The Journey to Data Intelligence and Governance at E.ON Group

All right, we are going to get started. Depending on where you're joining us from, good evening, good afternoon, or good morning. My name is Lance Dickerson. I'm a Field Marketing Manager here at Erwin by Quest. All right, a couple things to know before we begin. First, type any questions you have in the chat. We'll answer those at the end of the session. Second, we are recording this session. I will send a link to this recording within the next couple of days, so if anything happens technology-wise, if you accidentally get dropped, whatever it may be, I will send you a link to this recording. You'll also be able to share that link with anyone else you would like to share it with. With that, I'm going to turn it over to Susan Lane. Susan is a DI Thought Leader, and she's also a Director of Solutions Strategist here at Erwin by Quest. Susan, you can take it away. Good afternoon, everybody. Thank you, Lance for that introduction. And I'm sitting here in London with Romina Pyplacz, and she is the Head of Data Management and Governance at E.ON. And it's a really interesting data day for us today when you consider the energy crisis that's going on right now. Energy is no longer a commodity. We cannot predict the price of energy. And for the last 10 to 15 years, we have been able to always predict what's going on, but today it's a black box, and you just don't know. And at this time in history, this one moment in time, data is so, so important, and it's a game changer at E.ON. For E.ON during this crisis, data has become a point of awareness not just internally but also to the masses as to what is going on. And bringing data, knowing exactly where you stand is helping them speed up the transition to sustainability and also help them scale within the organization to meet the crisis. So with that, I'm going to turn it over to Romina. Romina has been implementing a data program inside of E.ON for the last five years, and we're so excited to have her here with us today. And over to you, Romina. Perfect. So thank you very much for the opportunity to share some of our insights and obviously our experiences. And Susan has just given already quite a very good overview about why it matters so much and even more than before for us to work properly with data. And before I actually go concretely into the journey that we have gone through in the last five years and giving you all the insights and learnings and stuff, hoping that it will help you along your way, I would just give you a short understanding of our organization because it is important to understand the complexity of our organization, the size, the different cultures, and so on to get a bit of a feeling for how complex it also is to create such a change in such a big organization. So starting off from there. We are basically the biggest energy provider across Europe as E.ON, so we do have around 72,000 customers that we are serving at the moment. And at the moment, the number is growing because smaller companies unfortunately get into problems through the energy crisis. And obviously, if there's one characteristic that is attracting right, now it's sustainability. That you can rely on someone, you will get your energy. At least you will get it. Even if it's expensive, but you will get it. And then we do have around about 900,000 renewable energy plants decentrally installed in the grid. That means that our customers have, for example, the solars on the rooftop or other installations like CHP if it's a B2B business. So we have quite a lot of them in the grid already that all put energy into our grids, right? Then in the end of the day, we do have 51 million customers that are relying on us as an energy provider for getting energy. And as Susan already shortly mentioned, it used to be normal that you just get electricity, and you will always be able to predict how much it costs. It will always just be there. And that dramatically changed. And now we are not just any longer an energy provider for the 51 million customers, but we are a partner in a difficult situation trying to help them as much as it's possible for us, to go through the crisis without a too dramatic impact on their, simply, finances in the end of the day, I would say, but also just mental health and everything. So we are way more than just an energy provider, and since the energy crisis, that got very, very clear. And then last but not least, the fundament for everything we are doing is our grid because it transports our electricity, and we have 1.6 million kilometers of grid across Europe in different countries that we are owning and operating at the moment for Europe or for our customers in Europe. So you can see we are quite a big organization. We do have also overall 13 countries that we operating in on in Europe, which means also 13 different mindsets, cultures, and it means also different strategies and ideas where we actually want to go, right? So of course we all work somewhat together, but we all know that in reality, these are companies by themselves, and they have also their own target. And what is also extremely important to understand also, why we are investing so much into data, is actually the key targets that we have set for ourselves before energy crisis, actually, for what we want to be seen. What should be our key characteristics that we are known for? So obviously, I think one that is not surprising, because a lot of companies are stating that, that's growth. Basically, growth not always just in turnover revenue, but it's growth in enabling the energy transition, allowing people to get independent from conventional