How To Use LinkedIn To Predict Employee Performance? We Know It.

Modern media are becoming vast source of information about people just simply because people are spending more and more of their time online. According to global web index research, we spend 6 hours from our day online and social media plays an important role in it.

Recruiting researchers are looking through Linkedin’s 400 million users to find ideal candidates and considering their online resume on a daily basis.
But data shows that more than that could be known about candidates besides their work history. The hottest skill on LinkedIn in 2014 was “Statistical Analysis and Data Mining” which got most people hired. In HR and personality profiling big data is in TOP 3 HR technology spendings for organizations.

Assessment Systems International ( recently conducted a research on few hundred employees with combining data analysis of LinkedIn profiles and their personality characteristics measured by Hogan inventories to see if online data can really help us in finding the right candidates.

When you are looking for an ideal manager you will be searching for those with relevant work history and characteristics to be ambitious, goal-driven, stress resistant, strategic, organized but still flexible and with tactful communication style. But could this be discovered from a LinkedIn profile?

Our data reveals that there is a significant correlation of ambitious and goal-driven personality with the length of their working experience. People with morethan 14 years of experience scored 46% higher than the ones with less than 7 years. Also those characteristics are related to number of managerial roles and number of positions within one employer. This means that they are searching for new challenges and responsibilities. Other predictor is willingness to publish their email address so they could be contacted and number of endorsements that could reflect their need for recognition. Last but not least we can say that the longer they stay within one employer the higher the ambition is.

Candidates’ potential of sociability could also be drawn. People with more than 372 connections showed 19% higher sociability on Hogan’s scale, while high number of skills and endorsements revealed association with it too. In addition to this we also found correlation with number of groups they joined or number of followers they had. We could conclude that those who are communicative have tendency to connect to more people thought their profile, groups or followers.

The tendency for interpersonal skills could be derived from willingness to public profile and length of years by last employer. It seems that those who encourage cooperation can last longer by their last employer and are open to share their profile.

Innovative potential and learning approach shows connection with the need for more source of information. Academic interest turned out to be a good predictor of it. We found that people with more than 8 years of academic studies scored 32% higher, besides that number of schools studied and number of schools followed also showed positive correlation with learning approach. Another relationship found is the number of groups joined and number of news followed. Also it seems they complete their LinkedIn data and profile more. There is correlation with number of filled categories and also number of words in summary.

Future trends will follow the possibility to analyze online data of potential candidates which will help speeding up the whole recruiting process. It opens ways for creating algorithms that will go through recruiter’s LinkedIn database and based on chosen criteria will find the best matching candidates with estimation of their personality. This way employers will already have relevant information before they make any first attempt to contact candidates.

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