Spinning Ideas into Action: Embracing the Messy Journey of Knowledge Creation in Systemic Design
From Sparks to Systems: Transforming Raw Ideas into Actionable Knowledge
Why Are We Avoiding Complexity in System Change?
The creation of systems and start of systemic interventions is a question that has captivated me throughout my engagement with systemic design and the theme of knowledge creation within it. In this moment of creation… Why are we more inclined to pursue projects that come with predefined blueprints, established frameworks, and streamlined pathways? Why do so few people venture into engaging with more complex systems, leaving those systemic interventions, which are often more crucial and impactful, unexplored?
We can observe that people are naturally drawn to standardized frameworks — those that offer clarity and predictability. These blueprints provide visible, actionable steps, making such projects more accessible and less daunting. On the other hand, most systemic interventions require navigating ambiguity, where both the path and the goal remain elusive and undefined.
Do we really think the challenge lies in a lack of skill or knowledge? Are these engagements too complex and impossible to act upon? I wonder if this assumptions truly holds. It feels as though the barriers are rooted in how we perceive and handle this messy, multifaceted process rather than in complexity, knowledge, or capabilities.
In my view, the key to unlocking these interventions lies in the area of knowledge creation — a dynamic, iterative process where chaotic ideas are shaped, refined, and ultimately transformed into meaningful action.
Where Does System Creation Really Begin?
System creation and the development of system interventions through systemic design are anything but linear. To understand this process better, I propose, we must first ask: Where does it start?
I think the answer lies in what I call the “insight spark” — a human, experiential, emotional, and cognitive moment when something feels interesting or possible, something that grabs our attention. I believe this spark, though fleeting, is the genesis of systemic design.
It begins with an intuition or a moment of clarity but quickly evolves into a whirlwind of fragmented insights, unfinished exchanges, incomplete thoughts, and unstructured conversations. These sparks are raw and messy, emerging from human interactions — random conversations, scribbles on napkins, personal reflections, and, if you’re lucky, some sketches. They are deeply human and unpolished, yet they hold the seeds of transformation.
It is precisely in this messiness that systemic change finds its potential.
Nurturing the Spark: The Human Challenge of System Creation
Why do so few of these sparks evolve into systemic interventions? The problem isn’t the absence new, following sparks; it is the challenge of nurturing them.
Many individuals lose sight of the whole amidst the overwhelming complexity of their disorganized ideas. Insight sparks are human and fragile, requiring persistence, clarity, and the courage to embrace uncertainty.
One significant barrier to nurturing these sparks is ambiguity aversion — our inherent discomfort with uncertainty. Research, such as the , reveals that people prefer situations where outcomes are articulated and thus perceived as predictable. When faced with uncertainty, many abandon their initial ideas rather than endure the discomfort of ambiguity.
This aversion is particularly relevant in systemic design. Insights often arise from messy, iterative processes that resist categorization and defy immediate clarity. Without a connection to familiar frameworks or predictable outcomes, these ideas appear risky and are often discarded prematurely.
For instance, consider an individual struck by a vision for change — a compelling, albeit fleeting, idea. This person would discuss it with others, sketch their thoughts, and explore possibilities. Yet, over time, the idea fades into the background, overshadowed by more straightforward, predefined pursuits.
This vulnerability underscores the human role in systemic design. The insight spark is not enough. To turn it into a system, we must acknowledge our biases, embrace ambiguity, and create environments that nurture these fragile beginnings.
The question then becomes: How do we harness this chaos and transform it into meaningful action?
Transforming Ideas: The Spinnery as a Metaphor for Knowledge Creation
Once we embrace the ambiguity of these early sparks, the next step is to shape and refine them, much like the transformation of wool into yarn, let’s consider this process as a guiding analogy. While it might be oversimplified, I hope it will effectively convey the concept.
During a visit to a sheep farm and spinnery in Norway, managed by a former biology researcher, I observed the journey of wool transforming into yarn. At first glance, the process seemed straightforward: sheep grow wool, the wool is washed, and then it’s spun into yarn using machines. Simple, right? But when you consider the purpose of each operation and its prerequisites, a rich metaphor for knowledge creation emerges.
This simple journey mirrors the evolution of raw human ideas into actionable knowledge. Just as sheep grow wool organically over time, we accumulate thoughts and ideas through our experiences — sparks of insight, energy, and interest arising from multiple conversations, reflections, and “aha” moments. This “wool” of ideas is messy and unrefined — much like our initial thoughts, which are often disorganized, unarticulated, and even a bit “smelly” due to their raw human origin. Yet, with care and intention, this chaotic “wool” can be transformed into a structured, usable form.
