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Title Page

STATISTICAL MODELS IN ASSESSING SERVICE

DELIVERY OF UNILEVER NIGERIA PLC

(A CASE STUDY OF UNILEVER NIGERIA PLC, APAPA, LAGOS STATE)

By

UGEZENE SUSAN CHINWEOKWU,

2005 / DEGR / DL / 1679

BEING A B.Sc. PROJECT REPORT SUBMITTED IN PARTIAL FULFILLMENT OF THE

REQUIREMENTS FOR THE AWARD OF A BACHELOR OF SCIENCE (B.SC) DEGREE IN

COMPUTER SCIENCE AND STATISTICS OF THE UNIVERSITY OF NIGERIA, NSUKKA.

SUPERVISOR: Dr. EMMANUEL MBA

DEPARTMENT OF COMPUTER SCIENCE / STATISTICS

UNIVERSITY OF NIGERIA, NSUKKA

September, 2013



Approval Page

This project was submitted to and approved by the Department of

Statistics, University of Nigeria, Nsukka in partial fulfillment of the

requirements for the award of B.Sc Degree in Computer Science and

Statistics.

Dr. EMMANUEL MBA

Project Supervisor

Dr.EMMANUEL MBA

Programme Co-ordinator

External Examiner



Certification Page

I hereby declare that this research work STATISTICAL MODELS IN

ASSESSING SERVICE DELIVERY OF UNILEVER NIGERIA

PLC was entirely my hand work. In areas where I needed assistance,

the authors were rightly referenced.

BY

UGEZENE SUSAN CHINWEOKWU2005 / DEGR / DL / 1679

Date



Dedication Page

I dedicate this research work to God Almighty, the giver of life,

strength and resources to complete this course.



Abstract

Everyone at one point or the other ventures into business be it fully or

part-time with the sole aim of making profit amidst different

Government policies, political instability etc. In view of this fact, the

research work uses statistical procedures and models to look at

assessing service delivery in UNILEVER NIGERIA PLC. To this

end, a raw data showing the aggregate sales of four major products of

the organisation was collected for ten consecutive years. The results

obtained showed that the sales are not normally distributed; the rate of

sales of products and the employment are on the increase though the

products have an unequal sales rate. The relationship between the

product sales and employment rate is an almost perfect positive

correlation and the trend line graph is positive.



Table of Contents

Title Page ................................................................................................................................................. 1

Approval Page ......................................................................................................................................... 2

Certification Page .................................................................................................................................... 3

Dedication Page ...................................................................................................................................... 4

Acknowledgement Page ......................................................................................................................... 5

Abstract ................................................................................................................................................... 6

Table of Contents .................................................................................................................................... 7

List of Figures .......................................................................................................................................... 9

Chapter 1. Introduction .................................................................................................................. 10

1.1. BACKGROUND OF THE STUDY ............................................................................................... 10

1.2. OBJECTIVES OF RESEARCH .................................................................................................... 14

1.3. SCOPE OF PROBLEM .............................................................................................................. 15

1.4. LITERATURE REVIEW ............................................................................................................. 16

Chapter 2. DATA COLLECTION ........................................................................................................ 24

2.1. METHOD OF DATA COLECTION ............................................................................................. 24

2.2. DATA REPRESENTATION........................................................................................................ 24

2.3. THE PRODUCTS ..................................................................................................................... 27

2.3.1. Blue Band ...................................................................................................................... 27

2.3.2. Knorr Cube .................................................................................................................... 28

2.3.3. Lipton Tea ..................................................................................................................... 29

2.3.4. Royco ............................................................................................................................ 31

Chapter 3. ANALYSIS OF DATA ........................................................................................................ 32

3.1. Data Analysis ......................................................................................................................... 32

3.2. Analysis of Variance Test on Product Sales for Equal Means .. Error! Bookmark not defined.

3.3. Test for Normality ................................................................................................................. 32

3.3.1. Test on the rate of sales ................................................................................................. 37



3.3.2. Test on Staff Employment Rate .................................................................................... 39

3.4. Significance of the sold products .......................................................................................... 41

