Upload
sapyadkozam
View
220
Download
0
Embed Size (px)
Citation preview
8/8/2019 2007 Version of Yesu Project
1/63
1
EXECUTIVE SUMMARY
The study on productivity of insurance consultant and the reasons there off was
basically done to know various reasons which affect the performance of the
insurance consultant and to find the solutions to overcome those problems. In
the first half, the study started with introduction and review of literature could
contribute to a better sales performance. Salesmanship is not inherent, it is a
skill, which acquire with the help of training means it can be learned and
taught. In insurance field, salesmen require mastering in sales. The basic
characteristics identified in the literature as common to successful salespersons
are: empathy, enthusiasm, desire to grow, persistency, patience,
trustworthiness, and self confidence. Skills identified include interpersonal
skills, communication, organizational, product, and service knowledge.
Motivation plays a critical role in the success of a salesperson. The other half
of the report tells about the interrelation between variables which are affecting
the performance of consultants. This survey was conducted with the help ofwell structured questionnaire. The methodology which was adopted was a
direct interview. After collecting the data it was analyzed using statistical tool
called factor analysis. By knowing the clients perception one will be able to
improve their productivity.
Further this study helped me to know the drawback of insurance consultant and
solutions to overcome and also this study focused on finding important factors
for giving optimal training to the insurance consultant by the company.
Because insurance penetration and density in India is very low comparing to
other developed and developing countries and positively Indian insurance
making 20% growth this is much more than developed countries. So this study
will help insurance consultants to improve their productivity and also helpful
for company to provide lead training
8/8/2019 2007 Version of Yesu Project
2/63
8/8/2019 2007 Version of Yesu Project
3/63
3
1.1 Introduction
The strategic goal of sustaining a market share or gaining competitive
advantage depends on effective selling skills. This skill is continuous
development in process. Companies adopt different type of effective selling
techniques according to environmental change and needs. It includes the need
of continuous improvement as consumers are more informed today than in the
past. Insurance products are different from other products. It is intangible, so
sales people face a lot of difficulties for selling insurance products. Here
effective selling skills are needed to be successful. Today Insurance Industry
faces a big problem of active insurance consultants. Company either terminates
the relationship or the consultants leave voluntarily because of insufficient
income.
This separation occurs in life industry after six month (due to licentiate
examination and training process). Company and consultants magnify the
implication of this separation in wasted resources in opportunity cost during the
engagement period. Insurance consultant is front liner, who is only a personwho directly contacts with customers.
Consultants do this work as a mediator between customer and company. It
means The agent is located at the place in the organization at which the
company financial security policy and plan are distributed to customers and
also at the place at which services are directly provided to the customer. Agent
provides such types of service in term of consultancy i.e. to make help in
financial planning strategies. Insurance is relationship business. Relationship
and emotion is the key of success in selling. People purchase insurance
because they love their family. It is humantendency that people agree/purchase
from such type of person who is trustworthy. Like and trust is the key in
insurance business. Due to this reason brand and price are insignificant when
client make a buying decision. It is seem that often people do not know much
8/8/2019 2007 Version of Yesu Project
4/63
8/8/2019 2007 Version of Yesu Project
5/63
5
To find where was problem or identify problem/challenges faced by consultant.
Set questionnaire according to problem.
In this project, two type of data were used: a) Primary Data b) Secondary Data.
With the help of interview and questionnaire primary data were collected for
finding actual and realistic problems and their solutions. Secondary data were
collected from books and Internet to go in depth of topic.
8/8/2019 2007 Version of Yesu Project
6/63
6
1.2 Literature review
In this process one can understood, how insurance is different from other
products, why sales persons fail to sell insurance. And also realized during this
process that motivation, behavior, characteristics and training factors affect
man power and its ability, how to generate lead and convert into sales, how
sales performance can be increased.
Mostly people think that seller skill is inherent, but it is not correct. It can be
achieved with the help of training and practices. When a person does more
practice and gets mastered in such skill, it seems easy and natural. Professional
salesmanship is a learned skill. Insurance sales are more complicated to general
sales. Insurance consultant cannot show insurance product, he can only
describe benefit with the help of verbal and non-verbal language. In this
process he plays with another emotion and sentiment. If he wins in this game
then he will be successful in selling and vice-versa.
Insurance is not purchased it is sold. Here consultant faces difficulty.
Consultant has had to do a lot of work for successful selling, such as to whom
he is to sell (prospective client), turn prospective client to customer. Only
insurable person can take insurance, so he has had to do segmentation and
targeting type of work also.
With the help of lead generation advisor can find prospective customer. There
are several methods to lead generation such as cold calling. Cold calling can be
a successful way to lead generation. If it is done with planning: for example
how to cold call, when to cold call, and how much cold call to make every day
in order to get appointment Public relation is also great way to expose in
market. Consultant can do it with the help of trade show or he can make public
relation with the help of promotional activity. The real key of public
relationship is to be friendly and focus on meeting, not selling product. Many
of the most difficult sales jobs are easy to obtain (i.e. selling specialty product
such as house hold, hardware, life insurance or encyclopedias). They have also
8/8/2019 2007 Version of Yesu Project
7/63
7
been graveyard of thousand of co-worker (Baker 1994). It means after a
minimum qualification and passing IRDA Licentiate examination, any one are
eligible to sale insurance policy. Due to this reason alteration rate is very high
in insurance industry. But now insurance companies are concentrating on other
distribution channels such as, bancassurance, Internet, NGOs, micro
insurance. Now insurance companies are concentrating on training program
and they recruit eligible candidate for executive trainee or other post (i.e.
PGPMI). Selling skill can be developed such type of skill with the help of
practice, practical training and experience.
Behavior style and interpersonal effectiveness is also important in selling.People fit into four categories. Insurance products can be sold to them in
different ways. Interpersonal effectiveness helps to understand in what way an
individuals mind works and his level of interest in a particular product /policy
which may act as guideline for the best way to approach sell for each category
developed in two ways: formal training and sales experience gained through
exercising the selling job over time. In formal training people know about
product and services, which help him to explain, what he has for other.
Secondly formal training is base of advisor carriers. In formal training people
know which type of skill is required for effective selling and they approach
each category in effective way.
Life insurance products are inherently more difficult to sell compared to other
kinds of products. Agents who are deficient in required characteristics and
skills are unable to sell successfully and consequently they are forced to leave
the company.
Although some of these characteristics may be developed through lifetime, the
skills could be taught and learned by insurance consultant can improve their
productivity.
8/8/2019 2007 Version of Yesu Project
8/63
8
Unique Attributes of Successful Salespeople
Characteristics and Traits
Trustworthiness
Self-confidence
Enthusiasm
Empathy
Desire to grow and improve self
Patience
Motivation for Sales Career
Unlimited income
Time autonomy
Recognition and power
Personal satisfaction
Selling Skills
Interpersonal skill
Communication
Organization
Profiling clients and prospecting
Planning meetings in advance
Presentation
Product and service knowledge
Information about companys products and services
8/8/2019 2007 Version of Yesu Project
9/63
9
Chapter -2
OBJECTIVE AND RESEARCH
METHEDOLOGY
8/8/2019 2007 Version of Yesu Project
10/63
10
Research Methodology
2.1 Objectives:-
Main objective:-
Find out the reasons which are affecting the performance of the insurance
consultant and the solutions to overcome those problems in order to boost their
performance.
