The field of people analytics is booming - there is a huge increase in investment as well. It's not only new software or new tools we have to analyze and store your data. Now we can go as far as to analyze "change in mood" or signs that your employee is looking for a new job. Soon we will also have programs that can analyze conversations and take note of the stress level. With all that developing the main question is: where is the ethical line between being advance and caring about your employees to converting to Big Brother and invading the privacy? What is the difference between employee data and private data? And what about organizational networking analysis if we are talking about social interactions?
Detecting burnout in the early stages as a way to prevent potential resignation. Burnout, recently included in the WHO’s International Classification of Diseases as an “occupational phenomenon”, causes an estimated 1 million workers per day call in sick. This data is backed by the poll conducted by Monster, with 61% of respondents claiming stress has been the cause of illness and 46% of respondents missing time at work due to work-related stress. The departure of a skilled employee may jeopardize the company's operations for months and the corresponding costs add up to a two-year salary in hiring, training, and getting a replacement up to speed. Learn in this session:
Artificial Intelligence and its role in detecting early signs of burnout
Why luck of managerial support is of the most common reasons behind burnout and how to change it
How to use Data to recognize signs of an employee’s dissatisfaction
Check out the incredible speaker line-up to see who will be joining David.
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