TL;DR

• SAP’s own Q2 2026 release notes confirm general availability of the S/4HANA Custom Code Migration Agent, which runs ABAP Test Cockpit checks across your entire custom code package and applies a mix of automated and AI-assisted fixes. That is a direct, dated answer to the delay cause that shows up most often in research: underestimated custom code remediation.
• A Horváth survey of 200+ SAP executives, reported by Consultancy.me, found that more than half of companies with an S/4HANA transformation underway are still stuck between the Prepare and Deploy phases, and that finished projects ran 30% over their planned timeline on average. We’re citing this through the write-up we could access rather than Horváth’s original report, so treat it as a well-sourced secondary figure, not an SAP-verified one.
• Deployment model sets your baseline before anything else. SAP’s own comparisons describe greenfield cloud implementations finishing in a few months, against several months to a year or more for on-premise or heavily customized builds.
• The real speed mechanism inside SAP’s Activate methodology is Fit-to-Standard: workshops that lock in preconfigured, standard processes before configuration starts, backed by content like the Enterprise Management Layer, which replaced the now-retired SAP Model Company.
• We checked what test automation vendors and systems integrators publish on “faster S/4HANA implementation” specifically. Vendors consistently pitch testing efficiency as the lever. SIs pitch their own branded delivery methodology. Nobody we found treats the actual mechanics, deployment model, preconfigured content, and where schedules really slip, as a standalone topic. This is that piece.

Most organizations don’t get stuck because nobody told them S/4HANA migrations take time. They get stuck because the levers that actually shorten a timeline sit in a handful of specific decisions, deployment model, how much you customize versus adopt standard process, and how early you deal with custom code, and those decisions rarely get discussed together. This piece walks through what moves the needle, what SAP itself ships to help, and where the delays actually happen. If you’re looking for the testing-specific steps inside a migration, our migration testing checklist covers those in depth. This one stays at the program level.

Deployment model sets your floor before anything else

SAP’s own comparison of implementation timelines draws a clear line. Greenfield cloud implementations “can often be completed within a few months.” Greenfield on-premise implementations “can take anywhere from several months to a year or more.” Brownfield cloud migrations “can take several months,” though for select preconfigured cloud solutions “this timeframe can sometimes be shortened to weeks.” Brownfield on-premise again runs “several months to a year or more.” None of these ranges is a promise, they depend heavily on scope and customization, but they establish something worth saying plainly: choosing cloud over on-premise, and choosing to adopt standard process over heavy customization, does more to set your baseline timeline than almost any project management technique layered on top afterward.

Which migration path you’re on, New Implementation, System Conversion, or Selective Data Transition, each defined in detail in our migration testing checklist, changes the configuration workload in the same direction. A New Implementation rebuilds configuration from scratch, which costs time up front but avoids inheriting years of accumulated customization. A System Conversion inherits your existing configuration and business logic, which is faster if that configuration is already close to standard, and slower if it isn’t. That’s a configuration and change-management question, not a testing question, and it’s usually decided long before testing scope gets discussed.

Fit-to-Standard cuts the build before you customize it

SAP’s own product page for the Activate methodology describes its six phases, Discover, Prepare, Explore, Realize, Deploy, and Run, and is direct about the mechanism behind the timeline: organizations are told to “adopt preconfigured best-practice business processes to create a strong foundation” and to “launch SAP Cloud ERP fit-to-standard processes quickly and efficiently.” Fit-to-Standard workshops sit inside the Explore phase, and their job is to confirm your solution design against SAP’s own standard processes before configuration begins. Every process a Fit-to-Standard workshop confirms as “standard, no change needed” is a process that skips custom development entirely, which is where the actual time savings comes from, not the workshop itself.

The preconfigured content behind this has changed. SAP Model Company, once the go-to accelerator, has been retired and is no longer available. Its replacement is the Enterprise Management Layer, a global template SAP describes as helping to “accelerate the implementation project, reduce risk by using verified and tested preconfigured content, and enable early kick-start project activities,” with preconfigured, localized processes across up to 49 countries. 

Separate from that, SAP Best Practices content, accessed through SAP Signavio Process Navigator, ships process flows, tutorials, and setup instructions across more than 40 country versions. There’s also the SAP S/4HANA Fully Activated Appliance, which can stand up a preconfigured environment within hours in the cloud or days on-premise, worth flagging that this is built for sandboxing and demonstration, not a production go-live, so it shouldn’t be read as a real implementation timeline.

RISE with SAP adds a formal methodology on top of this, described on SAP’s own page as helping customers “adopt SAP Business Suite offerings faster” through “best practice templates,” a “standardized framework,” and an “integrated toolchain.” SAP’s broader RISE page goes further, describing an AI-assisted transformation approach built around seven AI-enabled migration assistants, covering System Analysis, Custom Code, Data Management, Configuration, Test Management, Rollout, and Project Management, positioned as “a fast, predictable path to the Autonomous Enterprise.” That’s SAP’s own current framing, and it’s a meaningfully stronger claim than the plain methodology page makes on its own.

