Details
Data quality is one of the most persistent challenges in large-scale SAP S/4HANA migrations, as noted in the SAPinsider Benchmark report. A key part of the process involves identifying critical data to migrate, addressing inconsistent data sources, and aligning information across functions to support reliable reporting and analytics.
In this session, Kyndryl speakers will share their insights on business decision-making needs, identifying the right data sets to migrate with a structured framework, and orchestrating and managing data decisions. They will discuss how user experiences (cost, UX, business continuity) informed their approach, including technical steps such as data refresh, testing, validation, and determining allowable deviations from standards.
Drawing from their extensive experience, our speakers will walk you through the processes and tools that have shaped their approach, offering practical steps to improve data quality, manage complexity, and create more consistent data flows across systems.
Discussion topics will include:
- Data-centricity as a Foundation: The role of data accessibility and alignment across business processes in supporting operational consistency.
- Migration Process and Validation: Techniques used for data integration, quality checks, and validation, with an emphasis on repeatability and transparency.
- Reliable Data for Decision-Making: How efforts to establish consistency and trust in data can support broader goals, including analytics and AI readiness.
Speakers
Post-event summary
The webinar titled “Navigating Data Integrity in Enterprise Migrations: Lessons from SAP Transformation,” was hosted by EDM Council and Kyndryl and focused on the business and technical realities of large-scale data migrations. The webinar featured expert insights from speakers:
- Frédéric Heinemann, Head of SAP Transformation Services, Kyndryl
- Andreas Nonnenmacher, Vice President, Data Transformation, Kyndryl
- Moderator: Jim Halcomb, Chief Research & Development Officer, EDM Council
Jim opened the session by highlighting the risks many organizations face when approaching data migration without a solid plan: “The lack of having a methodology, based on lessons learned, is really dangerous territory.” Speakers discussed key challenges that derail migration projects such as poor data quality, overwhelming data volumes, and the presence of multiple, often conflicting, sources of truth. Both Andreas and Frédéric stressed that these issues are rarely isolated and are often interconnected, compounding risks like project delays, budget overruns, and reputational damage. A participant poll confirmed that most attendees faced “all of the above” as their primary challenge, reinforcing the universal nature of these obstacles.
Drawing from Kyndryl’s own complex separation from IBM, the speakers shared practical lessons learned. They explained how they successfully migrated from over 1,800 applications down to approximately 350 in just 18 months. Rather than replicating legacy systems, the team focused on the future state, prioritizing SAP best practices and using a standardized approach to avoid unnecessary customization. Andreas advised against asking legacy system users what they wanted to preserve, noting that people tend to cling to the familiar rather than embracing new opportunities. Instead, decisions were guided by business needs and long-term value.
Data quality and selective migration emerged as central themes. The speakers recommended migrating only the data necessary for future operations while archiving legacy data separately, emphasizing that carrying forward outdated information inflates costs and risks. “Take the data you need and leave the rest behind,” Andreas advised. The speakers also shared how automating parts of the data discovery, mapping, and validation process through a tailored data transformation suite enabled faster testing, improved quality, and reduced rework.
The human element of transformation was equally important. Change management, user engagement, and early success events like transitioning to modern collaboration tools were key to gaining buy-in and easing adoption. The speakers underscored that successful migrations require alignment between people, processes, and technology, not just technical execution.
The conversation touched on the growing role of AI and knowledge graphs in improving data migrations and business processes. The group agreed that while technology continues to evolve, the fundamentals of sound data management, governance, and cross-functional collaboration remain critical to long-term success
