Why S/4HANA Programmes Go Live but Fail to Deliver
SAP ends standard maintenance for ECC in 2027. Extended maintenance is available until 2030 — but at a surcharge. The clock is running, and most organisations know it. What many CIOs and IT leaders are less prepared for is how difficult the transition tends to be in practice: according to a Horváth study of 200 senior leaders at SAP-using companies, 60% of S/4HANA projects exceed both budget and timeline, projects run an average of 30% over schedule, and nearly two thirds report significant quality deficits in the outcome.
Why so many projects fall short
The Horváth research is specific about the causes: scope creep, weak project management, and underestimated data migration and testing phases. These are not isolated failures. In our view, they point to a common root: most S/4HANA programmes are scoped as system replacements. Move the processes across, cut over to the new platform, close the project. The technical migration is treated as the destination. It isn’t. The technical migration is the starting point. Everything SAP promises on the other side of it — Business AI, real-time analytics via BTP, integrated dashboards — depends on the quality and architecture of the data beneath it. When data migration is treated as a line item to be resolved under go-live pressure rather than a foundation to be designed upfront, organisations arrive at cutover with a new system running on poorly understood data.
How AmaliTech approaches it differently
The Horváth research points to a consistent pattern: project complexity and resource requirements are underestimated from the start.
AmaliTech works alongside the migration programme as a dedicated data partner. We scope and deliver the data foundation as a first-class programme workstream so that when the system goes live, the analytics, reporting, and AI capabilities organisations are investing in are ready to activate, not still on the backlog.
The 2027 deadline is fixed. Project timelines rarely are — and in our experience, it is often the data foundation that slips first. Not because organisations don’t care about it, but because no one inside the programme is specifically accountable for it. That’s the gap we fill.