Just as the process of turning wool into yarn unfolds in distinct stages, the creation of knowledge involves a progression from raw, unorganized thoughts to structured insights. Let’s break it down:
Shear the Sheep (Capture “Insight Sparks”)
The first step is to gather or forage the raw material — our unstructured ideas. This process is akin to shearing sheep: messy, unglamorous, and unrefined. Thoughts, notes, and spontaneous conversations are captured without judgment or immediate concern for quality.
In the world of personal knowledge management (PKM), this is often referred to as “quick capture.” The goal here is not refinement but ensuring that no spark of insight is lost.
Sort and Wash (Organize and Refine)
After shearing, the wool is sorted for quality and color and then washed to remove impurities. Similarly, we must sort and distill our captured ideas, filtering out redundancies and clarifying their essence. This is where patterns begin to emerge, and the raw material starts to take shape.
However, this step demands intentionality — a return to our “sheared” ideas with a farmer’s mindset. Like a farmer who envisions yarn as the ultimate output, we must recognize that the act of sorting is not the end goal. It is a bridge to something greater: actionable knowledge.
Importantly, we need to recognize our tendency to “quick capture” thoughts and then abandon them. Like sheep burdened by unshorn wool, unprocessed ideas weigh us down; we yearn to be free from this weight. The farmer, however, respects the process, knowing that yarn is a resource enabling forward movement. This transition from raw material to structured output is the most critical part of the process.
Niklas Luhmann’s Zettelkasten method mirrors this philosophy, emphasizing the need to return to raw ideas. For Luhmann, organizing thoughts was not a single act but an iterative process that connected and refined ideas into meaningful knowledge. Similarly, we must revisit and work through our initial “quick capture” notes.
Spin into Yarn (Create Usable Knowledge)
The cleaned wool is spun into yarn — a versatile material ready for use. This is the stage where our refined ideas become coherent knowledge. This knowledge, like yarn, is not the final product but a resource that can be woven into a variety of applications.
At this stage, formalization is essential: validation through external feedback, creating narratives or analyses, and ensuring outputs are tangible and usable. Just as a farmer sees yarn as the ultimate output enabling countless possibilities, we must treat knowledge similarly. While its final form may vary, knowledge outputs serve as inputs for further engagement and systemic exploration.
Crafting Knowledge from Sparks: Knowledge Creation as a Process
The wool metaphor underscores an essential truth about knowledge creation: it is a process that requires responsibility, intention, and an eye toward output. This notion of a cyclical process of knowledge creation aligns with theories like , where tacit knowledge is transformed into explicit knowledge through a cycle of socialization, externalization, combination, and internalization.
However, as discussed earlier, real-world knowledge creation often resists linearity. It is messy, non-linear, and profoundly human. Unlike the clean cycles of a theoretical model, the journey of transforming raw, experientially created human ideas into structured knowledge involves detours, iterations, and moments of ambiguity. Nonaka’s theory provides a useful framework, but it must be adapted to reflect the nuanced realities of our messy nature.
We must treat knowledge creation with a farmer’s mindset and as an iterative craft, much like the production of yarn. By acknowledging the messiness of the process, embracing ambiguity, and staying committed to output-driven actions, we can transform fleeting insights into powerful tools for change. This approach enables us to see beyond the chaos of raw ideas, turning them into the threads that weave systemic interventions capable of addressing the complex challenges of our time.
Enabling Action Through Mental Clarity
Organizing ideas is not only a technical necessity but also a profound psychological relief. Much like sheep feel lighter after being shorn, we experience mental clarity and focus when we articulate and organize our chaotic thoughts. This act of mental “offloading” reduces cognitive load, enabling clarity and meaningful action.
Raw, unstructured ideas can create mental clutter, leading to overwhelm and stagnation. Without a structured process to externalize and refine these thoughts, they linger as unproductive burdens, hindering creativity and decision-making. Externalizing thoughts — through writing, sketching, or verbalization — frees mental resources, enhancing problem-solving and focus.
Refined and organized thoughts empower us to prioritize tasks, manage complexity, and take decisive action. Structured thinking transforms chaos into manageable steps, fostering clarity and confidence. By adopting a routine of capturing and refining ideas, we lighten our cognitive load, enabling sustained progress and engagement with the systems we aim to influence.
Much like unshorn wool can hinder a sheep’s health, unprocessed thoughts obstruct progress. Externalizing and refining ideas transforms dormant potential into actionable outputs, creating space for clarity and action.
Ideas Require Action and Responsibility, Not Luck
Why do so few people engage in creating systemic interventions — individually, as entrepreneurs, or within organizations?
I believe, the answer lies in how we approach knowledge creation. Too often, it is seen as a matter of luck or a passive byproduct of other activities rather than an active, structured process. This mindset must change.
