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May 27, 2024
Here's a step by step Power BI use case guide on Workforce Analysis.
Let's start with a bit of background on Infosys. It's one of the leading global consulting and IT services companies, with a storied legacy dating back to 1981. Over the decades, Infosys has grown into a multinational powerhouse, serving clients across 50 countries and employing over 300,000 professionals worldwide.
That's an incredible journey, right? And a big part of their success story is their focus on building a world-class workforce through advanced HR analytics. By collecting and analyzing vast amounts of employee data, Infosys has been able to uncover valuable insights into talent acquisition, retention, and development strategies.
So, how did they achieve this? By embracing the power of HR analytics and using it to shape a highly engaged, productive, and future-ready workforce – one that is well-equipped to drive innovation and deliver exceptional value to their clients.
The HR employee dataset offers a comprehensive view of the workforce, capturing demographics (Age, Gender, Marital Status, Education Field), job details (Department, Job Role, Job Level, Distance From Home), satisfaction metrics (Job Satisfaction, Environment Satisfaction, Relationship Satisfaction, Work Life Balance), and tenure information (Years At Company, Years In Current Role, Years Since Last Promotion, Years With Curr Manager).
This rich dataset enables analysis of attrition patterns across various segments, identification of high-turnover areas, and understanding of drivers impacting employee engagement, job satisfaction, and retention. With these insights, HR professionals can develop data-driven strategies to foster a stable, satisfied, and high-performing workforce. Dataset consists of 35 columns and 1470 rows.
As a data analyst, it is crucial to address extensive datasets such as HR dataset. We have developed a five-step plan focused on understanding the key aspects of HR data analysis.
By leveraging HR analytics, It is possible to spot patterns in employee turnover and retention issues in different departments and demographics. This helps HR professionals customize retention efforts, improve engagement tactics, and enhance workforce stability by identifying high attrition risk areas. By using data to analyze employee departures, we can improve job satisfaction and create a more engaged and dedicated workforce in line with organizational goals.
The first step involves determining the intended recipients of the data, in this scenario, an individual known as an HR Manager. The HR Manager handles numerous responsibilities like overseeing recruitment and onboarding, creating pay structures, setting up employee benefits, ensuring adherence to labor laws, and promoting employee welfare, employee attrition and involvement.
Stakeholders need in-depth data to make well-informed choices, such as details on employee demographics, turnover rates, and market trends for talented individuals. They face difficulties like attracting and keeping top talent, managing employee interactions, following employment rules, upholding a healthy company culture, Managing attrition and resolving workplace issues.
To truly connect with the experiences and expectations of a HR Manager, the creation of an empathy map is invaluable. This visual tool allows for a deeper understanding of the emotions, aspirations, and pain points of users.
By empathizing with their perspectives, we can design a data story that not only meets functional requirements but also resonates with the human elements of their roles.
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Once an empathy map is ready. As a data analyst, you need to decide on the most important things to keep an eye on, called KPIs (Key Performance Indicators).The heartbeat of any analysis lies in KPI’s and their Metrics. It's crucial to identify the KPIs that matter most to achieving the defined objectives and by focusing on the most relevant metrics, organizations can gain actionable insights into HR Analytics.
Based on the Empathy Map and KPIs, it is essential to establish the goals and objectives of the Users. This will help align with the data story functionalities for effective decision making. Here are the Key Objectives & Goals:
Analyze the organization's human capital management practices to reduce employee turnover, improve recruitment, and support a skilled workforce. Use data to understand attrition rates, recruitment costs, training impact, and program success. The aim is to find areas for improvement and introduce strategies that boost talent retention, growth, and organizational performance.
The main goals are to reduce employee turnover rates significantly and consistently, especially in departments experiencing high attrition. It is important to avoid losing top-performing employees and key talent. The aim also to improve recruitment procedures, cut costs, and use new methods to find the right talent efficiently. Additionally, the focus is on improving training quality to boost performance and ensure high completion rates for required programs, all aimed at developing a skilled and motivated workforce for long-term success.
Beyond KPI’s, organizations must engage in business-driven inquiry. This involves asking strategic questions that directly align with overarching business objectives.
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SELECT
Department,
COUNT(*) AS TotalEmployees,
SUM(CASE WHEN Attrition = 'Yes' THEN 1 ELSE 0 END) AS AttritionCount,
(SUM(CASE WHEN Attrition = 'Yes' THEN 1 ELSE 0 END) * 100.0 / COUNT(*)) AS AttritionRate
FROM
Employee_HR
GROUP BY
Department
ORDER BY
AttritionRate DESC;
SELECT
Gender,
COUNT(*) AS TotalEmployees,
SUM(CASE WHEN Attrition = 'No' THEN 1 ELSE 0 END) AS ActiveEmployees,
SUM(CASE WHEN Attrition = 'Yes' THEN 1 ELSE 0 END) AS LeftEmployees
FROM
Employee_HR
GROUP BY
Gender;
SELECT
CASE
WHEN TotalWorkingYears BETWEEN 0 AND 10 THEN '0-10 years'
WHEN TotalWorkingYears BETWEEN 11 AND 20 THEN '11-20 years'
WHEN TotalWorkingYears BETWEEN 21 AND 30 THEN '21-30 years'
ELSE '31+ years'
END AS ExperienceRange,
COUNT(*) AS AttritionCount
FROM
Employee_HR
WHERE
Attrition = 'Yes'
GROUP BY
ExperienceRange
ORDER BY
ExperienceRange;
SELECT
CASE
WHEN Age < 18 THEN 'Under 18'
WHEN Age BETWEEN 19 AND 30 THEN '19-30'
WHEN Age BETWEEN 31 AND 40 THEN '31-40'
WHEN Age BETWEEN 41 AND 50 THEN '41-50'
ELSE 'Over 50'
END AS AgeGroup,
COUNT(*) AS TotalEmployees,
SUM(CASE WHEN Gender = 'Male' THEN 1 ELSE 0 END) AS MaleEmployees,
SUM(CASE WHEN Gender = 'Female' THEN 1 ELSE 0 END) AS FemaleEmployees
FROM
Employee_HR
GROUP BY
AgeGroup
ORDER BY
AgeGroup;
Examining data based on job role and job satisfaction ratings can offer valuable insights into possible areas for enhancement.
SELECT
JobRole,
COUNT(*) AS TotalEmployees,
SUM(CASE WHEN Attrition = 'Yes' THEN 1 ELSE 0 END) AS AttritionCount,
ROUND(AVG(JobSatisfaction), 2) AS AvgJobSatisfaction
FROM
Employee_HR
GROUP BY
JobRole
ORDER BY
AttritionCount DESC, JobRole;
These discoveries establish a solid groundwork for HR to create targeted initiatives that tackle high-attrition departments, boost employee engagement at all experience levels, and ultimately contribute to a more stable and productive workforce.
The HR Analytics dashboard uncovered important information. The R&D and Sales departments experience the most employees leaving, especially among new hires with 0-10 years of experience. A connection between job satisfaction and employee turnover was noticed among laboratory technicians, indicating a need to investigate this pattern in all positions.
Taking action on these insights through focused retention programs, engagement efforts, and potentially improved recruitment strategies can help HR create a more robust and dependable workforce.
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