Remove Data Remove Knowledge Management Remove Recruiting Software Remove Succession Planning
article thumbnail

HR Data Makes Its Own Gravy (Part 2)

HR Examiner

“The majority of information consumed by intelligent tools are various forms of text. Over time, that will shift into a heavy prevalence of machine generated or monitored data like movement patterns, keystrokes, social interaction, vocal intonation, environmental measurements, and communication patterns.”

article thumbnail

Modern HR Data Types and Attributes (from text to machine generated and monitored data)

HR Examiner

Data has a funny property. It wants to make more data. There’s a saying, ‘data makes its own gravy.’ Using data creates data about usage. Interestingly, the metadata created by data is often more useful than the data itself.” Modern HR Data Types and Attributes. Text / Language.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

7 Ways the U.S. OPM Competency Models Can Support Your Workforce Planning

AvilarHR

But if you’re just getting started, or haven’t updated your model in a while, what tools or assets are available to help? Office of Personnel Management (OPM) shares its General Competencies and Competency Models with the public. An updated competency model will help you align workers’ skills with your business needs.

article thumbnail

How HR Chatbots Can Improve HR Processes (Includes Company Examples)

Analytics in HR

HR chatbots are software programs that use artificial intelligence (AI) to handle various human resource functions like answering basic questions, performing tasks, and offering support. The high adoption of this technology and the presence of large players in this area will create enough growth opportunities for the market.

article thumbnail

9 HR Trends for 2023: Breaking Boundaries

HR Trend Institute

From work for income to work as an expression of purpose From a collective to a personalised approach From technology as ‘nice to have’ to technology as a major transformational driver From slow to fast to faster > focus on current burning urgent issues From intuition and biases to evidence-based working.,