Most of the information needed for the management in the decision making process is essentially based on subjective and imprecise concepts expressed primarily by "experts" in a natural language or based in simples indicators and it's not capable to check the strategy in a more integral way. In the present research we show two application of the compensatory fuzzy logic to resolve the problem mentioned above. As the main contributions we show first an aggregation method to design new indicators based on the statistic and compensatory fuzzy logic approach and as second we define a new indicator to measure the IT governance level.

The main goal of this research is develop a sensitive analysis (SA) among some fuzzy operators, to ask the question: which is the most robustness fuzzy operators? The fuzzy operators consider in this study are: Zadeh operators, Probabilistic operators and finally the compensatory fuzzy logic operators: Geometric mean and Arithmetic mean. The Sobol model and the Monte Carlo simulations was been used to develop the SA. According with the main result of the study the compensatory fuzzy logic operators are the most robust.