Hiring-Process-Analytics-Project

Overview

This project's main goal is to examine our company's hiring procedure in order to learn more about different facets of our recruitment efforts. I want to give a thorough overview of our hiring procedures and point out areas for improvement by using Excel and data visualization approaches.

Project Tasks and Outputs

Task 1: Gender Distribution in Hires

• Insight: The hiring process has resulted in 2562 male and 1854 female hires.
• Recommendation: Consider gender diversity initiatives to ensure equitable representation and attract a more balanced talent pool.

Task 2: Average Salary Analysis

• Insight: The average salary offered in the company is 49,878.
• Recommendation: Compare the average salary with industry standards and competitors to optimize our compensation packages.

Task 3: Salary Distribution by Class Intervals

Class Intervals	Frequency
100-6758	444
6758-13416	479
13416-20074	488
20074-26732	480
26732-33390	453
33390-40048	493
40048-46706	544
46706-53364	478
53364-60022	503
60022-66680	452
66680-73338	486
73338-79996	493
79996-86654	467
86654-93312	460
93312-99970	444
99970-More	0

• Insight: Majority of employees fall within the 40048-46706 salary range.
• Recommendation: Review salary distribution for fairness and competitiveness, especially in the higher salary brackets.

Task 4: Gender Proportions Visualization

• Insight: Male employees are more than the number of Female employees.
• Recommendation: Assess gender distribution against strategic goals and consider adjustments if needed.

Task 5: Post Tier Representation Analysis

• Insight: "Operations Department" post tier has the highest representation, followed by "Sales Department" and "Service Department."
• Recommendation: Evaluate post tier distribution for career progression opportunities and alignment with growth plans.

How to Use

1. Clone this repository to your local machine.
2. Open the Excel file Hiring Process Analytics.xlsx to access the dataset used for analysis.
3. Review the Excel sheets for data details and formulas used for calculations.
4. Explore the generated visualizations in the graphs directory.
5. Refer to the project report for detailed insights and recommendations.

Contributions

Contributions to this project are welcome! If you have suggestions for improvements, data enhancements, or new analyses, please feel free to open an issue or submit a pull request.

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By Vighnesh Gannedi