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Storytelling About Talent Health Index By Cornerstone With Mike Bollinger

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Manage episode 378857422 series 2796887
Content provided by William Tincup. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by William Tincup or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

Welcome to our enlightening conversation with Mike Bollinger from Cornerstone, the brains behind the innovative Talent Health Index. This global research project is transforming the way companies understand and bridge the skill confidence gap between employers and employees. We're taking a deep dive into the four-level maturity model, an enlightening framework that guides organizations from foundational to transformative levels. We're also unraveling the seven dimensions of a healthy talent program, with key areas like culture, skills strategy, and learning and development under the spotlight.
As the conversation progresses, we take a closer look at how top-tier organizations are leveraging the Talent Health Index to reassess their skills strategy, content strategy, and gig assignments. We stress on the need for a holistic approach, employee confidence, and the role of technology in doing away with talent hoarding. The conversation then takes a futuristic turn with a riveting discussion on the inclusion of AI and machine learning in talent development. Join us as Mike unfolds how HR leaders can utilize the Talent Health Index to identify their organization's strengths and areas of growth, equipping you with insights that can revolutionize HR and talent management!

Listen & Subscribe on your favorite platform
Apple | Spotify | Google | Amazon

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Chapters

1. Storytelling About Talent Health Index By Cornerstone With Mike Bollinger (00:00:00)

2. Talent Health Index (00:00:02)

3. Using Town Health Index to Improve HR (00:07:29)

4. Action Layer and Data Feed (00:16:31)

372 episodes

Artwork
iconShare
 
Manage episode 378857422 series 2796887
Content provided by William Tincup. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by William Tincup or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

Welcome to our enlightening conversation with Mike Bollinger from Cornerstone, the brains behind the innovative Talent Health Index. This global research project is transforming the way companies understand and bridge the skill confidence gap between employers and employees. We're taking a deep dive into the four-level maturity model, an enlightening framework that guides organizations from foundational to transformative levels. We're also unraveling the seven dimensions of a healthy talent program, with key areas like culture, skills strategy, and learning and development under the spotlight.
As the conversation progresses, we take a closer look at how top-tier organizations are leveraging the Talent Health Index to reassess their skills strategy, content strategy, and gig assignments. We stress on the need for a holistic approach, employee confidence, and the role of technology in doing away with talent hoarding. The conversation then takes a futuristic turn with a riveting discussion on the inclusion of AI and machine learning in talent development. Join us as Mike unfolds how HR leaders can utilize the Talent Health Index to identify their organization's strengths and areas of growth, equipping you with insights that can revolutionize HR and talent management!

Listen & Subscribe on your favorite platform
Apple | Spotify | Google | Amazon

  continue reading

Chapters

1. Storytelling About Talent Health Index By Cornerstone With Mike Bollinger (00:00:00)

2. Talent Health Index (00:00:02)

3. Using Town Health Index to Improve HR (00:07:29)

4. Action Layer and Data Feed (00:16:31)

372 episodes

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