How to control attrition through data analytics

How to control attrition through data analytics?

  • 10th Feb, 2017

Attrition is an obscure but one of the largest cost factors for organizations. This sounds quite upsetting because retaining employees is economical and easy than replacing them with new hires, especially when you have to replace highly potential employees and count the number of weeks or months of knowledge gaps to be bridged with the new hire.

Sometimes attrition is unavoidable as well as unpredictable. This is because of limited data as well as some human factors involved in attrition. But still there are chances for you to use certain statistical techniques that can predict and help in controlling attrition largely. One of the best ways is Data Analytics (which many companies are using religiously) rather than keeping track on exit interviews or working on surveys.

Root causes for attrition

It is crucial to become proactive so that you can save a good staffer from resigning. Firstly, it is important to understand and analyze the root causes that are triggering attrition rate within the organization. These root causes can be categorized as professional and personal. Following are some of the professional issues.

  • Dissatisfied with compensation, is the most prevalent reasons where employees simply quit their jobs for a better salary and perks from some other organization. Where many organizations slip up is salary correction. Some employees may not have started with higher base salaries and due to standard and limited increment ranges; their salaries develop a significant gap with what they can get in the market.
  • Lack of opportunity to rise, where employees seek promotion after several years of sincere work contributed towards the growth of the company. Not everyone can rise to the top, but, in today’s world, organizations need to have multiple smaller and flatter hierarchical teams. Empower their roles. Allow them to make a difference with their inputs. This will give opportunity to more people to rise as per potential and have greater satisfaction.
  • Many employees have strained relationships with managers, where they feel that their bosses do not respect them. This usually happens if the manager tries to micro manage or their actions express doubt on the integrity or capability of their team members. A manager should focus on mentoring, channeling their inputs and facilitating rather than dictating.
  • Employees may find their job responsibilities boring or simply do not enjoy the task assigned to them.
  • Inadequate facilities, where the infrastructure of the organization is not as per the expectations of employees.

Apart from these, there are some personal root causes also, such as marriage, spouse transfer, medical reasons, higher education, and relocate near to the family.

Organizations should collect information on the above-mentioned factors that can be processed by data analytical tools to predict which set of employees are susceptible to attrition and take corrective action to create a more satisfied pool of employees.

Conclusion

Collecting information on identified root causes of attrition makes it easy to analyze and come to a conclusion from the collected data. For example, organizations can use statistical techniques, such as predictive modeling and take necessary steps to retain the deserving employees.

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