DATA ANALYSIS AND INTERPRETATION OF EMPLOYEES PERSPECTIVES ON HIGH ATTRITION

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1 DATA ANALYSIS AND INTERPRETATION OF EMPLOYEES PERSPECTIVES ON HIGH ATTRITION Analysis is the key element of any research as it is the reliable way to test the hypotheses framed by the investigator. This chapter deals with the analysis of the primary data collected through the administration of the questionnaire. The collected data has been codified, tabulated and analysis has been conducted using the different statistical tools such as Reliability Analysis, Factor Analysis, Multiple Regression analysis, and Testing of the Hypotheses focusing on Analysis of Variance (One-way ANOVA), Chi-Square test, t-test, pie-charts, averages, percentages graphs and bar diagrams. The five major analyses conducted in the study focusing on the employee s perspective are listed as: 4.1 Reliability Analysis 4.2 Factor Analysis 4.3 Analysis of personal and other factors 4.4 Data Analysis based on Objectives 4.5 Multiple Regression Analysis The above five analyses are conducted and the results of the different statistical procedures are discussed below: 4.1 RELIABILITY ANALYSIS A pilot study has been conducted for a sample of 50 respondents and reliability analysis (scale- split) is done. Three measures of reliability are given. The scale consists of 40 items, which measures the attitude of the respondents on a Likert type five point scale. 50 respondents were selected for reliability analysis. Chapter-IV 133

2 Table: No.4.1 Analysis of Factor Variables Statistics for of items Part Part Scale The scale items were divided into two parts (forms) each part containing 20 items selected randomly. The correlation between two forms was found to be , indicating that the items between the two parts correlates well. Spearman-Brown and Guttman split-half reliabilities are used to find reliability coefficients of the scale by dividing the scale items into two halves in some random manner. Table: No.4.2 Reliability coefficients No. of Cases 50 No. of Items Items in part 1 20 items in part 2 Correlation between forms Equal-length Spearman-Brown Guttman Split-half Unequal-length Spearman-Brown Alpha for part Alpha for part The correlation between forms is used to find the Spearman Brown reliability and the variances of sum scale and forms are used to find Guttman reliability. Cronbach's coefficient alpha (α) uses variances for the k individual items (40) and the variance for the sum of all items. If there is no true score but only error in the items then the variance of the sum will be the same as the sum of variances of the individual items. Therefore, coefficient alpha will be equal to zero. If all items are perfectly reliable and measure the same thing (true score), then coefficient alpha is equal to 1. In all, the reliability of the three statistics namely, Spearman-Brown, Guttman and Cronbach s alpha show that the reliability of scale constructed for the General Assessment is between 0.70 and 0.87, which makes the constructed scale fairly reliable. Therefore the scale reliability is good. Since it was found that the reliability of the scale was good, factor analysis was performed on all the 400 valid responses. Chapter-IV 134

3 4.2 FACTOR ANALYSIS The set of 40 items included in the Employee Attrition Scale was used to find the underlying factors in it. The Factor analysis conducted in this study proceeds in four steps: Step 1 Correlation matrix for the variables, item 1 to item 40, was analyzed initially for possible inclusion in Factor Analysis. (The results of the correlation between item1 to item40 are given in Appendix). Since one of the goals of the factor analysis is to obtain 'factors' that help explain these correlations, the variables must be related to each other for the factor model to be appropriate. A closer examination of the correlation matrix may reveal what are the variables which do not have any relationship. Usually a correlation value of 0.3 (absolute value) is taken as sufficient to explain the relation between variables. All the variables from 1 to 40 have been retained for further analysis. Further, two tests are applied to the resultant correlation matrix to test whether the relationship among the variables is significant or not. Table: No 4.3 KMO and Bartlett's Test Kaiser-Meyer-Olkin Measure of Sampling Adequacy.823 Approx. Chi-Square Bartlett's Test of Sphericity df 780 Sig. ** One test is Bartlett's test of sphericity. This is used to test whether the correlation matrix is an identity matrix. i.e., all the diagonal terms in the matrix are 1 and the off-diagonal terms in the matrix are 0. In short, it is used to test whether the correlations between all the variables is 0. The test value ( ) and the significance level (P<.01) are given above. Chapter-IV 135

