SAP expert Eric Stajda shares what will reshape S/4HANA migrations in 2026 — from automated data prep to continuous validation and reconciliation.
As SAP S/4HANA migration programs intensify worldwide, one lesson from 2025 stands out above all others: data readiness — or the lack of it — is what makes or breaks a migration. This was the central theme of a recent LeverX webinar, “S/4HANA Migration Gone Wrong: Three Costly Mistakes and How DataLark Helps to Avoid Them,” where Eric Stajda, VP of Services and Product Development at LeverX, dissected the most common reasons S/4HANA migration projects fail. From fragmented legacy data to misaligned engineering processes and late-stage reconciliation chaos, Eric outlined the issues that repeatedly undermine migration efforts and introduced practical approaches that organizations can immediately adopt to avoid them.
Now, with 2026 on the horizon, the conversation is shifting. If 2025 was the year organizations finally recognized the depth of their data challenges, 2026 will be the year they transform how they tackle them. Automation, AI-assisted mapping, continuous validation, and proactive reconciliation are no longer emerging ideas — they’re becoming essential capabilities for delivering migrations on time and with confidence.
To understand how the SAP data migration landscape will evolve next year, we sat down with Eric to explore the trends, technologies, and practices that will define successful S/4HANA transformations in 2026. With more than two decades of expertise across SAP PLM, Document Management, Engineering Change Management, BOM and Material Management, Classification, Workflow, and CAD/PDM integration, Eric brings a front-line perspective on how automation will reshape the end-to-end migration lifecycle.
Eric: For the first time, we’re seeing three major forces collide.
First, S/4HANA timelines are now very real. Organizations delayed their transformations for years and suddenly realized they no longer have the luxury of multi-year migration cycles.
Second, system landscapes have become highly distributed: PLM, CAD, multiple ERPs, cloud applications, supplier portals. Manual mapping and cleansing simply can’t keep up with the volume or complexity.
Third, automation and AI capabilities have matured enough to cover the entire migration lifecycle, not just early preparation. In 2026, automation stops being experimental and becomes a necessity for delivering migrations on time.
This combination is reshaping how companies approach their projects.
Eric: Data preparation has long been the biggest bottleneck of any SAP migration.
Teams often spend months trying to understand legacy data structures, identify gaps, and figure out how everything needs to map into S/4HANA. It’s slow, it’s manual, and it usually relies on spreadsheets that are out of date almost as soon as they’re created.
But in 2026, we’ll see a very different approach. Automation will take over the heavy lifting. It will analyze large volumes of data upfront and surface issues immediately — everything from missing attributes and inconsistent formats to duplicate records and structural problems across materials, BOMs, documents, and classifications. Instead of manually searching for what’s wrong, teams will review insights that are generated for them.
The biggest shift is that data preparation stops being a detective exercise. It becomes a decision-making exercise. Automation gives teams a clear picture of what needs attention, how legacy data aligns with SAP expectations, and which corrections will have the greatest impact.
This dramatically shortens the preparation timeline and gives organizations a much more confident starting point before they move into the later phases of migration.
Eric: The biggest shift is that mapping will no longer be a static exercise.
For as long as I’ve been doing this, teams have treated mapping as something you “finish.” But source data isn’t static. Engineering updates materials and BOMs. Classifications evolve. Legacy systems keep changing. So your mapping is technically outdated the moment you finish it.
Automation changes the model entirely. Instead of trying to finalize mapping in one pass, systems will detect changes in source data as they occur and adjust mappings accordingly. Teams will approve recommended updates rather than redoing everything manually. Rules will stay consistent across all migration cycles, and alignment between engineering systems and SAP will be automatically maintained.
It becomes a living process rather than a one-time task. That’s a huge improvement we are bound to see in 2026.
Eric: This is where automation has the biggest impact: 2026 is the year cleansing and validation move fully upstream.
Traditionally, teams load data into SAP, discover a bunch of errors, go into panic mode, fix what they can, and then repeat the cycle. It’s stressful and inefficient.
