EFFECT AND IMPACT OF EMPLOYEE ABSENTEEISM AND …
Transcript of EFFECT AND IMPACT OF EMPLOYEE ABSENTEEISM AND …
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EFFECT AND IMPACT OF EMPLOYEE ABSENTEEISM AND
PERSONNEL CONSTANT TURNOVER IN AN ORGANIZATION
Raj Kumar Singh
Research Scholar
Singhania University,
Rajasthan
Dr. Parul Khanna MBA, Ph.D
Assoc. Prof. & Dean R&D,
Institute of Management & Technology,
Faridabad
Abstract:
Productivity loss due to absenteeism is a serious and growing challenge. In the United States,
the annual cost to employers for time lost due to accidents is almost $100 billion, and other
unscheduled worker absences costs even more. Absence management is a growing body of
knowledge and experience that managers apply to the control and reduction of these costs.
Many organizations are struggling to find the ideal remedy for increased unscheduled
employee absenteeism.
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ABSENTEEISM:
The scheduled time off from work which occurs when, an employee is not present at work,
during a normally scheduled work period.
Excused absences are scheduled in advance for such events as vacation, medical
appointments, military service, family activities, surgery, jury duty, funerals and more that
cannot be scheduled outside of regular work hours.
EMPLOYEE TURNOVER
In view of human resources management and organizational behaviour, the classical
employees’ turnover is the rotation of employees around the labour market between firms,
jobs and occupations, and between the states of employment and unemployment (Abassi et
al., 2000).
The term “turnover” is defined by Price (1977) as the ratio of the number of organizational
members who have left and divided by the average number of people in that organization
during the period. However, the managers frequently refer to turnover as the entire process
associated with filling a vacancy: each time a position is vacated, either voluntarily or
involuntarily, a new employee may be hired and trained.
Research Objectives:
This paper will focus on the impact that the absenteeism and the constant turnover of
personnel have in the organizations and the causes of this common situation. It will also
present prevention programs and strategies to overcome the negative effects, like motivation,
communication, career planning, retention programs, and training. The purpose is to
determine the reasons why employees skip their working schedules or change jobs
continuously. These reasons will be found by a survey applied to different people. After
knowing the reasons, it will be easier to find out which programs will help organizations
avoid these high rates of absenteeism and turnover.
Research Methodology:
The target population for this study consisted of respondents from three groups within the
company, namely, Managers, Supervisors and Workers at C & S Electric Limited,
Noida.
The total headcount1 within the factory was taken into account in determining the number of
respondents to be taken from each of the three groups (Managers, Supervisors and Workers).
It would not have been feasible to include all employees in the company as that would have
required the preparation, issuing and collection of 650 survey questionnaires. Instead, a non-
1 The total number of employees (Managers, Supervisors and Workers) at C & S Electric, Limited, Noida is 650 as per the data provided by the HR Head of the Organisation.
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probability convenient sample, consisting of 120 respondents, representing all three groups,
was selected.
The researcher issued exactly 120 questionnaires to the HR Administrator at the factory
premises. These questionnaires were issued to the predetermined number of Managers,
Supervisors and Workers.
The HR Administrator succeeded in retrieving the full complement of questionnaires issued.
A 100 percent response rate was therefore achieved in respect of the number of
questionnaires issued and the number of completed questionnaires received from the
respondents. This was largely due to a well-controlled questionnaire administrative process.
The results were presented in tables, and a cross-tabular analysis was made by means of
descriptive statistical analysis. This required an analysis of the Mean Scores2 and the
Standard Deviation3 and Population Standard Deviation
4. In addition, an inferential
statistical analysis was done by means of the one-way ANOVA (multivariate analysis)5 to
determine whether there is a statistically significant difference between the mean scores of
the three groups (Managers, Supervisors and Workers).
These tests indicated whether there were statistically significant differences between the
responses obtained from managers, supervisors and employees. The independent variables
identified for purposes of analysis were the monitoring and management of absenteeism.