3.5. Correlation study of the sales and the employment rate ..................................................... 43

3.6. Determination of Significance of Correlation Value (r) ........................................................ 45

3.7. Trend study on the sales of product ..................................................................................... 46

Chapter 4. SUMMARY, CONCLUSION AND RECOMMENDATION ...................................................49

4.1. Summary ...............................................................................................................................49

4.2. Conclusion .............................................................................................................................49

4.3 Recommendation.................................................................................................................50



List of Figures

Figure 2-1 .............................................................................................................................................. 25

Figure 2-2 .............................................................................................................................................. 26



Chapter 1. Introduction

1.1. BACKGROUND OF THE STUDY

Statistics serves as a great measure in determining the average performance of every business

organization. With the help of statistical models applied, number of goods/services produced

is measured to assess their profitability ratio, productivity and the growth of a business.

Statistical models are used both at the micro (small scale business) and macro (public

enterprises, private limited liability companies, etc.) business enterprise level. The statistical

models are primarily the application of readily formulated statistical formula designed for

solving problem systems and relating correlative patterns for solution and decision theory

derivation. Statistical models help to forecast and predict events in the business economy

environment.

Service Delivery is measured based on the following;

Tangibility, physical facilities, equipment, and appearance of employees.

Reliability – ability to perform the required service dependably and accurately.

Responsiveness – willingness to help customers and provide prompt service.

Assurance – knowledge and courtesy of employees and their ability to inspire trust

and confidence.

Empathy – caring and individual attention provided by the staff.

On the other hand, the concept of satisfaction is more inclusive than the concept of quality

service. Customer satisfaction is influenced by five variables, namely: service quality,

product quality, price, situation and personality.



Statistics refer to the collection, arrangement and representation of numerical (mathematical)

data. This data can be the result of data analysis from various fields. Almost each and every

area of business and industry uses statistical reporting to understanding business data for

decision making purposes. The organization of data into a common format provides a

benchmark for historical performance and future benchmarking. The standardization of data

also serves as a common point of reference so that interested parties can deduce meaningful

relationships from the data.

Statistics provide the necessary data in a meaningful way to support strategic decision

making. Without the use of statistics, businesses could not calculate returns on investment

and business decision making would become a hit and miss affair. Industry and business in

general each have different data and information requirements. Business statistics can

literally be formulated and shaped according to individual requirements. Ultimately, the data

must be designed to provide meaningful and useful results. This assists companies and

individuals to make more informed decision that affect business outcomes and provide a way

for on-going performance measurement. For business decision making, it is very important to

understand the composition and breakdown of business activity. For this, industry statistics

provide data in a meaningful format. Industry statistics define each and every aspect of a

particular industry and assist business operators to extract and manipulate data to assist

strategic decision making.

Generally, industry or business organization statistics include hard data such as production

volumes, sales revenues, employment statistics, accounting records, and anything to do with

industry’s demographics and industry’s trends for service delivery performance. If one is

starting a business or already a proprietor, it is very important to have a way to benchmark

progress and assess critical data. The use of industry statistics provides a consistent

framework of reference that allows business owners to draw meaningful conclusions from



data that has a consistent reporting format. (Agranoff, Robert and Michael M cGuire, 2003).

Small Business Statistics Irrespective of whether a company is small or large, business

statistics provide key performance indicators to support primary decision making.

Every company wants to reduce costs, increase market share, maximize return on investment,

penetrate new markets and improve the return on investment for labour and capital.

Standardized business statistics are used to measure a company’s progress on key business

activities.

Month to month analysis and quarterly review periods provide the ideal opportunity for key

business managers to reflect and analyse data to determine whether performance is in line

with original forecasts. Questions over sales growth, advertising initiatives and campaign

results provide insight into how successful a company has been in aligning its business

objectives with overall company goals and objectives. Adjustment or new strategy

formulation ultimately results to drive the business in the intended business direction.

