It was assumed that they were bored, disaffected, or going for interviews. When jobs were plentiful this group of employees were more likely to leave sooner rather than later. When jobs were scarce they hung on being disruptive through their absences.
Now, according to a report in The Times, companies such as Joberate are developing software using so-called “big data” to help them predict which employees are unhappy and likely to leave.
Indicators include opening a LinkedIn account, or spending Friday afternoons on twitter following other companies, or looking at job postings on FaceBook. But the state of the recruitment market and company performance can also be factored in.
Joberate compares an employee’s social media activity with a previous base-line and when it changes can notify the company, or a head-hunter, of the possibility that this person might be in the job market.
All the data they use is publicly accessible so can be accessed without the individual’s permission. Perhaps a stark reminder of being careful about what you put in the pubic domain.
However another software programme Workday uses internal company data such as promotions, management decisions, job cuts and satisfaction surveys.
Companies apparently think that once they have identified employees who might be at risk of moving they can intervene and persuade them to stay.
I’m not so sure. Once people start on activities such as LinkedIn job profiles they are already distancing themselves psychologically from their organisation (and probably more likely to take time off).
And usually people leave because of a poor relationship with their immediate boss.
One piece of research based on 32,000 Fortune 100 companies found that from the time an employee had a bad meeting with their boss it took only three months for that person to resign.