California Pay Data Reporting Most Commonly Asked Questions

California Pay Data FAQs

2 minute read On September 30, 2020, California Governor Gavin Newsom signed Senate Bill 973 (“SB 973”) into law. SB 973 authorizes California’s Department of Fair Employment and Housing (DFEH) to enforce the annual reporting of pay and hours worked data for employers with California employees. Here are a few answers to frequently asked questions…

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DEI Measurement, Analysis, & Implementation During COVID-19

7 minute read: COVID-19’s Assault on Equality It is well-known that the global COVID-19 pandemic has exacerbated inequalities by race/ethnicity, gender, education level, and income. Here in Los Angeles, the mortality rate for the least affluent communities is four times larger than that in the most affluent communities. Black and Hispanic/Latinx death rates are more…

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No Pay Data, No Pay Gap Benchmarks. Conduct a Pay Equity Audit Now

Under the stewardship of Trump-appointee Janet Dhillon, the EEOC is rolling back federal pay reporting requirements. This returns the United States to the back of class of developed countries in terms of pay reporting. This rollback also contradicts the Commissions earlier finding that these data are “necessary” to the Commission’s ability to efficiently address pay…

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Optimal Investment in Data Error Assessment

My last post discussed some of the ways that data errors weaken the reliability of conclusions drawn from those noisy data. Even measures of the uncertainty in conclusions (such as statistical confidence intervals) can be inaccurate. This raises the question as to how one assesses data for such errors, and at what cost? The Data…

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Beware the Two-Step Process of Measuring Pay Disparities

Companies should be wary of any pay equity analysis that offers to look at wage disparities after controlling for legitimate business factors. The term “after” is open to interpretation, but a defensible, reliable pay equity assessment must measure wage disparities in a full model — one that also measures the effects of legitimate business factors…

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Clean Data Essential for Reliable Data Analysis

How much confidence can you place in the conclusions of your data analysis? For regulatory compliance actions, the cost of errors can involve fines, lawsuits, and damage to the brand. When being wrong involves significant costs, it is important to consider ways in which errors in the underlying data could be undermining your results. Many…

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Data: The Good, The Bad, and The Ugly

Data analysis informs our daily business decisions, but that analysis is only as good as the data supporting it. Organizations should invest in ensuring that their decision-making is based on accurate information. As data analysis is becoming increasingly sophisticated, machine learning is becoming a sought after technology. Organizations that haven’t already incorporated machine learning predictions…

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