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PROJECT BY
Gourishankar Hosur
Thorough understanding of the attrition
trends.
 To identify patterns and potential
factors that contribute to attrition.
Potential implications and strategies for
addressing attrition.
Building dashboard - will elevate simple
metrics, by linking them to one another
and visualizing them as a whole.
Objective
• OBSERVATION:
 A consistent attrition rate across almost all departments.
 This can be seen as a positive aspect, as it indicates that the
organization is maintaining a certain level of employee satisfaction
and engagement across the board.
 Room for improvement in Research & Development and Software
department.
• IMPACT:
 Extended work hours over a prolonged period can contribute to
burnout and reduced job satisfaction, potentially influencing attrition
rates.
KPI 1 – Average Attrition Rate for all Departments
• RECOMMENDATIONS:
 Evaluate project timelines and resource allocation.
 Fix abnormally high overtime hours by hiring and
training new workers.
Observation:
• Average hourly rate for all depart is almost similar.
• For male research scientist is 114.45
• Sales representative have lowest hourly rate.
• Male have lowest hourly rate compare to women.
• Less the hourly rate high the attrition rate.
Conclusion:
• If we want to decrease the attrition rete we hove to
improve Hourly rate for all department.
• In each department if the attrition rate is high and hourly
rate is also high then improve the others aspects.
KPI 2 – Average Hourly Rate of Male Research Scientist
Observations:
• Attrition rates show minor variations around 50% across
monthly income bins, suggesting balanced turnover, with
consistent patterns but no clear linear correlation, visually
depicted in the chart.
Trends & Fluctuations:
• Attrition rates exhibit fluctuating but generally stable trends
across income bins without a consistent upward or downward
pattern
Possible Reasons:
• Possible reasons for attrition include job dissatisfaction (roles,
culture, growth), market demand enticing better offers, and
potential salary concerns (though not clearly indicated by data
alone).
Potential Changes:
Recommended actions involve salary analysis for competitiveness, exit interviews
to uncover reasons, and implementing retention programs like career development
and mentorship.
KPI 3 – Attrition Rate vs Monthly Income
 Due to rapid growth in salary and rapidly evolving
technology younger generation prefer to spend
more years in software.
 R &D employees spend lesser years as very less
people develop ability to research and develop
new technologies
 Working in Sales employees receive additional
commissions for their hard work. Their job
involves interacting with their clients.
KPI 4 – Average Working Years for Each Department
 These differences in working years are also found due to
industry trends, company practices, and geographic location.
KPI 5 – Job Role vs Work Life Balance
.
.
As per our observation, the work life balance of all
department is approximately same except some
departments.
In conclusion, the pursuit of a balanced life is not a
compromise but a strategic investment. It's a recognition
that personal growth, relationships, and rejuvenation are
foundational to excelling in any job role.
KPI 6 - Attrition Rate vs Years Since Last Promotion
Attrition Variation: The attrition rates vary within a relatively
narrow range, from around 49.18% to 62.50%. This suggests
that the overall attrition rate is not drastically changing with the
years since the last promotion.
Inconsistent Trend: At first glance, there isn't a clear linear or
consistent trend in attrition rate as years since last promotion
increase.
Other Factors: It might be worth considering other factors that
could influence attrition, such as job role, department , Monthly
Income , Work Life Balance , and overall job market conditions.
Conclusion : Even though there is no clear relation between attrition and years since last
promotion and there may be other factors that could be influencing attrition , like I
mentioned above . We can conclude that employees getting promoted early are not
leaving the company , so company should promote employees within 10 year period to
avoid employees leaving the company.
.
.
.
HR Analytics Project.pptx

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HR Analytics Project.pptx

  • 2. Thorough understanding of the attrition trends.  To identify patterns and potential factors that contribute to attrition. Potential implications and strategies for addressing attrition. Building dashboard - will elevate simple metrics, by linking them to one another and visualizing them as a whole. Objective
  • 3. • OBSERVATION:  A consistent attrition rate across almost all departments.  This can be seen as a positive aspect, as it indicates that the organization is maintaining a certain level of employee satisfaction and engagement across the board.  Room for improvement in Research & Development and Software department. • IMPACT:  Extended work hours over a prolonged period can contribute to burnout and reduced job satisfaction, potentially influencing attrition rates. KPI 1 – Average Attrition Rate for all Departments • RECOMMENDATIONS:  Evaluate project timelines and resource allocation.  Fix abnormally high overtime hours by hiring and training new workers.
  • 4. Observation: • Average hourly rate for all depart is almost similar. • For male research scientist is 114.45 • Sales representative have lowest hourly rate. • Male have lowest hourly rate compare to women. • Less the hourly rate high the attrition rate. Conclusion: • If we want to decrease the attrition rete we hove to improve Hourly rate for all department. • In each department if the attrition rate is high and hourly rate is also high then improve the others aspects. KPI 2 – Average Hourly Rate of Male Research Scientist
  • 5. Observations: • Attrition rates show minor variations around 50% across monthly income bins, suggesting balanced turnover, with consistent patterns but no clear linear correlation, visually depicted in the chart. Trends & Fluctuations: • Attrition rates exhibit fluctuating but generally stable trends across income bins without a consistent upward or downward pattern Possible Reasons: • Possible reasons for attrition include job dissatisfaction (roles, culture, growth), market demand enticing better offers, and potential salary concerns (though not clearly indicated by data alone). Potential Changes: Recommended actions involve salary analysis for competitiveness, exit interviews to uncover reasons, and implementing retention programs like career development and mentorship. KPI 3 – Attrition Rate vs Monthly Income
  • 6.  Due to rapid growth in salary and rapidly evolving technology younger generation prefer to spend more years in software.  R &D employees spend lesser years as very less people develop ability to research and develop new technologies  Working in Sales employees receive additional commissions for their hard work. Their job involves interacting with their clients. KPI 4 – Average Working Years for Each Department  These differences in working years are also found due to industry trends, company practices, and geographic location.
  • 7. KPI 5 – Job Role vs Work Life Balance . . As per our observation, the work life balance of all department is approximately same except some departments. In conclusion, the pursuit of a balanced life is not a compromise but a strategic investment. It's a recognition that personal growth, relationships, and rejuvenation are foundational to excelling in any job role.
  • 8. KPI 6 - Attrition Rate vs Years Since Last Promotion Attrition Variation: The attrition rates vary within a relatively narrow range, from around 49.18% to 62.50%. This suggests that the overall attrition rate is not drastically changing with the years since the last promotion. Inconsistent Trend: At first glance, there isn't a clear linear or consistent trend in attrition rate as years since last promotion increase. Other Factors: It might be worth considering other factors that could influence attrition, such as job role, department , Monthly Income , Work Life Balance , and overall job market conditions. Conclusion : Even though there is no clear relation between attrition and years since last promotion and there may be other factors that could be influencing attrition , like I mentioned above . We can conclude that employees getting promoted early are not leaving the company , so company should promote employees within 10 year period to avoid employees leaving the company. . . .