Enterprise transformation rarely fails because of strategy. It fails because of execution, and one of the most complex parts of execution is data migration.

In this episode, Mehmet speaks with Dominik Wittenbeck, CTO at SNP, about the real mechanics behind SAP transformations and why data migration is often the most underestimated phase of enterprise modernization.

They explore how organizations approach SAP migrations, the risks of underestimating data transformation projects, and why Selective Data Transition (SDT / Bluefield®) is becoming a preferred strategy for many enterprises.

The conversation also dives into how AI is beginning to reshape large-scale IT transformation projects, from presales and planning to testing and root cause analysis. Dominik shares practical insights on how AI can augment consultants rather than replace them, helping organizations manage increasingly complex system transformations with greater speed and accuracy.

⸻

About the Guest

Dominik Wittenbeck is CTO at SNP Schneider-Neureither & Partner SE with over 20 years of experience in SAP-centric enterprise transformations. His focus is Selective Data Transition (SDT / Bluefield®) and scaling scarce migration expertise through structured methods and AI-supported orchestration.

Connect with him on LinkedIn:

https://www.linkedin.com/in/dominik-wittenbeck-61a64669/

⸻

About SNP

SNP is a global software and consulting company specializing in data transformation, system landscape modernization, and SAP migrations. With its Kyano® platform, SNP enables complex transformations in a structured, rule-based, and scalable way.

https://www.snpgroup.com/

⸻

Key Takeaways

• Data migration is often the most underestimated element of digital transformation projects.

• Selective Data Transition (SDT / Bluefield®) offers a middle ground between greenfield implementations and full system conversions.

• AI can significantly accelerate presales, documentation, and root cause analysis in complex IT transformations.

• Automation and AI are augmenting consultants rather than replacing them, enabling teams to manage more projects at scale.

• Structured transformation platforms and methodologies are becoming essential as enterprise change accelerates globally.

⸻

What You Will Learn

• Why SAP migrations remain one of the most complex enterprise IT initiatives

• The differences between greenfield, brownfield, and selective data transition approaches

• How AI is being used today in data migration planning and execution

• The hidden risks that organizations face when migration projects are underestimated

• How enterprises can scale transformation expertise despite the shortage of experienced consultants

⸻

Episode Highlights (Chapters)

00:00 Introduction and Dominik’s background

01:00 Why data migration expertise is scarce

05:00 Why migration projects often scare IT teams

09:00 Misalignment between IT and business in transformation projects

14:00 What Selective Data Transition (Bluefield®) means

18:00 The biggest risks when data migration is underestimated

21:00 Where AI is already helping transformation teams

27:00 How AI improves project handovers and knowledge transfer

30:00 Ensuring deterministic and auditable data transformations

33:00 Using AI for root cause analysis in migration projects

36:00 MCP servers, agents, and AI orchestration

38:00 AI-powered testing and validation

41:00 The knowledge loss problem in consulting projects

45:00 The future of AI in enterprise transformation

48:00 Will AI replace consultants? Dominik’s perspective

52:00 Staying relevant in the age of AI