Based on the survey results of the literature survey and empirical survey, recommendations
were provided to improve the Absenteeism and Personnel Constant Turnover monitoring and
management system at C&S Electric Limited, Noida.
This research article presents the analysis of response obtained from the survey
questionnaires distributed to the respondents.
The first and foremost research objective is sought to identify and analyse the effect and
impact of absenteeism and personnel constant turnover on the organizations specifically the C
& S Electric Limited, Noida, India, by demographical analysis of total surveyed Managers,
Supervisors and Workers in the categories of: gender, age, designation, total work
experience, current company job experience and marital status.
The second Research objective is focused to analyze the details about the effect and impact
of absenteeism and personnel constant turnover on the organizations specifically the C & S
2 For a data set, the mean is the sum of the values divided by the number of values. The mean of a set of
numbers x1, x2, ..., xn is typically denoted by x , pronounced "x bar". This mean is a type of arithmetic mean. If
the data set were based on a series of observations obtained by sampling a statistical population, this mean is
termed the "sample mean" (x) to distinguish it from the "population mean" (μ or μx). 3Standard deviation is a widely used measurement of variability or diversity used in statistics and probability
theory. It shows how much variation or "dispersion" there is from the average (mean, or expected value). 4 Population standard deviation, in a statistical sense, deals with the amount of variation one would expect to see
in a population, for some given attribute. To determine the actual standard deviation for a population, you would
have to sample each individual member of a population for the specific trait you are investigating. 5 In statistics, analysis of variance (ANOVA) is a collection of statistical models, and their associated
procedures, in which the observed variance in a particular variable is partitioned into components attributable to
different sources of variation. In its simplest form ANOVA provides a statistical test of whether or not the
means of several groups are all equal, and therefore generalizes t-test and are useful in comparing two, three or
more means.
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Electric Limited, Noida, India, Further, the various strategies that can be adopted to reduce
and curb the absenteeism and the personnel turnover have been discussed.
The third Research objective is sought to analyse the relationship between the respondent’s
opinions with reference to the effect and impact of absenteeism and personnel constant
turnover on the organizations.
A 32-item structured opinion survey with a 4-5 point scale will be used. This survey will
evaluate respondent’s perceptions in 11 key dimensions:
I. Background: This is sub-divided into:
a. Corporate Plan/Departmental Plan (Questions 1-2)
b. Policy (Questions 3-5)
c. Disciplinary Procedures (Questions 6-7)
d. Time constraints (Questions 8-9)
e. Rating of Attendance (Questions 10-11)
II. Job & Work Culture (Questions 12-20)
III. Job Satisfaction (Questions 21).
IV. Motivators for Job Satisfaction (Question 22-23)
V. Causes of Employee Absenteeism (Questions 24)
VI. Strategies to curb Absenteeism (Questions 25)
VII. Causes of Employee Turnover (Questions 26)
VIII. Strategies to curb Personnel Constant Turnover (Questions 27)
IX. Impact of Absenteeism (Questions 28)
X. Absenteeism Management (Questions 29)
XI. Miscellaneous (Question 30-32)
1.1 Descriptive Statistics on Demographical Factors of the respondents
In section A of the questionnaire respondents were required to provide information about
their gender, age, designation, total work experience, current company job experience and
marital status. Further the section unfolds their perception of absenteeism in the company as
well as their own level of absenteeism, whether they had access to the absenteeism policy and
whether they understood the policy.
The information obtained from these questions in section A is presented and discussed below.
A total of 120 questionnaires were issued and all the questionnaires were returned. Table 1.1
provides a tabulated composition of the respondents:
1.1: Categories of Employees Surveyed:
Table 1.1.1: Number of people included in the study
Category Number of Respondents Percentage
Managers 31 26
Supervisors 28 23
Workers 61 51
Total 120 100%
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In addition to Table 1.1.1 the following Chart 1.1.1 represents the data visually:
Chart 1.1.1 Categories of employees surveyed.
