Why SAP relies on the Selective Data Transition Community

When competitors team up

Reik, you lead SAP’s Selective Data Transition Community, a network of direct competitors. How do you turn competition into genuine collaboration?

Reik Boettner: That really only works through trust, and trust does not develop overnight. At the beginning, things were very different. Naturally, everyone was asking themselves: What can I share? Where should I hold back? After all, we are all competitors.

But that has changed over the years through joint projects, ongoing dialogue, and working together on real challenges. At some point, you realize that the others are dealing with exactly the same issues. And then something decisive happens: you stop pretending.

Today, we go into the meetings and consciously leave the competition outside. We work very openly and talk about what is not working, about mistakes, and about difficult situations with customers. This workshop-style approach is extremely important. Everyone contributes their own perspective, and in the end, everyone benefits.

I find it fascinating every time: In the market, we are clearly competitors. But within the community, we genuinely work as one team.

What is your role within the community?

Reik Boettner: I basically wear two hats. On the one hand, I am part of the governance team and represent SAP. In this role, I am responsible for the community from SAP’s perspective.

On the other hand, I work in the Customer Evolution stream, where I help raise awareness of Selective Data Transition in the market and further develop go-to-market approaches.

How do you end up working in a field like this? It is not exactly a traditional career path.

Reik Boettner: For me, it was actually a fairly natural progression. I had been involved in transformation projects for a long time, particularly in the context of the global move to SAP S/4HANA. The central question was always: What is the best path for the customer That brought me into contact with the SDT approach and the community at an early stage, and eventually I officially became part of it.

Why SAP Is going for a community

The idea behind the community is unusual: SAP deliberately brings strong partners to the table who are also competitors. Why?

Reik Boettner: There are two reasons. First, we wanted to develop an approach that is genuinely viable in the market. That is only possible if you look beyond your own perspective and incorporate the experience of the partners.

Second, it is about scalability. SAP cannot handle all the transformations in the market on its own. This requires a strong partner network made up of partners with whom we can also collaborate closely on content and methodology.

Let’s talk about SDT itself. When is this approach particularly suitable for companies?

Reik Boettner: The classic scenario is a company that wants to transform but does not want to migrate all of its historical data. In other words, it wants a clear cut while selectively transferring relevant data and customizing.

SDT becomes particularly valuable in complex system landscapes, such as large systems, consolidation projects, or data cleansing initiatives. This is where the approach plays to its strengths because it can be tailored to the company’s specific requirements.

Are there also situations in which you would clearly advise against SDT?

Reik Boettner:  Yes. If someone says, “I simply want to move quickly and cost-effectively”, without focusing on data quality or innovation, a traditional system conversion may be more suitable. However, this should not be underestimated.

Many companies have to adjust their strategy during the course of the project. Your study with NTT DATA Business Solutions confirms that more than 70 percent of companies make at least one adjustment to their migration method. And that is exactly when a rigid approach becomes problematic.

So, does that mean the original plan rarely holds up until the end?

Reik Boettner: Exactly. Large transformations often take two to three years. And during that time, something always happens: companies are sold or acquired, and processes change. The assumption that everything will remain constant is simply unrealistic.

Status quo: AI in transformation

How is artificial intelligence shaping transformation projects?

Reik Boettner: We are in the midst of a major shift. In the past, AI was primarily used for relatively simple analyses. Today, we are already seeing significantly more complex applications, such as in mapping. However, when it comes to highly complex scenarios like SDT, AI is not there yet. We are still at the beginning.

Where is AI being overestimated?

Reik Boettner: Primarily in complex, customer-specific areas, especially when it comes to custom Z developments. The ideas are there, but implementation has not yet reached a point where companies can rely on it completely.

What do companies need in order to use AI effectively in transformation projects?

Reik Boettner: Two things: openness and skills. Many customers now expect us to use AI-powered tools to work faster and more efficiently. But that also requires the right expertise on both sides.

Outlook and tips for IT transformations

What is most commonly underestimated in transformation projects?

Reik Boettner: Clearly, testing. Everyone knows how important it is, yet it is still consistently underestimated. And then it comes back to haunt you at go-live.

And in the long term, where is the broader field of transformation heading?

Reik Boettner:  Transformation and change are constants in today’s world. While the past few years were shaped primarily by cloud transformation, AI may now bring about an even more profound shift, both in our solutions and in our tools and services.

Another major transformation trend is sovereignty. Against the backdrop of a changing geopolitical environment, system and data security are becoming increasingly important and are developing into a central issue across the IT landscape.

Data lies at the heart of all these transformations and continues to grow in importance. Data security, data quality, and data management are essential for customers to protect their business and use AI to future-proof both business models and day-to-day processes.

Ultimately, data is the foundation for everything, especially AI. If the data quality is poor, even the best technology will not work. That is why we are also seeing a clear trend toward standardization and a clean core.

Will we eventually see transformations at the push of a button?

Reik Boettner:  In the public cloud, yes, definitely. In on-premises environments, however, that is still difficult to imagine at the moment. The systems are simply too individual and too complex.

If you could give a customer just one piece of advice, what would it be?

Reik Boettner:  Listen to your consulting partners! (laughing)

 Thank you for the interview!