Since several years, the Airbus High Lift System Test Department at Bremen successfully performs Virtual Testing (VT). The approach of VT by means of computer simulations of physics-based models has been applied for all major aircraft development programmes of the last years since the Airbus A380. In the given context, the preferred simulation methodology is multibody simulation (MBS). One important strength of simulation compared to physical testing is the possibility to perform parameter variations for identification of trends and dependencies in a rather easy way. Generally the variation of parameters such as flexibilities, friction coefficients, masses or dimensions is complicated or even impossible on physical test benches. In computer simulations however, model parameters can be simply and directly modified prior to execution of the simulation. Generally the modified models are independent of each other, hence the simulation execution can easily be parallelized, whereas physical test on benches usually have to be performed sequentially. In order to perform the parameter variations in an efficient and traceable way, it is obviously highly recommended to use a systematic approach, instead of attempting to interactively and manually change the model, execute a simulation and perform a postprocessing. Dedicated COTS tools exist to support simulation engineers to perform parameter variations. Besides that, state of the art pre processors (e.g. Adams View) also provide features for parameter variations. Nevertheless, depending on the availability of these tools and the characteristics of the study that is to be performed, it can make sense to use customized, simpler approaches as they can enable job submission to high performance compute environments via job scheduling tools (enabling parallell computing) or can be more efficient in terms of file handling. As a small to medium solution, a table defined and script based approach was established at Airbus High Lift Test. It is used for definition of the parameter space, modification of the related model, creation of related simulation run directories and job submission. As the created run directory structure is compatible to an existing post processing tool, the efficient evaluation of the obtained simulation results, e.g. for extraction of requested key information, such as sensitivities or the ranges of specific result quantities, can be performed directly after execution of the simulation runs. The paper presents and descrbes the major steps of the table defined, script based parameter variation process and the major features of its implementation. Beides that, the related post processing approach is presented by means of charcteristic application cases.