During the past three years, the Credit Suisse bank has focused on the analysis of everything that happened with employees (promotions, salary increases, but also significant changes in personal lives), in an attempt to predict whether they would leave the following year. The result was the launch of an internal recruitment programme, whose objective was to activate employees' interest in applying for new jobs. Thanks to this programme, more than 300 employees, who would otherwise probably have left, were promoted.
The company wants to continue testing the predictive algorithm by focusing, for example, on the differences in the departures of men and women from different positions. William Wolf, Credit Suisse's global head of talent acquisition and development, told the Wall Street Journal that the reduction in unwanted employee turnover by one percentage point could save the bank $100 million annually.
Wal-Mart has decided to follow a similar path. The supermarket chain wants better to predict when employees may want to leave a particular position but not necessarily the entire company. It is trying to speed up the prediction of when individual employees will be promoted in order to ensure new people will enter the vacant lower positions quickly enough. The company promotes up to 170 000 employees a year.
As summarised by lpida Ormanidou, Wal-Mart's vice president of global people analytics: “If we can tell three months in advance [that a position is going to be open], we can start hiring and training people."
How do you use people analytics in your company?
-kk-
Article source The Wall Street Journal Online - website of the prestigious economic daily