Written by David Turetsky
August 3, 2021
In 2016, I had the honor of designing and developing a pay equity technology solution that companies could use to visualize the potential pay gaps that might exist inside an organization. The tool was developed to review gaps in pay based on ethnicity and gender. For most organizations, this was certainly not their first review of pay equity at the organization. However, for some this was an eye-opening exercise as they reviewed the data that showed them how people were being paid and what potential gaps existed.
As developers and product owners, we were excited to provide an insight tool that could expose these potential key issues inside organizations; however, it was clear that the issues being uncovered were not about the analyses themselves, but about the data that underlie the analysis. For most organizations, this analysis exposed that they had a long way to go before reviewing potential pay gaps. The more important part of these analyses was that the data that derive them needed to be cleaned to ensure that the outcomes were more accurate.
This is not a small undertaking. As we have discussed many occasions on the HR Data Labs podcast, reviewing and auditing HR data is a constant exercise that needs to be completed in earnest in order to make sure the analytics gleaned from that data are at all accurate.
So for headcount, turnover, termination reasons analyses; in order to be able to glean any insight, the first step must be data integrity. This could take the form of an HCM settings review, HR process reviews or just a simple HR demographic data audit. Any or all of the above will help ensure more accurate insights, but unless all of them are undertaken the analyses should be used as purely directional instead of insightful.
This is especially the case of Diversity, Equity and Inclusion analyses. One cannot emphasize enough that data integrity is THE key to having not just appropriate analytics but that the conclusions that are reached are of value.
…And, let us be very clear, there are very few analyses that HR can help generate that add more value and purpose to an organization in 2021 than good diversity, equity and inclusion metrics. As Siri Chilazi said on the HR Data Labs podcast Season 2 – Episode 11 “We need to approach DE&I in our organizations with the same seriousness, with the same rigor, and the same data driven approach that we use for all other aspects of our business.”
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