This is an Scenairo analysis using Tableau dashboard with filters to assess overtime work, compensation and management impact as a part of a comprehensive IBM project in solving 2024 LA office's Attrition Problem. The company has faced recent challenges related to workforce management, including layoffs, talent retention, and employee dissatisfaction. IBM has been restructuring its workforce by offshoring roles to India and laying off senior employees in the U.S., particularly those in levels L7–L9 who are between 50–55 years old and at the top of the pay scale. To address these challenges, we are assigned to analyze the a historical 1500 employees' and 37 features dataset, and we proceeded to specfically looked into 5 areas: Employee Demographics, Job-Related Features, Compensation Metrics, Satisfaction Metrics, Relationship Satisfaction, and measure how they affect employees' Attrition.
- Target variable: "Attrition", whether an employee has left the organization (Yes/No).
- Employee Demographics: Age, Education, Marital Status, Job Level, Job Role.
- Job-Related Features: Department, Years at Company, Years in Current Role, Total Working Years.
- Compensation Metrics: Hourly Rate, Monthly Income, Monthly Rate
- Satisfaction Metrics: Work-Life Balance, Job Satisfaction, Environment Satisfaction, Relationship Satisfaction.
- Workforce Features: Business Travel, Distance from Home.
- Consisting of 5 steps: Problem Statement, Time-series Analysis, Sceniro Analysis, Solutions, Quantifying ROI.
- Sceniro outcome: enabling to cut down attrition rate from 16% to 5%.
- Analyzed 5 features
- Overtime Work (1 feature)
- Compensation (2 features: Monthly income, Salary Hike)
- Management's Impact (2 features: Years since last promotion, Years with current manager)
- Rationale: these three factors theoretically can be controlled by the company as independent variables
- Note: Scenarios will be more granular in level of departments and job roles to provide insights