SAP developers are building up skills debt

SAP modernization generates “skills debt” without adequate developer training

Enterprises can spend tens of millions modernizing an SAP landscape and still leave a critical constraint unfunded: developer skills. The German-Speaking SAP User Group (DSAG) warns that companies often underestimate this part of an S/4HANA transformation. Its position is clear. Developer education should be a planned investment.

DSAG calls the resulting gap “skills debt.” It develops when a company introduces new SAP technologies faster than its internal teams learn how to use them correctly. The problem may not be visible at first. Existing developers can often keep systems working with methods they already know. But working software is not the same as maintainable software.

The cost appears later. DSAG links skills debt to longer projects, higher maintenance costs, poor architectural choices and greater dependence on external service providers. Teams may also create custom developments that require additional work with every SAP release. This weakens one of the important objectives of modernization: reducing complexity that makes future upgrades difficult.

This also creates technical debt. Developers who do not understand the newer SAP development model may reproduce old patterns on a new platform or create workarounds where standard capabilities would be more appropriate. Those decisions become expensive to reverse once applications, integrations and business processes depend on them.

For CIOs, the key issue is capacity allocation. Buying S/4HANA technology without allocating paid time for employees to master it leaves the transformation incomplete. Training needs its own budget, schedule and measurable learning paths. It must also happen early enough to influence design decisions.

The distinction matters at board level. SAP modernization is an infrastructure or application program. It changes the technical methods used to build and maintain business processes. Companies that fund the platform but not the skills needed to operate it risk moving technical debt into the new environment rather than removing it.

Legacy SAP expertise is insufficient for new S/4HANA development paradigms

Decades of SAP experience remain valuable, but they do not automatically prepare a development team for S/4HANA. Many ABAP developers have deep knowledge of SAP R/3 and ECC, including the business processes behind highly customized enterprise systems. DSAG argues that the development model has nevertheless changed enough to require deliberate retraining.

Three changes are particularly important: S/4HANA, Clean Core and ABAP Cloud. Clean Core aims to keep modifications to the standard SAP system under control so upgrades remain easier to manage. ABAP Cloud introduces development rules and approved interfaces designed for modern SAP environments. These practices can differ materially from the approaches developers learned while maintaining ECC systems for many years.

The same issue affects the user experience. DSAG says many business consultants still depend too heavily on classic SAP graphical user interface transactions and do not give enough attention to Fiori, SAP’s modern application and user-interface approach. This is not simply a visual redesign. It can affect how business processes, applications and user roles are designed.

The risk comes from applying proven legacy methods to a platform designed around different constraints. DSAG warns this can produce poor architectural decisions, time-consuming workarounds and custom software that needs attention with each new release. Deep ECC expertise therefore remains useful, but it needs to be combined with knowledge of current SAP architecture.

Executives should not treat this as a reason to replace experienced teams. Their process knowledge has substantial value. The better approach is to update their technical capabilities before important architecture decisions are made. This preserves institutional knowledge while changing the development practices that no longer fit the target environment.

The business objective is straightforward. S/4HANA should leave the organization with a system that is easier to evolve. Achieving that outcome requires developers and business consultants to change how they design software, extensions and user processes. Without that change, the company can complete the migration while missing a substantial part of its modernization goal.

Proactive and ongoing upskilling is critical before, during, and after migration

Training must start before an S/4HANA migration reaches critical design decisions. DSAG warns that waiting until implementation is underway increases project risk. By then, developers may already have made architectural choices based on outdated SAP practices.

The knowledge gaps are specific. Developers need to understand technologies such as Core Data Services (CDS), the RESTful Application Programming Model (RAP), and Fiori. CDS provides a modern way to define and consume business data. RAP supports the development of modern SAP applications and services. Fiori changes how teams design and deliver business applications to users. These technologies influence architecture.

Timing therefore matters. A team that learns these concepts after design work has started may need to revise applications or technical architecture later. DSAG warns that such corrections can be expensive. The company also faces a capacity problem. Developers cannot easily maintain existing systems, deliver a migration, and acquire substantial new skills at the same time without dedicated learning hours.

CIOs should connect training plans directly to the migration schedule. Employees responsible for architecture and development need the required knowledge before those decisions become difficult to reverse. Training time should be included in capacity planning rather than added to existing workloads.

Education should also continue after go-live. S/4HANA does not force developers to stop using every ECC-era practice. Some older approaches may continue to work technically. That creates a risk: teams can complete the migration without adopting the capabilities that justified modernization in the first place.

Post-migration work provides an opportunity to reinforce new skills through practical use. Developers can apply what they learned to active requirements while becoming more proficient with current SAP methods. For executives, the objective should be sustained internal capability.

