In faculty member selection, the large number of candidates is often a great challenge to the selection committee. A large number of candidates requires a large number of pairwise comparison matrices which leads to considerable time to obtain the final ranking of candidates. To determine a suitable approach we compared the singular value decomposition (SVD) and the duality approach in AHP for the average time taken to obtain a final ranking of candidates and compared them for their rank consistency. Simulation results showed that SVD is three times faster than the duality approach in AHP. A linear regression study and a two-way ANOVA study of the two approaches are presented.