5 min to read
Chasing Zero: A Quest to Reduce Attrition Rate
Uncovering the hidden drivers of employee turnover in a tale of data
During my study in the RevoU course, I have been given an assignment to assess a critical aspect of data analysis, which is understanding business problems. The assignment is intended to enhance my analytical thinking and proficiency in identifying business problems, and is inspired by a real case study from a top-notch company.
This project was completed as part of the assignment for the RevoU Full Stack Data Analytics course.
As a disclaimer, the analysis on this project is based on assumptions and uses the provided data only for an overview of possible metrics to provide, with no need for technical data processing.
Business background
The company XYZ Ltd, which employs 4000 people, is facing a significant issue with its annual attrition rate of 15%, resulting in numerous open positions that need to be filled with new hires. The CHRO has requested the data analytics team to determine what factors should be prioritized in order to decrease the attrition rate by next year.
Organizational structure
Data
The datasets and data dictionary related to this case study are available here for reference purpose.
DARCI
I need to define the DARCI framework in order to establish clear expectations for each stakeholder’s role in this project.
- The decider is the Chief Human Resource Officer.
- The accountable person is the Head of Data.
- The responsible parties consist of the Data Analyst Team and HR Associate.
- Those who are consulted include the Human Resource Team, Business Development Team, Marketing Team, and Engineering Team.
- Those who are informed consist of the COO, CMO, CDO, CTO, Business Operations Team, Product Team, BD Associate, Marketing Associate, and Engineers.
Problem statement
Once the roles have been assigned, I need to clarify the problem to be solved by stating the problem statement using SMART, as follows:
“How to reduce the employee attrition rate from 15% per year to 10% within the next year by analyzing the data and implementing appropriate strategies?”
Objective
Then I include the following objective to ensure clarity and establish the project’s goal.
“To identify the factors that contribute to employee attrition and implement strategies to reduce the attrition rate from 15% to 10% within a year.”
Issue tree
To find the root cause of the problem, I use an issue tree to pinpoint and eliminate its underlying cause.
All potential root causes identified in the issue tree are based on assumptions. In reality, to confirm their impact on the problem, testing with data and statistical methods is necessary.
Hypotheses and metrics
After identifying all the root causes from the issue tree, I create hypotheses with priority based on their impact on the problem statement. I then focus on the hypotheses with high priority and propose key metric recommendations based on those hypotheses to monitor the attrition rate’s performance.
- Lower salary
If employees receive a higher salary than they currently do, then it will reduce job dissatisfaction and potentially reduce the attrition rate to 10% within a year.
Priority: Medium - Lack of advancement
If employees receive more recognition and advancement opportunities, then it will lead them to feel more valued and motivated which could result in an increase in job satisfaction.
Priority: Medium - Culture clash
If the company addresses and resolves employee culture clashes or conflicts by placing employees in departments where they have a better cultural fit, then it will improve the environment satisfaction.
Priority: High
Metric: 1) Voluntary employee turnover rate—measures the rate at which employees are leaving the company voluntarily, indicating how satisfied employees are with the company’s culture; 2) Employee satisfaction—measures the level of employee commitment have towards the company and this can be influenced by the work environment and culture within the company. - Heavy workload
If a company can assess the workload of its employees and identify the specific tasks or projects that are causing the most strain, then it will create a better balance between work and life for those employees.
Priority: High
Metric: Absenteeism rate—measures the rate at which employees are absent from work, indicating the level of stress or burnout they may be experiencing due to an unbalanced workload. A lower absenteeism rate suggests that employees are able to manage their workload and maintain a healthier work-life balance. - Long distance
If the company allows for remote work or provides housing options closer to the workplace, then it will improve the work-life balance of its employees.
Priority: Low - Lack of motivation
If the company improves job design to make roles more challenging and meaningful, then it will increase employee motivation and job involvement.
Priority: Low - Lack of training
If employees are provided with more training and development opportunities, then it will increase the employee performance.
Priority: High
Metric: 1) Employee performance post-training—measures the overall performance of employees after they have completed training and development opportunities. It can be compared to their performance before training to determine if there is an improvement; 2) Work efficiency—measures the productivity of employees in terms of the amount of work completed in a specific period of time, and it measures the employee’s productivity after the training.
Please note that in reality, all the root causes must be proven through hypothesis testing.
Conclusion
Understanding the business problem is a crucial step in finding solutions. Using the right framework, including understanding the background, setting objectives, identifying root causes, and writing hypotheses, can help identify important metrics to effectively address the problem. This enables the company to implement the appropriate strategy to reduce the attrition rate from 15% to 10% within a year.
