2010 Data Talent Acquisition Talent Management 
HRExecutive
JUNE 12, 2020
Once Catalyte turned 10 (in 2010), Rosenbaum began incubating what was to become Arena. The idea was to apply the predictive/big data/matching tools to the problem of workforce stability in healthcare. Most recruiting and talent acquisition providers steer clear of promising results because the data can be hard to acquire.
HR Lineup
OCTOBER 19, 2023
Founded in 2010, Phenom has emerged as a leader in the HR tech industry, providing solutions that empower companies to optimize their talent acquisition and management processes. Phenom’s platform offers a comprehensive suite of tools that cater to all stages of the talent lifecycle.
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Littal Shemer
OCTOBER 11, 2022
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.
Visier
JUNE 5, 2018
According to a 2010 study of California’s policy by Linda Aiken, et al., HR needs to take a compassionate approach to reducing nurse burnout and, strange as it may sound, people analytics and data can truly help in the effort to see the issues from the nurse’s point of view. How to Leverage Data as Your Diagnostic Tool.
HR Examiner
NOVEMBER 17, 2020
We’re finishing up the series today in part four with the data from the 90-day study where we racked up 450+ hours watching demos, asking questions, and working to understand the business model and technical approach of 110 companies. Director Talent Acquisition: 12%. Talent Management. Talent Management.
HR Digest
JUNE 15, 2023
Image Courtesy – Freepik The role of HRs spreads across but is not limited to talent acquisition, workplace diversity, employee engagement, and organizational culture. Here are 9 recommended HR podcasts of 2023 that can allow you to grasp the latest and popular HR trends and information on the go.
Analytics in HR
AUGUST 31, 2020
The main difference between predictive analytics and forecasting is best characterized by the data used. Generally, forecasting relies upon historical data, and the patterns identified therein, to predict future values. Data Collection. The time-series data we will use for our example comes directly from Google Trends.
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