Specific objectives:-
1) Find out the level of relationship between different variables andexploring the reasons for such a relation.
2) Identifying the different set of insurance consultants in Bajaj Allianz
based on their characteristics and performance.
3) Find out the important factors among all variables which are affecting
the productivity of consultant
2.2 Procedure:-
The procedure followed, is enlisted below:
Studying the topic
Decision on objective needed to be work on i.e. conduct interview with
insurance consultant and sales manager.
Developing Survey instruments
Getting questionnaire filled through interacting with different branches of bajaj
Allianz consultants in Chennai.
Finally analyzing the data of various areas and trying to study about various
influence factors such as behavior, which is important in sells.
8/8/2019 2007 Version of Yesu Project
11/63
8/8/2019 2007 Version of Yesu Project
12/63
12
research will cover many variables even one of the variable affected by
respondent bias or other factors it will substituted by the other variables at
finally on an average this will give effective output.
2.5 Data collection
Awareness/Knowledge:
They are used in marketing research refers to what respondents do or do not
knowabout the effective selling style.
Motivation:
Through questionnaire have tried to find the hidden need or want of an
individual and have tried to find out that which factor increases satisfaction and
productivity of insurance consultant.
Behavior:
Behavior concerns what subjects have done or are doing. Through made
questionnaire we have tried to find out the behavior of the individualsregarding
Do you keep attention on client non-verbal response during sells meeting?
Do you update yourself?
Thus, it helps to draw a comparison between the selling style and the observed
behavior of the advisor.
Obtaining the Primary Data:
The data collection was primarily through communication. Communication
involves questioning respondents to secure the desired information, using a
data collection instrument called questionnaire. The questions were in writing
and so were the responses.
Secondary data search
8/8/2019 2007 Version of Yesu Project
13/63
13
The first of Research consisted of secondary data search from the following
sources:
Books
Websites
For the conclusive research, questionnaires been developed on basis of
secondary data and interview from insurance personal to gather information on
the research
The final draft of the questionnaire (see Appendix) was then prepared on the
basis of extensive study on insurance sector and discussions with consultants
and sales manager. These then finally filled by 50 consumers, for the
conclusive study.
2.6 Data collection methods:-
Survey: - conducting survey for data collection by using closed and open
ended questionnaire from the sample or primary sources (insurance consultantsand sales managers)
Interview method:- using open ended questions for conducting unstructured
face-to-face interview with the sample.
Field work plan
Some of the respondents are identified with in the office and other respondents
are identified by taking address of them from the company, sales managers will
help to find out consultants who are working under them.
8/8/2019 2007 Version of Yesu Project
14/63
14
2.7Analysis plan:-
Analysis based on answers given to the questions, by using various suitable
statistical techniques data will be analyzed with SPSS software and ms-excel.
Chi-square and ANOVAs for test the confidence level of the variables
Correlation is to find out the type of the relation like positive, negative or zero
relation
Factor analysis for Identifying most appropriate factors which are affecting
mostly the performance of the consultant
Cluster analysis is used to grouping the respondents based on common
variables among them
2.8. Limitations of the study:-
1) The sample population statistics may vary from the total population.
2) Even though it was explained that the survey was purely for academic
purposes many of them are afraid to reveal their actual performance.
8/8/2019 2007 Version of Yesu Project
15/63
8/8/2019 2007 Version of Yesu Project
16/63
16
3.1 Industry profile
The insurance sector in India has come a full circle from being an open
competitive market to nationalization and back to a liberalized market again.
Tracing the developments in the Indian insurance sector reveals the 360-degree
turn witnessed over a period of almost 190 years. The business of life insurance
in India in its existing form started in India in the year 1818 with the
establishment of the Oriental Life Insurance Company in Calcutta.
Insurance sector growth is measured in two criteria in a country
I. Insurance penetration = premium/GDP*100
The value for India is 4.10, the value for Asia is 5, and the value for World is
4.5.
II. 2. Insurance density = premium holder/total population*100
The value for India is 33.2, the value for Asia is 154.6, and the value for World
is 330.6
These figures show that insurance in India still in infant stage there is great
headroom to insurance sector in India.
Compared to developed and industrialized countries, India is at the lower end
of the spectrum when it comes to penetration of the market. However has a
young demographic profile; nearly two thirds of the population is under 30. Yet
about 10 percent of the population is above 60. This portion is expected to risesharply. By 2030, the Indian population is expected to rise sharply. By 2030,
the Indian population is expected to stabilize at 1.1 billion, about 20 percent of
which will be over 60. Therefore, a great potential for the insurance industry
lies in providing support for this segment of the populace i.e. over 220 million
senior citizens.
While LIC is the is the sole operator in the public sector, the following is the
list of private companies in the Life Insurance Sector in India
8/8/2019 2007 Version of Yesu Project
17/63
17
LIFE INSURERS COMPANIES IN INDIA:-
ICICI Prudential Life Insurance, HDFC Standard Life, SBI Life Insurance,
Birla Sun life, Bajaj Allianz Life, Aviva Life Insurance, Kotak Mahindra Life
Insurance, Tata AIG Life, Reliance Life Insurance Company Limited (formerly
known as AMP Sanmar LIC), ING Vyasya Life Insurance, MetLife India Life
Insurance, Max New York Life Insurance, Shriram Life Insurance, Bharti AXA
Life Insurance Company Limited
Life insurance sector in the red in 2007-08
Profits (losses) of life insurance cos
2007-08
cr
2006-07
cr
Birla sun life -445 -140
ICICI prudential -1395 -694
ING vysya -191 -178
HDFC standard -244 -126
Max new York life -257 -60
Reliance life -768 -315
Bajaj Allianz -297 -72
SBI life -34 4
Kotak Mahindra -72 -110Tata AIG -339 -72
Metlife 21 -12
AVIVA -202 -132
Sahara 3 -1
Shriram life 5 10
Bharti AXA -242 -80
LIC 845 774
Future generali -30 -3
IDBI fortis -26 _
Total -3600 -1162
The life insurance sector in the country is in the red, going by the figures
released by the Insurance Regulatory and Development Authority in it annual
report for 2007-08.The largest losses were posted by ICICI-Prudential Life
Insurance at Rs 1,395 crore and Reliance Life at Rs 768 crore during 2007-
08.The public sector giant, LIC managed to post a modest growth in profits at
Rs 845 crore in 2007-08 compared with Rs 774 crore in 2006-07.