energy production, and reducing our CO2 footprint, and not only for E.ON, but for our customers and for B2B businesses. So the growth is actually the growth in being more sustainable, which is what you see as a key sticking point. So we want to grow because we want to be more sustainable. And we want to make the whole world more sustainable. Maybe the whole world is no more Europe for us. But in general, it's also a mindset, and it's about how we are communicating around that. In the end of the day, we want to really make a difference as a company, and that goes very beyond just serving customers. And then last but not least-- and this is a topic that got an immense priority since the energy crisis, especially-- all of this is not possible to the speed level that we want it to be without digitization. So you can grow, of course, but growing in that business is reasonably slow, if we are honest, because you need to take a lot of investments, and it takes quite a lot of money. And it is something that is not something you can do very quick. But what we can do is we can use digitization to be faster. And also, for example, we can digitize the grid that we already have. So we have various different factors that are actually allowing us to be faster, but without digitization we won't meet the other two pillars. And that's why obviously all of them are existing because of the other targets that we have, and they all fit very, very well together. And what we were extremely proud of, on the one hand, if you can see something positive from the crisis, is that we did have the right mindset already before. We have been already aware of this before we actually started to go into the critical situation. And why do I tell you all of that? It is just to understand where am I coming from. What is the environment that we are working in and that we do have around us? Which can be different in every company because of your targets, because of the way you are set up, because of your size. And this is exactly why it was important to set the scene a little bit here. Now Coming to our journey. I hope this is going to be the more exciting part, although I'm very excited about energy. But I think for you maybe that one is more relevant. So I will shortly start off with what is the purpose of having a team that I'm actually leading since a while. So we are a global team of experts and that is allowing and helping the different organizations that I've mentioned earlier to successfully implement the way they're managed and the way they work with their data. Why are we actually doing it? I mean, at the very beginning, I think we started off with some regulations like GDPR that were coming up. That was giving us some pressure, but by now we have just understood that we do have an immense impact on the business and efficiency through the fact that we are not working properly with data, and also that the quality of data, for example, is a problem in our general daily business, and this needs to be fixed. And this is something where we can concretely make a difference in the day to day business for our organization. And in the end of the day, we also, on the same road, need to create the awareness that the people understand how valuable the data is that they are working with. And that it's not just a pain in the ass. Sorry to say that directly, if you have problems with it every day, if you're wasting 30 minutes of your time by just trying to correct an error. But it is something you should value and you should treat in a way that you want to really take care of it and treat it as a potential source for improvement, insights, whatever you can imagine. And how we are doing it actually? We are running a federated approach in the organization where we do have a central team. I try to keep it small. It doesn't work as good as it [INAUDIBLE], but we do have in every single other legal entity a team that is supporting the initiative, and these are the ones who are really kind of doing it, right? They are the ones making the difference in the organization, and we are by their side to help them along the road. And what we actually do-- and I will just make it very quick here to give an overview about the team itself. We have technology as one key thing that we are responsible for and that we need to be top-notch in. We are actually owning six technologies, including the data catalog from Erwin. We are also the owners of the data modeler. And for example, also for the data platform that we are implementing right now with the E.ON Data House. So we are really owning and developing technology for the group. And with that technology, we are offering 14 different capabilities, which is data modeling, for example, data governance, implementation, data quality management. So whatever you can imagine around that Is what we are offering as a team to the people. So they can come to us with a problem. We help them. And what we do have in that is also, at the moment, around 31 persons that are helping the organization to improve and do whatever they want to do. We do have obviously also the big pillar of data governance that we have in our responsibility. So we have the mandate to roll out the data governance across our group, and that we also have the colleagues, of course, to set up the organization and help them to understand what a data owner is and so on and so forth. And in that context, we are supporting various projects operatively, where we are helping them really to shape it and set it up. So it's eight at the moment that we are running at the same time. And last but not least, what is extremely important is also to develop skills and