“This morning, 82% of you came into this room fully energised, pumped up to attend this conference, while 15% were lukewarm in your excitement, and the remaining 3% really had great party last night, somehow managed to make it to the event.” This opening line by Stephan Amling from SAP might scare you that how did he manage to find out your mood? But relax! All he wanted was to show you the element of truth in his statement. The fact is he could’ve predicted your mood with a simple technology using a camera at the entrance of the conference room and send the data mapping your facial expression to Google and then Google would be telling us the exact mood with which you have come to attend the conference. 

The technology would also be telling us that on diversity, the conference might have done a great job, but could do some more with regard to the age-diversity with more Millennials in the show. This could be possible with a publicly available app. 

But what does Amling want us to know? 

He says that with technology which is available everyday to map your progress, productivity, your engagement towards your work, why should organizations be stifled in mapping it only once a year with annual performance surveys. What is the relevance of such data if they are not mapped daily?

This is machine learning technology, and this technology can also be applied to email. It can constantly scan the language of the email you are sending to know in mathematical value the emotional stage of the author, can also know how detached or compatible or incompatible the employee is towards his/her organization.  

Applications for jobs: In order to scour through the number of applications received for a particular position, a highly automated process can scan through the initial applicants, track who are eligible, then automatically a chatbot or a robot can talk to the potential applicants and send them thoughtfully designed games to know their intellectual capabilities and then the last 5 or 10 candidates are called for ‘human’ interaction to select the final one. And this is not science fiction, but reality. Unilever is one company which does it.

Machines can erase biasness in hiring as well. HR recruiters sometimes use words in JDs which are biased. For example: if ‘Outspoken communication’ is written, then automatically it points to talent who are white, male candidates. But machines can eliminate this unconscious bias. 

So, as Amling said, “We need to align both our people and HR strategy with our organization and company strategy”.

(This article is curated from the Mega Keynote session: Consider the future: How tech will change every stage of employee life-cycle by Stephan Amling from SAP at TechHR’17)