8/8/2019 2007 Version of Yesu Project
18/63
18
The general insurance sector fared better than the life sector, although profits
were down by 80 per cent for the private sector players. Profits of 10 private
players were down to Rs 44 crore in 2007-08 compared with 228 crore in 2006-
07. The biggest loss among private players as well as the industry was posted
by Reliance General Insurance at Rs 165 crore. The four public sector
insurance companies saw their combined profits come down by about 24 per
cent to Rs 2,205 crore. While three of them saw their profits declining, United
India Insurance managed to buck the trend and post a 19 per cent growth in
profits during 2007-08
Even though 2007-08 is bad experience to many private insurance companies,2008-09 is giving good results for many companies noted profits and running
in good progress.
3.2 Company profile
Bajaj Allianz Life Insurance Company Limited is a Union commit Between
Bajaj Auto Limited, an of the largest 2 - & - 3 wheeler manufacturers in the
world and Allianz AG, world largest life insurance (formerly Allianz Bajaj Life
Insurance Company Limited).
Allianz SE is a prominent world-wide conglomerate insurance and one of the
largest asset managers in the world, the management of active to value of more
than a Trillion Euro (more than R. 55,00000 cores). Allianz SE has more than
115 year of the financial experience in more than 70 countries. Bajaj Car is one
of the most familiar name is Indian car for more than 55 year. On Bajaj
Allianz customer joy is our guide. See to world-class solutions through the
offering of adapted products with transparent advantages, supported by the best
technology is the philosophy of Bajaj Allianz.
8/8/2019 2007 Version of Yesu Project
19/63
8/8/2019 2007 Version of Yesu Project
20/63
20
Unmatched flexibility to meet changing lifestyle and insurance
requirements.
Bajaj Allianz new unit gain super
Insure fully and get MAX allocation along with a host of additional benefits to
choose from a flexible unit linked plan that allows partial & full withdrawal
after 3 years.
Additional benefits:
UL Accidental Death Benefit and UL Disability Benefit.
UL Critical Illness Benefit and UL Hospital Cash Benefit.
4 funds to choose from & flexibility to pay top-up any time
New unit gain/ fortune plus
Fortune plus have formulated as a unique combination of protection and
prospective of attractive returns with investment in various mix of securities to
make a perfect plan.
Some of the key features of this plan
Guaranteed life cover, with a flexibility to insurance cover according to
client needs
More than 100% allocation after first 10 years of company association
Flexibility of with drawls (partial or full)
Get maturity value equal to the fund value at the time of maturity or in
periodic installment spread over a maximum period of 5 years
Option to increase or decrease customer regular premium to get a
portfolio that suits to their needs
A host of optional additional benefits, which ensures enhanced
assurance to customer family.
Opportunity to make additional investments
Flexibility to switch money from one fund to other to manage
investment better.
8/8/2019 2007 Version of Yesu Project
21/63
21
Chapter -4DATA ANALYSIS AND
INTERPRETATION
8/8/2019 2007 Version of Yesu Project
22/63
22
Frequency analysis:- Table 1:-importance of basic characteristics
most important important neutral unimportant
communication skill 42 8
Network 27 20 3
soft skills 28 17 4 1
Confidence 37 13
Hardworking 29 19 2
Experience 21 20 7 2
Above table shows that importance of each characteristic using likert scale
given by insurance consultants of the Bajaj Allianz. This is just their
psychological importance which may not give same importance in real life
practice. Even though they are not having those skills this likert scale
presenting their mental importance to acquire each.
From the above table it is obvious to find that communication skill is most
important among all and next is confidence of the consultant.
Ranking of the each characteristic was given by using data from table
1. Communication skill
2. Confidence
3. Hardworking
4. Network
5. Soft skills
6. Experience
8/8/2019 2007 Version of Yesu Project
23/63
23
Insurance consultants who have good communication skills and doing hard
work would have successful career than other because communicational skill
can bring confidence and can increases the net work so those will succeed
irrespective of experience thats way experienced ranked least even though it is
important in insurance sector.
4.2. Percentage of the differentFactors which keeping away from success
Table 2:-Factors which keeping away from success
This table explains the frequency and percent of each variable which affecting
negatively the performance of the insurance consultant. From the table it found
that nearly 60 percent of the insurance consultant performance badly affected
by two variables is lack of communication skills and lack of network.
There are only 20% people dont have any drawback and remaining 80%
people have at least one drawback so it is better to continue training classes on
developing communication skill along with product knowledge this ultimately
leads to increase their network.
9 18.0 18.0 18.0
16 32.0 32.0 50.0
4 8.0 8.0 58.0
5 10.0 10.0 68.0
4 8.0 8.0 76.0
10 20.0 20.0 96.02 4.0 4.0 100.0
50 100.0 100.0
50 100.0
lack of
communication
skills
lack of network
lack of
confidance
lack of efforts
lack of knoledge
not applicablemore than one
Total
Valid
Total
Frequency Percent
Valid
Percent
Cumulative
Percent
keeping away from success
8/8/2019 2007 Version of Yesu Project
24/63
24
Cross tabulation:-
4.3. Comparison between salary of consultant with his/her qualification.
Table 3:-cross tabulation between qualification and salary of consultant
The above table represents the range of salary with respect to the qualification
of the insurance consultant. Most of the consultants has completed their
graduation in BA, BBA, Bcom AND Mcom.
People from science and technology back ground are not preferring to work as
a consultant or sales manager they have other opportunities so from this we can
deduct that people who dont has better other opportunities are only preferring
to work as consultant, this field still suffering to attract other higher educated
people.
Count
1 1 2
6 7 13
1 1 1 3
1 3 5 9
8 9 2 19
1 3 4
2 21 23 4 50
btech or
BE
bcom or
BBA
Bsc
BA
PG
+2
highest
qualification
Total
less than
1 lac 1 to 2 2 to 3 3 to 4
salary or commission for last year
Total
highest qualification * salary or commission for last year Crosstabulation
8/8/2019 2007 Version of Yesu Project
25/63
25
Frequencies
4.4 Measuring the achieved skills of consultants in Bajaj Allianz
Table 4:- The level of capacities achieved by consultant for eachcharacteristic.
Interpretation of the table
This table explains the level of capacities of characteristic like learning
capacity, emotional intelligence, intelligent quotient, convincing power and
degree of satisfaction in terms of percentages.100 is the complete achievement
of the characteristic, and through this we can measure the level of their
achievement hope to improve.
Percentage 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
learning
capacity 0 0 0 2 4 4 4 15 13 8
emotional
intelligence 0 1 3 0 2 7 8 13 9 7
intelligent
quotient 0 0 1 3 5 9 9 8 7 8
convincing
power 1 0 1 6 2 3 6 6 14 11
degree of
satisfaction 0 0 0 0 4 1 3 14 10 18
total 1 1 5 11 17 24 30 56 53 52
average 0.2 0.2 1 2.2 3.4 4.8 6 11.2 10.6 10.4
8/8/2019 2007 Version of Yesu Project
26/63
26
In the first row there are values with an interval of 10 up to 100, complete
achievement of any characteristic showed as 100 percent 10 percent shows
1/10th
of their actual capacity there is a scope to improve nine times
accordingly remaining values.
