For decades, the classic product development process (PDP) was the backbone of industrial development: clearly structured, linear, with fixed handover points between mechanics, electronics, and software. However, this structure is becoming less effective in an increasingly networked world. Modern products are no longer self contained objects, but part of complex system landscapes embedded in data flows, digital services, and feedback from operations. This means that the old logic of ‘define design produce’ is no longer sufficient. PDP must be thought of as a dynamic system that integrates interactions, dependencies, and learning loops from the outset. Systems thinking means recognizing connections rather than optimizing in isolation. Today, decisions in mechanics affect software, data architectures and service processes and vise versa. A modern PDP must structurally reflect this interconnectedness. This begins with a system architecture developed at an early stage that brings together requirements, functions, data flows, and operating conditions. It serves as a common language between disciplines and forms the basis for traceability, simulation, and adaptation throughout the entire AI based Lifecycle management. Instead of rigid phases, iterative cycles are needed: short architecture and integration sprints, early testing, virtual prototypes. In this way, learning becomes part of the process and not a corrective measure. In addition, end to end data chain digital threads are crucial for making changes transparent and keeping knowledge usable across disciplinary boundaries. In systemic thinking, quality is understood as an emerging property: safety, reliability, maintainability, and data integrity arise from the interaction of components. This perspective requires not only new methods (e.g. MBSE, DSM, AI supported lifecycle management), but also a rethinking of the organization. Roles such as system architects and lifecycle owners link disciplines, while management creates the framework for interdisciplinary decisions. Those who embed systems thinking early on in the PDP reduce late waves of change, improve integration capabilities, and create sustainable knowledge continuity. This makes the PDP itself an adaptive system capable of producing products that can hold their own in networked environments. The transition from product to system is not a trend, but a necessary evolution of technical development.
Systems thinking in the product development process: why PDP needs to be rethought
Published 2025 in Journal of Intelligent System of Systems Lifecycle Management
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2025
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Journal of Intelligent System of Systems Lifecycle Management
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2025-11-12
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