4 With the value of test statistic and the associated significance level is so small, it appears that the correlation matrix is not an identity matrix, i.e., there exists correlations between the variables. Another test is Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy. This test is based on the correlations and partial correlations of the variables. If the test value, or KMO measure is closer to 1, then it is good to use factor analysis. If KMO is closer to 0, then the factor analysis is not a good idea for the variables and data. The value of test statistic is given above as which means the factor analysis for the selected variables is found to be appropriate to the data. Step 2 Next step is to determine the method of factor extraction, number of initial factors and the estimates of factors. Here Principal Components Analysis (PCA) is used to extract factors. PCA is a method used to transform a set of correlated variables into a set of uncorrelated variables (here factors) so that the factors are unrelated and the variables selected for each factor are related. Next PCA is used to extract the number of factors required to represent the data. The results from principal components analysis are given below. To start with, in the correlation matrix, where the variances of all variables are equal to 1.0. Therefore, the total variance in that matrix is equal to the number of variables. In this study, there are 40 variables (items) each with a variance of 1 then the total variability that can potentially be extracted is equal to 40 times 1. Chapter-IV 136

5 The variance accounted for by successive factors would be summarized as follows: Table: No.4.4 Total Variance Explained Initial Eigen values Extraction Sums of Squared Loadings Component % of % of Cumulative Variance Cumulative % Variance Variance Variance % Chapter-IV 137

6 In the second column (Initial Eigen values) the column titled Variance, we find the variance on the new factors that were successively extracted. In the third column, these values are expressed as a percent of the total variance. As we can see, factor 1 account for about percent of the total variance, factor 2 about 9.6 percent, and so on. As expected, the sum of the eigen values is equal to the number of variables. The third column contains the cumulative variance extracted. The variances extracted by the factors are called the eigen values. From the measure of how much variance each successive factor extracts we can decide about the number of factors to retain. Retain only factors with eigen values greater than 1. In essence, this is like saying that, unless a factor extracts at least as much as the equivalent of one original variable, we drop it. This criterion is probably the one most widely used and is followed in this study also. In this study, using the above criterion, 13 factors (principal components) have been retained. The tableno.4.5 shown below gives the Component Matrix or Factor Matrix where PCA extracted 13 factors. These are all coefficients used to express a standardized variable in terms of the factors. These coefficients are called factor loadings, since they indicate how much weight is assigned to each factor. Factors with large coefficients (in absolute value) for a variable are closely related to that variable. For example, Factor 1 is the factor with largest loading (0.639) for the variable, Statement 33. These are all the correlations between the factors and the variables, Hence the correlation between Statement 33 and Factor 1 is Thus the factor matrix is obtained. These are the initially obtained estimates of factors. Chapter-IV 138

7 Table No.4.5 Component Matrix Statements Components Chapter-IV 139

8 Table No.4.6 Communalities Items Initial Extraction Items Initial Extraction Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement Statement The Table No.4.6 titled Communalities is given above. This provides communalities for each variable calculated from the factor matrix described above. The proportion of variance explained by the common factors is called Communality of the variable. For example the proportion of variance explained by the 13 factors in the variable, that is the statement-1 is That is 65.3% of the variance in Statement 3 is explained by all the 13 factors. So the communality of the variable Item 1 is Further, the table titled Total Variance Explained gives the proportion of total variance explained by all the factors. The column '% of Variance' explains how much variance is attributed to each factor and the next column is the cumulative percent of variance. So, Factor 1 is the one which accounts for maximum proportion of total variance. These eigen values are calculated from the factor matrix described above. Thus for any factor, its corresponding Chapter-IV 140

9 highest factor loading will contribute much to that factor. By looking at the last column it is understood that the 13 factor model explains 63.32% of the variance in the selected variables. Step 3 Although the factor matrix (Table No.4.5 titled Component Matrix) obtained in the extraction phase indicates the relationship between the factors and the individual variables, it is usually, difficult to identify meaningful factors based on this matrix. Since the idea of factor analysis is to identify the factors that meaningfully summarize the sets of closely related variables, the Rotation phase of the factor analysis attempts to transfer initial matrix into one that is easier to interpret. It is called the rotation of the factor matrix. The Rotated Factor Matrix (Table titled Rotated Component Matrix) using Oblique rotation is given in Table: No 4.7 where each factor identifies itself with a few set of variables. The variables which identify with each of the factors were sorted in the decreasing order and are highlighted against each column and row. Chapter-IV 141

