Proceskompleksitet

Proceskompleksitet, or process complexity, describes how difficult it is to understand, model, design, and manage a process because of the number of elements and how they interact. It is used across fields such as software development, operations management, and industrial engineering. Higher complexity generally reduces predictability and increases cycle times, error rates, and the risk of bottlenecks, while lower complexity improves clarity and control but can limit flexibility.

Key dimensions of proceskompleksitet include structural complexity (the count of activities, decision points, branches, and handoffs), dynamic complexity (variability in inputs, demand, or performance of steps), temporal complexity (scheduling and synchronization across steps), and cognitive complexity (how hard it is for participants to understand the process). External complexity arises from dependencies on other processes, suppliers, or regulatory requirements.

Measuring process complexity involves metrics such as cycle time, throughput, defect rate, rework, number of variants, and the frequency of handoffs. Techniques like process mining and value-stream mapping help visualize flows and identify sources of complexity. Simulation can estimate how changes affect performance under different conditions.

Management approaches aim to reduce unnecessary complexity while preserving essential functionality. Strategies include standardization and simplification of steps, modularization and automation, reducing handoffs, decoupling processes, adopting common data models, and improving governance and documentation. It is important to balance flexibility with predictability; some complexity may be necessary to handle variation, customization, or regulatory demands. The goal is to achieve maintainable processes that perform reliably at acceptable cost.