In 2026, cleansing and validation will happen continuously, long before anything gets loaded into SAP. Automated checks will ensure material, BOM, document, and classification data meets SAP requirements right from the start. Dependencies will be validated automatically. Engineering workflows and SAP workflows will stay aligned, without the usual manual reconciliation.
The result is that data enters test cycles in a far more stable state. Teams spend less time firefighting and more time actually validating the system.
Eric: Much smoother and much more predictable.
When data is pre-validated and mappings stay in sync, test cycles take on a very different rhythm. You can run more incremental loads with far fewer issues. Transformation logic doesn’t have to be reinvented for every cycle. And since validations run continuously, each test load becomes more about confirming the process rather than discovering new problems.
It gives teams confidence; and that confidence is something we haven’t always had in past migrations.
Eric: Reconciliation has always been tough because you’re trying to confirm that what ended up in S/4HANA actually matches the source. Doing that manually is incredibly time-consuming.
In 2026, automation is going to redefine that experience. Systems will be able to compare source and target automatically, highlight discrepancies instantly, and show exactly what needs attention. You’ll have real-time dashboards that track readiness, show trends across cycles, and document everything for audit purposes.
It becomes far less of a scramble and more of a controlled, transparent process. In many ways, reconciliation will evolve from being the most stressful phase to one of the most predictable ones.
Eric: Start early, and treat data as a first-class workstream, not an afterthought.
The projects that struggle are the ones that underestimate the effort needed to get data ready.
I always recommend running a readiness assessment right away, even before configuration begins. Look for the places where manual work is slowing you down, and identify where automation can give you the biggest gains. And above all, approach mapping, cleansing, and validation as continuous activities. That mindset shift alone can save months of effort.
When organizations embrace automation across the lifecycle — not just in one area — they tend to see smoother migrations, fewer surprises, and more predictable outcomes. That’s exactly what 2026 is going to reward.
And I’ll add this: tools like DataLark are emerging as extremely helpful in bringing that automation into the process early, not halfway through the project. What I like about platforms in this category is that they integrate seamlessly into existing migration workflows. They don’t replace your methodology — they accelerate it. They give teams the ability to identify issues sooner, iterate faster, and enter test cycles with a level of confidence that simply wasn’t possible a few years ago.
So my advice is simple: treat data as a continuous workstream, embrace automation from the start, and use tools designed specifically to support SAP migration teams. If you do that, 2026 will feel a lot less like a deadline and a lot more like an opportunity to modernize the right way.
Our conversation with Eric Stajda is clear: 2026 will usher in a fundamentally new era for SAP data migrations. The patterns of 2025 — late-stage surprises, manual spreadsheets, fragmented rules, and reactive reconciliation — simply won’t scale to the demands of modern S/4HANA programs. The organizations that thrive in 2026 will be the ones that treat data readiness as a continuous, automated, end-to-end discipline.
The shift isn’t just about efficiency. It’s about confidence, predictability, and the ability to keep complex global programs on schedule. Automated profiling brings clarity from day one. Dynamic mappings keep engineering and SAP synchronized as both evolve. Continuous cleansing and validation eliminate rework before it begins. Predictable test cycles reduce stress on teams. And automated reconciliation closes the loop with accuracy that manual methods can’t match.
For organizations looking ahead, the path forward doesn’t have to be overwhelming, but it does need to be intentional. Depending on where your team is today, your next step could be one of several:
As Eric highlighted, the value of automated tools lies in how seamlessly they fit into existing migration methodologies. They don’t replace a team’s expertise or the structure of the project — they multiply the impact. By embedding automated profiling, continuous validation, transformation insight, and reconciliation into the migration pipeline, platforms like DataLark help organizations avoid the patterns that have historically derailed SAP programs.
Ultimately, 2026 offers organizations a choice: continue relying on manual processes that introduce risk and unpredictability, or adopt the kind of automation that allows teams to move faster, react with clarity, and enter their S/4HANA cutover with confidence.
For teams ready to modernize their approach, now is the ideal moment to explore how automated data readiness can reshape not just their migration, but the long-term integrity and agility of their entire SAP landscape.