Step 6 of 6 Intermediate 12 min

Capstone: Building Your Own Migration Roadmap

Lesson 6, the capstone — Everything in this journey lands here: a real roadmap, built from your own readiness data, that survives contact with a steering committee instead of just a slide with a countdown on it.

S
s4ready.ai Team

Prerequisites

  • Lesson 5: Data migration

Everything in this journey has been building toward one deliverable: a roadmap built from your own actual readiness data, not a generic template with a countdown pasted on top of it. This capstone is where the five prior lessons become one document you could genuinely hand to a client.

The roadmap, one picture

The migration roadmap, built from five prior lessonsWorking forward: run the readiness assessment to get the severity distribution. Apply the remediation hierarchy, swap first, retire second, rewrite last, sequenced by where critical findings concentrate. Run data quality rules in parallel, early, not at cutover. Reserve real cutover time, counted backward from the verified deadline. Each phase’s duration comes from what the previous phase actually found, not a generic template estimate.1 · ASSESSReadiness scan →severity distribution(Lesson 3)2 · REMEDIATESwap → retire → rewrite,sequenced by concentration(Lesson 4)3 · CLEAN DATADQ rules run in parallel,early — not at cutover(Lesson 5)4 · CUTOVERReal time reserved,counted backward fromthe verified deadline(Lesson 1)
Every phase’s duration comes from what the previous phase actually found — not a generic template estimate copied from the last project.

Why this roadmap survives a steering committee and a generic one doesn’t

A generic migration timeline is a set of assumed durations. This roadmap is a set of durations derived from your own data — the actual severity distribution from your assessment, the actual proportion of findings that are simple swaps versus genuine rewrites, the actual state of your master data from real DQ rule results. When a client sponsor asks “why does remediation take four months, not two?”, the honest answer is a specific number from Lesson 3’s severity breakdown — not “that’s roughly what these projects usually take.”

The one discipline that ties the whole journey together

Every lesson in this journey has quietly reinforced the same idea from a different angle: verify before you commit to a number, a date, or a claim — the mainstream-maintenance date in Lesson 1, the “unused” assumption in Lesson 4, the data quality assumption in Lesson 5. A roadmap built on verified specifics is defensible in a steering committee. One built on assumptions and templates is a guess wearing a Gantt chart.

Try it yourself — the actual capstone

Using the four-phase structure above, draft a real roadmap for a landscape you know: an actual estimated severity distribution, an actual remediation sequence based on it, an actual data-quality checkpoint before cutover, and cutover time counted backward from a deadline you’ve verified rather than assumed. If any of the four boxes has to be filled with a guess instead of a real number, that’s exactly where your next piece of work should go — before the roadmap goes in front of a client.

You’ve finished S/4HANA Migration & Clean Core

From “the countdown already running” to a roadmap built on your own verified data — that’s the complete arc. Combined with SAP AI Foundations and Build SAP AI Agents, you now have the full picture: the clean foundation this journey builds, and the AI capability the other two journeys build on top of it.

Where to go next:

Key takeaways

  • A defensible roadmap has four phases whose durations come from your own data — assessment, remediation, data cleaning, cutover — not from a generic template.
  • The single discipline running through this whole journey: verify before you commit — to a date, an “unused” assumption, or a data-quality claim.
  • A roadmap built on verified specifics survives a steering committee. One built on assumptions is a guess wearing a Gantt chart.