The prediction of the behaviour of complex systems remains a costly and time consuming activity due to their data intensive nature. Such dynamic systems do not always lend themselves to a quantitative behavioural analysis. Davies et al have developed a novel qualitative approach aimed at determining how a system element deviates from a pre-defined “normal” operational mode due to a change in the operation of another element existing within the same architecture, or due to an interaction with an external environmental condition. This qualitatively determines the elements in the system that would be affected by a modification, and can aid in system development by identifying relationships and interdependencies prior to implementation. Previous analyses have shown it to difficult to comprehend the impact results due to large numbers of fluctuations in impact arising from noise. In Air Traffic Management systems there are many minor delays occuring daily but they do not affect the system operations or the stakeholders, these have been classed as noise. This paper introduces the application of a noise level into the impact analysis and, through a modelled scenario and variance in the computational boundary, demonstrates that it improves the understanding and transparency of the results, and an optimum level can be determined. The capability and potential for analyzing large scale complex systems has been demonstrated further.