10 Table No.4.7 Rotated Component Matrix Chapter-IV 142

11 Step 4 Normally, from the factor results arrived above, factor score coefficients can be calculated for all variables (since each factor is a linear combination of all variables) which are then used to calculate the factor scores for each individual. Since PCA was used in extraction of initial factors, all methods will result in estimating same factor score coefficients. However, for the study, original values of the variables were retained for further analysis and factor scores were thus obtained by adding the values (ratings given by the respondents) of the respective variables for that particular factor, for each respondent. Thus the 40 variables considered in the primary data were reduced to 13 factors model and each factor was given a name which associated with the corresponding variables. The factor names and descriptions of the factors are given in the following Table No.4.8. Table No Factors Model Item No. Statement 25 Unclear performance goals causes high attrition 26 Missing of personal touch in the organization leads to high attrition 27 Lack of scientific goal setting process causes high attrition 24 Lack of integration of people in the company leads to high attrition 28 This company s location is good and it makes my work easier 09 The culture of this company is such that it creates a very positive work environment 30 Salary hike in every six months can be a better option to reduce high attrition 07 I feel that I get self-respect and dignity in this organization 21 This company s infrastructure is good and makes my work easier 34 Introduction of family benefit plans will reduce high attrition 35 Social isolation is a major cause for high attrition 23 Family issues and influence of family members leads to high attrition Factor Name 1. Lack of integration and goal setting 2. Work atmosphere 3. Work and family conflict Chapter-IV 143

12 15 My organization provide hygiene and timely food to the employees 13 This organization conduct stress reduction programs like yoga, meditation etc. 4. Food and relaxation This company is not very open to ideas and suggestions 10 given by employees 5. Motivation and This organization does not conduct effective 06 appreciation motivational programs 17 Internal job rotation will lead to high attrition 18 Work from home option will reduce high employee attrition 6. Work from home This organization provides sufficient holidays for Dissatisfaction with employees salary and perks 03 I am paid enough for the work I do in this company 02 Odd working hours causes high employee attrition 8. Maximum hours worked/ 01 Lengthy working hours leads to high attrition abnormal working hours 38 Absence of counseling and medical health checkups causes high attrition 9. Occupational health 36 Lack of spiritual sessions organized in the company problems leads to high attrition 32 Eye fatigueness and vision deterioration leads to high attrition 40 This organization has a logical, bias free promotion policy 16 Sleeping disorders causes high employee attrition 39 This organization do not provide labour welfare measures like housing schemes, health club etc. 08 This company has high standards of corporate governance 10. Labour welfare and 04 I believe that the company s leadership is doing what is corporate governance required for its growth 31 Low perceived equity of rewards system leads to high attrition 05 I am not satisfied with the kind of salary hikes I get 11. Dissatisfaction with 20 Reward systems in this organization are not transparent rewards and hikes 37 Lack of talent management in the organization leads to high attrition 12. Miscellaneous-lack of 14 Lack of safe and good transportation facility leads to transportation and talent high attrition 33 Lack of communication around total value causes high attrition 19 Lack of work value and ethics causes high attrition 29 Absence of performance-based bonus causes high attrition 13. Lack of work ethics 12 Constant pull of higher salaries leads to high attrition 22 Mismatching of job expectations creates the problem of attrition Chapter-IV 144

13 4.3 ANALYSIS OF THE PERSONAL AND OTHER FACTORS The personal factors included in the study are gender, location, age, designation, qualification, area of work, salary, and global position. An analysis of the respondents based on gender, location, age, designation, qualification, area of work, salary, and global position have been conducted and the findings are discussed as follows: Gender-wise distribution of the sample: Analysis of the respondents based on the gender is conducted and the results are given as follows: Table No.4.9 Gender-wise distribution of the sample Gender No. of respondents Percentage of the total sample Male Female Total Source: Survey Data Table No.4.9 indicates the classification of data according to their gender as male and female. There are 236 male respondents and 164 female respondents included in the sample. Chart No.4.1 Percentage distribution of the gender Gender 59% 41% Male Female 0% 50% 100% Percentage Chapter-IV 145