Modern Business Statistics are used extensively in the internet marketing space. Traffic

analysis, advertising campaign analysis, organic search traffic and pay per click campaign

provide important insight into consumer behaviour which is used to formulate future strategy

for an organization. Without the use of online bench marketing tools to gather critical

business statistics intelligence, companies would face high degrees of difficulty for

determining advertising direction, marketing spend and overall online business direction.

A statistical model according to Kaw (2008), is a set of mathematical equations which

describe the behaviour of an object of study in terms of random variables and their associated

probability distributions. If the model has only one equation it is called a single-equation

model, whereas if it has more than one equation, it is known as a multiple-equation model.



1.2. OBJECTIVES OF RESEARCH

The study is carried out to achieve the following objectives:

To determine the rate of sales and employment rate.

To determine the significance of the sold products

To find the Correlation study of the sales and the employment rate

To determine the trend on the sales of the products



1.3. SCOPE OF STUDY

The study considered Unilever Nigeria Plc. Unilever Nigeria Plc, was incorporated as Lever

Brothers (West Africa) Ltd on 11th April, 1923 by Lord Leverhulme, but the company’s

antecedents have to be traced back to his existing trading interests in Nigeria and West Africa

generally, and to the fact that he had since the 19th century been greatly involved with the

soap business in Britain. Located at No 1 Billings Way Oregun, Ikeja, Nigeria, Unilever

Nigeria Plc. started as a soap manufacturing company,(when?i.e Date!) and is today one of

the oldest surviving manufacturing organizations in Nigeria.

After series of mergers/acquisitions, the company diversified into manufacturing and

marketing of foods, non-soapy detergents and personal care products. These

mergers/acquisitions brought in Lipton Nigeria Ltd in 1985, Cheesebrough Ponds Industries

Ltd in 1988. The company changed its name to Unilever Nigeria Plc. in 2001.Unilever

Nigeria Plc. is a public liability company quoted on the Nigerian Stock Exchange since 1973

with Nigerians currently having 49% of equity holdings.(Unilever Nigeria PLC, 2013)

Unilever Nigeria Plc. was considered the case study of this research work because their

brands are household favourites and the company is so deeply committed to meeting the

everyday needs of people everywhere in Nigeria. Also, they have been a socially responsible

and responsive organization that takes strategic actions for the improvement of the

communities and environments in which it operates. The company has made provision for

assistance in fields of health, education/children welfare and potable water/hygiene as part of

its social responsibility programme in the Nigerian communities. The food and nutrition

department of the company was chosen because of the fast rising growth of the need of their

brands ranging from blue band to Lipton tea, Royco cube to Knorr seasoning cube, the need

grows exceedingly.



1.4. LITERATURE REVIEW

Materson (1981) concluded that customer service delivery and customer loyalty goes

hand in hand-when a service is delivered exceptionally it then follows that the customer

will be satisfied and will be loyal to the services rendered. According to him, customer

service deliverance taps into business, marketing, and psychological research and

practices to provide a satisfied customer. Customer service delivery also provides a

framework for customer service as a process and an outcome. Customer expectations,

loyalty satisfaction, product versus service delivery, measurement, brand equity, regional

and cultural differences, and organizational impact are the factors revolving in the

carrying out of a good business and hence will gain the loyalty of customers.

According to Kelvin (Kelvin, 1981), service quality is generally viewed as the output of

the service delivery system, especially in the case of pure service systems. Moreover,

service quality is linked to consumer satisfaction. Although there is no consensus in the

research community about the direction of causality relating quality and satisfaction, the

common assumption is that service quality leads to satisfied customers. He cited an

example of customers leaving a restaurant or hotel and asked if they were satisfied with

the service they received. If they answer "no," then we tend to assume service was poor.

Direct service providers, such as waitresses, also note that at times the best service

efforts are criticized because the customer's perceptions of the service are clouded by

being in a bad mood or having a disagreement with someone just before arriving at the

restaurant. These service providers recognize that in practice the influence of service

quality on customer satisfaction is affected by other factors, one of which is the

customers themselves.



