HR DATA ANALYSIS
HR DATA ANALYSIS
Overview
This HR data analysis project focused on assessing salary discrepancies across various positions within the organization. The primary objective was to identify patterns and potential inequalities in compensation, with a particular emphasis on finding the highest earner in each job role. Using Power BI, dataset was imported and analyzed, visuals that highlighted salary distributions, gender pay gaps, and other relevant metrics was also created. The insights derived from this analysis were instrumental in informing HR decisions on salary adjustments and policy reviews.
Analytical Process
Dataset for 2017 to 2023 was pulled from the company's database . This data contains information on employees which includes the employees details, qualifications, roles and salary ranges. The below processes were carried out:
1. Data validation and cleaning
2. Exploratory Data Analysis (EDA)
3. Data Modeling
4. Interpretation
5. Recommendation
These streamlined processes helps transform raw data into actionable insights.
Job Title By Head Count:
\This chart shows the head count for different job titles, with "Packaging Associate" having the most employees (22) and "Marketing Manager" and "Marketing Specialist" the least (10 each).
Employee by Gender and Education Qualification:
These charts illustrates the breakdown of employees by education level and gender : 30% have a Bachelor's Degree, 26% possess a High School Diploma, 25% hold a Diploma, and 18% have a Master's Degree. The gender distribution is illustrated with 55% of employees being female and 45% male.
Count of Employee by Year:
Employment rate increased from 2017 to 2019.The highest number of employee was seen in 2019 and 2020 after which employment rate decline till 2013.
Salary Range by Educational Qualification and Job Title :
Does education qualification affects employee's salary range? Average salary answers this question. Other factors such as job title and number of years in service also contributes to the minimum and maximum salary of employees. Significant differences are also observed in the different job roles.
RECOMMENDATIONS:
Based on this HR data analysis, I recommend prioritizing strategies to address the declining employment rate, such as exploring why job openings are concentrated in lower-paying roles.
Additionally, it’s crucial to evaluate the impact of qualifications on salary, particularly in non-HON roles, to ensure equitable compensation. With 55% of the workforce being female and a significant portion (51%) lacking a BSC, tailored development programs could help upskill employees and potentially bridge any pay gaps.
PROJECT IMAGE