14 The Chart No.4.1 reveals that there are 59% male respondents and 41% female respondents in the selected sample. Inference: From the above chart, it is inferred that approximately 60% of the respondents selected for the study are male and nearly 40% of the respondents are female. It shows that the selected number of male and female respondents in the study is moderate Location-wise distribution of the sample: Analysis of the respondents based on location is conducted and the results are given as follows: Table: No.4.10 Location wise distribution of the respondents Location No. Percentage Karnataka Kerala Total Source: Survey Data Table 4.10 shows the location-wise distribution of the sample. There are 285 respondents from Karnataka state and 115 respondents from Kerala state in the sample. Also the percentages of the two groups are tabulated along with their numbers. Chart No.4.2 Percentage-wise distribution of the location Percentage 80% 70% 60% 50% 40% 30% 20% 10% 0% 71.3% Karnataka 28.7% Kerala Karnataka Kerala Location Chapter-IV 146

15 The chart No.4.2 shows that 71.3% of the respondents in the sample belong to Karnataka State and 28.7% of the respondents are from Kerala. Inference: From the percentage distribution, it is inferred that approximately 70% of the respondents are from Karnataka and approximately 30% of the respondents are from Kerala which shows that the selection of respondents from Karnataka and Kerala are moderate for the present study Global position-wise distribution of the sample: Analysis of the respondents based on global position is conducted and the results are given as follows: Table No.4.11 Distribution of the sample based on global position (national/ multinational) Global Position Number of respondents Percentage National Multinational Total Source: Survey Data Table No.4.11 shows the grouping of the respondents under national and multinational BPO employees. 212 respondents belong to national BPO s and 188 respondents belong to multinational BPO companies. Chart No. 4.3: Percentage wise distribution of Global position Percentage 60% 50% 40% 30% 20% 10% 0% 53% 47% National Multinational Global Position National Multinational Chapter-IV 147

16 Chart No.4.3 indicates the grouping of the respondents in the sample under national and multinational BPO employees. It shows that 53% of the sample belongs to national BPO employees and 47% of the sample belongs to multinational BPO employees. Inference: From the chart No.4.3, it is inferred that 53% of the respondents are selected from national BPO s and 47% of the respondents are selected from multinational BPO s which shows that there is almost equal representation from national and multinational BPO s Age-wise distribution of the sample: Analysis of the respondents based on age is conducted and the results are given as follows: Table: No.4.12 Age-wise distribution of the sample Age No. of respondents Percentage of the total sample < 18 yrs yrs yrs Above 25 yrs Total Source: Survey data Table No shows the grouping of the respondents under different age groups as less than 18 years group, years, years and Above 25 years group.260 respondents belong to years group, 109 respondents belong to above 25 years group, 27 respondents under years group and 4 respondents belong to less than 18 years group. Chart No 4.4 Percentage distributions of the age groups 27.30% 1% 6.80% 65% < 18 yrs yrs yrs. Above 25 yrs. Chapter-IV 148

17 From the chart No. 4. 4, it is found that 65% of the respondents fall in the age group of years and 27.3% of the respondents fall in above 25 years category. Also, 06.8% of the respondents belong to years group and 01% of the respondents belong to less than 18 years category. Inference: From the chart it is observed that among the respondents 65% of them are in the age group of years and 27.3% of the respondents are above 25 years. Also, 06.8% of the respondents are in years group and only 01% of the respondents are less than 18 years. It is found that majority of the respondents (65%) are in the entry level age group of years which accounted for the highest employee attrition in BPO sector Experience-wise distribution of the sample: Analysis of the respondents based on experience groups is done and the results are given as follows: Table: No Distribution of Experience groups in the organization Experience Groups No. of Respondents Percentage of the total sample < 6 months months 1 year years years > 5 years Total Source: Survey Data Table No gives the classification of the respondents as per their experience in the present organization. Five groups have been formed to include the experience groups ranging from less than 6 months to above 5 years groups. Chart: No.4.5 Percentage distribution of Experience groups Percentage 50% 45% 40% 35% 30% 25% 20% 15% 10% 9.8% 20.0% 47.8% 19.5% 5% 0% < 6 months 6 months 1 year 1 2 years 3 5 years > 5 years Experience 3.0% Chapter-IV 149

