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People Analytics and How to Get Started
Manage episode 404982244 series 3493037
Το περιεχόμενο παρέχεται από το Felicia Shakiba and Chief People Officer. Όλο το περιεχόμενο podcast, συμπεριλαμβανομένων των επεισοδίων, των γραφικών και των περιγραφών podcast, μεταφορτώνεται και παρέχεται απευθείας από τον Felicia Shakiba and Chief People Officer ή τον συνεργάτη της πλατφόρμας podcast. Εάν πιστεύετε ότι κάποιος χρησιμοποιεί το έργο σας που προστατεύεται από πνευματικά δικαιώματα χωρίς την άδειά σας, μπορείτε να ακολουθήσετε τη διαδικασία που περιγράφεται εδώ https://el.player.fm/legal.
About
This discussion shares the critical importance of establishing solid data foundations for effective people analytics. Guest speaker, Richard Rosenow VP, People Analytics Strategy at OneModel, emphasizes the need for organizations to prioritize data governance, structure, and quality to unlock valuable insights that can enhance various areas such as recruitment, retention, and diversity. Richard explains that building people analytics on shaky data foundations is akin to building on sand, stressing the necessity of confidence in data before diving into deeper analytics. They highlight common mistakes organizations make in data architecture, including overlooking the unique challenges of HR data, underestimating the importance of time sequencing, and neglecting regulatory considerations.
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Richard Rosenow is a recognized leader in HR technology, named one of the 2023 Top 100 HR Tech Influencers by HRexecutive.com. With a background in HR and People Analytics at Facebook, Uber, Nike, and Argo AI, he now applies his expertise at One Model as the Vice President of People Analytics Strategy.
A respected figure in the people analytics community, Richard shares his knowledge and insights on LinkedIn. He guides those new to the field, discusses ethical considerations and new regulations, and helps professionals understand the data foundations that are needed to power modern people analytics. His practical approach influences the way companies leverage data to make workforce decisions.
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