In last row representing the average number of the sample falling under its
respective percentages, by observing it last three columns there are 32 people
achieved up to 80 to 100 percent of each characteristic.
Degree of satisfaction has more number of consultants than other this shows
most of the employees of bajaj Allianz are satisfied very well and next big
value is convincing power this shows people who have more convincing power
also have more satisfaction levels.
Average of the last column is 10 is approximately 20 percent of the sample and
also equal number people achieved completeness in learning capacity and
intelligent quotient because generally people who have more learning capacity
also have good intelligent quotient.
Among all most of all little bit suffering to achieve completeness in emotional
intelligence if company concentrating on to improve it this definitely helpful to
consultants to increase their performance.
The scope of improvement in capacities of the insurance consultant less than
expected through training because more than 75 percent people are already
agreed they achieved more 70 percent of their actual capacity so there is only
1/4th people only have scope to improve nearly double of their present
performance.
8/8/2019 2007 Version of Yesu Project
27/63
27
4.5 Correlation: relationship among variables
1.000 -.014 .244 -.156 .226 .041 .303* .065 -.028 .088 -.128
-.014 1.000 .017 .026 -.075 .128 -.137 .165 .093 .247 .093
.244 .017 1.000 .016 .476** .235 .400** .018 -.195 -.290* .245
-.156 .026 .016 1.000 -.004 -.104 .063 .048 -.029 -.093 .003
.226 -.075 .476** -.004 1.000 .222 .394** .015 -.222 .051 .262
.041 .128 .235 -.104 .222 1.000 .756** -.097 -.311* -.037 -.162
.303* -.137 .400** .063 .394** .756** 1.000 .037 -.209 -.107 -.013
.065 .165 .018 .048 .015 -.097 .037 1.000 -.010 .106 .100
-.028 .093 -.195 -.029 -.222 -.311* -.209 -.010 1.000 .088 -.030
.088 .247 -.290* -.093 .051 -.037 -.107 .106 .088 1.000 -.030
-.128 .093 .245 .003 .262 -.162 -.013 .100 -.030 -.030 1.000
. .920 .087 .278 .115 .778 .033 .653 .847 .545 .374
.920 . .907 .857 .603 .374 .343 .252 .521 .083 .520
.087 .907 . .911 .000 .100 .004 .900 .174 .041 .087
.278 .857 .911 . .980 .472 .665 .742 .843 .521 .981
.115 .603 .000 .980 . .122 .005 .920 .121 .727 .066
.778 .374 .100 .472 .122 . .000 .503 .028 .800 .260
.033 .343 .004 .665 .005 .000 . .797 .145 .458 .928
.653 .252 .900 .742 .920 .503 .797 . .945 .464 .490
.847 .521 .174 .843 .121 .028 .145 .945 . .541 .834
.545 .083 .041 .521 .727 .800 .458 .464 .541 . .834
.374 .520 .087 .981 .066 .260 .928 .490 .834 .834 .
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
number of
calls per d
net work
flexible
working ho
highestqualificatio
wealthmaximisati
convincing
power
emotional
intelligent
quotient
market upand statisti
analysis
confidence
experience
backgroun
number ofcalls per d
net work
flexibleworking ho
highestqualificatio
wealth
maximisati
convincing
power
emotional
intelligentquotient
market upand statisti
analysis
confidence
experience
backgroun
number of
calls per d
net work
flexible
working ho
highestqualificatio
wealth
maximisati
convincing
power
emotionalintelligent
quotient
market up
and statisti
analysis
confidence
experience
backgroun
Pearson
Correlatio
Sig.(2-tailed)
N
umber ocalls per
day net work
flexibleworking
hours
highest
ualification
wealth
aximisatio
onvincing
power
motionalintelligent
quotient
market
updateand
tatistical
analysis onfidenc xperienceackground
Correlations
Correlation is significant at the 0.05 level (2-tailed).*.
Correlation is significant at the 0.01 level (2-tailed).**.
8/8/2019 2007 Version of Yesu Project
28/63
28
Table of correlation was placed in annexure due to its big size.
The values in the correlation table are standardized and ranging from 0 to 1.
Variables ranging from 0.73 to 0.95 are highly correlated.
Number of calls per day 0.92 correlated with building network.
Flexible working hours 0.9 correlated with network.
Educational qualification 0.85 correlated with building network.
So from the above correlation values building network is directly related to
number calls dialed by consultant, flexible working hours provided by
company and educational qualification of insurance consultant.
Educational qualification is 0.91 directly related with flexible working hours
Educational qualification is 0.98 directly related with wealth maximization of
the company. This shows that people who have higher qualification are
preferred work in insurance sector when there is a flexible working system and
also they try to work on long term wealth maximization not on short term
profits.
Statistical analysis and market update have 0.946 correlations with confidence
Statistical analysis and market update have 0.92 correlations with wealth
maximization.
Statistical analysis and market update have 0.968 correlations with mode of
communication with client.
From the above relations one can deduct that people who are doing regular
update and market analysis are more confident than others and they can create
more wealth to the company. Back ground of consultant means he/she from
rural or urban can determine the some of the aspects like emotional quotient
0.93, availability to the client in the time of need have 0.92 correlation with
back ground of the consultant.
8/8/2019 2007 Version of Yesu Project
29/63
29
Convincing power and communication skill have a good positive correlation
0.938 this shows that obviously people who have good communication skills
can easily convince the clients than others.
One way- ANOVA analysis
4.6 Gender can decide the salary range of the insurance consultant
Table 5 :-significance of gender on salary.
Input
Independent variable: gender (nominal)
Dependent variable: salary (interval)
Null Hypothesis
Gender cant decide the salary range of the insurance consultant
The null hypothesis for this problem can be expressed as
H0 D1=D2; Where D1,D2 are the gender 1 for male,2 for female
Our group tested at 95% confidence level whether any of the above mentioned
nominal variables is being decides the salary range of the insurance consultant.
Analysis of out put
From the out table of one-way ANOVA, in the last column the significance of
the F-test is found to be 0.017. This indicates that at a confidence level of 95
percent. The F-test proves the model is significant. In other words the gender
2.738 1 2.738 6.130 .017
21.442 48 .447
24.180 49
Between
Groups
Within
Groups
Total
salary or
commission
for last year
Sum of
Squares df
Mean
Square F Sig.
ANOVA
8/8/2019 2007 Version of Yesu Project
30/63
30
can decide the salary range of the insurance consultant. So our null hypothesis
is rejected.
4.7 Qualification can also decide the salary range of the insurance
consultant
Table 6:-significance of qualification on salary
Input
Independent variable: qualification (nominal)
Dependent variable: salary (interval)
Null Hypothesis
Qualification cant decide the salary range of the insurance consultant.
The null hypothesis for this problem can be expressed as
H0 D1=D2; Where D1,D2 are the scale of the qualification.
