employee attrition 2

8/7/2019 Employee Attrition 2

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EMPLOYEE ATTRITION

An Analysis of Factors Influencing Attrition in the growing Economies

-NMIMS

INTRODUCTION

In the recent decades the Indian industry has changed its outlook. The

employment scene has changed its appearance. The factors like skill sets, job

satisfaction drive the employment and not just the money. The employer hence

faces the heat of continuous employee turnover. Continuous efforts are made by

organisations to control the employee turnover rate as it directly affects the


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performance of the organisation as many key people leave the organisations for

various reasons at crucial points. This turnover is normally known as ATTRITION.

Defining attrition:

A reduction in the number of employees through retirement, resignation or death.

Defining Attrition rate:

The rate of shrinkage in size or number.

In the best of worlds, employees would love their jobs, like their coworkers, work

hard for their employers, get paid well for their work, have ample chances for the

advancement, and the flexible schedules so they could attend to personal or familyneeds as and when necessary.

But then theres the real world. And in the real world, employees do leave, either

because they want more money, hate their co-workers, want a change or because

their spouse gets a dream job in another state. So, what does the turnover cost?

And which employees are likely to have the highest turnover? Who is likely to stay

the longest?

Impact of attrition

Direct impact: A high attrition indicates the failure on the companys ability to set

effective HR priorities. Clients and business get affected and the companys

internal strengths and weaknesses get highlighted. New hires need to be constantly

added, further costs in training them, getting them aligned to the company culture,

etc.,all a challenge.

Indirect impact:

Problem for the company in attracting potential employees. Typically, high attrition

also leads to a chronic or systemic cycleattrition brings decreased productivity,

people leave causing others to work harder and this contributes to more attrition.

All this has a significant impact on the companys strength in managing their

business in a competitive environment.


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Productivity and profitability are both impacted, either negatively and positively,

according to the type of attrition. The cost of hiring is sometimes not less than two

to three times the salary of the employee.

The impact on work progress is tremendous, particularly if a project is underway

and one of the key people leaves. It leads to dip in entire organizational efficiency,

and a lot depends on how it is able to cover the setback,

Organizations should execute top of the line retention policies in the right earnest

and consistency. They should be more employee-centered and look for further ways

to bond employees to their companies. Company performance is optimally

aligned to the skills its employees possess. High attrition implies that certain

necessary skills are vulnerable or are not present due to employees being lost. It

results in lower than optimal levels of business performance. If the skills areconstantly not available, the situation gets compounded into a crisis with key

projects, revenues, etc., getting affected. Business is then reduced to just

managing crisis.

Reasons why organizations are not able to retain employees

1. Performance goals are unclear. In a fast growing team or business the focus is on

getting the thing done today, but rarely are performance goals thought throughand employees told as to which resources to approach for help.

2. Reward systems are not transparent. Most employees who get salary increases

because they have a rare skill at a particular point of time think they got their raise

for excellent performance. Can you share details about how they have been

compensated?

3. Perceived equity of reward systems is low. Like it or not, employees discuss salary

details and if there is any perceived lack of equity then you have an issue !

4. Goal setting process is not scientific. Most organizations impose a normal curve

fitment, but do not train managers to set realistic goals or goals that tie up with

organizational or functional goals. This also leads to point number 6

5. External equity is missing too. Don't do an annual compensation survey when the

market moves every 3-4 months. If your practitioners feel that externallycomparable professionals are being valued more, then they will leave.


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6. No communication around total value. If you offer benefits apart from only

monetary terms do you communicate that to employees too. Things like being a

global or niche industry leader, value of the brand of the organization, should also

be made explicit.

7. No career planning. Are people aware of the ways in which they can grow in the

organization? Who are the role models within the organization? Do they know what

they have to do to gain the competencies to move to various levels? (update: Can

you be radical enough and create an internal

The decision to choose this project was taken by us for the following reasons:

1. The project was inherently complex and involved imparting objectivity to factorsthat are inherently subjective in nature. Also the complexity of the project ensures

for us a thorough and in-depth understanding of the concepts and fundamentals of

marketing research which is the most important aim of this basic course on

Research Methodology.

