Reward Management: Analyzing External Pay Equity at P&G Singapore

This report analyzes the external pay equity of Procter & Gamble (P&G) in Singapore, focusing on determining the overall market variance weighted by employee demographics. The analysis includes descriptive statistics of the respondents' demographic characteristics and inferential statistics through six sub-sections: t-tests to assess gender and marital status differences, ANOVA using Duncan Multiple Range Test to relate quality of work life with demographics, chi-square tests to correlate quality of work-life with demographic factors, Friedman tests to identify differences in mean ranks, correlation analysis to measure the relationship between quality of work life and socio-psychological variables, and regression analysis. The report highlights salary structures for various roles within P&G, identifies jobs with inequity based on market ratio and compa-ratio, and explores potential causes for these disparities. T-test results are discussed to determine the difference between male and female employees with respect to socio-psychological factors of quality work life. The report concludes by noting that jobs with compa-ratios less than 0.9 indicate employees being paid approximately 10% less than the average company pay.

2019
[REWARD MANAGEMENT]

Table of content
Introduction 2
External Pay Equity 2
References 7

Introduction
The objective is to verify the external pay equity of an employee working for Proctor and Gamble in
Singapore by determining the overall market variance which is weighted by employee demographics.
To come up with a solution for proper analysis and interpretation of data is necessary. This is done
with analyzing the statistics of the respondent in terms of demographic characteristics. The second
analysis is done through inferential statistics. Six Sub-Sections are present while analyzing the later
(Hofmann, 2007). The six sub-section consist firstly of t-test, to find out the number of employees in
each of the gender, marital status, whether they are of technical nature or not, with regard to the
external pay equity. The second sub-section deals with the Analysis of Variance using Duncan
Multiple Range Test. Analysis of variance is done to get the relation between quality of work life with
that of the demographic variables. The third sub-sections deal with the chi-square test which tests the
quality of work-life with that of the demographic factors. Fried-Man test consists of fourth sub-
section, which is done to find out the difference between Quality work life and that of mean ranks of
employees. The Fifth consist of correlation which measures the relation between Quality work life
and that of the socio-psychological variable that stimulates an employee, which is followed by
regression analysis (Schanz and Schank, 2010).
External Pay Equity
The below table shows us the salary structure of an FMCG company operating in Singapore Procter &
Gamble (P&G). The Structure shows us the salary for three different years:-
Role Permanent salary in
SGD/Annum
2017 2018
MARKETING

Managing Director 180-240K 180-240K
Market Research Director 120-220K 120-220K
Marketing Manager 100-120K 100-120K
Brand Manager 85-100K 85-100K
Market Research Manager 80-120K 80-120K
Retail Operations Manager 80-100K 80-100K
Visual Merchandising Manager 80-100K 80-100K
Product Marketing Manager 70-120K 70-120K
Trade Marketing Manager 70-100K 70-100K
BUSINESS DEVELOPMENT
Sales and Marketing Director 180-240K 180-240K
Sales Director 160-240K 180-240K
Account Manager 140-200K 140-200K
Sales Manager 80-140K 100-140K
Business Development Manager 80-120K 80-120K
Key Account Manager 70-100K 80-100K
PUBLIC RELATION AND COMMUNICATIONS
Corporate Affairs Director 140-200K 140-200K
Public Relations Director 120-180K 120-180K
Digital Marketing Manager 80-160K 100-160K
Corporate Communication Manager 80-120K 80-120K
Public Relations Manager 70-120K 70-120K

Sub-Section 1- T-Test
A statistic which is descriptive in nature consists of five hundred employees (n=500). It is also known
as percentage analysis which deals to describe the sample in terms of demographic characteristics
such as technicality, gender, age, education qualification, nature of the job, marital status, department
and designation, total work experience, monthly income. The table below shows the different age
wise distribution of employee in Procter & Gamble (Martin, 2012).
AGE WiSE DISTRIBUTION OF EMPLOYEES
Age (in years) Frequency Percentage
Below 30 225 45%
31-45 175 35%
Above 45 100 20%
TOTAL 500 100
From the above table, we can notice that the majority of the workforce is below the age of 30. We
know the young and dynamic employees are required in FMCG sectors, those are able to understand
the market and has great knowledge about the consumers' taste and preference. We know that a
perfect combination of both senior and junior employees helps the organization reach its potential and
are able to accomplish the objectives set (Broadbent and Cullen, 2012).
Salary wise Distribution of Employees
Monthly Income (in SGD) Frequency Percentage
Below 10000 251 50.20%
10001-20000 154 30.80%

