How To Use LinkedIn To Predict Employee Performance

Modern media are becoming a 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 a day online, and social media consumes an important part of that time.

Recruiters are seeking to fill positions by searching Linkedin’s 380 million users to find ideal candidates and considering their online resume. Can they use LinkedIn to predict employee performance for the future?

Data shows that more could be known about candidates besides their work history. The hottest skill on LinkedIn in 2014 was “Statistical Analysis and Data Mining” a skill that got most people hired.  In HR and personality profiling, big data is in the TOP 3 HR technology expenditures for organizations. Assessment Systems International recently conducted research on few hundred employees by combining data analysis of LinkedIn profiles with personality characteristics as 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 should be searching for those with relevant work history as well as the personal attributes of: ambition, goal-driven, stress resistant, strategic thinking and organized, while being flexible and possessing a tactful communication style.

Could all this be discovered from a LinkedIn profile?

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

Candidates’ sociability could also be a good predictor: People with more than 372 connections showed 19% higher sociability on Hogan’s scale, while a high number of skills and endorsements revealed association with sociability as well. In addition to this we also found a correlation between the number of groups they joined or the number of followers they had. We could conclude that those who are communicative have tendency to connect to more people through their profile, groups or followers. Further evidence of a high tendency for interpersonal skills would be the willingness to post a public profile as well as the number of years with their current or most recent employer. It seems that those who encourage cooperation will have spent a longer time at their current or most recent job and are open to share their profile.

Academic interest turned out to be a good predictor of innovative potential and learning approach as it shows a connection with the need for more sources of information. We found that people with more than 8 years of post secondary academic studies scored 32% higher.  This, combined with the number of schools attended and number of schools followed on LinkedIn also showed positive correlation with learning approach. Another relationship found is the number of groups joined and number of news links followed.  Finally, Innovators tended to provide more information in their LinkedIn data and profile more.

Future trends will follow the possibility to analyze online data of potential candidates which will help to accelerate the recruiting process by opening ways to create algorithms that will go through a recruiter’s LinkedIn database and find the best candidates along with an estimation of their personality based on selected criteria. In this way, employers will have relevant information to predict employee performance before they make any first attempt to contact candidates.

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