MS in Business Analytics - Capstone Project
This project dealt with the following:
- Business Problem and Objectives
- Executive Summary
- Data Overview and Key Business Assumptions (if any)
- Data Preparation and Pre-processing
- Sanity checks, treatment and transformations for analytical dataset preparation
- Exploratory Data Analysis
- Key Business Findings and Insights
- Model Development and Validations
- Model comparisons on key scoring metrics and model finalization
- Dashboarding (required only when it is in scope of analysis)
- Businesss Recommendations and Potential Business Impact
- Next Steps
Business Problem:
- The aim of the following project is to help HR department in predicting potential employees who are likely to be promoted. To investigate and gain insight into the future of HR analytics if integrated into the company to assist managers in predictive decision – making based on statistical evidences and relevant HR analytical data. To undertake an exploration of existing scenario with the aim of understanding the relationship between human resource and analytics and understand the role it plays in the improvement of the existing range of managerial and HR related ways.
Executive Summary
- A typical HR analytics system collects employee data from HRIS (Human Resources Information system), business performance records and social media merges into Data Warehouse, statistical analysis and data mining techniques to provide understanding of hidden data patterns, relations, probabilities and forecasting. HR Analytics is a relatively novel intervention in the larger domain of human resource management. It can be understood as being more credible because it provides statistically valid data and evidence that can be used in the process of creating new strategies and other measures. The effective HR analytics will help the HR managers in performing HR functions such as forecasting the demand and supply of people, identifying suitable employments test to suit applicant profiles, creating list of employees to be promoted and managing employee discipline This project contributes greatly to the HR Managers to make decisions based on data about the list of employees to be promoted based on number of trainings, previous year rating, length of service, KPIs met, awards, and average training score.