18 Chart No. 4.5 indicates that 47.8% of the respondents belong to 1-2 years group and 20% of the respondents belong to 6 months 1 year group. Also 19.5% of the sample belong to 3-5 years category, 09.8% of the sample belong to less than 6 months group and 03% of the sample fall in above 5 years group. Inference: It is observed that among the respondents, approximately half of them are in the experience group of 1-2 years and an equal number of them are either in 6 months 1 year group, or 3-5 years experience group Salary-wise distribution of the sample: Analysis of the respondents based on salary groups is done and the results are given as follows: Table No Salary-wise distribution of the respondents Salary groups (per month) No. of respondents Percentage <Rs. 5, Rs. 5,000 10, Rs. 10,000 15, Rs. 15,000 20, Above Rs. 20, Total Source: Survey Data Table No exhibits classification of respondents as per their salary per month. There are five salary groups included in the sample as less than Rs. 5000, Rs group, Rs group, Rs. 15,000 20,000 and above Rs. 20,000 group. Chart No. 4.6: Percentage-wise distribution of salary groups 14.2% 23.5% Salary 20.5% 40% 1.8% 0% 5% 10% 15% 20% 25% 30% 35% 40% Percentage < Rs. 5,000 Rs. 5,000 10,000 Rs. 10,000 15,000 Rs. 15,000 20,000 Above Rs. 20,000 Chapter-IV 150

19 Inference: From the chart, it is observed that among the respondents 40% of them are in the salary group of Rs.10, ,000 and 23.5% of the respondents are in Rs.15, ,000 salary group. Also 20.5% of the samples are in Rs. 5,000 10,000 salary group, 14.2% of the samples are in above Rs. 20,000 group and 1.8% of the samples fall in less than Rs. 5,000 category. Thus analysis shows that majority of the respondents salary is above Rs which accounts to higher salary drawers group Designation-wise distribution of the sample: Analysis of the respondents based on designation groups is done and the results are given as follows: Table No.4.15 Designation-wise distribution of the sample Designation No. Percentage Process Analyst Senior Process Analyst Team Leader Supervisor Manager Total Source: Survey Data Table: No gives an account of the designation groups and their numbers and percentages in the sample. The groups included are process analyst, senior process analyst, team leader, supervisor and manager. The process analysts group has 246 respondents, senior process analyst group has 95 respondents, team leader has 34 respondents, supervisor has 15 numbers and manager has 10 respondents. Chart: No.4.7 Percentage distribution of Designation groups 61.50% Percentage 80% 60% 40% 20% 23.80% 8.50% 3.80% 2.50% Process Analyst Senior Process Analyst Team Leader Supervisor Manager 0% Chapter-IV 151

20 Inference: From the chart, it is observed that among the respondents 61.5% of them are in the designation group of process analyst (entry level), and from the total sample 23.8% of the sample are in senior-process analyst group. Also, 08.5% of the sample belongs to team leader category, 03.8% of the sample belong to supervisor group and 02.5% of the sample belong to manager category. Thus it is concluded that from the total sample, majority (61.5%) of them are from process analyst (entry level) group, where employee attrition is highest which further justifies the sample selection Qualification-wise distribution of the sample: Analysis of the respondents based on qualification groups is done and the results are given as follows: Table: No.4.16 Qualification wise distribution of the sample Qualification No. of respondents Percentage ITI/Diploma Undergraduate Graduate Postgraduate Total Source: Survey Data Table No gives an account of the qualification groups, the number of respondents in each group and their percentage distribution. The four qualification groups included are ITI/Diploma, undergraduate, graduate and postgraduate. The graduate group has 217 respondents, post graduate group has 147 respondents, and under graduate group have 21 respondents and ITI/Diploma group have 15 respondents. Chart: No. 4.8 Percentage distribution of Qualification groups Postgraduate 36.80% Qualification Graduate Undergraduate 5.30% 54.30% ITI/Diploma 3.80% 0% 10% 20% 30% 40% 50% 60% Percentage Chapter-IV 152

