Explanation of Problem-Solution Co-evolution in Facing Problem Complexity Levels through Adaptation to the Cynefin Framework

This paper explores the concept of problem-solution co-evolution and its application across various levels of problem complexity. It aims to provide a clearer understanding of the role of co-evolution in problem-solving, thereby assisting designers in selecting more appropriate strategies when facing design challenges. To achieve this, the concept of problem-solution co-evolution was expanded upon through the analysis of relevant scholarly literature. Furthermore, the “Cynifin’” model is introduced to organize the study’s findings and facilitate a more effective understanding of the role of co-evolution in addressing complex problems.This qualitative study, employing a descriptive-analytical approach, examines the role and application of problem-solution co-evolution across different levels of design problems. The research methodology involved a mixed-methods approach, incorporating a qualitative content analysis of selected scholarly texts to explore the theoretical underpinnings of co-evolution, and semi-structured interviews with six expert designers to gather empirical data. The designers were purposefully selected to ensure diverse perspectives from various design backgrounds and experiences. Thematic analysis was employed to identify patterns and key themes within the interview data. Data triangulation, using multiple data sources, was utilized to enhance the credibility and validity of the research, ensuring the robustness of the findings.The research findings suggest that problem-solution co-evolution is a promising approach for tackling complex issues. While this approach facilitates the creative direction of the problem-solving process at simple and pseudo-complex levels, it becomes the primary strategy for addressing more complex challenges. However, our knowledge regarding the role and function of this mechanism in chaotic situations remains insufficient.The study aligns with previous research and concludes that problem-solution co-evolution is an effective approach for solving complex problems. The study also indicates that while co-evolution facilitates achieving a result in simple and complex-seeming problems, in complex situations, there is no escape from the co-evolution process, and in practice, the problem-solving strategy at this level passes only through problem-solution co-evolution.The findings also indicate that designers’ ability to navigate complex and ambiguous problems is a critical skill. Our categorization equips designers with the means to select the right strategy to deal with the problem. The implications of this research extend to informing design education, emphasizing the importance of teaching adaptive problem-solving skills, and to professional practice, encouraging designers to embrace iterative and co-evolutionary approaches when tackling complex and ill-defined problems. Future research should focus on developing specific strategies for navigating chaotic design scenarios, which remain poorly understood. A deeper exploration into the underlying mechanisms driving co-evolutionary processes is also warranted, potentially through longitudinal studies or computational modeling to simulate the dynamic interplay between problem and solution spaces. Furthermore, investigating how non-designers might leverage insights from problem-solution co-evolution could broaden the applicability of these findings beyond the design domain, fostering more adaptive and resilient problem-solving approaches in various fields.This study acknowledges limitations inherent in its qualitative design, particularly the small sample size of expert designers, which may limit the generalizability of the findings. However, the depth of insights gained from these interviews provides a rich understanding of the co-evolutionary process.