HR Data Labs

Craig Friedman - How Skills Data is Transforming HR into True Business Partners


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Craig Friedman, Talent and Skills Transformation Leader at St. Charles Consulting Group and author of Enterprise Skills Unlocked, joins us this week to discuss the shift toward skills-based organizations. He breaks down how data-driven transformations allow companies to move from simple headcount management to true capability management. Craig also shares practical advice on how to prioritize skills projects to ensure they solve real business problems and deliver ROI.


[0:00] Introduction

  • Welcome, Craig!
  • Today’s Topic: How Skills Data is Transforming HR into True Business Partners
  • [5:05] What does a skills-based transformation look like in practice?

    • Shifting the talent process from an exercise in headcount management to an exercise in capability management.
    • Moving away from static "boxes on an org chart" to using granular data that supports the entire talent infrastructure.
    • Leveraging skills data that lives in both business systems (capabilities) and people systems (individual skills) to better align with business functions.
    • [11:57] How different teams leverage skills data differently

      • Why L&D teams need granular skill details, while staffing teams prioritize context on scope and scale for compensation purposes.
      • The importance of creating an enterprise data taxonomy where different departments can agree on a skill but append their own metadata.
      • Using machine learning to handle the searches, connections, and adjacencies required to make the data useful across teams.
      • [26:14] The impact on Learning and Development (L&D)

        • How real-time skills gap analysis simplifies curriculum redesign when jobs or organizational structures change.
        • The growing need for assessment and validation to verify skills learned through informal methods like coaching or on-the-job experience.
        • Identifying business cases where skills can make a clear difference and prioritizing them based on value and risk.
        • [36:20] Closing

          • Thanks for listening!

          • Quick Quote

            “A lot of the reason we're doing this now when we couldn't do it before is because of these more advanced tools in data analytics and AI and machine learning that actually help us manage data at that scale.”


            Link to Craig's book: https://a.co/d/0naqmvh

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