Our group tested at 95% confidence level whether any of the above mentioned
nominal variables is being decides the salary range of the insurance consultant.
Analysis of out put
From the out table of one-way ANOVA, in the last column the significance of
the F-test is found to be 0.044. This indicates that at a confidence level of 95.6
percent. The F-test proves the model is significant. In other words qualification
can also decide the salary range of the insurance consultant. So the null
hypothesis is rejected.
5.372 5 1.074 2.513 .044
18.808 44 .427
24.180 49
Between
Groups
WithinGroups
Total
salary or
commission
for last year
Sum of
Squares df
Mean
Square F Sig.
ANOVA
8/8/2019 2007 Version of Yesu Project
31/63
31
4.8 Family size of the consultant is trouble to quit the job or exchange to
other job
Table 7:-significance of experience with size of the consultant family.
Experience as insurance consultant or sales manager * size of the family
1 1 2
50.0% 50.0% 100.0%
4 10 2 16
25.0% 62.5% 12.5% 100.0%
1 13 14
7.1% 92.9% 100.0%
6 5 1 12
50.0% 41.7% 8.3% 100.0%
2 4 6
33.3% 66.7% 100.0%
14 32 4 50
28.0% 64.0% 8.0% 100.0%
Count
% within
experience
as ic or sm
Count
% within
experience
as ic or sm
Count
% within
experience
as ic or sm
Count
% within
experience
as ic or sm
Count% within
experience
as ic or sm
Count
% within
experience
as ic or sm
below one
year
1 to 3
years
3 to 5
years
5 to 10
years
more than10 years
experience
as ic or sm
Total
1 to 3 4 to 6
more than
7
size of the family
Total
Crosstab
15.173a
8 .056
15.945 8 .043
1.973 1 .160
50
Pearson
Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asymp.Sig.
(2-sided)
Chi-Square Tests
12 cells (80.0%) have expected count less than
5. The minimum expected count is .16.
a.
8/8/2019 2007 Version of Yesu Project
32/63
32
This test can link what insurance consultants size of the family with his /her
experience in field.
Input data:-
This test is attempting to find out the relationship between independent variable
(size of the family) and dependent variable (experience).
Null hypothesis
Family size of the consultant is never trouble to quit the job or exchange to
other job.
Explanation of output:-
The value of the pearson chi-square test clearly states that there is a significant
relationship between dependent and independent variable.
The chi-square test is carried out at a 90 percent confidence level (equivalent to
100-90 divided by 100 or 0.1 significant level which is more than obtained
significance 0.056).
There is 94.4 percent significance between the variables Family size of the
consultant is causing trouble to his/her profession to quit the job or exchange to
other job so the null hypothesis is rejected. That means consultants from big
family have lower experience than people from medium size families if
company want to recruit a employees for longer use seeing their family size
also will be a clue to estimate their adaptability.
From the table we can see that people have a family size 4 to 6 will have on
average of 3 to 5 years experience in this field in particular company. people
from smaller families are also have more experience than all.
8/8/2019 2007 Version of Yesu Project
33/63
33
4.9 Salary of the insurance consultant depending on the their experience
Table 8 :-significance of experience on salary
This test can link insurance consultants salary with his /her experience in the
field.
Null hypothesis
Salary of the insurance consultant doesnt depending on the their experience
Input data:-
This test is attempting to find out the relationship between independent variable
(experience) and dependent variable (salary).
2 2
100.0% 100.0%
2 10 4 16
12.5% 62.5% 25.0% 100.0%
4 9 1 14
28.6% 64.3% 7.1% 100.0%
5 6 1 12
41.7% 50.0% 8.3% 100.0%
4 2 6
66.7% 33.3% 100.0%
2 21 23 4 50
4.0% 42.0% 46.0% 8.0% 100.0%
Count
% within
experience
as ic or sm
Count
% within
experience
as ic or smCount
% within
experience
as ic or sm
Count
% within
experience
as ic or sm
Count
% within
experience
as ic or smCount
% within
experience
as ic or sm
below one
year
1 to 3
years
3 to 5
years
5 to 10
years
more than
10 years
experience
as ic or sm
Total
less than
1 lac 1 to 2 2 to 3 3 to 4
salary or commission for last year
Total
experience as ic or sm * salary or commission for last year Crosstabulation
8/8/2019 2007 Version of Yesu Project
34/63
34
Explanation of output:-
The value of the pearson chi-square test clearly states that there is a significant
relationship between dependent and independent variable.
The chi-square test is carried out at a 90 percent confidence level (equivalent to
100-90 divided by 100 or 0.1 significant level which is more than obtained
significance 0.052).
There is 94.8 percent significance between the variables, by the experience
insurance consultants are earning more that means Salary of the insurance
consultant depending on the their experience so the null hypothesis is
rejected.
20.913
a
12 .052
23.495 12 .024
13.151 1 .000
50
Pearson
Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asymp.
Sig.
(2-sided)
Chi-Square Tests
14 cells (70.0%) have expected count less than
5. The minimum expected count is .08.
a.
8/8/2019 2007 Version of Yesu Project
35/63
35
Chi-square test:-
4.10 Null hypothesis
There is no significant relationship between salary of consultant and their
perception on customer satisfaction.
Input data:-
This test is attempting to find out the relationship between independent variable
(customer satisfaction) and dependent variable (salary or commission).
Customer satisfaction * good package
Table 9 :-significance of customer satisfaction on good package
Explanation of output:-
The value of the pearson chi-square test clearly states that there is a significant
relation ship between dependent and independent variable.
The chi-square test is carried out at a 90 percent confidence level (equivalent to
100-90 divided by 100 or 0.1 significant level which is more than obtained
significance 0.061) so the null hypothesis is rejected.
20.311a
12 .061
16.955 12 .151
4.279 1 .039
50
Pearson
Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asymp.
Sig.
(2-sided)
Chi-Square Tests
18 cells (90.0%) have expected count less than
5. The minimum expected count is .10.
a.
8/8/2019 2007 Version of Yesu Project
36/63
36
From this explanation it can be deducted that insurance consultants who are
much concern about customer satisfaction could earn more than other
consultants.
4.11 Training given by the Bajaj Allianz Company motivating the
employees
Null hypothesis
Training given by Bajaj Allianz Company shouldnt motivating the employees
to improve customer satisfaction approach.
Input data:-
This test is attempting to find out the relationship between independent variable
(customer satisfaction) and dependent variable (training).
Table 10:- significance customer satisfaction with training
Customer satisfaction * number of hours attending for training per month
Explanation of output:-
The value of the pearson chi-square test clearly states that there is a significant
relationship between dependent and independent variable.
21.099a
12 .049
17.900 12 .119
.719 1 .397
50
Pearson
Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asymp.
Sig.
(2-sided)
Chi-Square Tests
18 cells (90.0%) have expected count less than5. The minimum expected count is .20.
a.
