strategy includes in a very specific way what needs to be done. However, we have not developed an action plan based on the motto “We must implement this measure tomorrow so that it comes out the day after tomorrow.” In my opinion, however, that is also not the task of a data strategy.

The task of a strategy is to give a certain order and structure to the relevant fields of action, to prioritize them and to put them in a chronological order and not to anticipate the result in detail. As a strategy department, we must build a bridge between long-term strategy and transfer to action level in the areas. This sometimes irritates the expectations of employees. But that is what implementation is there for, which we now want to tackle with great determination. But of course, as a strategy department, we must build a bridge and develop the transfer to the action level together with the areas.

“As a strategy department, we must build a bridge between long-term strategy and transfer to action level in the areas.”

ben: With a pure backlog as a strategy document, you would be in the same place again in a year, with new problems. Of course, in one or two years, we will also have to talk about new areas of action or adjustments to the data strategy. But these will be much easier discussions, because you won't just get from one problem to the next, but will be able to assess the status quo for very specific topics based on previous experience and objectives.

Heiner: From my point of view, that is exactly the crux of the matter. With your support, we managed to do a short, concise strategy project in a relatively sporty way. You have to quickly formulate a data strategy, then quickly show initial successes with specific use cases and then move on to implementing larger projects.

ben: The specific discussions and projects can now get off to a very good start. Everyone is picked up and works on the same denominator. The motivation is high. It is also an ambition in a strategy project that people feel included and want to get started and are not already exhausted by all the problems discussed. And I think we did well with that.

How does developing a strategy work with so many different levels and stakeholders, Ben?

ben: The involvement of opinion leaders in the company is an important basis. Together with stakeholders and sponsors, they are among the most important sources of input in such a project. One thing is clear: In an organization of this size, it is not about developing the “right” plan and pushing it through from above, but about getting people who are already data-active to get involved — finding solutions and then implementing them. By involving these groups of people, you not only get good quality results, but also commitment from the most important opinion leaders — who helped to develop the results.

How exactly did you proceed?

Heiner: We have a total of 15 divisions. We knew we couldn't start with them all at once. At the same time, we naturally want to support as many areas as possible in the future. That's why we said we'd start with the network area and the three sales areas. We started with these four areas in order to develop a kind of blueprint for the relevant fields of action. We now want to gradually integrate other areas and take up their needs.

Speaking of interviews, Ben. You have opted for a workshop-based approach to developing a strategy. Why

ben: A structured workshop format, combined with the right tools, is the fastest way to absorb a lot of input. This enabled us to record and record employees' topics even in relatively short appointments of one or two hours. Workshop formats help to establish comparability and to identify different focuses or different priorities.

Heiner, did you like the methods?

Heiner: I really liked the methods. It made sense to start with workshops in each area, to bring people together locally and to create a common understanding. The interviews in between were also effective. We did a lot in Miro and used formats that required a high level of participation. That was good.

“We now have a fixed order and structure, we know which topics we want to work on and we as a company are clear about our priorities.”

The implementation of the strategy has now begun. How well is that working so far?

Heiner: We now have a fixed order and structure, we know which topics we want to work on and we as a company are clear about the priorities. I think this is already relatively transferable to many companies in our industry. We are now developing a concept with our divisions on how we can maintain the speed of implementation.

ben: I think anchoring the data strategy in the company worked very well. First of all, everyone is convinced of the result and knows that now the work starts. Second, we have created structures primarily to drive the issue of data at RheinEnergie in the long term.

Heiner: For me, as Ben just said, the decisive factor was to define responsibilities with the individual stakeholders and determine the degree of centralization. Given the size of the company, we cannot centrally control everything from strategic corporate development and IT. We must always balance issues that can be implemented by the areas themselves and topics that must be organized centrally for the entire RheinEnergie and on which we should all work together. Our idea is to take a flexible approach to implementation now. We try to develop certain areas of activity on a smaller scale with selected market areas and then transfer them to other areas. Otherwise, we would have the situation again and again that we would have to discuss a field of action with 15 areas and at least 15 contacts in large workshops. In the end, the communication effort is too great at the beginning. Here we must proceed gradually and in waves.

