DeepChurn
Employee Flight Risk Predictor.
DeepChurn is an AI driven employee attrition prediction and analytics product from InnoHAT systems. It helps organizations to predict attrition both at employee level as well as at a group level. A group could be an organizational unit like a department or division or a work location or an employment type or an employee job, position or grade etc The post prediction analytics engine of DeepChurn has multiple derived charts from the predicted data. The frequency plot from group prediction gives distribution of the attrition percentage over departments/groups/location etc. DeepChurn also ranks possible factors contributing to employee attrition so that organizations can fix the root of the problem than handling attrition as a symptom. DeepChurn has a unique feature ranking technique that is derived from the prediction algorithm. It also has a time-series prediction engine which can predict the attrition count on a regular interval based on the past data.
Key Features
1. Employee attrition at an individual and group level.
2. Compute attrition rate
3. Post prediction analytics
        a. Reason ranking
        b. Employee Attrition Frequency Plot
4. Time-Series prediction engine to predict bulk attrition on regular intervals
5. Alerts on attrition from critical projects/positions
6. Analytics on skill/job/role level attrition.
7. Descriptive analytics on employee rate over location/BU etc.
All these analysis and prediction are performed with standard HR data available in every organization
Almost every organization would capture the following HR master or transaction data in one or multiple systems. There is no need to capture any other specific information other than what is available already within an organizationEmployee Name
Date of Birth
Marital Status
Date of joining
Overall experience
Home Address
Office Address
CTC
Last Salary hike
Last appraisal rating
Job
Position
Grade
Band
Department / Division
Division/Project
Supervisor
Visa details
Shift details
Passport
details
Travel details
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