8/8/2019 2007 Version of Yesu Project
37/63
37
The chi-square test is carried out at a 90 percent confidence level (equivalent to
100-90 divided by 100 or 0.1 significant level which is more than obtained
significance 0.049).
There is a 95.1 percent significance between the variables so the null
hypothesis is rejected.
From this explanation it can be deducted that insurance consultants who
undergone through more Training given by the Bajaj Allianz Company
motivating the employees to improve their customer satisfaction approach.
4.12 Find out the relationship between customer satisfaction and flexible
working hours.
Null hypothesis
Flexible working hours provided by the Bajaj Allianz Company to the
insurance consultants and sales managers shouldnt motivating them to
improve their customer satisfaction approach.
Input data:-
This test is attempting to find out the relationship between independent variable
(customer satisfaction) and dependent variable (flexible working hours).
8/8/2019 2007 Version of Yesu Project
38/63
38
Table 11:-significance of customer satisfaction with flexible working
hours.
Customer satisfaction * flexible working hours
Explanation of output:-
The value of the pearson chi-square test clearly states that there is a significant
relationship between dependent and independent variable.
The chi-square test is carried out at a 90 percent confidence level (equivalent to
100-90 divided by 100 or 0.1 significant level which is more than obtained
significance 0.029).
There is 97.1 percent significance between the variables so the null hypothesis
is rejected.
From this explanation it can be deducted that flexible working hours provided
by the Bajaj Allianz Company to the insurance consultants and sales managers
should motivating them to improve their customer satisfaction approach.
26.921a
15 .029
27.607 15 .024
4.044 1 .044
50
Pearson
Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asymp.
Sig.
(2-sided)
Chi-Square Tests
22 cells (91.7%) have expected count less than
5. The minimum expected count is .10.
a.
8/8/2019 2007 Version of Yesu Project
39/63
39
4.13 flexible working system to insurance consultants was boosting its
wealth maximization.
Null hypothesis
An insurance company like Bajaj Allianzs flexible working system to
insurance consultants was not boosting its wealth maximization.
Input data:-
This test is attempting to find out the relationship between independent variable
(wealth maximization) and dependent variable (flexible working hours).
Table 12:- Relation between wealth maximization and flexible working
hours
Wealth maximization * flexible working hours
Explanation of output:-
The value of the pearson chi-square test clearly states that there is a significant
relationship between dependent and independent variable.
The chi-square test is carried out at a 90 percent confidence level (equivalent to
100-90 divided by 100 or 0.1 significant level which is more than obtained
significance 0.002).
50.252a
25 .002
43.577 25 .012
11.084 1 .001
50
Pearson
Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asymp.
Sig.
(2-sided)
Chi-Square Tests
34 cells (94.4%) have expected count less than5. The minimum expected count is .02.
a.
8/8/2019 2007 Version of Yesu Project
40/63
40
There is 99.8 percent significance between the variables so the null hypothesis
is rejected.
From this explanation it can be deducted that An insurance company like Bajaj
Allianzs flexible working system to insurance consultants was boosting its
wealth maximization.
4.14 Consultant intension to earn commission affecting their performance
(earned commission)
Null hypothesis
Consultant intension to earn commission doesnt affect their performance
(earned commission).
Input data:-
This test is attempting to find out the relationship between independent variable
(intension to earn commission) and dependent variable (earned commission).
Table 13:- what insurance consultants earned and their intension to earn.
getting more commission * salary or commission for last year
This test can link what insurance consultants earned and their intension levels
to get more commission.
21.484a
12 .044
17.327 12 .138
2.449 1 .118
50
Pearson
Chi-Square
Likelihood Ratio
Linear-by-Linear
Association
N of Valid Cases
Value df
Asymp.
Sig.
(2-sided)
Chi-Square Tests
18 cells (90.0%) have expected count less than
5. The minimum expected count is .08.
a.
8/8/2019 2007 Version of Yesu Project
41/63
41
Explanation of output:-
The value of the pearson chi-square test clearly states that there is a significant
relationship between dependent and independent variable.
The chi-square test is carried out at a 90 percent confidence level (equivalent to
100-90 divided by 100 or 0.1 significant level which is more than obtained
significance 0.044).
There is 95.6 percent significance between the variables. Consultant intension
to earn commission affecting their performance (earned commission) so the
null hypothesis is rejected.
8/8/2019 2007 Version of Yesu Project
42/63
42
Cluster analysis:-
4.15 Identification of the different set of insurance consultants in Bajaj
Allianz based on their characteristics and performance
Table 14:-Different clusters of insurance consultants in Bajaj Allianz
Clusters 1 2 3 4
find out the clients 2 1 2 2
getting more commission 4 7 4 7
customer satisfaction 7 6 6 6
good package 7 6 1 6
Number of hrs attending for
training in a month
1 1 2 4
network 2 2 2 1
hard working 1 1 3 2
experience 1 1 4 2
performance 1 1 2 1
By observing the table there is no much difference in values of each cluster this
shows that most of the insurance clusters are roughly with same attitude, but
when we look into data there are four clusters that means based their response
we can divide them into four different categories.
Cluster 1
The person belong to this cluster are highly concern for their clients and giving
more importance to their satisfaction and also getting commission is less
important than customer satisfaction. This cluster people are hard workers and
believing that experience is most important to succeed in insurance field, may
be because these people believe in practical experience they tempted to haveless attendance in company training classes.
8/8/2019 2007 Version of Yesu Project
43/63
43
Cluster 2
This cluster of individuals use mostly cold calling strategy, they will give more
preference to get more commission than customer satisfaction even though they
are not bad at that. Performance of this cluster is satisfactory but not up to the
mark.
Cluster 3
The performance of this group not up to the mark even though they are giving
less importance to get more commission than customer satisfaction because
they are not hard workers. These groups of people are mostly using direct
contacts and references to find out the clients. For them this is not a core
business activity, it is a part time earning activity for them.
Cluster 4
People belong to this cluster are moderately hard workers .they are much
importance to improve their customer base through direct contacts. They give
preference to commission as well as customer satisfaction. This people will all
attend all the training programs conducted by company. This group of people
have good track record.
8/8/2019 2007 Version of Yesu Project
44/63
44
Factor Analysis
4.16 Find out the important factors among all variables which are
affecting the productivity of consultant
Table 15:-important factors which are affecting productivity of consultant
2.015 25.187 25.187 2.015 25.187 25.187 1.786 22.326 22.326
1.459 18.240 43.427 1.459 18.240 43.427 1.598 19.972 42.298
1.283 16.038 59.465 1.283 16.038 59.465 1.373 17.168 59.465
.933 11.658 71.124
.776 9.694 80.818
.579 7.241 88.058
.513 6.409 94.467
.443 5.533 100.000
Compon1
2
3
4
5
6
7
8
Total
% of
ariance
umulativ
% Total
% of
ariance
umulativ
% Total
% of
ariance
umulativ
%
Initial Eigenvalues tion Sums of Squared Lo ion Sums of Squared Loa
Total Variance Explained
Extraction Method: Principal Component Analysis.
