Author: Sven Semet, HR Thought Leader Watson Talent, IBM Germany
The issue concerning the future necessity of HR is currently a widely debated topic and is definitely an initiative that personnel decision-makers should be paying attention to. This plan is slowly starting to take shape and can be read up on, for example in the IBM white paper “How Cognitive Computing will transform HR and the Employee Experience”. In it, IBM sounds out the field for an uptrend in “Cognitive HR” within the scope of a large-scale survey. This question will also be an important topic at the #HRFestival, on 9 May in Berlin, being discussed in different lectures, panel discussions and workshops.
The survey comes to the conclusion that specific areas, such as Talent Acquisition and Onboarding, Talent Development and HR Operations, could profit from the use of artificial intelligence.
The research evaluated if the surveyed persons would make the same decision following advice from either a human or a machine, who they felt better instructed or advised by, and whom they trusted more. The results showed that there was no area where the pro-machine percentage of the answers fell under 50 percent. In terms of consistency in the decision-making, humans came out on top, if only slightly with 60 percent to AI’s percent. The machines had the advantage as far as the comprehensiveness of information was concerned, with 68 percent to 64 percent. In the case of trustworthiness (for example, decisions concerning requests for time off), machines were once again ahead with 58 to 54 percent. It was solely on the issue of who they would rather turn to in case of a recurrent question that the more standard methods (human) performed better, with a substantial gap of 71 percent to percent. A fairly small advantage for the human counterpart, or to answer the initial question here: no, HR can get along without humans. The HR world is ready for the intelligent machines, IBM concluded. And is right on the money, in the opinion of Wollmilchsau (see the current blog post).
The developments surrounding IBM Watson play a decisive role here. The cognitive intelligence of a Watson system allows business sectors to read massive amount of data, to analyse and assess them and then, through interaction with the application, continually keep learning through new findings.
Who has the time or overview to keep track of the countless innovations and all the associated new buzzwords these days? Analytics, Big Data, Predictive, BI Strategy, Digital Transformation – you could continue this list ad infinitum. The question keeps coming up: what’s actually behind all of these concepts? In which areas does one even need to take topics such as Big Data, Analytics and other Business Intelligence (BI) solutions into consideration? The fact that 80 percent of all data is available in an unstructured form is something that many may have already heard, but what exactly does that mean for one’s own company?
Big Data: already available in HR today
The question regarding if HR will be confronted with Big Data in the future can be answered with a resounding ‘Yes!’ And not just in the future, but now, at this very moment – with the next potential top talent posting their thoughts on their job search on Twitter. Or with the next electronic application that comes flying in and needs to be processed today, but could already be automatically evaluated. Or a complete candidate analysis could be carried out, including social media data, sentiment analysis and then compared with assessment data, so as to create a fully comprehensive talent profile with information on the personality of the applicant. All the relevant data is already there! It just depends on what HR does with it.
There’s so much more possible besides the simple analysis of individual candidates in recruitment – from Personality Analytics of an individual to the Workforce Analytics of the entire staff. The prediction of which employee might possibly quit and which measures can be taken to prevent this. Cognitive applications in personnel management can support decision-making for these questions and issues through data-based analyses and predictions.
image credit: IBM