Russell and Kabanuk(Kabanuk, 2005) summarize two studies conducted to improve the

emergency service delivery in St. Albert, a small city near Edmonton, Alberta. The first

study dealt with selecting the location of a new fire station. The goals of the study

included an assessment of the performance of the current system, an identification of the

areas) with poor coverage, a selection of a site among a set of given candidate locations,

and an assessment of the improvement in the system performance upon the addition of

the new fire station. A geographical information system was used for storing and

displaying the spatial data, computing service areas for given travel times, and for

communicating the results of the study. The second study considered an evaluation of

the resources available for emergency service. A probabilistic model was used to

evaluate labour costs for different platoon sizes and a simulation model was used to

evaluate the adequacy of the current staff and fleet sizes. They both concluded that there

may be deterioration in the quality of the service in the near future for the following

reasons:

1. The city's population is growing and (perhaps more importantly) aging. This

increases the call rate.

2. Recent changes to the health care system resulted in patients being discharged

earlier from hospitals and persons with a higher level of acuity being taken care

of at home or in non-hospital care environments. This results in increased call

rates for ambulances.

3. The city is planning an expansion. Three new developments have been approved.

This increases the total area that has to be covered (as well as the population).



4. The current Firefighter/EMS staff is aging which decreases the amount of time

they are available (vacation entitlement and sick leave usage increase with length

of service and age respectively), and age may increase risk of injury. In addition,

as the current staff retires, there will be significant loss of experience.

Nowell (1987) in his publication on improved service delivery stated that proper service

delivery helps companies deal more effectively with an open, collaborative and complex

service creation environment by facilitating the development and deployment of new

services from both internal and third-party sources. He also said that proper service

delivery provides the infrastructure and common business functions that can drive high

performance by helping providers create, deliver and manage a wide range of products

and services for consumers and enterprises more quickly, and at lower cost and risk.

Vaux and Vismann (2005) concluded that delivery of services such as health and

education can play an important role in the context of conflict. The distribution of

resources and their accessibility to different groups can address existing social

inequalities. On the other hand, it can heighten them. Equity and inclusiveness are

critical to ensuring that service delivery promotes sustainable peace. They are also

indicators of sustainable peace. However, because peace-building has rarely been an

explicit objective of interventions, it is difficult to gauge the effectiveness and impact of

service delivery in this regard.

There are a number of issues that can help maximize the capacity of service delivery to

promote sustainable peace. These include the need for strategic analysis and an

integrated approach, supporting equitable distribution of, and access to, resources. Also

important are: legitimacy, representing the poor, empowering women and harnessing

non-state actors within a regulatory framework.



According to them, service delivery does the following:

1. Touch on issues of legitimacy.

2. Strengthens the representation of poor people through user groups, parents

associations and civil society organizations.

3. Engagement of the poor in decision-making takes time, particularly when people

are most concerned with meeting their immediate needs.

4. This is particularly true for women, who usually have

responsibility for child-care and the strongest interest in delivery of services, but

who may be under-represented in user groups.

5. Choices between state and non-state actors need to reflect the interests of poor

people.

6. Systems of public accountability are required and, where service delivery is

privatized, the state will need to ensure socially responsible regulation.

Then with regards to conflict, service delivery can

1. Promote sustainable peace – building; interventions need to be developed through

on-going strategic analysis of the causes of conflict and the role of different

actors in conflict and development.

2. Enable the identification of indicators to gauge more accurately the positive and

negative impact of the support provided.

3. Prompt early government prioritization of policy reform and allocation of

resources for service delivery are critical to development actors.



4. Reform of services as countries emerge from conflict provides important

opportunities for ensuring the representation of poor people in the formation of

service delivery policy.

5. Through reform provide opportunities for strengthening local ownership of these

services through on-going monitoring.

Parmita and Zhao (2005) in their publication on service delivery noted that one of the

key challenges of the Internet as a service delivery channel is how they manage service

quality, which holds a significant importance to customer satisfaction. The purpose of

this research was to gain a better understanding of the service quality dimensions that

affect customer satisfaction in the Internet banking sector from a consumer perspective.

