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.
- Complex to knowable
Snowden, (2002) uses the analogy of Just In Time (JIT) stock, used within the supply chain industry to advocate the case for JIT knowledge management for this knowledge flow. The idea revolves around the concept that it cannot be known in advance all that an organization needs to know, and when the organization needs that. Therefore, Snowden, (2002) states that “informal communities of the complex domain can self-organize and self-manage their knowledge in such a way as to permit that knowledge to transfer to the formal, knowable domain on JIT basis”. There are a number of techniques presented in this regard which include flagging by subject matter (e.g. organizational storytelling), expertise location systems, and clustering, which here implies clustering of like-minded or like-interested people (Snowden, 2002).
By my reckoning, there are at least two areas, within the context of new rolling stock introduction, where such an approach to knowledge management can be fruitful and effective. The first is at the managerial and strategic level where program managers and program directors require just in time knowledge to enhance their knowledge about the subject matter. For instance, when deciding between the acquisition of a new sprinter series and double-decker trains. The second area is around the development of expertise locations where experts such as material managers, production engineers from different programs can share ideas on complex issues and use each other experiences and learn from each other in a trustworthy environment.
- Knowable to chaotic
Disruption from knowable to chaotic is regarded as a necessary measure to disrupt the entrained thinking of expert communities by Snowden, (2002). In this regard, he proposes linking experts from different fields for such disruptions. However, he stresses that mere linking of experts is not enough and states that linking of experts in combination with pressure and starvation of resources is critical to creating powerful results. The technique is suggested more as a ritual rather than an unexpected process. Moreover, such disruptions are deemed more effective and facilitate better learning if performed cyclically.
From my perspective, such intended disruption can play a significant role in preparing the organization in general for future unknown uncertainties. More specifically, within the context of new rolling stock introduction, such cyclic disruptions can assist in reducing the initial number of failures of new train series mostly commonly known as childhood diseases within the new rolling stock introduction teams. Besides this, cyclic intended disruptions can provide an opportunity, to the rolling stock teams to enhance their resilience and improvise effective solutions under a scarcity of resources and time pressure.
- Knowable to known
Kurtz & Snowden, (2003) regard movement from knowable to known domain and back as “incremental movement”. Since known domain is a domain of process reengineering and the focus is on efficiency, Kurtz & Snowden, (2003) state that “structured techniques are not only desirable but mandatory in this space”. In contrast to this, not all cause of effect relationships are fully known in the knowable domain. Kurtz & Snowden, (2003) regard knowable domain the domain of “systems thinking, the learning organization, and the adaptive enterprise”. Furthermore, organizations mostly rely on expert opinion in the knowable domain mainly because of time and cost constraints.
By my reckoning, from time to time several areas emerge out of complex Netherlands Railways sector and become knowable to the key stakeholders. Within the context of new rolling stock introduction current challenge is to determine how to share the accumulated lessons learned and best practices in a manner that enhance their utilization and learning. Some aspects of this challenge are knowable and can be made known through incremental movement and further scientific investigation.
- Chaotic to complex
Snowden, (2002) states that disruptions in chaos can be used to “create radically new capability within the ecology” and “transform the knowable domain of experts and stimulate the creation of new networks, communities and trust/experience relationships.”. Besides this, it is also explicitly pointed out by Snowden, (2002) that “chaotic space is not of itself the only source natural communities” and “normal day to day interaction of human agents is a constant source of new communities”.
Fortunately, chaos now is rare and unwanted domain within the context of new rolling stock introduction. However, complex systems like railways are always prone to chaotic situation. The Netherlands rail sector as a whole has come a long way from that chaotic situation and many lessons have been learned along this journey. Nevertheless, it reiterates the need to be critical of one’s preparation for upcoming challenges especially now when off the shelf train acquisition is more mainstream. Therefore, there is a need to have a coherent, learning and resilient approach towards lessons learned and best practices accumulated in this journey.
Kurtz, C. F., & Snowden, D. J. (2003). The new dynamics of strategy: Sense-making in a complex and complicated world. IBM Systems Journal, 42(3), 462–483. https://doi.org/10.1147/sj.423.0462
Snowden, D. (2002). Complex acts of knowing: Paradox and descriptive self-awareness. Journal of Knowledge Management, 6(2), 100–111. https://doi.org/10.1108/13673270210424639