Sentiment analysis and NLP is a hot topic for employee engagement, and sometimes potential flaws of the sentiment analysis are overlooked. What matters most for employee engagement is apparently “just open up our ears and listen.”
Recidivism risk algorithms – Should AI decide who goes free and who goes to jail?
Using AI to asses interviews / The pros and cons.
Health insurance plans meet user data – but is such use of our data a healthy development for society?
In this post, I share my thoughts on the article, “Employee mood measurement trends” by Tom Haak, which amongst other things, describes three main means of measuring employee mood: traditional surveys, simple daily feedback tools, and passive data mining of employee online communications (emails, Slack, Yammer etc.).
I share my assessment of each method. Furthermore, I discuss why passive communications mining is likely to generate data that is unrepresentative of employee mood. Instead, it is more suited for analyzing supervisor effectiveness, which is a leading indicator and arguably the most important determinant of employee mood (the symptom).
Finally, I opine that analyzing supervisor effectiveness through communications data mining could be combined with traditional employee mood surveys to generate actionable insights to improve overall employee performance.
We often bring up the topic ethics when evaluating various strategies for people analytics. My post is focused on pushing the discussion further by raising though questions (such as how much are we willing to sacrifice? and is it worth it?) we as a society have to deal with as we accept people analytics to make better decisions.
There's notoriously high human error in medicine, but algorithms can be imperfect, too. How should we handle this?
Humans are notoriously lousy decision makers, especially when it comes to hiring. To help streamline that process, HireVue has introduced algorithmic-based video-assessment to help companies make better hiring decisions. Over 700 companies have adopted this new approach, but is that the right decision?
Using analytics to identify nontraditional job candidates who are as qualified and high performing as traditional candidates
