It was shown during TRIZ Future 2018 conference, that a diagram resulting from Cause-Effect Chains Analysis (CECA) might be transformed into a state machine model. Although the conversion was described with a set of rules, no specific benefits of switching to a state machine approach were presented then.This paper focuses on enhancing the conversion and exploring the possibilities to simplify the output model without losing its information content. It briefly shows relations between the state machines and the formal grammars, proposes regular expressions as a compressed representation of the processes producing target disadvantages and provides SWOT-like analysis of the behavioral state machine CECA model with respect to the classic structural CECA model. It also shows the similarity of the state machine model to hardware-software approach.