Based on a detailed literature review, a frame of reference was developed. Five service

quality dimensions were selected to be tested in the Internet banking sector in order to

explore the relationship between service quality and customer satisfaction. A qualitative

research approach was used to get a better understanding of this issue. However, a small

quantitative survey was also conducted to support the results obtained from the

qualitative study. The empirical data were gathered through in-depth interviews with

four people by using a semi-structured questionnaire and a survey were conducted with

25 people. Data presentation and analysis were done in accordance with the research

questions and the frame of reference. Finally, in the last chapter findings and conclusions

were drawn by answering the research questions. Nine service quality dimensions in

Internet banking were identified in this study (i.e., efficiency, reliability, responsiveness,

fulfilment, privacy, communication, personalization, technology update, and

logistic/technical support). The quality performance of all the nine dimensions was

shown to have a strong impact on customer satisfaction. Efficiency, reliability,

responsiveness, fulfilment, privacy was found to be the core service quality dimensions



in Internet banking. Finally, technology update and logistical or technical support was

two new dimensions found in this study.

Karen (2007) reported that the results of a review of the Chinese- and English – language

literatures on service delivery in China, asking how well China's health-care providers

perform and what determines their performance. Although data and methodological

limitations suggest caution in drawing conclusions, a critical reading of the available

evidence suggests that current health service delivery in China leaves room for

improvement, in terms of quality, responsiveness to patients, efficiency, cost escalation,

and equity. The literature suggests that these problems will not be solved by simply

shifting ownership to the private sector or by simply encouraging providers – public and

private – to compete with one another for individual patients. By contrast, substantial

improvements could be (and in some places have already been) made by changing the

way providers are paid – shifting away from fee – for – service and the distorted price

schedule. Other elements of active purchasing by insurers could further improve

outcomes. Rigorous evaluations, based on richer micro-level data, could considerably

strengthen the evidence base for service delivery policy in China

Onil (2008) using the method of environmental scan of peer-reviewed and grey literature

was use to select exemplars of innovation. A case series of organizations was

purposively sampled to maximize variation. He examined these cases using content

analysis and constant comparison to characterize their strategies, focusing on business

processes.

In his conclusion, he stated that private sector organizations demonstrate a range of

innovations in health service delivery that have the potential to better serve the Poor’s

health needs and be replicated. However, more rigorous evaluations are needed to



investigate the impact and quality of health services provided and determine the

effectiveness of particular strategies.

Robert (2009) saw delivery as"D" is for Dedicated. The moment a customer needs help,

the dedicated customer service representative swings into action. "E" is for Empowered.

The empowered customer service representative is given what he needs to be able to

provide outstanding customer service. "L" is for Linked. The members of a customer

care team must work together and share information. "I" is for Informed. In the past the

customer service department was often neglected by management. Representatives, seen

as workers at the bottom of the totem pole, went untrained and uninformed. Workers of a

company should be informed in all aspects of the company and its products and services.

"V" is for Valued. Before customer service representatives can value their work and your

customers, you must show them that you value them. "E" is for Experienced. An

experienced customer service representative learns to be knowledgeable but not overly

technical with customers. "R" is for Representative. The customer service representative

should always act in the best interests of the company. "Y" is for "Your Responsibility."

The customer service representative accepts responsibility for his role as a front-line

representative for the company. He knows that to a customer, he is the company.

According to Jones and Paul (2009) Statistics are used by all industries and businesses as

a standardized unity of measurement for presenting data in a useful and meaningful

format. Statistics can be used to measure historical performance and to forecast future

targets. For business managers and leaders, statistics provide insight into how business

units are performing relative to an organizations goals and objectives. Statistics also

forecast future trends and are in all areas of human thought an endeavour for planning

purposes. Statistics are used in all areas of trade and commerce. Governments frequently



undertake studies for the purposes of formulating policy and business use data to identify

what is currently working and what is not. Business initiatives are altered to improve

organizational performance based on feedback from statistical studies. Advertising

companies use statistics to assess target markets and formulate campaigns. Marketers use

statistics to identify opportunities for business development.



Chapter 2. DATA COLLECTION

2.1. METHOD OF DATA COLECTION

The method of data collection used for this research work is the method of Registration. It is

an unpublished data because it took a lot of time, effort, money and the required level of

confidentiality was very high.

