This paper addresses the problem of finding the parameters of the arrival law which most significantly influence expected occupation and loss of a finite capacity queue. The input process is supposed to be ergodic and wide sense stationary. We show that it is mostly possible to fit an MMPP(2) to the decisive parameters of observational data. Numerical examples illustrate the importance of the decisive parameters, called key parameters, and also show the accuracy of the proposed fitting procedure. Finally, in the appendix we present the solution of the finite capacity queueing problem with Special Semi Markov Process (SSMP) arrivals and a general service strategy.