It is evident from the above mentioned table and chart that the non-supervisory and the non-
management employees i.e., workers were the majority participants in the study (n=61; 51%)
followed by the Managers of various departments (n=31; 26%) and finally the Supervisors
(n=28; 23%). The number of respondents is therefore representative of the number of people
employed by the organization.
1.1.2: Age of Employees Surveyed:
Table 1.1.2: Age of the respondents
Age Group Number of Respondents Percentage
20-30 yrs 38 32
31-40 yrs 36 30
41-50 yrs 32 27
51-60 yrs 13 11
>60 yrs 1 1
It is hereby clear that the maximum respondents belong to the age group of 20-30 yrs. (n=38;
32%), followed by the age group of 31-40 yrs. (n=36; 30%), then the respondents were of the
age of 41-50 yrs. (n=32; 27%), however the age group of 51-60 yrs. Had a respondent
number of 13; 11%. In the age group of more than 60 years only one respondent responded.
Chart 1.1.2: Age Group Classification of the respondents
26%
23%51%
Categories of employees
surveyed
Manager
Supervisor
Worker
31%
30%
27%
11%1%
20-30 yrs
31-40 yrs
41-50 yrs
51-60 yrs
> 60 yrs
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1.1.3: Gender of Employees Surveyed:
Table 1.1.3: Gender representation of the total surveyed employees:
Gender Number of Respondents Percentage
Male 86 72
Female 34 28
Chart 1.1.3: Gender representation of the total surveyed employees
The above Table 1.1.3 and Chart 1.1.3 clearly draw a distinction between the gender
representations of the surveyed population. It is evident that the maximum number of the
surveyed population is Males (n=86; 72%) where as the female population is (n=34; 28%).
1.1.4 Total Work Experience:
Table 1.1.4: Total number of work experience of employees:
Total Experience Number of Respondents Percentage
0-2 yrs. 15 13
2-5 yrs. 32 27
> 5 yrs. 73 61
Chart 1.1.4: Total number of work experience of employees
0
20
40
60
80
100
R %
8672
34 28
Male
Female
13%27%61%
0-2 yrs.
2-5 yrs.
> 5 yrs.
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Out of the total number of surveyed population majority had an experience of more than 5
years (n=73; 61%) followed by employees with 2-5 years of work experience (n=32; 27%)
and only 12% (n=15) of the employees said that they have a total work experience of 0-2
years.
1.1.5 Current Company Work Experience:
Table 1.1.5: Work experience of surveyed respondents in C& S Electric, Limited:
Total Experience Number of Respondents Percentage
0-2 yrs. 19 16
2-5 yrs. 26 22
> 5 yrs. 75 63
As far as the work experience of the surveyed population in the C & S Electric Limited is
concerned, the majority of the respondents self-reported that they have been working in this
organization for more than 5 years now (n=75; 63%); however 22% (n=26) reported to have
worked for 2-3 years and just 16% (n=19) reported that they are here from the last two years.
This has been visually shown in the Chart 1.5 below:
Chart 1.1.5: Work experience of surveyed respondents in C& S Electric, Limited
1.1.6 Marital Status:
Table 1.1.6: Marital Status of the surveyed respondents in C& S Electric, Limited:
Marital Status Number of Respondents Percentage
Single 26 22
Married 94 78
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Chart 1.1.6: Marital Status of the surveyed respondents in C& S Electric, Limited
The above Table 1.1.6 and Chart 1.1.6 clearly draw a distinction between the marital status
representations of the surveyed population. It is evident that the maximum number of the
surveyed population is Married (n=94; 78%) where as the single/unmarried respondents is
(n=26; 22%).
I. Various causes of employee absenteeism
Table 1.2.1: Causes of employee absenteeism
S Tech. Env. R M. Style R Pers. Fac. R Ext. Fac. R
1 Conditions of
Work & hrs.
of Work
29 Quality &
style of
Supervision
29 Marital
Harmony
32 Level of
Unemployment
27
2 Accidents 81 Selection,
Induction &
placement
25 Family size
& resp.
