PCI_{2} and associated enhancements offer multiple advantages compared to the initial formulation (PCI_{1}).

- PCI
_{1}required bipolar scales (e.g., -3 to +3) with a neutral point (0) and scale widths were constrained to 3, 5, 7, and 9. PCI_{2}can be used with scale widths of 2, 3, 4, 5, 6, 7, 8, and 9, and can be applied to bipolar scales (with or without a neutral value) and unipolar scales (e.g., not at all important to extremely important). This expanded flexibility of PCI_{2}allows researchers to use the statistic with virtually all fixed length scales used in survey research. - PCI
_{2}formulation allows for an indefinite number of distance functions. Current implementation includes two distance formulations (D1 and D2) for bipolar scales and a distance function for unipolar scales (D3). Given that people with negative or positive responses may perceive no disagreement or conflict with a person who is neutral on a topic, D1 does not include neutral responses in the calculation of distance. The second distance function, D2, includes neutral responses when calculating the PCI_{2}. Although D1 is recommended for bipolar scales, the PCI_{2}allows researchers to experiment with impacts of excluding (D1) or including (D2) “neutral” or “neither” values when calculating the PCI_{2}. For unipolar scales, D3 should be used. - Because distances need not be linear functions of responses. PCI
_{2}allows for powers of distances. Researchers can examine the impact of linear and non-linear response patterns using the PCI_{2}distributions generated by the simulation routines. Power 1 (i.e., P1, the unsquared version) is currently recommended for use unless there is a rational for increasing weight as differences between responses become more extreme (i.e., P2, the squared version). Given that any power > 0 can used, options for transforming a distance function are infinite - The original formulation of the PCI
_{1}required users to calculate a variable’s frequency distribution in a statistical program (e.g., SAS, SPSS) and then type or copy the distribution into Microsoft Excel. The second generation of this statistic allows researchers to produce the statistic directly from SAS or SPSS, or use an Excel spreadsheet. - The SAS, SPSS and Excel programs also generate a simulation based on a variable’s actual distribution of PCI
_{2}; PCI_{1}did not include such routines. This simulation produces a mean and standard deviation for the estimated PCI_{2}. The standard deviations from the simulated PCI_{2}is critical in testing for a significant difference from a value (e.g., from 0 or 1) and for testing for significant differences among PCI_{2}values. The simulation is based on an n of 400, but this default can be changed to any sample size.