AI acceleration requires foundational developer expertise

AI can generate and explain code, but it cannot remove the need for developer expertise. DSAG’s position is explicit: “Only those who understand what constitutes good SAP code can use AI as an accelerator.” The developer still needs to determine whether generated code is correct, maintainable, secure, and appropriate for the target SAP architecture.

This changes where the constraint sits. Faster code generation has limited value if the organization lacks people capable of reviewing the output. Poor code can also be produced faster. DSAG warns that, without sufficient expertise, AI can amplify risk and accelerate the accumulation of technical debt.

Three capabilities are prerequisites according to the report: solid software engineering knowledge, automated testing, and an understanding of modern SAP development. Automated testing is particularly important because generated code still needs systematic validation. Knowledge of current SAP development practices is also necessary to identify code that technically works but conflicts with the organization’s intended architecture.

For CIOs considering AI-assisted development, this makes skills investment part of the AI business case. Productivity gains should not be measured only by how quickly developers generate code. Maintainability, testing, architecture compliance, and the amount of rework also affect the economic result.

AI and developer education are therefore complementary investments. Skilled developers can use AI to reduce time spent on suitable development tasks while retaining technical control over the result. Organizations that pursue AI without strengthening engineering competence risk increasing software volume without improving software quality.

The practical priority is to establish engineering standards before scaling AI-generated development. Teams need clear review practices, automated tests, and developers who understand S/4HANA, Clean Core, and modern SAP development methods. Under those conditions, AI can improve development speed without weakening the technical foundations of the SAP environment.

CIOs must institutionalize structured developer education as part of transformation

SAP training needs formal capacity, funding, and accountability. DSAG recommends that CIOs integrate continuing education directly into their transformation strategy. Leaving employees to learn new technologies when their schedules permit creates a predictable problem: operational work and project deadlines take priority, while skills gaps remain unresolved.

DSAG proposes five concrete measures. Organizations should define mandatory learning paths for specific roles, including ABAP, SAP Cloud Application Programming Model (CAP), integration developers, and business consultants. They should provide sandbox and test environments where employees can apply new skills without affecting production systems. Training hours should be included in capacity planning rather than added on top of existing workloads.

The other two measures concern timing and standards. Training schedules should align with migration and modernization projects so employees acquire relevant skills before they need to make important technical decisions. DSAG also recommends using its existing guidelines as a reference framework for development. This gives teams a common basis for applying modern SAP practices.

For CIOs, capacity planning is a central constraint. A training budget has little value if developers have no protected time to use it. The same applies to online courses and certifications. Organizations need to decide how much development capacity will be reserved for learning and reflect that commitment in project schedules and resource plans.

Hands-on environments are equally important. Understanding a new development method conceptually does not establish the ability to use it in enterprise software. Sandbox and test systems allow developers to work with technologies such as ABAP Cloud, CDS, RAP, and Fiori before applying those methods to critical applications. They also give teams a controlled setting for testing technical standards and development practices.

Role-based learning prevents another common problem: treating SAP education as one generic curriculum. An ABAP developer, integration specialist, CAP developer, and business consultant make different decisions and therefore require different skills. Mandatory learning paths can define the minimum knowledge each role needs while giving management a clearer view of capability gaps.

Executives should also connect education to measurable transformation outcomes. Useful measures can include completion of required learning paths, proficiency with target technologies, adoption of approved development practices, automated test coverage, and the amount of custom code that requires remediation. These are management options rather than metrics specified by DSAG, but they can help companies determine whether training is changing engineering behavior rather than merely recording course attendance.

The objective is not training for its own sake. It is to build enough internal capability to develop and maintain S/4HANA without repeatedly creating avoidable technical debt or relying unnecessarily on external providers. When skills development is synchronized with technology investment, organizations are better positioned to use modern SAP capabilities throughout the system’s operating life.

Key takeaways for decision-makers

• Skills debt raises SAP transformation risk: Large S/4HANA investments can underperform when developer capabilities lag behind the technology. CIOs should fund skills development as part of the transformation budget to limit technical debt, maintenance costs, and external dependence.
• Legacy expertise needs an S/4HANA upgrade: Deep R/3 and ECC knowledge remains valuable, but developers and consultants need current skills in Clean Core, ABAP Cloud, and Fiori. Build these capabilities before legacy practices shape the new architecture.
• Train before critical migration decisions: Waiting until an S/4HANA project is underway to teach CDS, RAP, Fiori, and other modern practices increases the risk of costly rework. Align learning milestones with migration phases and continue training after go-live.
• AI requires stronger engineering skills: AI can accelerate SAP coding, but developers must be able to assess its output and prevent technical debt. Establish modern SAP expertise, engineering standards, and automated testing before scaling AI-assisted development.
• Make education part of operating capacity: Formalize role-based learning paths, protected training time, sandbox environments, and schedules aligned with modernization projects. Measure whether training changes development practices rather than only tracking course completion.