Similarity operator is a formidable tool for decision-making under uncertain domain like Pythagorean fuzzy set (PFS). PFS is a generalized intuitionistic fuzzy set (IFS) with better accuracy in real-world applications. Many of the discussions bordering on the applications of PFSs were carried out based on similarity operators (SOs). Several approaches of computing similarity between PFSs have been studied. Among the extant SOs, the work of Zhang et al. is deemed to contain some flaws which needed to be enhanced for reliable interpretation. To this end, this chapter explicates the SOs of Zhang et al. and develops an enhanced SO, which appropriately satisfies the similarity conditions and yields a more robust results in comparison to the SOs of Zhang et al. In order to validate the enhanced SO, we discuss its properties and find out that the SO is well applicable in decision-making problems. In addition, the enhanced SO and the SOs of Zhang et al. are compared in the context of precision, and it is substantiated that the enhanced SO can successfully measure the similarity between vastly related but inconsistent PFSs and as well yields a very precise results. Lastly, the enhanced SO is applied to decision-making problem and clustering analysis, and it is certified that the enhanced SO can deal with diverse everyday application problems more precisely than the SOs of Zhang et al.