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https://github.com/mainak-97/hiring_process_analytics_excel_project

A data-driven analysis of company recruitment trends using Excel. This project explores gender distribution, average salary, salary distribution, departmental representation, and position tiers to optimize hiring strategies and enhance decision-making. Includes detailed visualizations and actionable insights for improving the recruitment process.
https://github.com/mainak-97/hiring_process_analytics_excel_project

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A data-driven analysis of company recruitment trends using Excel. This project explores gender distribution, average salary, salary distribution, departmental representation, and position tiers to optimize hiring strategies and enhance decision-making. Includes detailed visualizations and actionable insights for improving the recruitment process.

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# Hiring Process Analytics



![Logo](https://i.imgur.com/CLJiEZu.jpeg)



# Overview

The Hiring Analytics project leverages Microsoft Excel to analyze and optimize the company's recruitment process. Key objectives include evaluating gender distribution, calculating average salary, analyzing salary distribution, and visualizing departmental and position tier distributions. By providing data-driven insights, the project aids in strategic decision-making, enhancing the company's hiring strategies and promoting a diverse, equitable workplace.

# Project Description

The Hiring Analytics project is designed to provide a comprehensive analysis of hiring trends and patterns within the company. The analysis aims to optimize the recruitment process by leveraging data-driven insights. This project evaluates various factors, such as gender distribution, average salary, salary distribution, departmental distribution, and position tier distribution, to support the company in making informed hiring decisions.

# Objectives



* Gender Distribution of Hires: Analyze the proportion of male and female hires to understand gender diversity within the company.



* Average Salary Analysis: Calculate the average salary offered to hires to assess the company's compensation trends.



* Salary Distribution: Create salary class intervals to analyze salary distribution and identify any disparities or trends.



* Departmental Distribution: Visualize the proportion of employees across different departments to understand departmental growth and resource allocation.



* Position Tier Distribution: Represent the distribution of different position tiers within the company to understand the hierarchy and growth opportunities.

# Project Approach

The project follows a structured methodology using Microsoft Excel to analyze and interpret the recruitment data effectively. The steps involved are:



### Data Preparation:



*Data Collection:* Gathered the dataset containing columns such as application ID, interview date, status (hired/rejected), gender, department, post name, and offered salary.



*Data Cleaning:* Ensured the dataset was error-free, with no missing values, duplicates, or incorrect data types.



1. Gender Distribution Analysis:



* Applied filters to the 'status' column to select only the 'hired' candidates.

* Used the =COUNTIFS function to count the number of male and female hires.

* Analyzed the results using a Pivot Table and visualized them through a Bar Chart.



2. Average Salary Calculation:



* Created a Pivot Table to calculate the average salary offered to hired candidates.

* Visualized the average salary using a Bar Chart.



3. Salary Class Intervals Creation:



* Created a Pivot Table to analyze salary distribution.

* Visualized salary distribution using a Bar Chart.



4. Departmental Distribution Visualization:



* Summarized the count of hires in each department using a Pivot Table.

* Visualized the distribution of hires across departments using a Pie Chart.



5. Position Tier Distribution Representation:



* Counted the number of hires in each tier using a Pivot Table.

* Represented the distribution of positions across different tiers using a Bar Chart.

## Screenshots



* Gender Distribution



![Image 1](https://i.imgur.com/497Y4gI.jpeg)

![Image 2](https://i.imgur.com/RNqPujt.jpeg)



* Salary Analysis



![Image 3](https://i.imgur.com/i4XHq3D.jpeg)

![Image 4](https://i.imgur.com/plYmqh3.jpeg)



* Salary Distribution



![Image 5](https://i.imgur.com/kcxDhj8.jpeg)

![Image 6](https://i.imgur.com/Xqvs4fX.jpeg)



* Departmental Analysis



![Image 7](https://i.imgur.com/vKl8YHB.jpeg)

![Image 8](https://i.imgur.com/GlW1Nzb.jpeg)



* Position Tier Analysis



![Image 9](https://i.imgur.com/1XlyxLR.jpeg)



## Results Summary



The Hiring Analytics project provided key insights that significantly enhanced the understanding of the hiring process within the company. The analysis led to actionable insights, supporting data-driven decision-making and strategic planning.



* Enhanced Decision-Making: Provided a data-driven foundation for making informed decisions regarding hiring strategies, salary structures, and departmental focus areas.



* Identification of Trends and Patterns: Identified key trends, such as the balance in gender distribution and salary concentration in specific ranges.



* Resource Allocation: Helped in planning resource allocation and identifying departments that may require more recruitment efforts.



* Strategic Planning: Supported strategic planning in terms of career development and growth opportunities within the company.

## Key Metrics



- Total Males Hired: 2,563



- Total Females Hired: 1,856



- Overall Average Salary: $49,983

### Author



- **Mainak Mukherjee**



- Email: [email protected]



- Linkedin: www.linkedin.com/in/mainak8



### Tech-Stack Used



- **Software:** 



Microsoft Excel [Office Professional Plus 2021] for Data Analysis and Data Visualization.



Microsoft PowerPoint [Office Professional Plus 2021] for Report Presentation.



- **Purpose:** 



Data Collection and Cleaning | Data Analysis | Pivot Tables | Data Visualization using Bar Chart and Pie Chart



### Concepts Used



* Advanced Excel Technicality



* Data Visualization



* Statistical Knowledge

## Usage Instructions



- Data Preparation: Load the dataset into Excel and ensure it is clean and free from errors.



- Analysis: Follow the approach outlined to perform each type of analysis (Gender Distribution, Average Salary, Salary Distribution, Departmental Distribution, Position Tier Distribution).



- Data Summarization: Use Pivot Tables for calculations.



- Visualization: Utilize Excel's charting tools to create visual representations of the data.



- Interpretation: Summarize the insights gained from the analysis and consider how they can be applied to improve the hiring process.

## Project Impact and Learning Experience



Through this project, I gained valuable insights into the company's hiring trends, compensation structures, and departmental growth. For example, in the Gender Distribution Analysis, I observed a significant hiring trend with males constituting 58% of the hires, while females made up 42%.



The project enhanced my understanding of data-driven decision-making, particularly in optimizing recruitment strategies and resource allocation. By analyzing salary distributions and departmental representation, I developed a deeper appreciation for how data can guide strategic planning and promote a balanced, equitable workplace.