37 Social,
Religious &
Cultural Aspects
35
3 Occupational
diseases &
Medical Care
67 Job
satisfaction
&
Challenges
37 Work
orientation,
Leisure
26 Time of the year
& day of the
work
41
4 Work Group 23 Wages &
Incentives
31 Bad Habits 11 Climate &
Related
conditions
32
5 - - Leave Rules
&
procedures
23 Emotional
Health
11 Housing (local) 15
6 - - Role of
Unions
13 Community
&
Obligations
13 - -
7 - - - - Transport 9 - -
8 - - - - Housing 7 - -
9 - - - - Std. of
Living
8 - -
10 - - - - In-debtness 13 - -
Total 200 Total 158 Total 167 Total 150
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Solution
Null Hypothesis
Ho: µ1= µ2= µ3= µ4 i.e. causes of absentees are similar.
Table 1.2.1: Solution: Causes of employee absenteeism
S. No Technological
Environment (X1)
Managerial
Style (X2)
Personal
Factors
(X3)
External
Factors
(X4)
Total
1 29 29 32 27 117
2 81 25 37 35 178
3 67 37 26 41 171
4 23 31 11 32 97
5 - 23 11 15 49
6 - 13 13 - 26
7 - - 9 - 9
8 - - 7 - 7
9 - - 8 - 8
10 - - 13 - 13
Total 200 158 167 150 675
N 4 6 10 15 35
∑ X 200 158 167 150 675
Mean 50 26.33 16.7 30 27
∑ X2 12420 4494 3843 4884 25641
Variance 806.67 66.67 117.12 96 309
Standard
Deviation
28.4 8.17 10.82 9.79 17.57
Standard Error 14.2 3.33 3.42 4.38 3.52
Standard Weighted- Mean Analysis
Table 7.2.1: Standard Weighted- Mean Analysis
Source SS df MS F P
Between Groups 3324.56 3 1074.85
5.39 0.006 Within Groups 4191..43 21 199.59
For V1 =3 & V2 =21, the table value of F at 5% I.o.s = 8.65
Since the calculated value of F is less than the Table Value, null hypothesis is accepted.
and alternative hypothesis is rejected that mean the causes of absentees are almost similar in
all organizations. However the impact of dissimilar causes may be different Technological
Environment is on the peak while external factors affect the least.
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II. Managing Absenteeism: Various methods to manage absenteeism
Table 1.2.2: Methods to manage absenteeism
Statement
Always
Sometimes
Rarely
Never
Sum Mean Standard
Deviation
Population
Standard
Deviation
Proper training
to deal with
absenteeism
12 64 24 20 120 30 23 20
Proper
communication
of
Absenteeism
Policies
36 42 17 25 120 30 11 10
Proper
recording of
Absenteeism
82 26 12 0 120 30 36 31
Comparison of
Dept.
Absenteeism
figures
52 38 21 9 120 30 19 16
Display and
explanation of
Cost of
absenteeism
12 36 54 18 120 30 19 16
Adoption of
Disciplinary
Action
77 31 9 3 120 30 34 29
Trade Union
Involvement
52 54 12 2 120 30 27 23
Total 30 24 21
Standard Deviation & Population standard deviation is smaller than mean depicts numbers
are close to their mean, resulting in the variability in the various methods that can be
implemented to manage absenteeism.
Amongst the most popular method to manage absenteeism at the C&S Electric Limited is the
Proper record keeping of employee’s absenteeism rate and probing the causes to
absenteeism.
Apart from the record keeping the next method is to take appropriate and timely
disciplinary actions for non-report to work as well as routine absenteeism from work.