Do you have an example?

Heiner: The topic of data governance, for example, has been developed with three different areas. We're not saying that there will be other market areas added in the first workshops, but they will of course also have to work and deal with the results in the future. Instead, we develop different roles in the fields of action in coordination with the areas, which enable the gradual integration of all areas without overburdening them in terms of resources. Another example is the topic of systematizing the development of competencies. Here, too, there is a need for different concepts, which are to be developed according to the needs and requirements of the respective specialist areas. But here too, it will be difficult to implement all of this at the same time. Priorities will have to be set here.

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How do you organize yourself?

Heiner: We have now established three formats that we want to use in implementation. The first format is the strategic anchoring of the strategy process, a top-down discussion with the Executive Board, so to speak. Here, we adjust the data strategy once a year and also change the strategic priorities if necessary. The second format is a kind of control board, in which we first coordinate quarterly with selected area managers: Do the fields of action still fit, what is the progress here, what do we need to adjust? Do we have to start new fields of action and close certain others? The third format, classic multi-project management, is at an operational level. Here we meet with all those responsible for action areas, give ourselves a kind of flashlight on the status quo and discuss very specific problems.

Who is one of the central contacts?

Heiner: IT and strategic corporate development will take over the organization together in the future. In addition, there will be a data team that has been under construction for a few weeks and will be heavily involved in the implementation.

What is the composition of the data team?

Heiner: This was recruited internally from various areas. These employees are no longer just responsible for one area, but work on the topics across the board. Since September, there has also been a new group leader who is now successively developing the main content areas with his team.

What will the next three to six months look like for you?

Heiner: We are now starting implementation in the first areas of action. We want to take colleagues on the journey and get them excited about the topics. Communication is crucial at this point. We started with data governance, where we really want to quickly define the roles and responsibilities so that we can then move on to further areas of action.

What advice do you give companies when they should seek external help for the topic of data strategy?

Heiner: If speed is an issue and a neutral view, then you can develop a data strategy with external support. If, on the other hand, there are enough resources available, you can do it alone first and then rely on support for implementation. The two are not mutually exclusive and always depend on the context and framework conditions.

“I would describe the ambidexterity of companies as a key success factor for the future. On the one hand, we must do our homework to further develop operational processes in our day-to-day business, for example through improved data quality, to automate repetitive tasks more or to improve existing products through new data sources. On the other hand, we need to start looking at applications that are further in the future.”

A quick look into the future: What data trends or capabilities do you see in the next two years?

Heiner: I would describe the ambidexterity of companies as a key success factor for the future. On the one hand, we must do our homework to further develop operational processes in our day-to-day business, for example through improved data quality, to automate repetitive tasks more or to improve existing products through new data sources. We must not forget that, otherwise we will not pick up the speed of transformation. On the other hand, we need to address future use cases today. Here, the goal should then be clearly focused on innovation, experimentation and testing new business ideas. We must increasingly build up both capabilities today in order to remain competitive.”

‍ben: I'm not saying anything new with Generative AI. I'm still understanding all of its consequences. I think that's true for most, as the upcoming changes are extremely profound. With <a href="https://www.taod.de/genai-prototyp" data-webtrackingID="blog_content_link" >GenAI</a>, we have the opportunity to treat actual qualitative data as if it were quantitative. This means that as a company, I can automate my work with text data, for example, previously mostly processed in manual processes, across the board without having to accept any loss of quality. So far, this has not been possible in this form — and there are still many impressive milestones ahead of us.

Thank you Heiner and Ben!

Read more about data strategy work in issue 4 of data! — Magazine for cloud services, data analytics and AI. <a href="https://www.taod.de/data-magazin" data-webtrackingID="blog_content_link" >Order now for free!</a>

sources:

https://www.rheinenergie.com/de/unternehmen/newsroom/nachrichten/news_72146.html

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