capabilities in the organization because we as a team, we do not want to do everything ourselves-- absolutely not-- so we need to help the people to build the skills and capabilities. And at the moment, we already have 24 legal entities across the group which are actively engaging with us and that we are helping on their roads and in various different aspects. So we have a quite broad field and a quite strong team behind it and a very good collaboration, which is also something we really enjoy with our organization. Now, what was the journey, right? We have, of course, already started this journey quite long ago. So it's nothing that happened just overnight. The first steps were done in 2018 where we did basically define the general framing-- you know, what do we want to do? In 2019, we then started to make things happen. So we start on the fundaments where we, for example, also implemented data governance and the data catalog across the group, and we started, actually, at that point. Still it's ongoing. And then at the moment that the fundament was there, and we know now we have the frame, and we have something to build upon, in 2020 we could start to really create the first use cases, solve the first problems, and also get faster, if you want to say, in the rollout of what we have already created in the year before. In the next year, then, we decided that, OK we have the fundament. We have the first experiences. Now we want to go into the next areas, which is where we add new levels, if you want. So we always relate it to a house, where you go from the fundament to the next level. And this is when we looked into data modeling stronger, when we looked into the topic of data quality, when we started to look into also the data provisioning, data as a service. So this was in that year where we started to really start on projects in capability areas that we didn't serve that extensively beforehand. And then, in 2022, that was-- I always say that that year was the craziest year, but I say that since five years. So I'm not very reliable. But it is-- definitely, it was completely crazy. We started off to build up our own data platform, which is the data house, where we used all the learnings of the four years before to make it in a way and to build it in a way that we have not seen it anywhere else, to really make it managed and properly managed and really establish the best practices of data management directly in the platform. And this was where we really started to hit the top notch and really do things, which are not only catching up with what we have missed upon the last years, but we started to move into being on top of the game with what we are doing. And this is what really started off in the last year is to kind of get into a game-changer mode where if we continue that way into for-- the next one or two years, we are going to have a standard that is beyond and above what you would see in the average, in the development of other organizations. And that's also a target for this year, of course. Now, we wanted to give a few examples-- and I will not go into all of them-- what we have done since 2018. So I'll just give you some kind of tangible, specific events that we had or activities. So for example, I said from the beginning that we made a plan. And in the plan, we decided that we want to invest into data governance and metadata management because it was fixing our key issues at that point in time. And actually, nine months of the first year, we actually spent on selecting the right product for us, selecting the right partner and product for us for being able to run the journey, not only in the beginning, but also thinking about what is it that I want to achieve on the long run, like with the platform, for example, right now. If I want to implement a platform, what kind of catalog solution do I need? Thinking big rather than small. And with that mindset, we have really taken a lot of time and a lot of different perspectives for the tier selection in the beginning. Then, obviously, we had the first go-live of one regulation GDPR, which was a huge thing for us where we helped and supported how to really operationally treat it. And for example, we also used the catalog to document our processing activities and show what processing activity is connected to what data source so that it was-- it was easier for us to trace back where the data is used from, which customer, and also, if we would need to delete data, that it is easier, as well. It was maybe not absolute perfect, but it helped a lot that we had this documentation and we knew where it is. Then what we have done in the next step is-- it was a bigger one-- we implement a materiality assessment for the organization where we have actually done or standardized the way we are evaluating how good we are and maybe also how bad sometimes. But in the end of the day, it was a standard approach to define where we want to go with one big picture because if you think about a maturity assessment, level 6 is your big picture. This is when you have achieved everything you ever wanted. And that means also, if everyone is using that maturity assessment, they are all working into the same direction and in the same targets that you want to achieve. And that was really essential because it allowed us to not only set the fundament, but also set the way to get to the target picture and the target picture itself. Then what we have heavily worked on the next step was get more people into our community. We have set up a internal community, but we have also set up some events, which already happened before, to motivate the people coming together, and just enjoying the