2. The study pertained to the industry and we could easily identify with one of our

own breed. Also since we all have experience this process in our daily work lives it

was easier for us to short list the major factors that go into the decision making.

The project as we see it at present can be divided into the following four major

stages:

1. Short listing the most important factors that are considered by employees at

various levels while making decisions regarding their own career choices.

2. Preparing a questionnaire that can give us as objective as possible a view about

the relative importance of these factors and also of how these factors change with

stage life and owing to socio-economic differences.

3. Conducting surveys in various organisations and ensuring that we get a proper

mix of gender, economic position, competency and other such instrumental

characteristics of students in our survey.

4. Analyzing the data we gather through the survey in (3) using various statistical

tools available to us and derive conclusions that are in coherence with theobjectives of the project.


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OBJECTIVES

What are the various factors involved in the process of deciding job objectives for

employed people.

To analyze the relative importance of factors discovered in last point.

To find out the similarities and differences in the decision making process for

when employee satisfaction with respect to the job profile and the organisation

changes.

Find how these factors for employees are influenced by demographic differences.

RESEARCH DESIGN

This can be divided into two major parts1. Brainstorming

2. Survey (Questionnaire)

Brainstorming

We brainstormed for factors drawing largely on the personal experience of the

group members. The major influencers that we came up with were:

Demographics

Industry segmentation

Job satisfaction

Job level

Miscellaneous influences

Questionnaire (Survey)

The design of questionnaire is of paramount importance. It will be used to translate

the information needed into a set of questions that the respondent could answer

and the answers thus obtained could in turn yield the desired result.

Questionnaire attached separately


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FOLLOWING FACTORS WERE FOUND OF IMPORTANCE THAT COULD

INFLUENCE THE DECISION:

Salary & Benefits

Connection between pay and performance

Security and administration of yours

Workload

Flexibility of work hours

Physical working environment

Opportunity for advancement

Job security

Ability to influence decisions that affect you

Opportunity to use new technologies

Opportunity to work on interesting projects

Access to company-sponsored training and seminars

Communication with your supervisor

Recognition received from your supervisor

Your supervisors management capabilities

Your supervisors active involvement in your career development

Your overall relationship with your supervisor

Your relationship with your peers

Your understanding of the business mission

Your overall satisfaction with your company

Overall satisfaction with your job

Work profile

Position

Inequality

Poor work environment and facility

Long distance Commuting

Growth opportunity

Change in industry

Personal commitments


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Easy Commute

RATIONALE OF THE WORK AND EXPECTED OUTCOME

The sudden opening up of economy has brought with it exponential increase in theopportunities and options for service class people. People find it difficult to leave a

well settled job unless and until there is a strong reason to it. A very common belief

for changing job is the remuneration, but to our surprise we found out that the

remuneration or salary is the third or fourth in priority if we arrange the

parameters in descending order.

This study can be used for working on a wider scope project on the same subject. It

is tricky to design and execute the project as it involves multiple influences and

their interaction.

Following are the expected outcome of the research project:

To determine Factors Influencing attrition patterns in the industry.

The objective is to see what factors are more influential than others, so that

proper factors could be used to analyse the factors to reduce attrition rates

by HR managers in the industry.

Data Collection Source

The data collection for this research will be from primary data sources. Though

usage of primary data will lead to higher collection cost, and more involved

collection process, it will ensure that the data is current, can be easily analyzed

and accurately reflects the present day reality. The usage of primary data sources

will also help us have more freedom in the choosing the data that we want to

use/analyze in course of our research. The sample group for this project is to bethe employees at different levels and from different organisations. We are also

interested in analysing the demographical features like marital status, sex and

educational background.

The survey will be having both qualitative and quantitative data collection. As the

research field is exploratory, the qualitative data will allow finding out the major

factors behind the choices made. The quantitative data will give us information


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regarding the relative importance of the various factors from the employee point of

view.

SAMPLING

Sampling is one of the key components of any research design. Details of our

sample are as follows:

Target Population

We are targeting respondents of 2 categories: Employees in their first job

Employees who have worked for minimum two or more organisations.

Sampling Technique

We will be using the traditional sampling approach of Probability sampling and

Non Probability sampling, i.e. the sample will be selected before data collection

begins and sampling without replacement will be performed.

