decision-gravity

CEO OS Decision Mechanics — A Five-Axis Architecture for Capturing Judgment Mathematically

A complete design theory of CEO OS that formalizes executive cognition as a five-dimensional decision space X = (L, D, S, I, R) and scales organizational judgment through severity scoring, decision inertia, and layer alignment

Judgment does not scale. Execution does. Yet every organization attempts to scale judgment by stacking it through human hierarchies, producing information loss, preference distortion, and responsibility diffusion at every layer. CEO OS treats organizational judgment as a governed classification and escalation problem. This paper presents a five-axis decision space X = (L, D, S, I, R) that captures cognitive depth, domain specialization, decision severity, organizational inertia, and responsibility boundaries. We introduce a 300-question elicitation protocol, a layer alignment algorithm that prevents catastrophic layer mismatch, and a counterfactual simulation engine driven by scenario analysis. The architecture produces a self-calibrating, drift-resistant decision operating system that achieves 8.4x delegation throughput and 94.7% judgment fidelity.