Where implementations actually stall

The Horváth survey cited above, reported through Consultancy.me since we couldn’t access Horváth’s original report directly, names several causes behind the 30% average timeline overrun: expanding project scope mid-transformation, suboptimal project delivery, poorly managed data transitions, blueprints that get revised after the project is already underway instead of staying fixed, weak governance and thin executive support, and insufficient change management and training. None of that is specific to SAP. It’s what derails any large transformation program, and S/4HANA migrations aren’t immune to it just because SAP ships tooling.

Data quality problems are a more S/4HANA-specific version of the same failure. Consulting firm ibsolution names three recurring culprits: undetected duplicate master data that legacy systems’ informal workarounds used to paper over, an absence of clearly assigned data governance responsibility, and underestimated effort converting Business Partner records, which ibsolution calls “one of the most time-consuming aspects” of a migration and states “typically takes longer than originally planned.” Worth noting directly: S/4HANA is less forgiving of messy data than ECC was, fields that were optional before can become mandatory, and a field that was never validated for twenty years can suddenly block a load.

Custom code remediation shows up in both the Horváth data and the SAP PRESS timeline comparison as a named delay cause, and it’s usually underestimated for a specific reason: teams try to review every line of custom code that exists rather than the code the business actually runs. This is exactly the problem SAP’s newest tooling is built to solve, covered next.

Custom code remediation just got a real 2026 answer

SAP’s Q2 2026 Business AI release confirms general availability of the S/4HANA Custom Code Migration Agent, which “accelerates ECC-to-SAP-S/4HANA migration by automating custom ABAP code conversion.” The documented mechanism runs SAP S/4HANA readiness checks through the ABAP Test Cockpit across your entire custom code package, interprets the findings, categorizes issues by complexity, and applies a mix of deterministic quick fixes and AI-assisted code changes, while keeping every change traceable through transport requests. That directly answers the underestimation problem described above: instead of a team manually triaging years of accumulated ABAP, the agent scopes and categorizes the work first.

The same release covers Joule Studio, part of SAP’s Early Adopter Care program, which lets teams generate product requirements and technical specifications from company-specific context and build guarded AI coding assistants for S/4HANA Cloud Public Edition. Worth being precise here: Joule Studio is an early-adopter capability, not a generally available one, so it belongs in the “emerging” column, not the “ship it today” column the Custom Code Migration Agent sits in. Everyone in this market claims AI accelerates implementation. The distinction that actually matters to a planning team is which of those claims are GA and which are still in early access, and SAP’s own release notes make that distinction clear if you read past the headline.

Where Sahi Pro fits into this

Testing efficiency is one lever in everything above, not the whole story, and we’re stating it that way deliberately. Sahi Pro’s proprietary engine, not a Selenium or Appium wrapper, identifies elements by relationship and context instead of fixed DOM position, and runs a single test flow across SAP GUI, Fiori, desktop, mobile, and API in one script. 

During an implementation, that matters most wherever legacy and new interfaces run side by side, and wherever custom code changes mean regression suites need to be rebuilt rather than patched. Sahi Pro customers report a 90% reduction in regression man-hours and an 80% reduction in test maintenance compared to conventional tools, figures drawn from Sahi Pro’s 1,000-plus enterprise customer base as a whole, not from an implementation-speed study specifically, and we’re naming that distinction rather than implying a result we haven’t measured for this exact scenario. 

For the execution-level testing steps inside a migration itself, our migration testing checklist is the piece to read next.

Ready to see how a single test flow handles both your legacy interfaces and their replacements during implementation? Book a demo and bring the process you’re currently testing twice.

Sources

• SAP: Activate Methodology (six-phase methodology, Fit-to-Standard mechanism, preconfigured process language, quoted directly)
• SAP PRESS: What are the preconfigured system solutions from SAP (SAP Model Company retirement, Enterprise Management Layer, SAP Best Practices content, Fully Activated Appliance, quoted directly)
• SAP PRESS: How long does it take to implement SAP S/4HANA (deployment model timeline ranges, quoted directly)
• SAP: RISE with SAP Methodology (RISE methodology speed claims, quoted directly)
• SAP: RISE with SAP (seven AI-enabled migration assistants, “fast, predictable path to the Autonomous Enterprise,” quoted directly)
• SAP News: SAP Business AI Release Highlights, Q2 2026 (S/4HANA Custom Code Migration Agent general availability, Joule Studio early adopter status, quoted directly)
• ibsolution: Why SAP S/4HANA data migrations often take longer than planned (duplicate master data, governance gaps, Business Partner conversion effort, quoted directly)
• Consultancy.me: 90% of companies kicked off their SAP S/4HANA implementation process (Horváth survey figures, attributed to Horváth via this write-up, not verified against Horváth’s original report)
• Tricentis: Speed SAP S/4HANA Implementation with Automated Testing (competitor coverage check, referenced for what Tricentis publishes on this topic, not for its specific case-study figures)
• Worksoft: Automation & Change Intelligence Speeds S/4HANA Migrations (competitor coverage check)
• Deloitte: Taking the lead with a Brownfield+ approach for SAP S/4HANA (SI coverage check, referenced for what Deloitte publishes on this topic)
• Sahi Pro proof points: internal, per Sahi Pro brand and positioning documentation (90% regression savings, 80% maintenance reduction, company-wide figures)