Sample Size

We will include around 253 people in our study. As data is being collected on alarge number of variables, a large sample will help in reducing the cumulative

effects of sampling error.

Execution

We distributed our questionnaire among organisations where we work, also sent

the questionnaire to friends who are working in different organisations. We have

tried to cover basic industry types like engineering, IT, finance, projects,

consultants, education etc.

DATA ANALYSIS TOOL

The process to be followed to analyze the data collected will be as follows:


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The data will be entered into an Excel sheet. The scores to the questions pertaining

to a particular factor will be grouped together and then an average score for the

factor can be calculated (simple arithmetic mean).

A correlation matrix of the influencing factors (mentioned in the questionnaire) can

then be generated to highlight the interrelationships.

Cluster analysis can be run to identify groupings in the population in the space.

The analysis can then be taken to a deeper level. For each of the factors, we can try

to find the influence of socioeconomic variables on the strength and direction of

each of the factors. This can be done through testing for statistically significant

difference in means between classifications based on the relevant socioeconomic

factors.

Graphical Representations

Pie Chart

Column Chart

GenderSatisfaction/NonSatisfaction

Total


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Female Neutral 20 Non Satisfy 13 Satisfy 56Female

Total 89

Male Neutral 59 Non Satisfy 22 Satisfy 83Male Total 164Grand

Total 253

Cylinder Chart


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FACTORS WHICH EFFECT CAREER DECISIONS

The Questionnaire contained questions analysing the satisfaction level of the current

job of an individual. The various factors were correlated to the Satisfaction rating

provided by the sample respondents

FactorsCorrelation

Salary 37%

Benefits 38%

Connection between pay and performance 32%

Workload 24%

Flexibility of work hours 9%

Physical working environment 5%Opportunity for advancement 46%

Job security 34%

Ability to influence decisions that affect you 46%

Opportunity to work on interesting projects 33%

Your supervisors management capabilities 22%

Your overall relationship with your supervisor 54%

Your relationship with your peers 34%

Salary has a correlation of only 37% where as Relationship with your

superior had a correlation of 25%

Second part of our Questionnaire contained reasons for leaving your Prior Job (if

any) and factors that would influence a persons to change Job in future. Depending

upon the ranks provided by the individual three important factors were identified

1. Compensation (Our Hypothesis)

2. Work Profile & Equality

3. Growth Opportunity


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Reason for leaving prior Job Weights Reason leading to Future attrition Weights

Less Compensation 2.86 Higher Compensation 2.49

Less growth opportunity 3.99 Better work profile 2.67 Stagnant work profile 4.49 Higher position 4.05

Lower position 5.57 Better work environment and facility 5.11

Change in industry 5.85 Faster Growth Opportunity 5.30

Change in work profile 5.93 Able to fulfill Personal commitments 7.01

Inequality 6.33 Easy Commute 7.33

Poor work environment and facility 6.54 Job in a MNC (applicable for people working in Local org) 7.42

Not able to fulfill Personal commitments 6.77 Change in work profile 7.53

Long distance Commuting 6.91 Change in industry 8.04

The detailed analysis is as follows:

Independent-Samples T Test

To test the general Hypothesis of Salary being the most influential factor forAttrition, we applied certain Hypothesis test.

The Independent-Samples T Test procedure compares means for two groups of

cases. Ideally, for this test, the subjects should be randomly assigned to two

groups, so that any difference in response is due to the treatment (or lack of

treatment) and not to other factors. This is not the case if you compare average

income for males and females. A person is not randomly assigned to be a male or

female. In such situations, you should ensure that differences in other factors are

not masking or enhancing a significant difference in means. Differences in average

income may be influenced by factors such as education (and not by sex alone).

The Independent-Samples T Test procedure tests the significance of the difference

between two sample means. Also displayed are:

for the difference between the two variables (95% or a value you specify)

Descriptive statistics for each test variable A test of variance equality

A confidence interval


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The Descriptive table displays the sample size, mean, standard deviation, and

standard error for the groups.

The procedure produces two tests of the difference between the two groups. Onetest assumes that the variances of the two groups are equal. The Levene statistic

tests this assumption.