2.2. DATA REPRESENTATION

The data collected is the most sensitive data of the Department of Sales considering its

statistical usage. It comprises of the sum total of the sale of each brand (Blue band, Lipton,

Knorr and Royco) for the last ten (10) consecutive years and the number of employed staff in

the factory department as well.

Aggregate of Quantity of product sold in carton/Year

Years Blue Band Lipton Knorr Royco Staff Size2000 140,016 141,040 144,042 145,093 30

2001 139,709 140,004 150,011 147,372 32

2002 141,083 142,381 145,273 146,365 32

2003 142,205 143,605 146,202 144,828 34

2004 144,018 145,679 147,213 146,369 38

2005 140,099 144,873 147,346 147,868 43

2006 143,259 143,382 147,458 149,453 51

2007 143,910 144,691 146,444 146,313 43

2008 143,400 145,022 146,523 146,001 40

2009 144,458 146,343 148,019 147,072 47

Table 2-1



Product Data Summary

Figure 2-1

134

136

138

140

142

144

146

148

150

152

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

N u m b e r o f C a r t o n s S o l d

T h o u s a n d s

Years

Quantity of Product Sold in Carton/Year

Blue Band

Lipton

Knorr

Royco



Staff Data Summary

Figure 2-2

0

10

20

30

40

50

60

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Aveage Staff Size / Year

Staff Size



2.3. THE PRODUCTS

2.3.1. Blue Band

Blue Band Good Start margarine is one of the brands under the group name - Family

Brand in Unilever. Unilever was the first company to commercially produce

margarine in 1878, through its founding Dutch company, Margarine Unie, as an

affordable alternative to butter. Unilever is the world’s leading margarine

manufacturer. Our products contain high-quality vegetable oils that are a good source

of essential fats and vitamins (A, D, E) which we all need to develop and maintain a

healthy body and enjoy a lifestyle full of vitality. Consuming fat does not necessarily

make you fat. If you cut out all the fat in your diet, your body will derive energy from

carbohydrates or proteins instead. So, without eating fat, you could still be obese and

moreover, you would be depriving your body of essential fatty acid which your body

cannot produce on its own and the protein it needs t build body cells. As long as the

energy you consume is equal to the energy you expend, you will not become fat! 15 –

30 minutes of physical activity a day is recommended to keep fit and health and to

prevent obesity heart disease and diabetes.



2.3.2. Knorr Cube

Knorr is a German food and beverage brand owned by the Anglo-

Dutch company Unilever since 2000, when Unilever acquired Best Foods. It produces

dehydrated soup mixes and condiments. The only country where Unilever did not

have rights to the Knorr name is Japan, where trademark of the product there is

controlled by Ajinomoto. It is sold under the name Royco in Indonesia, and under the

name Continental in Australia. Knorr was founded in 1838 by Carl Heinrich Theodor

Knorr. Knorr headquarters is inHeilbronn, Germany. Products previously sold under

the Lipton brand are now being absorbed into the Knorr product line. With annual

sales topping €3 billion, Knorr is Unilever's biggest-selling brand. In cooperation

with Slim-fast, also owned by Unilever, Knorr markets a line of low-calorie

products.(WIKIPEDIA, 2013)

Knorr believes that every meal is an opportunity for family bonding and everyday

meals can be just as magical as special occasions. Food is not just fuel; it really is the

glue of life. This conviction lies at the heart of Knorr's success – it is Unilever's no. 1

brand. A passion for good food goes right back to Knorr's earliest days. The business

was formed in 1838, when founder Carl Heinrich Knorr pioneered experiments in

drying seasonings and vegetables to preserve their flavour and nutritional value. Since

then Knorr has become an international brand offering a wide range of bouillons,

soups, seasonings, sauces, soupy snacks, dressings and frozen and ready – made meals.

