Knowledge-Driven Enterprise Engineering relies on the composition paradigm. Composition describes the process of assembling and orchestrating a digital enterprise organism. In a more detailed view, composition is the orchestrated assembly of data, processes and services.

The entire enterprise is regarded as a coherent universe, meaning that there are no isolated data, process and application islands. There is only one model type with well-defined syntax and semantics.

The activities of business architect, process designer and application designer are combined in one role: the role of the business analyst. Business analysts fulfill composition roles.

Composition is a collaboration-driven effort that involves non-technical business subject matter experts and business analysts. In contrast, traditional application development still is an IT expert-driven effort.

Knowledge-Driven Enterprise Engineering combines three principles: meta data-driven, model-driven and component-based. All of these principles materialize in an Integrated Composition and Execution Environment (ICEE), which supports the entire engineering process.

Knowledge-Driven Enterprise Engineering relies on a semantically rich ontology-based knowledge asset repository. Semantic integration is not an afterthought but is enforced from the start.

Knowledge-Driven Enterprise Engineering produces dynamic and executable models. Changes to the model immediately impact the execution without requiring intermediate recompiles and coding. Knowledge-Driven Enterprise Engineering implements the 'model > validate > execute' paradigm, which forms a distinct contrast to the traditional 'model > code > debug > test > install > execute' paradigm.

With Knowledge-Driven Enterprise Engineering, business process models are always explicit, rather than implicit (i.e. coded processes). Also, Knowledge-Driven Enterprise Engineering supports both deterministic and non-deterministic processes (case management). Processes are built for rapid modification and extension, and there is no entry barrier for processes built for short-lived situational needs. The result is higher process flexibility and operational transparency at the organizational level.

Knowledge-Driven Enterprise Engineering is a highly iterative process, supporting iterative data and process refinement as well as iterative application evolution. Iterative and incremental engineering with short iterations provides more frequent feedback from stakeholders and users.

Knowledge-Driven Enterprise Engineering is a very lean engineering process that produces consistent, predictable results. It forms a stark contrast to the traditional software engineering process that is considered complex and typically requires 20+ role types with expert IT knowledge in various specialist domains.