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III. Impact of Absenteeism:
Summary of the Mean Scores, Standard Deviation & Population Standard Deviation
Table 1.2.2: Combined Responses:
Q. IMPACT OF ABSEENTISM N MEAN STANDARD
DEVIATION
POPULATION
STANDARD
DEVIATION
Q 2 Reduction of absenteeism, a key
goal within the Departmental
Plan
120 30 31.34 27.14
Q 3 Existence of absence policy 120 30 14.72 12.74
Q 5 Reporting of Absentees 120 30 31.9 27.63
Q 6 Dismissal Policy in place to deal
with recurring and frequent
absence
120 30 21.71 18.8
Q 7 Excessive absences subject to
sanctions
120 30 37.31 32.31
Q 8 Opinion about timings 120 30 38.99 33.77
Q 9 Satisfaction with leave facility 120 30 37.34 32.34
Q 10 Description of attendance in
company
120 30 52.1 45.12
Q 11 Describing own attendance 120 30 35.22 30.5
Q 12 Work environment 120 30 30.73 26.62
Q 13 Work monotonous 120 30 24.23 20.98
Q 14 Explanation of job
responsibilities
120 30 43.3 37.5
Q 15 Options of job rotation 120 30 25.54 22.12
Q 16 Relationship with superior 120 30 34 29.45
Q 17 Relationship with subordinate 120 30 37.63 32.59
Q 18 Relationship with peer 120 30 33.55 29.06
Q 19 Satisfied with the working
condition
120 30 32.34 28.01
Q 20 Improvements in the working
conditions
120 30 30.05 26.02
Q 21 Factors influence Job
satisfaction
120 30 27.54 23.85
Q 22 Work motivating factors 120 45 16.49 15.42
Q 23 Work non-motivating factors 120 45 22.03 20.61
Q 29 Methods to manage absenteeism 120 30 24.13 20.90
Q 32 Satisfied with the general
opinion of the company
120 30 31.03 26.87
An analysis of the mean scores, standard deviations & population standard deviation of the
variables reveals that an average mean score of the responses are almost similar i.e 30 & 45
(in 2 cases since selection of the responses was increased.
The standard deviation of the responses varies among 14.72 to 52.1 it presents how the data
will deviate from the normal number. These tendencies are not only for this year of data but
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this can be analyzed effectively to look at the following years. If a trend is able to be
developed then all that will have to be done is a minor tweak to get next year’s perdition.
Mean: Mean = Sum of X values / N (Number of values)
Standard Deviation:
Generally, we are interested in the standard deviation of a population. However, as we are
often presented with data from a sample only, we can estimate the population standard
deviation from a sample standard deviation. We are normally interested in knowing the
population standard deviation as our population contains all the values we are interested in.
Therefore, it is always recommended to calculate the population standard deviation.
Population Standard Deviation:
Population standard deviation gives more accurate picture as to what would be the outcome if
the whole population would have been selected as our target to perform the analysis. The
standard deviation of the responses varies among 12.74 to 45.12 it presents how the data will
deviate from the actual numbers.
IV. Various strategies that can be implemented to curb the employee absenteeism
Table 1.2.4: Strategies to curb employee absenteeism
S. No Opinion Observed
Frequenc
y (O)
Expected
Frequenc
y (E)
O-E (O-E)2 (O-E)
2/E
1 High Collaborative culture 6 6 0 0 0
2 Develop open
communication between
managers, supervisors and
employees
11 15 -4 16 1.0667
3 Regularly scheduled
department meetings
7 10 -3 9 0.9
4 Encourage risk taking &
experimentation among
members
6 7 -1 1 0.1429
5 Awareness, commitment &
involvement by all staff
levels
8 13 -5 25 1.9231
6 Official warnings 9 3 6 36 12
7 Effective training and
development program
13 10 3 9 0.9
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8 Awareness of problems
that effect employee
attendance or performance
15 10 5 25 2.5
9 Cooperation with union
representatives
7 2 5 25 12.5
10 Familiarize with
community programs
7 8 -1 1 0.125
11 Bonus for unused sick
leave
13 10 3 9 0.9
12 Counsel individual
employees
10 13 -3 9 0.6923
13 Effective career planning
And development program
8 13 -5 25 1.9231
Total 120 120 35.573
Table Value 2
0.05 for d.f. 12= 21.06 Hypothesis is rejected &
test is accepted
At 95% confidence level, the critical value obtained from the chi –square test is 2
0.05,
12=21.06, 2
is calculated as 35.573 which is more than the tabular value. Hence test is
accepted and null hypothesis is rejected.