game, and exchanging with other people. And we also started to make more transparent how the progress looks like for each and every country, but also for us as a team so that people could see what is happening and that there is something happening. And that was extremely helpful, also, for us sometimes to just see how things are moving. And in the next step, after we have built the community, we have shown people the way, we have shown people the vision, the next thing was to foster the rollout of the metadata management platform because this was always our core of basically everything we have been doing because this is where we have all information, and this is where we bring all the different worlds together. The IT was the business world, but also the insights to the data, and to the physical assets, and so on. And this was always our connection point for everything. And also in the P, in the core, it is our, let's say, base for automation and base for efficiency in all the different disciplines that we are looking into and the different capabilities. So this is why we have fostered to roll it out, and basically, together with that, we have also implemented the data modeling. So where we started to look closer into standardizing the way we are describing our data and even just describing our data. And that was really a cool move. And what we have done in that manner-- because we were not that experienced-- we started to have our external community that we started to talk with-- this is this external data management roundtable-- where we asked other people how they have done it, because you can learn a lot by just listening to others. This is one of the reasons why I'm speaking today, because I had other people telling me what I can do. So I try to do the same with others. And that was extremely important. And then what was definitely a game-changer-- and funnily-- I have to make that joke because it was not really a joke, but it was just amazing-- when we designed our maturity assessment, that was before 2018. And in that assessment, to get to level 3 or 4, yes, you need to have a group-wide platform where data is provisioned because this is your way of then managing your data properly and in the same way. And there's no other way to do it. And what happened in the beginning of 2022 is that we got asked to implement exactly that platform. So we could already predict in 2018 that something like this is going to happen because if not, we wouldn't mature any longer as an organization. And to see that something like this coming that you somewhat already knew would be the need to be there at a point in time was scary and motivating at the same time. I would say so, yeah. And then, last but not least, I think the one that I would like to share is after then three years of a journey-- I'll even go four years, it was finally that data ownership as a role was defined as being mandatory across the whole ion group, and every single legal entity in our organization needs to implement it now. And that was also something we worked for really hard, that this is in our functional policy and that the people are now really recognizing it as being absolutely important and essential. And what you maybe can see, just as a small kind of comparison of numbers, we started the journey in 2018 with two people, and now we are more than 30. We had no business really cooperating with us in the beginning, and now it's at 15-plus. But you have already seen, we have 24, and it's growing basically week over week. We do have the different technologies that we are owning I already said, but it's six actually right now. And we do have more than 500 users right now working already in our metadata management platform. And it is continuously growing because of our new data platform. So what can we say? It was fun. It was a ride and definitely a lot of work. But it worked. And what we said, what is going to happen in 2018, it happened. You just need to wait. You need to push for it. Also, if it's hard, right? So and that is basically the summary maybe of what you have-- what you have here in front of you. Now, what I would love to share with you, because I think that's something that is sometimes not often enough talked about are the key challenges that we have had along the road because it was not always easy. And the first one was that-- was the quote that we really love and that you already have seen on the first slide is, how to eat an elephant? It's one bite at a time. And this is what I can tell you is one of the most important quotes if you get started because at the moment you get started, and the moment you start to understand how much of an impact data has on your organization, and you start to read about it, and you start to understand it better, you find so many problems, so many things that you could do. And I can tell you you won't be able to do them all. So to prioritize and to accept that you won't do them all, but you will find those few things which are going to make the difference and which are your fundament for whatever comes afterwards is really essential. And for us, for example, these were two things. The one thing was to have a data governance framework, to know that what roles we generally want to have and the responsibilities you would like to implement. And the second one was building and having our technology platform, having the catalog as a base, which is actually not a catalog. It's a data governance platform. It's way more than a catalog. And with that, we have taken these two things and deprioritized everything else. I didn't work on data quality, not on data modeling, not on anything. I just did these