Knorr products owe their tastes and flavours to the culinary skills of its chefs. Knorr

embodies a truly global cuisine, which began when the globe-trotting sons of its

founder started importing new ideas from overseas. The tradition stands today and

Knorr's drive for innovation still centres around its original factory in Heilbronn

where international teams of chefs contribute to product innovation.

http://en.wikipedia.org/wiki/Germany

http://en.wikipedia.org/wiki/Food

http://en.wikipedia.org/wiki/Beverage

http://en.wikipedia.org/wiki/Brand

http://en.wikipedia.org/wiki/England

http://en.wikipedia.org/wiki/Netherlands

http://en.wikipedia.org/wiki/Unilever

http://en.wikipedia.org/wiki/Hellmann%27s_and_Best_Foods

http://en.wikipedia.org/wiki/Soup

http://en.wikipedia.org/wiki/Condiment

http://en.wikipedia.org/wiki/Japan

http://en.wikipedia.org/wiki/Ajinomoto

http://en.wikipedia.org/wiki/Indonesia

http://en.wikipedia.org/wiki/Australia

http://en.wikipedia.org/wiki/Heilbronn

http://en.wikipedia.org/wiki/Lipton

http://en.wikipedia.org/wiki/Slimfast

http://en.wikipedia.org/wiki/Slimfast


http://en.wikipedia.org/wiki/Heilbronn

http://en.wikipedia.org/wiki/Australia

http://en.wikipedia.org/wiki/Indonesia

http://en.wikipedia.org/wiki/Ajinomoto

http://en.wikipedia.org/wiki/Japan

http://en.wikipedia.org/wiki/Condiment

http://en.wikipedia.org/wiki/Soup

http://en.wikipedia.org/wiki/Hellmann%27s_and_Best_Foods


http://en.wikipedia.org/wiki/Netherlands

http://en.wikipedia.org/wiki/England


http://en.wikipedia.org/wiki/Beverage

http://en.wikipedia.org/wiki/Food

http://en.wikipedia.org/wiki/Germany



2.3.3. Lipton Tea

Lipton is a brand of tea and was also a supermarket chain in the United

Kingdom before it was sold off to Argyll Foods, to allow the company to focus solely

on tea. The company is named after its founder Thomas Lipton.In 1871, Lipton used

his small savings to open his own shop, in Glasgow, Scotland and by the 1880s the

business grew to more than 200 shops. In 1929, the Lipton grocery retail business was

one of the companies that merged with Home and Colonial Stores to form a food

group with over 3,000 stores. The group traded as Home and Colonial Stores until

1961 when it took the name of Allied Suppliers. Lipton became a supermarket chain

focused on small towns, before Allied's 1982 acquisition by Argyll Foods: The

supermarket business was re-branded as Presto during the 1980s.Thomas

Lipton began travelling the world for new items to stock in this store, one such item

was tea, since sales had doubled from £40 million from late 1870s to £80 million by

the mid-1880s. Lipton believed that the price was far too high so he started growing

his own tea and selling it in packets by the pound (454g), half pound (227g), and

quarter pound (113g), with the advertising slogan: "Direct from the tea gardens to the

teapot." Lipton teas were an immediate success in the United States. Thomas Lipton

was knighted by Queen Victoria, who made him Sir Thomas Lipton in 1898 at the age

of forty-eight.

The Lipton tea business was acquired by consumer goods company Unilever in a

number of separate transactions, starting with the purchase of the United States and

Canadian Lipton business in 1938 and completed in 1972 when Unilever bought the

remainder of the global Lipton business from Allied Suppliers.


http://en.wikipedia.org/wiki/Tea

http://en.wikipedia.org/wiki/United_Kingdom


http://en.wikipedia.org/wiki/Argyll_Foods

http://en.wikipedia.org/wiki/Thomas_Lipton

http://en.wikipedia.org/wiki/Glasgow

http://en.wikipedia.org/wiki/Scotland

http://en.wikipedia.org/wiki/Home_and_Colonial_Stores


http://en.wikipedia.org/wiki/Presto_(UK_supermarket)









http://en.wikipedia.org/wiki/Presto_(UK_supermarket)



http://en.wikipedia.org/wiki/Scotland

http://en.wikipedia.org/wiki/Glasgow





http://en.wikipedia.org/wiki/Tea




In 1991, Unilever created a first joint venture with PepsiCo, the Pepsi Lipton

Partnership, for the marketing of ready to drink (bottled and canned) teas in North

America. This was followed in 2003 by a second joint venture, Pepsi-Lipton

International (PLI), covering many non-United States markets. PLI was expanded in

September 2007 to include a number of large European markets. PepsiCo and

Unilever each control 50% of the shares of these joint ventures.

