What in-house teams can own in an S/4HANA programme

"Should we do this ourselves, or bring someone in?" is the most expensive question on an SAP programme, because it is usually answered by default rather than on the merits. The default is to outsource the lot — which is safe, and costly, and often unnecessary.

A more useful approach is to split the work honestly. Some of it genuinely needs specialist, current SAP expertise. A surprising amount of it does not — it needs structure, ownership and a head start, all of which your own people already have or can acquire cheaply.

Here is a clear-eyed view of what sits on the in-house side of that line.

Readiness assessment

Before anything is built, someone has to establish where you actually stand: which processes are affected, where the gaps are, what decisions need making and by whom. This is business knowledge work — and the people who understand your processes best already work for you. Structured properly, a readiness assessment is one of the most ownable pieces of the whole programme, and one of the highest-value, because it shapes everything that follows.

Data quality and master-data preparation

As SAP's own guidance makes plain, data readiness is the single biggest predictor of a smooth migration — and getting data clean is structured, methodical work, not specialist build. Profiling for duplicates, gaps and inconsistencies; agreeing what "complete" looks like; fixing at source before cutover. Your team knows your data. Owning this early is both cheaper and safer than discovering it under deadline pressure.

Business testing

Test scenarios are most valuable when they are written by the people who actually run the process — they know the edge cases a generic script will miss. Designing business-led test cases and acceptance criteria is exactly the kind of work an in-house function should own, with structure rather than a consultant's template.

Change, communications and adoption

A new system that nobody adopts is a failed project regardless of how well it was built. Communications, training material, stakeholder engagement and change planning are firmly business activities. They benefit enormously from structure and consistency — and not at all from being outsourced to people who don't know your organisation.

Where the specialists earn their fee

To be clear, this is not an argument for doing it all yourself. The technical build and configuration, the deep release-specific expertise, the genuinely hard integration work — that is where external specialists earn their fee, and trying to cut corners there is a false economy.

The point is narrower: the surrounding work — readiness, data, testing, change — is structured knowledge work, and McKinsey's analysis is clear that structured knowledge work is precisely where AI is now delivering real value. With the right method, your team can carry that work to a standard that holds up, without paying specialist rates for it.

Drawing your own line

A practical exercise: list every workstream in your programme and mark each one specialist build or structured knowledge work. The second column is your in-house opportunity — and it is usually larger than anyone expects.

Our toolkits map directly onto that second column: readiness, data, testing, cutover and change, structured for the functions that own them. They are how an in-house team takes back the work that never needed a day rate in the first place.