Can you identify the authors who take a radically different approach to hoverstadt's laws and why they adopt their approach
Patrick Hoverstadt’s approach is built on the “Grammar of Systems,” a set of 33 natural laws and principles (such as Ashby’s Law of Requisite Variety and the Viable System Model) intended to serve as a rigorous, universal “bedrock” for managing organizational stability and change[1].
However, several authors in the sources take a radically different approach, arguing that the search for universal “natural laws” or “master keys” to control systems can be a category error that leads to systemic failure.
1. The “Anti-Methodologists”: The Other Group (Waring, Elliott, James)
This group takes a stance they term the “Death of Methodology,” directly critiquing Hoverstadt for “functionalism”[4][5].
• The Approach: They reject the idea that “turning the handle” on a theoretical framework like the VSM can automatically generate value[5][6]. Instead, they propose a Risk-Based Framework (using the “Italian Flag” model) focused on experiential knowledge and “strategic nudges”[4][7].
• Why they adopt it: They argue that rigorous adherence to a single methodology often distorts reality to fit the model[8]. They believe that in complex socio-technical systems, “truth outruns provability” (referencing Gödel), meaning no single set of laws can fully represent or control a complex system[8][9].
2. The “Naturalizer”: Dave Snowden (Cynefin)
Snowden offers a fundamental challenge to the management orthodoxy that views the world as a predictable system amenable to engineering[10].
• The Approach: Snowden explicitly rejects the Viable System Model (VSM)—a cornerstone of Hoverstadt’s work—as outdated, arguing that if its creators were alive today, they would have abandoned it for Complex Adaptive Systems (CAS)[11]. He uses the Cynefin framework to categorize systems into different ontologies (Simple, Complicated, Complex, Chaotic), each requiring its own unique logic[11][12].
• Why he adopts it: He argues that “systems thinking” often assumes a level of discoverable causality that simply does not exist in the Complex domain, where cause and effect are only visible in retrospect[13][14]. To him, applying “laws” to complexity leads to “entrained thinking” and failure[14].
3. The “Minimalist”: James Wilk (Metamorphology)
Wilk rejects the entire project of building complex diagnostic models, which sits at the heart of Hoverstadt’s grammar[15][16].
• The Approach: Wilk advocates for filtering complexity rather than modeling it[15][17]. He replaces the standard Newtonian logic of “cause-and-effect” (even the circular feedback loops used by Hoverstadt) with a concept of “flux-and-constraint”[18][19].
• Why he adopts it: He believes that traditional systems models actually obscure the unique reality of a situation by burying it under “mid-level abstractions”[16][20]. His goal is the “Science of the Singular,” finding the one specific “idiosyncratic constraint” that, if lifted, would allow a system to “flip” instantly to a desired state[21][22].
4. The “Post-Structuralist”: Paul Cilliers (Critical Complexity)
Cilliers distinguishes his work from what he calls “Restricted Complexity”—the reductionist desire to find general, essential principles or universal laws to predict behavior[23][24].
• The Approach: He champions “General” or “Critical” Complexity, which asserts that complex systems are incompressible; they cannot be reduced to a simpler description (like a set of 33 laws) without losing essential information[24].
• Why he adopts it: He warns against the “madness of absolute coherence”[27]. He argues that because we cannot know complex things completely, any model is a strategic, normative choice[28]. To claim one has a “master key” is not only technically wrong but ethically irresponsible, as it suppresses the “otherness” and diversity that make the system viable[29][30].
Summary of Differences
| Feature | Hoverstadt’s “Grammar” | The Radical Alternatives |
|---|---|---|
| Logic | Natural laws of systems[1]. | Orientation, context, and risk[4][31]. |
| Goal | Structural viability and control[3]. | Navigating “muddles” and “messes”[32][33]. |
| View of Models | Essential maps for diagnosis[34][35]. | Inevitably flawed/dangerous abstractions[8][26]. |
| Action | Optimization via VSM/Cybernetics[36]. | ”Safe-to-fail” experiments and “nudges”[37][38]. |
Do these “radical” departures help you see where the boundaries of your own project might be, or are you still finding value in the “bedrock” Hoverstadt provides?
References
[1] 💬Gists.md [3] 💬What is Complexity.md [4] 💬Gists.md [5] 💬Questions.md [6] 💬Keywords + Jargon.md [7] 💬Keywords + Jargon.md [8] 💬Gists.md [9] 💬Keywords + Jargon.md [10] 💬Gists.md [11] 💬Distinctions.md [12] 💬Gists.md [13] 💬Distinctions.md [14] 💬Gists.md [15] 💬Distinctions.md [16] 💬Gists.md [17] 💬Nutshell (Process).md [18] 💬Distinctions.md [19] 💬Gists.md [20] 💬What is Complexity.md [21] 💬Gists.md [22] 💬Gists.md [23] 💬Distinctions.md [24] 💬Gists.md [26] 💬Questions.md [27] 💬Questions.md [28] 💬Perspectives.md [29] 💬Distinctions.md [30] 💬Gists.md [31] 💬Keywords + Jargon.md [32] 💬Gists.md [33] 💬Questions.md [34] 💬Gists.md [35] 💬What is Complexity.md [36] 💬Gists.md [37] 💬Gists.md [38] 💬Gists.md