QCL-15-v4_[4]_[Banasthali University]_[Bhavya Madan]

EMPLOYEE DISSATISFACTION

QCL V4

PARETO ANALYSIS

SUBMITTED BY:AASTHA BANSALBHAVYA MADANBHAWNA UPRETI

PARETO ANALYSISINTRODUCTION

Pareto Analysis is a statistical technique in decision-making used for the selection of a limited number of tasks that produce significant overall effect.

It uses the Pareto Principle (also known as the 80/20 rule) that by doing 20% of the work (Vital few), you can generate 80% of the benefit of doing the entire job.

How to use it?

Arrange the rows in the decreasing

order of importance

of the causes

Form an explicit table

listing the causes and

their frequency

as a percentage

Add a cumulative percentage column to the table

Plot with causes on x-

and cumulative percentage

on y-axis

Join the above points

to form a curve

Plot (on the same graph) a bar graph with causes

on x- and percent

frequency on y-axis

Draw a line at 80% on y-axis parallel to x-

axis. Then drop the line at the point

of intersection

with the curve on x-axis. This

point on the x-axis

separates the important causes (on

the left) and trivial causes (on the right)

Explicitly review the

chart to ensure that

causes accounting to at least 80%

of the problems are

captured

1 2 354

6 7 8

When to use it?

When analyzing data about the frequency of problems or causes in a process.

When there are many problems or causes and you want to focus on the most significant.

When analyzing broad causes by looking at their specific components.

When communicating with others about your data.

STRATIFICATION OF EMPLOYEE DISSATISFACTION

ODD WORKING HOURSLACK OF INTERESTWORK LOADPOOR PAY JOB INSECURITYLACK OF PROMOTIONPOOR BENEFITSFAMILY LIFEHEALTH ISSUECAREER DEVELOPMENT.

PRIORITIZED TABLE

Sl.No. CAUSE FREQUENCY COMULATIVE FREQUENCY

1 Family Life 22 22

2 Odd Working Hours 18 40

3 Lack Of Interest 16 56

4 Poor Pay 11 67

5 Job Insecurity 8 75

6 Work Load 7 82

7 Lack Of Promotion 6 88

8 Poor Benefits 5 93

9 Health Issue 4 97

10 Career Development 3 100

PARETO ANALYSIS

Family

Life

Odd worki

ng Hours

Lack

Of In

terest

Poor Pay

Job In

secu

rity

Work

Load

Lack

Of P

romotion

Poor Benefits

Health Iss

ue

Career D

evelopment

0102030405060708090

100

Frequency

2218 16

11 8 7 6 5 4 3

22

40

5667

7582 88 93 97 100

FrequencyCumulative%

Cumulative %

SYMPTOMS THAT ACCOUNT FOR 80% FREQUENCY

Family LifeOdd Working HoursLack Of InterestPoor Pay Job Insecurity

PROBLEM DEFINITION

Sometimes due to workload, employees have to work even after their working hours.

Evenings are the best time to spend quality time with your spouse and children and those are actually your working hours.

Due to different transfers which take place in the offices, employees have to live away from their family.

Your life as an employee can be very lonely and frustrating at times.

FAMILY LIFE

ODD WORKING HOURS

Most of the BPOs (Business Processing Outsourcing) in India support overseas operations and majority of professionals have night shifts. 

In majority of cases Indian BPO jobs mostly have odd hours. 

Odd working hours leads to weird eating schedule.

Sleep is also affected.

Lack Of Interest

Today everyone focus on getting best job suited according to their interest.

Due less opportunity in that particular field they are forced to work in the places where they don’t have interest and so they are unsatisfied.

Work without interest is found to be comparatively more tiresome.

Poor Pay

In private sector, people are recruited at low wages which is not sufficient for livelihood.

The stress of paying bills with limited income, causes many workers to feel dissatisfied with their jobs.

Low wages family are more at risk for health problems.

Job Insecurity

Due to high competition among the employees, job is not secured.

There are larger number of employers for the particular post as compared to the available vacancy.

Job insecurity leads to stress among the individual.

LESSONS LEARNT

We learnt about the different problems which leads to Job switching.

With the help of pareto graph, we analyzed the most significant causes of job switching.

It enable better preparation and improvements in decision making for future challenges.

THANK YOU!