Sensemaking has evolved as a growing movement over recent decades as a way of understanding the dynamics of complex systems. It emphasizes a holistic understanding of human beings and how we navigate the contexts we are part of. To understand human behavior in teams, organizations and in other societal groups, human sensemaking processes have proved to be of great importance.
Mapping the domains of human experience, Dave Snowden’s Cynefin framework challenges linear, rational cognitive frameworks and assumptions of order or control. This framework supports decision-making through approaches that help recognizing the domain in which we are operating in; simple, complicated, complex, chaotic or disorder. Jenifer Garvey-Berger provides a brief introduction to Cynefin here. The complex domain is characterized by unpredictability, non-linearity and ambiguity. Applying methods based on assumptions of linearity and control in the complex domain can have potentially catastrophic consequences.
To address these and other issues, another method for gathering data is necessary. Common approaches simply capture opinions, typically through Likert scales. However, due to the subjective and partly subconscious nature of sensemaking processes, as well as various psychological mechanisms, methods of direct inquiry fall short in capturing deeper components of meaning. The sensemaking method is designed to capture not only behaviors, but also motivations, perspectives and feelings, helping us learn about why we behave as we do in a complex system. Use of this kind of data lets us monitor and evaluate systems, detecting trends and weak signals.
The sensemaking method utilizes open micro-narrative captures to start with actual experience. The invitation to reflect and reveal tacit aspects of the sensemaking process relevant to an individual’s experience is facilitated by prompts designed to elicit the meaning surrounding a given experience. The combination of qualitative narrative data and quantitative data related to the tacit dimensions of experience can reveal rich data useful for designing interventions and navigating complex systems.
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