20001-30000 95 19.00%
TOTAL 500 100
The data mentioned in the table explains to us that more than 50% of employees earn below 10000
SGD/month and that between below 20000 but above 10000 is earned by 30% employee approx and
the remaining 19% earns in between 20000 and 30000. It is surprising to note that the majority of the
employee used in this study earns a salary below 10000 SGD. We can fetch the data for every
particular condition mentioned above. Only two are elaborated (Gitman, Joehnk, and Billingsley,
2013).
In the below table t-test is done to find out the difference between male and female employees with
respect to the variables present in Socio-Psychological factors of quality work life .
Socio-Psychological
factors
Gender Mean SD t value P value
Leadership Style of managers/team
leaders
Male 22.64 3.735
0.946 0.345
Female 22.95 3.514
Work Culture
Male 23.96 3.488
1.426 0.154
Female 24.41 3.447
Employee Attitude to Job
Male 22.29 3.338
0.832 0.406
Female 22.53 3.185
Occupational Self Efficacy
Male 24.10 3.412
0.657 0.511
Female 23.91 3.118
Employee Participation in Non-Work Related
Male 17.48 5.523 1.861 0.063
Female 18.35 4.900

Activities
Self-Concept
Male 24.81 3.107
3.101 0.002**
Female 23.97 2.934
Employee Perception of the Company
Male 11.67 2.118
2.540 0.011*
Female 12.10 1.663
Quality of Work-
Life
Male 58.00 8.096
0.734 0.013*
Female 57.46 8.369
Employee Satisfaction
Male 7.16 1.533
1.175 0.241
Female 7.31 1.325
Employee
Performance
Male 10.87 2.345
1.273 0.204
Female 11.13 2.208
**At 1% Level
*At 5% Level
From the above table, we can derive that the value of p is greater than 0.05 in Leadership Style, Work
Culture, Employee attitude, Occupational Self Efficiency, Employees participation in extracurricular
activities. Since the value of P is greater than 0.05, the acceptance of null-hypothesis is accepted at
5% level of significance. From the above analysis, we can conclude that there is no difference
between work culture, leadership style and employees attitude. When we see that the value of P is less
than 1%, the null hypothesis is rejected and we come to a conclusion that there is a difference between
male and female workforce with respectto socio-psychological factors prevailing in the quality work
life. With respect to mean it can be seen that the male employee score is 24.81 which is much more as

compared with that of female 23.97 with respect to self-concept. Thus it can be concluded that the
male has a higher self-concept as compared to the female workforce of the organization. The reason
for the same can be derived from the problem of upbringing, the culture and portrays us the difference
in submissive nature of the gender (Secrett, 2010).

Manager
5 salaries
2,000,000/yr₹
155K 3,000K₹ ₹
Assistant Manager
3 salaries
1,805,599/yr₹
1,298K 2,000K₹ ₹
Intern - Monthly
3 salaries
60,000/mo₹
50K 64K₹ ₹
Regional Manager
3 salaries
3,724,000/yr₹
2,554K 5,639K₹ ₹

Purchasing Manager
2 salaries
About
2,097K - 3,071K₹ ₹
2,097K 3,071K₹ ₹
Manager - Monthly
2 salaries
About
22K - 165K₹ ₹
22K 165K₹ ₹
Assistant Brand Manager
2 salaries
About
1,913K - 2,294K₹ ₹
1,913K 2,294K₹ ₹
IT Project Manager
2 salaries
About

387K - 2,081K₹ ₹
387K 2,081K₹ ₹
Operations Manager
2 salaries
oPERATIONS MANAbout
2,248K - 4,151K₹ ₹
2,248K 4,151K₹ ₹
Unit Manager (Sales)
2 salaries
About
2,019K - 2,919K₹ ₹
2,019K 2,919K₹ ₹
Consumer & Market Knowledge Associate Manager
2 salaries
About
908K - 2,344K₹ ₹
908K 2,344K₹ ₹
Senior Program Manager

2 salaries
About
2,229K - 4,172K₹ ₹
2,229K 4,172K₹ ₹
Associate Director
2 salaries
About
6,306K - 8,457K₹ ₹
6,306K 8,457K₹ ₹
Key Account Manager - Monthly
1 employee salary or estimate
About
79K - 85K₹ ₹
79K₹
There are three groups with compa ratio less than 0.9 percent ratio and this generates to the
fact that the employees in that group are paid around 10 percent less than the average
company pay.