Boost Employee Engagement With Artificial Intelligence And Machine Learning

Stephan Amling

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 individualized 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 smile

Thanks 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 analyze 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 organization 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, which allows the organization 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. 

Robots: Moving from shop floor to service desk

From doing repetitive tasks on the shop floor, robots are now performing tasks that so far have been done by knowledge workers in the services industries. From tax accounting and auditing to drug research – the contribution is significant. In India, one of its leading banks has robots to service branch customers. Chatbots are already able to handle the majority of HR service requests in a shared service center and they can even do recruiting interviews.

Robot teachers for one-to-one learning

Improving engagement scores doesn’t stop with gathering analytics; what lies in the root of the matter is innovative learning methods that boost employee productivity. Likewise, recommendations are no more synonymous only with online shopping. They empower HR or people leaders to identify the best matching training requirement for an individual, while robots monitor learners, adjust the content, recommend repetitions, and draw conclusions about the learner’s effectiveness. 

Gamification and virtual reality for the Pokemon era employee

Employee engagement scores soar when learning is fun, engaging, multi-sensory, and goal-oriented. This is where gamification plays a crucial role. It makes the whole experience holistic, and the competition boosts learners’ motivation. Similarly, there are virtual reality technologies that offer seamless experience on the training task outcome during the training sessions. Social learning and video-based learning makes learning community driven and continuous, a part of the daily job, rather than a separate activity.

The road ahead for HR with AI

None of the above examples are science fiction anymore. They are available today or are coming soon, most likely even in a disruptive way. But how exactly this change will look like, is up to us as business leaders to define and to design. Hence we need to understand those technologies, evaluate their capabilities as well as their risks, and then make a conscious decision how to use them. As always, they are just tools, and tools are there to support and serve a business purpose. It is up to us to stay in command of this process and decide how we want to leverage those technologies for the benefit of our people and for the benefit of our businesses. SAP, for example, is currently not having any plans to leverage video information for automated mood detection or email sentiment analysis to understand the engagement of its employees.

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Stephan Amling

About Stephan Amling

Stephan Amling is a Senior Vice President at SAP SuccessFactors, based out of Singapore. Prior to that, Stephan was Chief Operating Officer (COO) for SAP’s Human Resources function and the lead of SAP’s global HR Business Transformation Program. He is bringing 30 years of management consulting together with his expertise and innovative thinking in HR as well his deep practical experience in cloud-based HR technologies. On that basis, Stephan is passionate about helping organizations to develop an ambitious people vision while actively supporting them in executing their digital transformation journeys and delivering on their initial objectives, through the use of state-of-the-art technologies.