The need for the agreed definitions was quite obvious from the beginning of the project. In response to this need, the first version of several basic definitions has been developed under the title of “Definition Guidelines”.Continue reading “Definition Guidelines”
As stated by Kurtz & Snowden, (2003) the Cynefin framework “originated in the practice of knowledge management as a means of distinguishing between formal and informal communities, and as a means of talking about the interaction of both with structured processes and uncertain conditions”. The framework provides a comprehensive overview of organizational knowledge exchange. Furthermore, it also identifies four main knowledge flows namely complex to knowable; knowable to chaotic; knowable to known; and chaotic to complex for more information see here. This post briefly elaborates these knowledge flows. In addition to this, the post also reflects on their applicability within the context of managing knowledge for new rolling stock introduction projects in the Netherlands Railways. Next section is distributed such that the first paragraph provides the elaboration and second the reflection on the applicability of each knowledge flow within the stated context.
There is no denying the rapid growth of the complex systems that continuously emerge in the world around us. Technological advancements spawn system after system, each increasing in interdependence on other systems that have come before. Systems, if ever they were separated are vigorously moving towards interconnectedness (Arnold & Wade, 2015). As systems continue to grow in scale and complexity, system integration (SI) has become a key concern (Madni & Sievers, 2014). (ISO 15288 Committee, 2015) states that the purpose of integration is: “to synthesize a set of system elements into a realized system (product or service) that satisfies system requirements, architecture, and design”. Moreover, SI involves interfacing and enabling the interactions of component elements to collectively provide the functionality needed by the system to accomplish its goals. SI increases in complexity when there are legacy systems that need to be integrated, and when humans are an integral part of the system (Madni & Sievers, 2014). All of which is the case for the railway operating network.