Discovering Constancy Through Systematic Variation: A Framework for Complex Systems

This paper proposes a systematic framework for identifying constancy—the stable invariants—within complex socio-technical systems. While traditional management often assumes stability, this framework treats constancy as a discovered stopping condition emergent from controlled variation. By intentionally probing a system along multiple axes and identifying points of saturation (where further variation produces no new patterns), practitioners can distinguish between rigid foundations and areas where change creates genuine value. Key Features: The φ-Cube: A diagnostic tool that maps the interplay between epistemic axes (dimensions of discovery) and commitment axes (dimensions of decision control). Physics-Based Validation: The methodology is grounded in "existence proofs" from fundamental physics, citing the Michelson-Morley experiment and Einstein’s equivalence principle as successful examples of constancy discovery via the systematic absence of difference. Multi-Dimensional Stability: The framework addresses the risk of "false positives," where a system appears stable on one axis while experiencing irreversible drift on unmonitored dimensions. Practical Governance: Introduces dual stopping rules for exploration and intervention, alongside the preservation of "scar tissue"—the organizational memory of where expected invariants failed. Applied to socio-technical environments, the framework demonstrates that many assumed invariants dissolve under scrutiny, suggesting that human interaction patterns often provide more reliable structure than technical variables.