21 Inference: From chart No. 4.8 it is observed that among the respondents 54.3 % of them are in graduate group and from the total sample, 36.8 % of the sample is in postgraduate group. Also, 05.3% of the sample belongs to under graduate group and 03.8% of the sample belong to ITI/Diploma group. Thus it is concluded that from the total sample more than half of them (54.3%) are from graduate group. Also 36.8 %of the respondents are in postgraduate group. Therefore minimum qualification of majority of the respondents is graduation which implies BPO jobs seekers must start their search after graduation Distribution of the sample as per area of work groups: Analysis of the respondents based on area of work groups is done and the results are given as follows: Table: No Distribution of the sample as per Area of work groups Area of work Number of respondents Percentage Financial Accounting Customer Services Procurement Human Resources Application Process Others Total Source: Survey Data Table No gives the grouping of the respondents as per their area of work groups. The six areas of work groups included in the sample are Financial Accounting, Customer Services, and Procurement, Human Resources, Application Process and Others. The number of respondents in each category is tabulated with their percentages. Chart: No. 4.9 Percentage distribution of Area of work groups Others 6.8% Application Process 16.8% Area of work Human Resource Procurement Customer Services 3.5% 10.3% 31.3% Financial Accounting 31.5% 0% 5% 10% 15% 20% 25% 30% 35% Percentage Chapter-IV 153

22 Inference: From chart No.4.9, it is observed that among the respondents31.5 % of them are in financial accounting group and from the total sample 31.3% of the sample is in customer services group. Also 16.8 % of the sample is from application processes group, 10.3% of the sample is in human resource group, 06.8% belong to Others group and 03.5% of the respondents is in procurement category. Thus it is concluded that from the total sample, majority (63%) of the respondents are chosen from the two important areas namely financial accounting and customer services groups Ranking of reasons for stress in the sample: Analysis of the reasons based on the ranks they scored in the survey is done and the results are given as follows: Table No.4.18 Ranking of reasons for stress Reasons Rank Long working hours 3.25 Working timings 3.75 Repetitive nature of work 4.06 Pressure to perform on metrics 4.80 Social isolation 6.24 Lack of quality of sleep 4.57 Lack of transportation 5.54 Stress due to verbal abuse 6.12 Travel time 6.67 Source: Survey Data Table No.4.18 gives the list of the reasons for stress to employees in BPO sector with their corresponding ranking. Chart No.10: Ranking of reasons for stress to BPO employees Rank Reasons Long w orking hours Work timings Repetitive nature of w ork Pressure to perform on metrics Social isolation Lack of quality of sleep Lack of transportation Stress due to verbal abuse Travel time Chart No.4.10 shows that the reason long working hours holds the rank 1, work timings is given rank 2 followed by the repetitive nature of work in the 3 rd rank position. The other ranks given by the respondents are 4 th rank pressure to perform on Chapter-IV 154

23 metrics, 5 th rank social isolation, 6 th rank lack of quality sleep, 7 th rank lack of safe and good transportation facility, 8 th rank stress due to verbal abuse and 9 th rank is travel time of respondents. Inference: It is inferred that long working hours is the primary reason for stress to BPO employees. Work timing is the second reason identified for stress to BPO employees. The third reason for stress is repetitive nature of work.the fourth reason identified for stress is pressure to perform on metrics. Social isolation stands as the fifth reason. The sixth reason identified is lack of quality sleep. Lack of safe and good transportation occupies the seventh position, eighth reason has been found as stress due to verbal abuse and finally travel time of respondents is identified as the ninth reason for stress to BPO employee Distribution of the respondents undergone training: Analysis of the respondents based on number of respondents undergone training and the results are given as follows: Table No.4.19 Distribution of respondents undergone training Opinion Number of respondents Percentage Yes No Total Source: Survey Data Table No.4.19 gives an account of number of respondents undergone training and their percentage. It also gives the number of respondents who have not undergone training. Chart No: 4.11 Percentage distribution of Respondents undergone training Percentage 91.50% 8.50% Yes No 85% 90% 95% 100% Opinion Chapter-IV 155

