The article is brought to you by SAP SuccessFactors.
Stephan Amling, SVP, SAP SuccessFactors, identifies some of the AI and robotics technologies that exist today and could help HR and the business to get a more real-time insight into the state of the workforce.Employee engagement is a dynamic and fluid metric. It has a direct bearing on productivity and business goals, which is why it is on every business agenda today. In truth, annual surveys do not match up to the real result, because what an employee feels during the annual survey is not the same say, after the most recent direct manager interaction. That’s why business leaders need real-time data and insights on Employee engagement to respond in a much more timely and individualised manner.
Let’s take a look at some of the artificial intelligence (AI) and robotics technologies that exist today and could help HR and the business to get a more real-time insight into the state of the workforce. It is worth mentioning that some of those technologies immediately raise various concerns and might not be considered appropriate, but it is a matter of fact that they exist, that they are already being used outside of the workplace, and that HR and business leaders need to start looking at them and make an educated decision if and how to leverage them.
Algorithms that measure your smileThanks to various sophisticated face recognition technologies, understanding shopping customers’ but also employees’ state of mind is now a real capability. Such technologies that are partly even available as public cloud services, can analyse headshot photos of employees as they enter, walk or leave the workplace, identify gender, classify the age group, and most importantly, rate the emotional state of the respective individual in real-time on a scale from very unhappy to very happy using machine learning (ML).
“Email sentiment analysis” using ML can mathematically calculate the emotional attachment of an employee to his/her organisation based on his/her emails. From deducing who is highly engaged with the company’s strategy to who is most likely to resign in the near future, this allows the organisation to initiate preventive interventions.
In an excellent example, Unilever is experimenting with using algorithm-based evaluations, video techniques as well as automatic data gathering for the hiring process. If successful, it will help to free up a significant portion of their recruitment team capacity and re-deploy them to advisory tasks, leaving only the final interviews to human recruiters.
In another example, SAP is using ML technologies in their SuccessFactors solutions to identify the unconscious bias in developing job postings or in calibrating team performance, or chat-bots to automate service request processes and evolving traditional system user interfaces to use written and even spoken natural language.