Choosing Your Path to S/4HANA: Fit-Gap Analysis and the Greenfield-Brownfield Decision
Before a program can commit to a realistic timeline, someone has to decide how the business will actually get to S/4HANA: redesign around the new defaults, carry the existing configuration forward, or take a selective path through specific processes. That call has to be made early enough to still hit the December 2027 deadline, and AI-assisted tools can help teams get through the underlying analysis faster.
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Choosing Your Path to S/4HANA: Fit-Gap
Analysis and the Greenfield-Brownfield Decision
Before a program can commit to a realistic timeline, someone has to decide how the business will actually get to S/4HANA: redesign around the new defaults, carry the existing configuration forward, or take a selective path through specific processes. That call has to be made early enough to still hit the December 2027 deadline, and AI-assisted tools can help teams get through the underlying analysis faster.
7 min read | Orpington Technologies Insights
SAP's mainstream maintenance for ECC ends December 31, 2027. That date alone would be reason enough to act, but the pressure builds from another direction too. As more of the installed base moves off ECC, the network of consultants, systems integrators, and third-party tools built up around that platform thins out with it. Specialist ECC support is already harder to book than it was a few years ago, and that will likely keep going as attention and staffing shift toward S/4HANA.
Long before a program sets a go-live date, it has to answer a harder question: what does S/4HANA actually change about how this specific business runs, and how much of that change is the organization prepared to absorb. That is the job of fit-gap analysis, working through SAP's roughly thousand-page simplification list to find which items apply and what they mean for existing processes. The result of that work is what determines whether the right path is greenfield, brownfield, or something selective in between, and putting off that decision eats directly into the runway a program has left before 2027. AI-assisted matching tools are increasingly used to speed up the early pass through the list, which helps, but the decision itself still belongs to people who understand the business.
A Thousand Pages, One Business at a Time
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The simplification list itself is the same for every SAP customer moving to a given S/4HANA release. What isn't the same is which of those thousand pages of changes actually touch a specific organization's configuration. That mapping exercise has historically been slow and manual, dependent on a small number of senior consultants who know the legacy system and the target state well enough to spot the gaps that matter.
Get the fit-gap analysis wrong, or rush it, and the consequences surface later, at the worst possible time: in testing, or in hypercare, when a process that quietly relied on a since-simplified data structure breaks in production. It happens more than it should. Horváth's 2025 study found that fewer than 10% of S/4HANA transformations finish without exceeding their original timeline, and incomplete or late fit-gap analysis is a recurring contributor cited across the consulting literature on why.
Getting Through a Thousand Pages Fast Enough to Decide
Matching a specific organization's transaction history and configuration against the simplification list is detailed, unglamorous work. Someone has to pull actual transaction codes, custom objects, and configuration tables, then check each item that plausibly matters against what S/4HANA does differently. Done by hand, that first pass alone can run into weeks, and it typically falls to a small number of senior consultants who know both the legacy system and the target state well enough to spot the gaps a less experienced reviewer would miss.
The pace of that first pass matters because everything downstream depends on it. The approach decision (greenfield, brownfield, or selective) cannot be made responsibly until the organization has a real inventory of what changes, and neither can a credible project timeline or budget. AI-assisted tools are one way teams are compressing this stage now, cross-referencing configuration data against the simplification list to flag what likely applies so consultants spend their time on judgment calls instead of manual lookups. That kind of help matters most when the analysis has to fit inside a shrinking runway to 2027.
How S/4HANA transformation projects actually split by approach, across a 200-company study.
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Why the Approach Decision Can't Wait
The transformation-approach decision and the support-timeline question are more connected than they might first appear. Basis Technologies' adoption modeling shows the share of the ECC and early S/4HANA installed base falling outside mainstream support climbing from 33% at the end of 2025 to 55% by the end of 2027. Organizations that delay a clear fit-gap decision aren't only delaying the migration itself. They're increasingly delaying it into a window where they're paying for extended or premium support on the system they're trying to leave.
Making the approach decision earlier doesn't remove the pressure a fixed deadline and a shrinking support window create. But it does give a program a credible basis for its timeline and its budget, built on an actual inventory of what has to change rather than a rough estimate. For many programs, that turns out to be the single biggest lever for keeping a transformation realistic from the start, and a faster fit-gap pass, helped along in part by AI matching tools, is one way to reach that decision sooner.
55%
of the SAP ECC/S4 installed base is projected to fall outside mainstream support by the end of 2027, up from 33% at the end of 2025. (Basis Technologies)
What AI Doesn't Decide
An AI-assisted match against the simplification list can tell an organization, with a high degree of confidence, which items are technically in scope. It can't tell them whether a given process change is acceptable to the business, what the change-management cost of a given redesign will be, or which of several technically valid options best fits the organization's actual appetite for process change versus technical risk. Those remain executive and functional-leadership decisions. The tooling works best when it's framed that way from the start: a way to reach the real decisions faster, not a substitute for making them.
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Orpington Technologies | SAP S/4HANA Migration Insights
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Where This Leaves You
Orpington Technologies' ERP Diagnostic work is built for exactly this stage: giving a program a clear, evidence-based view of scope, and a defensible transformation-approach decision, before the 2027 deadline narrows the options further. Our team pairs deep ECC-to-S/4HANA migration experience with AI-assisted analysis tools where they speed the work along, but the recommendation itself is grounded in judgment built over real programs, not a scan of the simplification list. Learn more about Orpington's approach to ECC-to-S/4HANA migration at orpingtontech.com.
Sources & Further Reading
[1]
Horváth — Study: SAP S/4HANA Transformations Rarely Go As Planned (2025)
[2]
Resulting IT / FusionGraph — Using the SAP Simplification List to Plan Your S/4 Journey
[3]
Basis Technologies — The True State of S/4HANA 2025
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