24 Chart No indicates that 91.5% of the respondents have undergone training and 08.5% of the respondents have not undergone training. Inference: It is found that majority of the respondents have undergone training programs Distribution of number of training programs undergone: Analysis of the respondents based on number of trainings undergone and the results are given as follows: Table: No.4.20 Distribution of number of training programs undergone Training groups No. of Respondents Percentage & Above Total Source: Survey Data Table No.4.20 shows the distribution of number of training programs undergone by respondents in the sample. It gives three numbers of training groups, the number of respondents in each category and their percentage. Chart: No.4.12 Percentage of training program undergone by respondents 15.30% 48.90% 35.80% & Above Inference: From the chart, it is found that15.3% of the respondents have undergone more than five training programs and 48.9% of the respondents have undergone 3-4 training programs. Also 35.8% of the respondents have undergone 1-2 training programs. Thus it is observed that nearly 84% of the respondents have undergone at least one training program, which Chapter-IV 156

25 shows that the BPO companies have made training programs mandatory for their employees Rating of the training programs undergone: Rating of the training programs effectiveness has been done and the results are given as follows: Table: No.4.21 Rating of training program effectiveness Grade/Opinion Number of respondents Percentage Poor Average Good Excellent Total Source: Survey Data Table No.4.21 gives an account of the rating of training programs effectiveness using the four grades namely excellent, good, average and poor. The number of respondents in each group has been tabulated with the percentage values. Chart No.4.13 Percentage distribution of rating of training program effectiveness 63.40% Percentage 70% 60% 50% 40% 30% 20% 10% 0% 27.0% 6.80% 2.70% Poor Average Good Excellent Opinion Inference: From the survey it is found that 63.4% of the respondents have rated the training program effectiveness as Good. 27% of the respondents have rated the training program effectiveness as Average and 02.7% of the respondents rated it as Poor. Chapter-IV 157

26 Since only 63 % of the respondents are happy with the effectiveness of the training programs, the quality of training programs is to be improved Distribution of maximum number of worked: Analysis of the respondents based on maximum number of hours worked is done and the results are given as follows: Table No.4.22 Distribution of maximum number of hours worked Number of hours groups Number of respondents Percentage 0 8 hrs hrs Above 12 hrs Total Source: Survey Data Table No.4.22 shows the distribution of number of hours worked by employees (respondents) and their percentage. There are 3 number of hours worked groups as 0 8 hours, 8-12 hours and above 12 hours group. Chart: No.4.14 Percentage distribution of the maximum number of hours worked 70% 60.80% 60% Percentage 50% 40% 30% 20% 10% 20.0% 19.30% 0 8 hrs hrs. Above 12 hrs. 0% 0 8 hrs hrs. Above 12 hrs. No. of hours Inference: From the chart, it is found that19.3% of the respondents have worked more than 12 hours and 60.8% of the respondents have worked for a period of 8-12 hours. Also 20% of the respondents have worked for a period of 0 8 hours. Chapter-IV 158

27 Therefore it can be found that maximum number of respondents has worked for a period of 8-12 hours. Therefore on an average the maximum number of hours worked by a BPO employee is more Distribution of opinion on level of satisfaction for strength factors: Analysis of the respondents based on opinion on level of satisfaction for the strength factors: high standards of corporate governance, exciting growth opportunities and company s work value and ethics is done and the results are given as follows: Table No.4.23 Distribution of opinion on level of satisfaction for strength factors Strength factors High standards of corporate governance Exciting growth opportunities Company s work value and ethics Source: Survey Data Very strongly agree Agree Opinion Partially agree Disagree TOTAL Number of respondents % Number of respondents % Number of respondents % Table No shows the distribution of opinion on level of satisfaction for the strength factors: high standards of corporate governance, exciting growth opportunities and company s work value and ethics. Chart No.4.15: Percentage distribution of level of satisfaction for strength factors Percentage 60% 50% 40% 30% 20% 10% 54.5% 25.3% 17.8% 2.5% 15.8% 38.3% 38.0% 8.0% 49.3% 27.0% 21.0% 2.8% 0% High standards of corporate governance Exciting growth opportunities Strength Factors Company s work value and ethics Chapter-IV 159

