Strategic objectives and transformation ambitions are clearly defined in most organizations. However, the results show that consistent execution remains limited. Only a minority of companies achieve a high level of execution maturity, while the majority operate at a mid-level of maturity.

Execution is therefore present, but not consistently embedded structurally. Objectives, KPIs, and responsibilities are often not aligned in a coherent way. Instead of a stable, end-to-end operating model, project-based initiatives and fragmented steering dominate.

The ability to systematically capture customer and market needs and translate them into relevant products and services is considered a key lever for future viability. In practice, however, strategic target visions and operational steering are often not consistently linked.

While customer-related objectives and initiatives are defined in many organizations, end-to-end ownership and their translation into measurable KPIs remain fragmented. As a result, product and service development often occurs within individual functions or projects—with limited scalability and impact.

End-to-end processes and organizational structures form the backbone of effective transformation. In many organizations, processes have evolved historically, are functionally oriented, and are only partially standardized. This limits both scalability and the consistent execution of strategic initiatives.

The results show that IT structures and process landscapes in particular often act as systemic bottlenecks. Heterogeneous system architectures and a lack of end-to-end integration hinder automation, transparency, and the speed of change—thereby constraining organizational transformation capability.

Technological capabilities, data availability, and the use of AI are considered key enablers of transformation. In practice, however, many organizations still operate at early maturity levels. Data structures are often fragmented, governance models inconsistent, and analytical capabilities only selectively embedded.

AI initiatives are largely in a pilot phase and are rarely integrated into existing steering and value creation logic. As a result, technology remains more of a supporting factor than a scaled value driver—with limited impact on efficiency, decision quality, and execution.

Change is broadly accepted across many organizations, but rarely actively shaped. Transformation is often reactive—triggered by external pressure—rather than driven by an intrinsically embedded mindset for change.

The results show that cultural drivers of change are only selectively developed. Agility, continuous learning, and adaptability are rarely firmly embedded in leadership approaches and day-to-day processes. Truly high-change organizations remain the exception, while the majority tend to manage transformation rather than actively drive it.