People Analytics and Data Science
summary
Defines people analytics as using demographic engagement and interaction data to run descriptive predictive and diagnostic tasks and shows concrete examples: models that predict years to 70% diversity, dashboards counting how many sales teams miss targets or drop >25% during the pandemic, and checks before deploying ML. Flags failures and biases with specifics: Amazon scrapped recruitment model in 2018 for penalizing women and a 2003 NBER test finds 50% more callbacks for white names. Emphasizes validate data diverse teams and explainability.
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