28 Chart No.4.15 indicates the percentage distribution of opinion on the level of satisfaction for each strength factor. For the factor high standards of corporate governance, it indicates that 25.3% of the respondents very strongly agree that there are high standards of corporate governance and 54.5% of the respondents agree that there are high standards of corporate governance For the factor, exciting growth opportunities, the chart indicates that 15.8% of the respondents very strongly agree that there are exciting growth opportunities and 38.3% of the respondents agree that there are exciting growth opportunities. Also, 38% of the respondents partially agree that there are exciting growth opportunities. For the factor, company s work value and ethics, the chart shows that 27% of the respondents very strongly agree that there is respect for company s work value and ethics and 49.3% of the respondents agree that there is respect for company s work value and ethics. Inference: From the opinion on high standards of corporate governance, it is found that overall 97.6% of the respondents agree that there are high standards of corporate governance in the organizations where they were working. Again for the same factor only 2.4% of the respondents have disagreed on there is high standards of corporate governance in the organization for which they are working. From the opinion on exciting growth opportunities, it is observed that overall 92.1% of the respondents agree that there are exciting growth opportunities in the organizations where they are working. Again for the same factor only 7.9% of the respondents have disagreed on there are exciting growth opportunities in the organization for which they are working. From the opinion on company s work value and ethics, it is observed that overall 97.3% of the respondents agree that there is work value and ethics in the organizations where they are working. Again for the same factor only 2.7% of the respondents have disagreed on there is work value and ethics in the organization for which they are working. Chapter-IV 160

29 Rating of Human Resource Management Practices: Rating of the Human Resource Management Practices has been conducted and the results are given as follows: Table No.4.24 Rating of Human Resource Management Practices Grade/Opinion Number of respondents Percentage of the total sample Excellent Good Average Satisfactory Poor Total Source: Survey Data Table No gives an account of the human resource management practices rating using the grades: Excellent, Good, Average, Satisfactory and Poor. The group Excellent has 32 respondents, Good has 180 respondents, Average has 129 respondents, Satisfactory has 43 respondents and the Poor group has 16 respondents. Chart No Percentage distribution of human resource management practices rating 50% 45.0% 40% 32.30% Percentage 30% 20% 10% 8.0% 10.80% 4.0% Excellent Good Average Satisfactory Poor 0% Excellent Good Average Satisfactory Poor Opinion Chart No shows that 45% of the respondents belong to the grade Good, 32.3% of the respondents belong to Average group, 10.8% of the respondents belong to the satisfactory group, 08% of the sample belong to the Excellent group and 04% of the sample belong to the Poor group. Chapter-IV 161

30 Inference: From the HRM practices rating, it is found that 08% of the respondents have rated HRM practices of their organizations as Excellent and 45% of the respondents has rated HRM practices of their organizations as Good. Therefore the HRM practices of the organizations have to improve for reducing high employee attrition. 4.4 DATA ANALYSIS BASED ON OBJECTIVES This section includes the testing of the hypotheses that were framed based on the set objectives and the results obtained. The analysis of the primary data obtained from questionnaire is conducted based on the set objectives and framed hypotheses and the results are summarized as follows: Objective: Variation in factors among different BPO areas The following hypotheses were framed to study the association between different BPO areas and proposed attrition factors : lack of integration and goal setting, motivation and appreciation, work atmosphere, labor welfare and corporate governance, maximum number of hours worked, dissatisfaction with rewards and hikes, human resource management practices, dissatisfaction with salary and perks, food and relaxation, lack of transportation and talent, work and family conflict, work from home and lack of work ethics. In each combination of BPO area and attrition factor, suitable hypotheses were framed and testing (ANOVA) of the hypotheses were done and the results are discussed as given below: Chapter-IV 162

31 Hypothesis 1.1: Lack of Integration and Goal Setting Vs BPO areas H0:1.1. There is no significant difference among the BPO areas in the average scores of lack of integration and goal setting. H1:1.1. There is significant difference among the BPO areas in the average scores of lack of integration and goal setting. Table: No Lack of Integration and Goal Setting Vs BPO areas Lack of integration and goal setting Financial Accounting Customer Services Area of work Procurement Human Resource Application Process Others Total Table: No.4.26 ANOVA for Lack of integration and goal setting Sum of Squares df Mean Square Between Groups * Within Groups Total F Sig. : One way ANOVA was applied to find whether there is significant difference among the area of work groups in the average lack of integration and goal setting scores. Since the calculated F-ratio value is higher than the table value at 5% level of significance, we reject the null hypothesis. Hence, it is inferred that there is significant difference among the area of work groups in the average lack of integration and goal setting scores. Chapter-IV 163