There are benefit could be obtained from
sensitivity analysis. Bannerman S. (1992)
suggests that sensitivity analysis is performed
to determine the robustness of the optimal
decision. It is also helpful in revealing the
geometry of the decision problem. The method
identifies those elements which have the
greatest impact on feasibility and allows them
to be subjected to management scrutiny. Thus,
sensitivity analysis enables the identification
of critical variables underlying forecasts of
relations and prioritising variables
accordingly. This process requires more effort
to be allocated to obtaining greater accuracy
when selecting these variables and, implicitly,
more reliable return forecasts will be
produced. In other words, sensitivity analysis
is conducted during early iterations of analysis
in order to determine where additional
modelling and assessment efforts are needed to
improve the quality of the analysis. The
method allows the effects of different variables
to be compared and facilitates comparison of
the effects of the different variables on the
project as a whole. It helps identify design
options that need to be considered in detail and
additional information which should be sought
on some variables as well as helping to convey
some idea of project risk.