IBM HR Analytics Employee Attrition & Performance
Analysing the historical data of an Organization and predicting the Attrition rate.
We are using machine learning algorithms to build prediction model for Attrition.
Uncover the factors that lead to employee attrition and explore important questions such as ‘show me a breakdown of distance from home by job role and attrition’ or ‘compare average monthly income by education and attrition’. This is a fictional data set created by IBM data scientists.
Education 1 'Below College' 2 'College' 3 'Bachelor' 4 'Master' 5 'Doctor'
EnvironmentSatisfaction 1 'Low' 2 'Medium' 3 'High' 4 'Very High'
JobInvolvement
1 'Low' 2 'Medium' 3 'High' 4 'Very High'
JobSatisfaction 1 'Low' 2 'Medium' 3 'High' 4 'Very High'
PerformanceRating
1 'Low' 2 'Good' 3 'Excellent' 4 'Outstanding'
RelationshipSatisfaction
1 'Low' 2 'Medium' 3 'High' 4 'Very High'
WorkLifeBalance 1 'Bad' 2 'Good' 3 'Better' 4 'Best'
- Lack of Growth and Progression
- Being overworked
- Lack of Feedback and Recognition
- Changes in Organizational processes and policies
- Loss of talent
- Productivity
- Profit
- Continuous ESAT improvement through predictive insights
- Inputs to strategic resource planning
- Thorough scanning of potential employees
- Sentiment based predictive analysis through multiple data sources like – corporate communication, social media, job portal site
- Recommendation through tool to control attrition
- Joining prediction model