Z3 is a widely used SMT solver with support for linear and non-linear arithmetic. While powerful, its performance is dependent on tactics -- user-defined strategies that guide the solving process. This paper systematically analyzes the performance of Z3 across various tactic sequences, including ones with parallelization, on benchmarks from SMT-LIB. The results reveal that certain problems can get a speed-up of up to 5 times with the appropriate strategy, however different approaches come with certain limitations. We explore a pattern in linear problems where parallelization and heavy preprocessing make a big difference to performance. Additionally, we discuss two non-linear benchmarks for which it is very evident that the right approach to tactic selection matters and there is no single optimal strategy in SMT solving. These are all important observations since SMT solvers are a key part of many industrial processes where speed and accuracy are crucial.