2
0.05, 12 21.06 < 2 35.573
Hence, various strategies to curb the absentees must be employed on selection basis rather on
altogether. Since the results of them will be different among the employees as per their
behavior, attitude etc. Awareness of problems is on the apex while culture, risk taking etc.
plays least important.
CONCLUSION
To summarise:
As most employers are aware, that too much absenteeism and turnover can adversely affect
labor productivity. Finding ways to effectively deal with these problems is an immense
challenge. Even an effective program will fail as the behavior of some employees won’t
change, no matter what the company does. Therefore, it is well worth it to proactively address
these problems. Many suggestions for reducing absenteeism and turnover presented in the
categories below were provided.
1. Redefine Overtime
It was established that a common practice for employees is to miss a day of regular pay to
work hours that pay time-and-a-half. Although they have taken a day off, they still work a
40-hour week but get overtime pay for any hours beyond regular work hours. Such workers,
in effect, have given themselves a raise. Some companies have redefined overtime in their
labor agreements as a way of addressing this problem.
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It was also found that companies should not offer overtime as an incentive to keep workers
from moving to other jobs. This approach can backfire and will adversely affect budgets.
2. Use Incentive Programs
Mixed responses about incentive programs were noticed. Most of the employees claimed
these programs would help reduce their absenteeism and turnover. However, management
believed that incentive programs don’t work. They felt that employees already receive good
wages. Although the effectiveness of incentive programs was not studied, many ideas from
respondents within the research were received. Workers should receive a reward of tools if 40
hours are worked on a consistent basis. A bonus (shared with apprentices) goes to the lead
installer for completing a project in fewer hours than estimated while maintaining a quality of
work acceptable to the company. This program promotes teamwork. Set up a program where
the employees get a certain bonus for every hour worked but have to have 40 hours worked in
a week, or give workers an extra $100 for working 40 hours the week before.
3. Change Work Schedules
Employees reported that one way to reduce absenteeism was to schedule 40 hours in four
days instead of five. A schedule of 10 hours per day, Monday through Thursday, would
leave employees time on Fridays to conduct business or rest. A missed day under this
schedule would also result in a higher financial loss for workers. Another suggestion was to
schedule four 9-hour days with a half-day on Friday.
4. Establish Safe Work Sites
Research showed that injuries play a key role in absenteeism. Employees also reported
wanting to work on safe construction sites. Potentially dangerous tools, equipment, and
materials exist on all construction sites. Therefore, an ongoing, proactive safety program can
significantly reduce both absenteeism and turnover. Having a good safety record can result
in a company becoming a company of choice. A company of choice is one that proactively
inspires worker productivity and loyalty and thus, has fewer problems with absenteeism and
turnover.
5. Become a Company of Choice
Many of the companies that were surveyed said they did not have much of a problem with
turnover simply because they were a company of choice. Companies of choice enjoy a stable
workforce because their programs and policies build worker loyalty. Following are some of
their methods:
Provide safe work sites
Treat workers with respect
Provide lunch
Host company get-togethers
Promote an “open-door” policy between workers and management
Provide training or assistance with training
Provide daycare or assistance with daycare
Provide flexible schedules
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6. Record Attendance Publicly
Supervisors can post the attendance record where all employees can see it every day.
Workers can track their own attendance and also see clearly who is not showing up for work
on a regular basis. This technique demonstrates that management values attendance and takes
absenteeism seriously. Workers who have already missed some time may be reluctant to see
more absences marked next to their names.
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