Question
What do these sources say about the role of sensemaking?
Based on the provided sources, the role of sensemaking is paramount because complexity is consistently defined not as an objective property of the world, but as a relationship between the observer and the system. Since complex systems cannot be fully “solved” or mathematically modeled in their entirety, sensemaking replaces traditional “analysis” as the primary method for navigation.
Here is what the sources say about the role and practice of sensemaking:
1. Sensemaking as the Foundation of Complexity Management
Because complexity is often “in the eye of the beholder”[1],[2] and constitutes an “epistemological condition” rather than a material one[3], sensemaking is the required bridge between human cognitive limits and the messy reality.
• Orientation over Analysis: In complex “muddles,” you cannot simply analyze data because the situation is not yet structured. The TOG source argues that practitioners must prioritize “orientation” to determine “which way is up” before attempting diagnosis[4].
• The Appreciative System: Geoffrey Vickers argues that sensemaking occurs through an “appreciative system,” a mental act that combines reality judgments (what is the case) with value judgments (what ought to be). This process determines what we notice and how we act, rather than goal-seeking logic[5],[6].
• Observer Dependence: Since complexity arises from the mismatch between an observer’s “variety” (mental capacity) and the system’s variety, sensemaking is the process of constructing a model that—while technically “wrong”—is useful enough to allow for action[2],[7].
2. Action as a Sensemaking Tool
In complex systems, you often cannot know what is happening until you interact with the system. Sensemaking is not a passive intellectual exercise but an active one.
• Probe-Sense-Respond: Dave Snowden’s Cynefin Framework asserts that in complex domains, cause and effect are only visible in retrospect. Therefore, one must act first (Probe) to generate data, then Sense the patterns, and finally Respond[8],[9].
• Stimulating the System: Similarly, Ladyman and Ashby argue that you must “stimulate the system” to learn from its response, essentially using action as a probe to reframe the problem[10].
• Retrospective Coherence: Sensemaking in this context involves acknowledging that we can often only explain the “why” after the fact, using narrative to make sense of the “unknown unknowns”[11].
3. The Role of Narrative and Metaphor
When formal mathematical models fail due to the contradictions and non-linearity of complex systems, authors suggest using story and metaphor to maintain coherence.
• Narrative for Contradictions: Tim Allen argues that narrative is the only device robust enough to handle the inherent contradictions of complexity[12]. A narrative can “stably juxtapose incommensurable components” that would break a formal logical model[12].
• Hermeneutical Narratives: Alicia Juarrero advises using “hermeneutical narratives” that retrace the specific history and context of a system, as universal laws cannot explain the unique trajectory of a complex system[13].
• Systemic Metaphors: Robert Flood and George Lakoff emphasize using metaphors (e.g., machine, organism, brain, flux) as filters. Since no single model captures the whole, sensemaking requires the “constant shifting of metaphors” to highlight different aspects of reality[14],[15].
4. Collective and Distributed Sensemaking
Because no single individual possesses the “variety” to understand a complex system, sensemaking must be a collective process.
• Group Dialogue: Vickers and Checkland highlight that “shared sense-making” through dialogue increases the “IQ” of the group[16]. Checkland’s Soft Systems Methodology is essentially a structured sensemaking process that surfaces conflicting worldviews to find “accommodations”[17].
• Distributed Cognition: Snowden and Boisot argue for utilizing “human sensor networks” and “distributed intelligence.” This involves using many human agents to scan for weak signals and patterns that a central executive would miss[18],[19].
• Visual Tools: To facilitate this collective sensemaking, authors like Warfield and Checkland advocate for physical tools—such as “Situation Rooms” with magnetic walls[20] or “Rich Pictures”[17]—to externalize the mental models so the group can see and discuss them.
5. Sensemaking as Filtering (Cognitive Strategy)
Finally, sensemaking is described as a process of subtraction—knowing what to ignore to prevent being overwhelmed.
• Lumping and Filtering: Ladyman and Ashby refer to the “Lump Law,” stating that to learn anything, one must “lump” many states together[21]. Boisot calls this “complexity reduction” through codification and abstraction[22].
• The Essential Selection Step: The TOG source calls this the “essential selection step”—mastering the art of ignoring variables to coalesce the “muddle” into a manageable form[23].
• Satisficing: Herbert Simon notes that sensemaking involves “satisficing”—finding a solution that is “good enough” rather than optimal, because the full complexity exceeds human “bounded rationality”[24].
References
[1] Herb Simon.md [2] MOM.md [3] Tim Allen from Ecology.md [4] Mastering the Muddle - Systemic Perspectives on Complexity Management.md [5] Geoffrey Vickers.md [6] Geoffrey Vickers.md [7] Patrick Hoverstadt.md [8] Claude Shannon.md [9] Dave Snowden.md [10] James Ladyman and Ross Ashby.md [11] Dave Snowden.md [12] Tim Allen from Ecology.md [13] Dave Snowden.md [14] George Lakoff.md [15] Robert Flood.md [16] Geoffrey Vickers.md [17] Peter Checkland.md [18] Dave Snowden.md [19] Max Boisot.md [20] John Warfield.md [21] James Ladyman and Ross Ashby.md [22] Max Boisot.md [23] Mastering the Muddle - Systemic Perspectives on Complexity Management.md [24] Herb Simon.md