8/8/2019 2007 Version of Yesu Project
45/63
45
The output factor analysis is obtained by requesting principal component
analysis and specifying the rotation. As evident from the above table, we find
that the three factors extracted together account for 59.46 % of the total
variance hence we have reduced number of variables from 8 to 3 underlying
factors.
The variables; flexible working hours and wealth maximization have loading of
0.80 and 0.844 on factor 1.This suggests that the factor is combination of these
two variables therefore this factor can be interpreted as Freedom to work.
The variables; company marketing strategies and customer satisfaction on
factor 2. This suggests that the factor is combination of these two variables
therefore this factor can be interpreted as Customer focused services.
2.536E-03 .696 -.130
-.135 -.373 .772
.549 .507 .242
.127 .213 .774
.209 .557 .315
.234 -.594 5.842E-02
.800 -8.98E-02 -6.01E-03
.844 -1.87E-02 -3.11E-03
companys
Marketing
Strategies and
EmployeesPerformance
getting more
commission
customer
satisfaction
incentives and
commission
good package
number of
hours
attending for
traing per
month
flexible
working hours
wealth
maximisation
1 2 3
Component
Rotated Component Matrix a
Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
Rotation converged in 6 iterations.a.
8/8/2019 2007 Version of Yesu Project
46/63
46
The variables; commission and incentives on factor 3. This suggests that the
factor is combination of these two variables therefore this factor can be
interpreted as Good payments to consultants.
Total eight variables are reduced to three variables named as freedom to work,
customer focused services and good payments to consultants.
If company concentrates mainly on innovative customer oriented products
along with better payments through commission or incentives to the insurance
consultants and also giving flexible working hours to work these three together
can improve the nearly 60% of company performance.
8/8/2019 2007 Version of Yesu Project
47/63
47
Chapter- 5
FINDING AND CONCLUSIONS
8/8/2019 2007 Version of Yesu Project
48/63
48
Findings
1) Building network is directly related to the number of calls dialed by
consultant, flexible working hours and educational qualification of
insurance consultant.
2) People who have higher qualification are preferred to work in insurance
sector when there is a flexible working system and also they try to work
for wealth maximization basis not on profits basis.
3) People who are updating and analyzing market are more confident than
others and they can create more wealth to the company.
4) Consultants who have good communication skills are also have great
convincing power than others clients.
5) Gender and qualification can decide the salary range of the insurance
consultant.
6) Most of the consultants have completed their graduation in BA, BBA,
Bcom and Mcom. People from science and technology back ground are
not preferring to work as a consultant or sales manager, people who
dont has better other opportunities are only preferring to work as
consultant, this field still suffering to attract other higher educated
people.
7) Insurance consultants who are much concern about customer satisfaction
could earn more than other consultants.
8) Insurance consultants who undergone through more Training given by
the Bajaj Allianz Company motivating the employees to improve their
customer satisfaction approaches.
8/8/2019 2007 Version of Yesu Project
49/63
49
9) Flexible working hours provided by the Bajaj Allianz Company to the
insurance consultants and sales managers motivating them to improve
their customer satisfaction approach.
10)Consultant intention to earn more commission affecting their
performance (earned commission)
11)Nearly 60 percent of the insurance consultant performance badly
affected by two variables is lack of communication skills and lack of
network. There are only 20% people without having any drawback and
remaining 80% people have at least one drawback.
12)By getting experience insurance consultants earnings also increasing so
salary of the insurance consultant depending on the their experience.
13)Most of the employees of Bajaj Allianz are satisfied very well and their
convincing power also well this shows that people who have more
convincing power also have more satisfaction levels with their working
company.
14)Approximately 20 percent of the sample and also equal number people
achieved completeness in learning capacity and intelligent quotient
because generally people who have more learning capacity also have
good intelligent quotient.
15)Among all most of them are difficult to achieve completeness in
emotional intelligence if company concentrating on it, this willdefinitely helpful to consultants to increase their performance.
16)The scope of the insurance consultant improvement is less than expected
through training because more than 75 percent people have already
agreed they achieved more than 70 percent of their actual capacity so
there is only 1/4th
of people only have scope to improve nearly double to
their present performance.
8/8/2019 2007 Version of Yesu Project
50/63
50
17)Communication skill is most important among all and next important
skill is confidence of the consultant these can create the trust worthy to
the client.
18)Importance of the each characteristic was ranked as follows by the
insurance consultant.
1. Communication skill
2. Confidence
3. Hardworking
4. Network
5. Soft skills
6. Experience
19)Insurance consultants who have good communication skills and doing
hard work would have successful career than other because
communicational skill can build confidence and it can increases the net
work so those only will succeed irrespective of experience thats way
experienced ranked least even though it is important in insurance sector.
20)An insurance company like Bajaj Allianzs flexible working system to
insurance consultants will boost its wealth maximization.
21)Mainly three factors are influencing the 60 percent productivity of both
company and insurance consultant
a) Flexible working hours and wealth maximization are comes under
factor 1 named as Freedom to work.
b) Company marketing strategies and customer satisfaction are comes
under factor 2 named as Customer focused services.
c) Commission and incentives are comes under factor 3 named as Good
payments to consultants.
8/8/2019 2007 Version of Yesu Project
51/63
51
CONCLUSION
A study on productivity of insurance consultant and the reasons there off had
given an insight on the employees of insurance company and the training given
to them. My basic objective was to make the insurance consultants productivity
analysis and find out the ways to develop their productivity. I could come to
know that there are around 21 life insurance companies till date. These
insurance companies have several plans which fulfill the needs of the
customers. So there is a huge competition among the companies and the
consultants in this competitive world innovative approach is must and should.
This research can suggest the company as well as consultant where to
concentrate more to increase productivity levels.
Nature of work existing in the insurance industry, the kind of deadlines
for sales managers under whom insurance consultants are working have
to meet, the kind of pressure and levels of stress which they work under
and the kind of recognitions given to them after they meet or exceed
their targets.
There is a greater scope to improve insurance consultant productivity
through training and motivation.
Work life satisfaction is very important both financially and non-
financially to sustain in the field for long time.
Interactions with consultants during surveys helped me to enhance my
marketing skills and communication skills.
8/8/2019 2007 Version of Yesu Project
52/63
52
Chapter- 6
SUGGESTIONS AND
RECOMMENDATION
8/8/2019 2007 Version of Yesu Project
53/63
8/8/2019 2007 Version of Yesu Project
54/63
54
payment for senior consultants, so in order to attract more consultants
and keeping them for long time it is recommended that company have to
fulfill those.
Bajaj Allianz nearly showing optimal performance at its best, it has
good computerized network and quick performance feedback to improve
the competitiveness among the consultants. Including direct selling it
has to adopting new strategies like bancassurance, shopassurance and
telemarketing..etc. also can fit well. it is recommended that company
must have innovative customized products and marketing channel to
increase its capacity as it now always.