two but in the right way. And this was-- what I would love to share-- this is, especially for the beginning, super important. And then this one is so relevant right now. And this is about if you take such a decision in the beginning, don't just think six months ahead because this might kill you or it might cost you a lot of money. If you think about data, think about, where is your end game? What is it that you would like to achieve? You know it is still 6 to 7 to 10 years to go. But where do you want to go? Because-- and this is what I described here-- if you take the right decisions, then it is how it is described here. You have built a fundament that is your fundament, no matter how tall you want to go. So you can build any level you want to because the fundament is very solid because you have taken the right decisions. But if you don't do that in the very beginning, at one point, it will limit you. You can only go to a specific level. For example, you can add up a specific amount of topics into your catalog or whatever. Or you can only do business terms, but you cannot do the recataloging to the source systems because you thought, oh, no one is going to need that in the beginning, but they will. And you need to already imagine what the people want in the longer run, and get prepared for it, and rather take a bold decision in the first glance, and then have-- pay it back to yourself, if you want to say, with developing it further than go too small, and then this is going to limit you and harm you to go as big as you wanted to in the beginning. And this is what is really, really, really important here, that I cannot even explain in the short amount of time that we have right now how essential that quote is at this moment in time where we, for example, use Urban for the autoconfiguration of pipelines. I did not imagine in 2018 that I will use a catalog to automatically configure pipelines, but I can. And this is what is so important is that I can and that I can do things which I even didn't think about when I got started. Then the next one is whenever we talk decisions, we were always looking into solving problems rather than being famous in a way of talking about everything we are doing and showing how successful you are. But we really wanted to fix business problems. We wanted to make things work that didn't work before. And you should always-- not should, but it's just-- it's maybe also a style question, but we never talked a lot about ourselves, for example, but we would rather focus on letting the people talk that could fix the problems for them. And we always rather said we only do three cases but do them properly than having 20, and everyone knows us, but we don't deliver. And this is what we mean with rather looking into being of success than actually-- or rather being of value than being of success. And then, at one point, you will realize that you have set the scene. You have gotten the people on board. You have selected the right cases. And then you can make it work. And it might not work at the same time, the first time you try it. But you need to make it happen. And if I mean-- make it happen, it means maybe you have to try 30 times to make it happen, but you may never stop or doubt that it can be made to happen. So it is really essential that the momentum you have created, the fundament that you have built, that you use it then to really make a difference in your company so that after that year later, or after that moment later, everyone knows you, and no one would ever do something without coming back to you and asking you for your opinion or your advice. So that is when you really, really just start to make the difference. And last but not least, I think everyone who knows in that field has been at that moment. There will be, at one point, more demand and more problems again. Actually, it's like in the beginning, just in a more comfortable situation because you're better than before, that there will be more to fix than you can. And you need to find the balance between solving problems but still developing further in your maturity, meaning understanding things better, putting better standards, improving the way you're working. So not only firefighting but really still progressing your capabilities, progressing with the organization, and that you find the right balance between fixing things without losing the long-term view because you're overwhelmed with what is it that still needs to be done and what is on the plate. So-- and that gets-- interestingly, it is hard in the first year, and it's almost harder when you know what you can do and you cannot deliver according to what you would like to, which is completely normal. But it is very interesting. Again, a very interesting situation where-- and also, maybe as a side cone there where you as a leader or as a person that wants to do that, you have to change yourself often. With every quote that I've shown to you, you have to change something inside you. You have to go yourself from different levels of maturity to be able to serve the organization and to be able to show where you want to go. So to summarize it, what would I say? I would say the first thing is, once you have realized how difficult it will be, do it, still. Dare. Dare to do it. And rather fail and fail 15 times than not having tried it. That's very important. Then be really, really, really aware of the change and change things, but manage that. Don't just put a change in the organization and let the people stand alone and being doubtful, and not knowing what to do, and so on. Manage it. Also, manage the resistance. Be aware that they will say no and manage them. Get them