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November 20, 2024
The workforce that roared
Leisure and hospitality workers have emerged as pay winners since the pandemic.
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June 29, 2023
When using AI to predict pay, context matters
by Tim Decker • Ben Hanowell
We built an algorithm to predict wages from job titles. Our findings reveal the promise and pitfalls of artificial intelligence as a way to study the labor market.
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December 1, 2017
Data Fluency Series #5: Case Study
by Marcus Buckingham
Let’s show you what good data looks like, and what we went through to get it to see what happens on the world’s most productive teams.
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November 23, 2017
Data Fluency Series #4: Do Current HR Tools Give Us Good Data?
by Marcus Buckingham
We know that a good HR tool will have reliability, variation, and validity. Let's look at a few common HR tools and see how they stack up.
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November 14, 2017
Data Fluency Series #3: Variation and Validity
by Marcus Buckingham
If you are using a tool to measure people data, there are two things it has to do: It has to reveal actual variation in the real world, and that variation has to validly relate to something else.
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November 7, 2017
Data Fluency Series #2: How to Get Reliable Ratings Data
by Marcus Buckingham
How do we know that the people data we’re collecting is reliable? How do we know that it’s measuring what we say it’s measuring? And can you really measure something like performance in another person?
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October 31, 2017
Data Fluency Series #1: How to Tell Good Data from Bad Data
by Marcus Buckingham
Bad data is a pervasive problem in our world, and especially in the world of work. People are being promoted and fired because this faulty data that actually tells us nothing about our employees.
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