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INTERVIEW: Dave Ulrich on How To Win the War for Talent

HR Bartender

The term “war for talent” was first used in 2001 in a Harvard Business Press book by the same name. It refers to a competitive landscape in recruiting and retention. The book shares an HR competency model with three core drivers: credible activist, strategic positioner, and paradox navigator.

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People Analytics and HR-Tech Reading List

Littal Shemer

If you are interested in additional free resources for data science and R programming, check the comment section of this post. “Technology, data analytics, and artificial intelligence already impact how people work and engage with organizations. Click titles for Kindle versions (Work in progress. First published: May 14th, 2018.

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New Bureau of Labor Statistics (BLS) Data – What does it mean for HR? (i4cp login required)

i4cp

About the data The latest U.S. Bureau of Labor Statistics (BLS) data was released last week. This included the JOLTS (Job Openings and Labor Turnover Summary) data and The Employment Situation report. The JOLTS data is current through November (preliminary), while the employment data is for December 2023 (preliminary).

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New Bureau of Labor Statistics (BLS) Data – What does it mean for HR? (i4cp login required)

i4cp

About the data The latest U.S. Bureau of Labor Statistics (BLS) data was released last week. This included the JOLTS (Job Openings and Labor Turnover Summary) data and The Employment Situation report. The JOLTS data is current through November (preliminary), while the employment data is for December 2023 (preliminary).

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The evolution of the dataset – why it’s not just about the algorithm

Hireability

Consider your average database holding all of your data. What portion of the data is unique? The fact that New York may be in your database several thousand times is part of your data, the item, ‘New York’ as a city or a state, would be one unique item in a dataset. . How is this relevant in the HR tech space?

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The evolution of the dataset – why it’s not just about the algorithm

Hireability

Consider your average database holding all of your data. What portion of the data is unique? The fact that New York may be in your database several thousand times is part of your data, the item, ‘New York’ as a city or a state, would be one unique item in a dataset. . How is this relevant in the HR tech space?

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The evolution of the dataset – why it’s not just about the algorithm

Hireability

Consider your average database holding all of your data. What portion of the data is unique? The fact that New York may be in your database several thousand times is part of your data, the item, ‘New York’ as a city or a state, would be one unique item in a dataset. . How is this relevant in the HR tech space?