Neumann series expansion is a method for performing matrix inversion that has received a lot of interest in the context of massive MIMO systems. However, the computational complexity of the Neumann methods is higher than for the lowest complexity exact matrix inversion algorithms, such as LDL, when the number of terms in the series is three or more. In this paper, the Neumann series expansion is analyzed from a computational perspective for cases when the complexity of performing exact matrix inversion is too high. By partially computing the third term of the Neumann series, the computational complexity can be reduced. Three different preconditioning matrices are considered. Simulation results show that when limiting the total number of operations performed, the BER performance of the tree different preconditioning matrices is the same.