The t column displays the observed t statistic for each sample, calculated as the

ratio of the difference between sample means divided by the standard error of the

difference.

The df column displays degrees of freedom.

The column labelled Sig. (2-tailed) displays a probability from the t distribution

with 251 degrees of freedom. The value listed is the probability of obtaining an

absolute value greater than or equal to the observed t statistic, if the difference

between the sample means is purely random.

The 95% Confidence Interval of the Difference provides an estimate of the

boundaries between which the true mean difference lies in 95% of all possible

random samples of 250 employed people.


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Since the significance value of the test is less than 0.05, you can safely conclude

that the average employees leaving the job is not due to chance alone. The priority

of changing the job is as follows

1. Opportunity for advancement

2. Connection between pay and performance

3. Salary

Paired-Samples T Test

The Paired-Samples T Test procedure compares the means of two variables for a

single group. The procedure computes the differences between values of the two

variables for each case and tests whether the average differs from 0.

One of the most common experimental designs is the "pre-post" design. A study of

this type often consists of two measurements taken on the same subject, one

before and one after the introduction of a treatment or a stimulus. The basic idea is

simple. If the treatment had no effect, the average difference between the

measurements is equal to 0 and the null hypothesis holds. On the other hand, if

the treatment did have an effect (intended or unintended!), the average difference is

not 0 and the null hypothesis is rejected.

The Paired-Samples T Test procedure is used to test the hypothesis of no difference

between two variables. The data may consist of two measurements taken on the

same subject or one measurement taken on a matched pair of subjects.

Additionally, the procedure produces: Descriptive statistics for each test variable

The Pearson correlation between each pair and its significance

A confidence interval for the average difference (95% or a value you specify)


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The Descriptive table displays the mean, sample size, standard deviation, and

standard error for both groups.

At 0.065, the correlation between the baseline and less compensation and high

compensation is not statistically significant. Levels were lower overall, but the

change was inconsistent across subjects.

On the other hand, the Pearson correlation between the baseline and Overall job

satisfaction is 0.792, a strong correlation.

The Sig. (2-tailed) column displays the probability of obtaining a t statistic whose

absolute value is equal to or greater than the obtained t statistic

The lower or higher compensation has no effect on the satisfaction but the job

satisfaction must have some effects with other work related factors which gives one

a job satisfaction.


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Correlations

In this example, the Partial Correlations table shows both the zero-order

correlations (correlations without any control variables) of all three variables and

the partial correlation controlling of the first two variables controlling for the effects

of the third variable.

The zero-order correlation between Communication and overall satisfaction is,

indeed, both fairly high (0.669) and statistically significant (p < 0.001).Similarly recognition received and the overall satisfaction has a correlation factor of

0.510 which is also fairly high.

ANALYSE RESULTS

1. From the above observation we can see that the salary is not the only

parameter of changing job.

2. The two factors for which we see people tend to change the job are the

job satisfaction and the relation with the immediate supervisor.

3. The other demographic features like commutation, marital status do

make an influence on job changing decision but not as a significant

factor.


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4. The factors like educational qualification, change in industry also tends

to influence but not significantly.

5. The fact of salary and recognition being important criteria they are

compromised on if the other factors are favourable.

LIMITATION OF THE WORK

Despite our best efforts, we feel that our study has a few limitations which are

listed below: The samples collected may carry a bias of field of work and position as

there is a large amount of data from lower or middle management people.

We could not test all possible combinations as there are large no of

interactions prevalent in the data which needs expert advice.

The demographic influence needs more objective data to analyse it

against the job satisfaction and attrition criteria.

CONCLUSIONS

From the findings of our study we could conclude that:

Relationship with immediate supervisor is the most important criteria

for changing jobs.

Recognition monitory or non monitory from the supervisor makes a

difference even in cases of lower salary.

Banking and construction sector are experiencing the large amount of

attrition apart from IT industry.

Middle management has higher attrition rate as it faces heat from

both the ends.


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The compensation for the job and compensation for the performance

are valued equally as an employee.

The satisfaction is a comparative term amongst colleagues and can

not be treated as independent entity. This calls for the transparency

in the evaluation system of any organisation.

employee attrition 2

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