UNRAVELING THE RETENTION ENIGMA
[ UNRAVELING THE RETENTION ENIGMA ]
LEVERAGING ANALYTICS TO DRIVE STRATEGIC INTERVENTIONS IN A LIFE SCIENCES CONGLOMERATE'S BATTLE AGAINST HIGH ATTRITION
- Key inference/learning through Predictive Model basis ML.
- Salary hike was effected basis natural intelligence and market forces. However it did not rank in top 5 influencing factors on attrition.
- Business context
- Purpose of Analytics
- Business actions and Impact
For one of the Life Sciences unit of a large conglomerate, one of the key issues was
attrition (19% (236/1470) in a quarter). Bench marking for Comp & Ben done and salary
adjustments effected. Its has not had desired effect. The leadership wanted to take
actions through appropriate interventions to improve retention.
- Determine the relationship between Attrition and impacting variables. Validate
existing assumptions. - Build predictive model for managing potential attrition.
- Define Metrics and Data source and
Acquire Data - 45 variables * 1470 data points from 4
different system - Data from Employee DB
- Time management system
- Data Payroll MS Data
- Other Databases
- Rotation policy crafted and implemented for job enrichment.
- Mentor –Mentee program.
- Soft nudges supported by OT policy (Layered approval, Transportation availability etc)
