Watercooler’s Post

Join Simon Sinek and Eitan Vesely as they discuss new research that can help make good leaders become great. We go behind the scenes to explore how Explainable AI is upending our understanding of leadership. Topics include: Am I a micro-manager? What does the data say? Should my employees work after hours? How many meetings are too much?  Is burnout predictable?  

Join Eitan Vesely and Konstantin Tskhay, PhD as they confront some challenging topics relating to the impact of AI on People and Leadership.

We are excited to announce our partnership with TriSearch, a globally recognized leader in talent acquisition. “This collaboration signifies a significant shift in the talent acquisition paradigm. By embracing data-driven insights, TriSearch and Watercooler move beyond anecdotes and subjectivity, towards a future of data driven talent insights that empower our clients, recruiters, and candidates to make better decisions,” says Anthony Fogel, President and Co-Founder at TriSearch. According to Eitan Vesely, Co-Founder and CEO of Watercooler, "As we deepen our AI capabilities in the areas of talent acquisition and development, we are thrilled about the opportunity to collaborate with TriSearch." For more information: https://lnkd.in/gVcyD-ve Anthony Fogel, Bob Aylsworth, Allison Halpern, John Grahame, Stevie Aylsworth, Michael Goetz, Sefi Kligler, Or Yair, Avi Nowitz

Watercooler CEO, Eitan Vesely joined Jeff Sample and Nathan C. Wood in a podcast to discuss how AI can help leaders detect burnout and other employee risk factors. #peopleanalytics #futureofwork

Please join Eitan Vesely, Watercooler CEO and Dr. Keren Tsuk, Founder of Wisdom to Lead as they explore the topic of New Approaches to Leadership in the Era of AI.

We need to stop thinking about employee tenure like it's 1995.    Here’s what we’re taught: job satisfaction, work/life balance, compensation, manager engagement, and career development all influence employee tenure. But predicting why an individual stays or leaves is complex. At Watercooler, we use AI and Game Theory to identify the root causes of flight risk. Instead of guessing, our AI algorithms analyze hundreds of variables from HRIS, IT, Applicant Tracking Systems and others, to uncover the real drivers of employee tenure. For example, we identified two employees at high risk of resigning next quarter. The first is driven by burnout—long hours and not enough time off. Factors like 1:1s with their manager and their tenure also play a role. The second is likely to leave due to failed onboarding—they're new and not engaging with their manager. What motivates one employee doesn't affect another the same way. With AI, we can move beyond a one-size-fits-all approach to understanding employee tenure. We are at the dawn of a new era. Tailored interventions, based on specific behavioral drivers, are now possible. AI can make work better for all of us, leading to more meaningful workplace engagement and improved employee tenure. #peopleanalytics #futureofwork

Human and animal behavior have more in common than you may think. #peopleanalytics #hranalytics

We need to set the record straight. Simon Sinek posted an article last week about Watercooler that generated a lot of discussion about the use of AI in understanding employee behavior.   We got some interesting comments about the study we provided. As a recap, Simon shared a graph of Interrupted time-off contribution to flight risk that shows how employees who do some work on weekends and vacations have a lower likelihood of resigning compared with employees who do not work, or work too much, during these periods. Let’s add some more context.  The graph tells the story of only one company. Other companies mean different cultures hence their data and patterns will most likely be different too. There is no one-size-fits-all when it comes to this type of analysis and many variables can skew the data.   Another issue that’s been raised is that this is a case of correlation and not causation.  Just because there is a relationship between working during time off and lower resignation risk, does not mean that it is the cause. In short, it may not be the actual reason they quit, but it's common to many who do Here, we couldn’t agree more.   What the data tells us is what is happening.      As an AI company, we do not believe that AI will solve all of humanity’s problems. Especially not inter-personal issues.  It’s up to us humans to figure out why people burn out and it’s the responsibility of managers to provide solutions.   Our mission is to make employees suffer less in their working environments, by providing a real-time view of what is really going on. Directing the attention to the right place at the right time, so people will be seen, heard and appreciated. In summary, AI used as part of HR analytics is not here to replace people managers, it's here to shed light on their talent vulnerabilities. The rest is up to us.