out of the no into a yes. Be aware of it and manage it actively. Then what I've mentioned with this maturity assessment, be consistent. Have a big picture. Know where you want to go. Number of different ways to get there-- not one way, different ways to get there. But know where you want to go and be consistent in your statements and be consistent in the way that you're working with your colleagues. And I've mentioned that already before, but still, it is essential, create value. If people have worked with you, they need to be thinking, oh, that was nice. That was good. That helped. That was really meaningful. And then they will come back, and they will talk about you. And that's going to help. And last but not least, and that's sometimes not easy still for me today, literally very much not easy, focus on what really matters, which means you need to know what matters. And if you have a lot of things in front of you, to know what matters is not always easy. So take time to think, what is the make-and-break thing? And if you know what it is, fix it. Do this and forget the rest. And then you will really be successful with the implementation of that area or in the implementation of data management and governance. OK, so I think I have finished off with that. And then I will take back to you. Yes, thank you, Romina. That was really inspirational. Thank you for that. I do have a few questions. Back to your maturity model, was that something that you created, or did you adopt it from an industry standard, perhaps? Actually, we have taken the industry standard as a base, and then we have adapted it to our needs. So it is still our own assessment, but it is based on already existing models that are in the market. OK. And so you made it your own? Yeah, that's true. And did it stand the test of time? Is it the same maturity model over the whole five years? It is. It is the same one? It is. And do you go back to it each year and do another evaluation and see how the maturity is increased? Oh, it depends on the legal entity. So some do it even more often, like quarterly or on a half-- half-yearly base. And some do it just to define where they want to go and then just walk the path until they really go back to an assessment because such an assessment is-- you need to see that you cannot do it super often because you need to let time for doing things. So if you just always assess and assess and assess, it doesn't help. If you do it every six months or even every 12 months, it's enough. You don't need to have it more often because you need to give yourself also time to conduct the change that you want to embrace. And did that tell a good story of your baseline when you started and where you are today? So did it really-- could you-- can you see the improvement-- Yeah. --based off of-- yeah, OK. Yeah, absolutely. I mean, I think it makes it even easier to see it with the maturity assessment, but even without it, we are a whole different organization compared to-- when I started in 2018, I would have never thought that we even are where we are right now. So it definitely is. I feel that. And I can definitely say from my experience of having done this with many global clients around the world for a very long time, the maturity that you have going on at Eon is remarkable. And we just had some discussion on marketplace, and it's something that some of the vendors are coming out with now, but you're already there. You're already see the value of having one place to even go and pull the data based off of the metadata, based off of the scoring, based off of everything you've done so far. And that, I find, must add a lot of value. And what do you see as the future? What's your utopia a year or two or three years from now? Sorry to put you on the spot. I think, rather-- I mean, I love automation. I mean, I want to have people working with data like they would shop on Amazon, really. That's why the marketplace is a very good topic. It should be. I mean, most of you may be a little data mesh, and the data product idea, and decentralized data ownership by providing data ownership or data products instead of reports, for example, or data sets, which is a data product in the end or sometimes like that. And this is where we want to go, basically. We want to have a very easy way of working with data where you can consume it, where also people which are not so skilled can easily work with data. And definitely, that would be, for me, the thing where we want to end up with at a point in time. And there are many more things. But I think that's already enough to start with. Yes, that's definitely appropriate for where you guys are and where you want to be. We do have a question from somebody asking if you can share the link to the maturity model that was used. It's not an official one. Got it. So it is actually called-- it is-- we do not really have a link where you can just get it described. Let's say it that way, but feel free to reach out. You know my name. And then we can see how we can have a talk around that, but there's not an official document that is shareable that easy because it was kind of developed in the scope of Eon directly. So it's not yet made public if they're asking. There's also methodology that is connected to it and so on. So there's a bit more than just a model where you describe it. You need to know how to use it. So but I'm happy to share that. It takes too much time today. Perfect. Thank you. I know you're needing to catch a flight. So I think we'll call it a day. Thank you, everybody, for joining us, and thank you, Romina. It was a very worthwhile session today. Thank you. Thank you so much. You're welcome.