Employers want to keep a track of employees having one foot out of the door.
Companies like Wal-Mart Stores Inc, Credit Suisse Group AG, and Box Inc are analyzing several factors that determine which employee is likely to leave a post, resulting in lower turns and tremendous savings with employee turnovers. Business Intelligence tools and analytics greatly provide the necessary tool to overcome this large “headache” for companies.
There are a dozen of factors used by corporate data managers that may include job duration, geographical details, performance analysis, employee survey, communication patterns, and even personality surveys. These are the factors that human resource departments use to determine the people who are likely to leave.
For example, according to an analysis by human resource analytics firm, Culture Amp, held at Box, an employee’s salary or relationship with his boss is a matter of least concern than how connected he feels to his team and job. But at Suisse, manager’s performance and team size turn out to be surprisingly powerful factors with a spike in attrition among workers working on large teams with low rated managers.
A human-resources software company named Ultimate Software Group Inc. assigns its own and its clients’ employees with a unique “retention predictor” number. This number is similar to the credit score and this indicates the employer about which employee is likely to leave.
Nowadays, companies are concentrating more on retaining the employees as replacing them is too costly. According to the Center Of American Progress, the median cost of turnover for most jobs is about 21 percent of an employee’s annual salary. On the other hand, Society of Human Resource Management says that on an average it may cost some $3,341 to hire a new employee.
But the fact remains as it is that no single piece of data predicts whether an employee will stay or leave the company. To overcome this, data scientists have created numerous of models to predict these factors. They might filter the calculations depending on, which factors are most predictive for a particular company and its employees. Business Intelligence and Data Mining (via a data warehouse) is not just to be reactive and try and dissect numbers, rather, it’s a tool to predict the future. What data can we garner from a large group of people to determine and avoid future problems. Without a question, a wanted employee that leaves creates a ripple in the company’s plans. Staying a head of the curve and avoiding such problems, saves on stress, money and most importantly keeps the corporate strategy flowing.
BP Analytics has carved a niche in the data warehousing sector. The company provides customized data warehousing applications to the companies that help determine the above stated factors. These services have helped companies to detect the early risk warnings and take suitable steps on time. For more details about BP Analytics visit www.bpanalytics.com.