To address complex challenges, we must place knowledge creation at the forefront. By embracing the messiness of initial ideas, committing to their refinement, and transforming them into actionable outputs, we unlock the potential for systemic change.
The wool metaphor reminds us that raw thoughts, like unshorn wool, hold immense value when processed with care and intention. The process is clear: capture, refine, transform and synthesize. These steps, although not linear, apply equally to individuals managing their own ideas and to organizations fostering collaborative innovation.
I invite you to adopt this process and take the first step. Start small — capture your ideas, refine them, and create tangible outputs. If you are part of a team or organization, advocate for systems that prioritize knowledge creation. By doing so, you cultivate a culture where messy sparks of inspiration evolve into meaningful actions.
The world needs more thoughtful systemic interventions — not blind adherence to outdated blueprints. Let’s treat knowledge creation as the foundation for change. In this way, we can transform chaos into systems that truly make a difference.
Some of the sources I have checked while preparing and validating this opinion piece:
Bühren, C., Meier, F., & Pleßner, M. (2023). Ambiguity aversion: Bibliometric analysis and literature review of the last 60 years. Management Review Quarterly, 73(3), 495–525.
Gourlay, S. (2006). Conceptualizing knowledge creation: A critique of Nonaka’s theory. Journal of Management Studies, 43(7), 1415–1436.
Handayanie, Y., Rahmat, A., & Priyandoko, D. (2021). Brain dump activities to overcome students’ intrinsic cognitive load in reproductive systems online learning. Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam, 26(2).
Klingebiel, R., & Zhu, F. (2023). Ambiguity aversion and the degree of ambiguity. Journal of Risk and Uncertainty, 67(4), 299–324.
Kucharska, W., & Erickson, G. S. (2023). Tacit knowledge acquisition & sharing, and its influence on innovations: A Polish/US cross-country study. International Journal of Information Management, 70.
Luhmann, N. (n.d.). Communicating with slip boxes: An empirical account. Retrieved from
Miura, H., & Matsuo, K. (2021). Does writing enhance recall and memory consolidation? Revealing the factor of effectiveness of the self-administered interview. Applied Cognitive Psychology, 35(3).
Nonaka, I. (1994). A dynamic theory of organizational knowledge creation. Organization Science, 5(1), 14–37.
Paas, F., & van Merriënboer, J. J. G. (2020). Cognitive-load theory: Methods to manage working memory load in the learning of complex tasks. Current Directions in Psychological Science, 29(4), 394–398.
Qudrat-Ullah, H. (2024). Creativity loops–based decision making: A systems thinking approach (1st ed.). Palgrave Macmillan.
Shi, W., & Xie, Y. (2024). From knowledge to success: Understanding the crucial role of governance, tacit knowledge sharing, and team leadership in project outcomes. Current Psychology, 43(3), 8219–8229.
Skulmowski, A. (2023). The cognitive architecture of digital externalization. Educational Psychology Review, 35(1), 101.
Smyth, J. M., Johnson, J. A., Auer, B. J., Lehman, E., Talamo, G., & Sciamanna, C. N. (2018). Online positive affect journaling in the improvement of mental distress and well-being in general medical patients with elevated anxiety symptoms: A preliminary randomized controlled trial. JMIR Mental Health, 5(4), e11290.
Young, J. (2012). Personal knowledge capital: The inner and outer path of knowledge creation in a web world. Chandos Publishing.
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This blog post is part of a series created during my studies at ETH Zurich in the Design Resilient Regenerative Systems (DRRS) program, under the Systemic Design Labs at ETH. While I was already familiar with systems thinking, complexity science, and their applications, this program encouraged me to transcend conventional methods. It combined high-level philosophical and theoretical perspectives on systems view of the world, ETH’s hallmark scientific rigor, methodological depth and experiential, embodied practice, together with practical applicability.
I believe that systemic design, both as a concept and a way of thinking, holds immense potential far beyond its current definitions and methods. It offers a foundational approach to development, change, and the creation of complex socio-technical, economic, and ecological systems. Practically, systemic design provides a critical framework for developmental work, policymaking, and, perhaps most significantly, business innovation. As businesses increasingly embrace system-oriented and complexity-aware thinking, systemic design is transforming operations and strategies, paving the way for a more adaptive and integrated future.
Through these blog posts, my goal is to share some of the ideas and insights we explored in this innovative program with a wider audience. I aim to make this knowledge more accessible and comprehensible, highlighting key points and emphasizing their importance. While this work may eventually lead to more in-depth publications, for now, it is an effort to convey these concepts coherently and spark meaningful dialogue.
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All of the ideas are mine and not necessarily represent any opinions, or content provided by ETH or DRRS program
