AI in HR: Three Distinguished Impacts
HR professionals seem to confound HR operations, People Analytics, and organizational readiness for AI. The article describes three distinguished effects of AI on HR and explains how they are interrelated.
HR professionals seem to confound HR operations, People Analytics, and organizational readiness for AI. The article describes three distinguished effects of AI on HR and explains how they are interrelated.
My People Analytics and HR-Tech reading list on Kindle includes +70 items! Find here inspiration, practical guidance, validation for practices, new ideas and innovative tools, an “open door” to a professional community.
Large language models (LLMs) altered how we work and create value. How can the People Analytics profession leverage these deep learning and natural language processing techniques to offer a better business case for its expertise?
A review of definitions, measures, and assessment tools of data literacy, and interpretation following the experience of educating and training HR professionals in People Analytics, to support the HR sector’s transformation to become a better client of data.
A successful data science function in the HR department requires balancing the analytics maturity of the business and HR leaders with the data scientist’s skills. It is essential and fascinating to explore how data science and HR needs are knitted.
I asked ChatGPT some questions about my current struggle in publishing R Bookdown and could not resist expanding the discussion to a broader context. Beyond information, I asked for advice, opinion, feedback, compliment, and prediction. I also brought my chutzpa to the conversation.
Simulating work with a data scientist in HR and People Analytics use case: The gender pay gap. Analyzing continuous variables instead of categorical variables, swapping between ANOVA and Linear Regression, and additional insights based on actual data.
What should HR professionals expect when working with a data scientist? What should HR professionals do for a successful data science project? How should you deal with insignificant results in the analysis? The article addresses these questions.
The Employee lifetime value is a scheme that connects the people processes to the business outcomes. It refers to the expected value the organization gains in the entire time an employee in a particular role spends working, quantifying how “people are our most important asset.”
The culture of the People Analytics community is remarkably open. While datasets, analytics, and insights are restricted, experiences, resources, and advice are generously shared. It inspired me to list the ABCs of success: autodidact habits, business understanding, and coding skills.