8/8/2019 2007 Version of Yesu Project
55/63
8/8/2019 2007 Version of Yesu Project
56/63
56
Bibliography
I. Narayanan H.Indian insurance a profile. Jaico publishing house, 2006.
II. Pandy.Risk management and insurance. Himalaya publications, 2007.
III. Bhargava. insurance theory and practice. Pearl book publications, 2001.
IV. Anonymous financial reports of life insurance companies for the year
2008-2009, www.irda.org, last accessed on 21-09-2009.
V. Anonymous, financial performance and various products provided by
Bajaj Allianz Life Insuance Co. Ltd,
http://www.bajajallianzlife.co.in/products.asp, last accessed 30-09-2009.
VI. Anonymous, http://www.thehindubusinessline.com, accessed on 27-07-
2009.
VII. Anonymous, information regarding insurance consultants of by Bajaj
Allianz Life Insuance Co. Ltd, http://solapur.olx.in/insurance-
consultant-of-bajaj-allianz-life-insurance-co-iid.
http://www.insurancemall.in/I-Opener/?tag=/bajaj+allianz+life+insurance
http://www.blonnet.com/2009/08/08/stories/2009080850331700.htm
8/8/2019 2007 Version of Yesu Project
57/63
57
Chapter- 8
APPENDICES
8/8/2019 2007 Version of Yesu Project
58/63
58
Appendix-1 table of correlation
1.000 -.014 .244 -.156 .226 .041 .303* .065 -.028 .088 -.128
-.014 1.000 .017 .026 -.075 .128 -.137 .165 .093 .247 .093
.244 .017 1.000 .016 .476** .235 .400** .018 -.195 -.290* .245
-.156 .026 .016 1.000 -.004 -.104 .063 .048 -.029 -.093 .003
.226 -.075 .476** -.004 1.000 .222 .394** .015 -.222 .051 .262
.041 .128 .235 -.104 .222 1.000 .756** -.097 -.311* -.037 -.162
.303* -.137 .400** .063 .394** .756** 1.000 .037 -.209 -.107 -.013
.065 .165 .018 .048 .015 -.097 .037 1.000 -.010 .106 .100
-.028 .093 -.195 -.029 -.222 -.311* -.209 -.010 1.000 .088 -.030
.088 .247 -.290* -.093 .051 -.037 -.107 .106 .088 1.000 -.030
-.128 .093 .245 .003 .262 -.162 -.013 .100 -.030 -.030 1.000
. .920 .087 .278 .115 .778 .033 .653 .847 .545 .374
.920 . .907 .857 .603 .374 .343 .252 .521 .083 .520
.087 .907 . .911 .000 .100 .004 .900 .174 .041 .087
.278 .857 .911 . .980 .472 .665 .742 .843 .521 .981
.115 .603 .000 .980 . .122 .005 .920 .121 .727 .066
.778 .374 .100 .472 .122 . .000 .503 .028 .800 .260
.033 .343 .004 .665 .005 .000 . .797 .145 .458 .928
.653 .252 .900 .742 .920 .503 .797 . .945 .464 .490
.847 .521 .174 .843 .121 .028 .145 .945 . .541 .834
.545 .083 .041 .521 .727 .800 .458 .464 .541 . .834
.374 .520 .087 .981 .066 .260 .928 .490 .834 .834 .
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
50 50 50 50 50 50 50 50 50 50 50
number of
calls per dnet work
flexible
working ho
highestqualificatio
wealthmaximisati
convincing
power
emotional
intelligent
quotient
market upand statist
analysis
confidence
experience
backgroun
number ofcalls per d
net work
flexibleworking ho
highestqualificatio
wealth
maximisati
convincing
power
emotional
intelligentquotient
market upand statist
analysis
confidence
experience
backgroun
number of
calls per d
net work
flexible
working ho
highest
qualificatio
wealth
maximisati
convincing
power
emotionalintelligent
quotient
market up
and statist
analysis
confidence
experience
backgroun
Pearson
Correlati
Sig.(2-tailed)
N
umber ocalls per
day net work
flexibleworking
hours
highest
ualification
wealth
aximisatio
onvincing
power
motionalntelligent
quotient
market
update
andtatistical
analysis onfidencexperienceackground
Correlations
Correlation is significant at the 0.05 level (2-tailed).*.
Correlation is significant at the 0.01 level (2-tailed).**.
8/8/2019 2007 Version of Yesu Project
59/63
8/8/2019 2007 Version of Yesu Project
60/63
60
7. Please rate how exact the productivity of insurance consultant
means?
True false
Getting more commission 7 6 5 4 3 2 1
Customer satisfaction 7 6 5 4 3 2 1
Wealth maximization 7 6 5 4 3 2 1
Getting more polices 7 6 5 4 3 2 1
8. Please rate how important or unimportant the different types of
motivations in the organization?
Important unimportant
Incentives and commission 7 6 5 4 3 2 1
Good package 7 6 5 4 3 2 1
Training and motivating classes 7 6 5 4 3 2 1
Flexible working hours 7 6 5 4 3 2 1
9. What is keeping you away from being successful?
Lack of communication skills Lack of network lack
of confidence
Lack of affords Lack of knowledge
8/8/2019 2007 Version of Yesu Project
61/63
61
10. Tick the corresponding block
Are you visiting company Branch on regular & Weekly basis asscheduled?[yes] [no ]
Are you Creating Prospecting List, their birthday List and Marriage
Anniversary List? [yes] [ no ]
Are you doing Market updates & statistical analysis [yes ] [no ]
Are you involving yourself in some social activities for welfare of People
around you? [yes] [ no]
Are you available to prospects & policyholders in times of need
[yes] [no ]
Do you Updating Policyholders new products available
[yes ] [no]
11. (100 marks are perfect score, out of 100 where you are):-
1. Learning capacity [ /100 ]
2. Convincing power [ /100 ]
3. Intelligent quotient [ /100 ]
4. Emotional intelligence [ /100 ]
5. Degree of satisfaction [ /100 ]
8/8/2019 2007 Version of Yesu Project
62/63
62
12. (Please rate how important or unimportant each characteristic is):-
13 .General information about the insurance consultant
Name
gender
Area
qualification
Experience
Commission
No of policies you have
Family size
No of earners In family
Rural or urban (background)
Duration Of training
Are you Satisfied With This job
Most
important[1]
Important
[2]
Neither imp
Nor unimp[3]
Unimporta
nt[4]
Most
unimportant
[5]
Communication
skills
Net work
Soft skills
Confidence
Hardworking
Experience
8/8/2019 2007 Version of Yesu Project
63/63
Open ended questionnaire for unstructured interview:-
1. Please explain what type of training this company given to you?
2. What is the structure of your company training?
3. What kind of development did you noticed after training?
4. Where you are poor and why?
5. What you need most for your productivity?
6. Are you ready to expertise?
7. In your point of view what is innovative way of convincing the clients?
8. How can you convince the clients?
9. What kind of external support you need for good productivity?