In Taguchi Methods, lot of emphasis is given to Signal-to-Noise (S/N) ratios. S/N ratio is a very important measure to improve the functionality of a system. In this paper, the importance of S/N ratios for improving the performance of multidimensional systems is discussed. The role of S/N ratios for predicting the performance of multidimensional systems using Mahalanobis-Taguchi System (MTS) or Mahalanobis-Taguchi-Gram-Schmidt (MTGS) process is also discussed. The paper describes the different types of S/N ratios with their advantages as compared to the classical multivariate statistical methods.