Two key roles of distribution analysis

 This post introduces a conceptual model for classifying and responding to distribution within organizational or operational systems. By distinguishing between unacceptable situations, desirable states, and other forms of variation, the framework provides actionable guidance for both convergence and expansion. This structure supports quality control, adaptive learning, and strategic decision-making.

Modeling Based on 後正武 『意思決定の​ための​分析の​技術』

Entity Name	Description
Distribution	A general category representing observed variation within a system or process.
Unacceptable Situation	A type of variation that must be identified and eliminated to maintain system integrity.
Desirable State	A positive form of variation that should be amplified or shared across the organization.
Convergence Action	An intervention aimed at suppressing or correcting unacceptable variation.
Expansion Action	A strategy to scale and disseminate desirable variation throughout the system.

By framing variation as a structured distribution, this model enables organizations to respond with clarity and purpose. Unacceptable situations are addressed through convergence, while desirable states are amplified through expansion. This dual approach transforms distribution analysis into a strategic tool for continuous improvement.