Due to the 2008 Chinese milk scandal, food giant Unilever started recalling its Lipton

milk tea powder in Hong Kong and Macau on 30 September 2008. The tea powder,

which used Chinese milk powder as its raw ingredient, was recalled after the

company's internal checks found traces of melamine in the powder.

Products target the mass market and are generally positioned in the middle of the

price spectrum for tea. Like most branded teas, Lipton teas are a blend selected from

many different plantations around the world, from well-known producing countries

like Sri Lanka, India, Kenya, and China. Lipton Yellow Label is blended from as

many as 20 different teas.

Apart from black leaf teas, the company also markets a large range of other varieties,

both in leaf tea as well as ready-to-drink format.Lipton's main pillar brands are Lipton

Yellow Label and Lipton Iced Tea. Other product lines exist as well, like the Lipton

pyramid range in Europe and North America, and Lipton Milk Tea in East Asia. In

2008, the brand launched Lipton Linea in Western Europe.(WIKIPEDIA, 2013)

Lipton became Unilever Nigeria’s brand in 1985. The tea blend is imported

from Kenya and packed into teabags in the factory at Agbara in Ogun State in the

Western part of Nigeria.

http://en.wikipedia.org/wiki/Joint_venture

http://en.wikipedia.org/wiki/Ready_to_drink

http://en.wikipedia.org/wiki/2008_Chinese_milk_scandal


http://en.wikipedia.org/wiki/Tea_blending_and_additives

http://en.wikipedia.org/wiki/Tea_production_in_Sri_Lanka

http://en.wikipedia.org/wiki/Tea_production_in_Sri_Lanka

http://en.wikipedia.org/wiki/Tea_blending_and_additives


http://en.wikipedia.org/wiki/2008_Chinese_milk_scandal

http://en.wikipedia.org/wiki/Ready_to_drink

http://en.wikipedia.org/wiki/Joint_venture



2.3.4. Royco

Royco was launched in 1978 as Roiko. It was the first beef flavouring in the market

and only one pack size (60g sachet) was launched. In 1993 Roiko was re-launched as

Royco. Royco believes that everyone should be able to prepare and enjoy good food,

every single day of the week. Good food has the magic of touching all our senses,

with an exciting aroma, good taste and actually putting smiles on our faces. A touch

of Royco to your meals will definitely transform every meal moment and make it very

special. You will not know, until you have experienced the New Royco Goat Meat

Flavour. In our quest to provide our cherished consumers with the best bouillon

product, the new Royco Goat Meat Flavor that is perfect with vegetable soup was

developed. This new product is:

Tastier than ever.

Crumbles smoothly.

Full of flavor and less salty.

The aroma of Royco easily whittles away the miles and years, so that no matter where

you are – in the office, at school, on a business trip, on vacation in a faraway land –

you become instantly reunited with the people and memories you cherish the most.

Food is a key ingredient in the make-up of the home. While it unites the members of a

home, it can also differentiate one home from another. In other words, food also gives

each home its identity! Only Royco gives that familiar taste of home cooking.



Chapter 3. ANALYSIS OF DATA

3.1. Data Analysis

The rate of service delivery can be measured with the rate of sales of the product and the

number of staff or the numerical staff strength of the Department of Food and Nutrition

Unilever Nigeria Plc. A steady growth in the rate of sales and employment depicts good or

quality service delivery, else, otherwise.

For the sake of brevity, we will denote the following by the variables B, L, K, R, and S:

B Blue Band

L Lipton Tea

K Knorr Cubes

R Royco Cubes

S Staff Size

3.2. Measure of Kurtosis (Test for Normality)

The moment Coefficient of Kurtosis is given by the formula=

=

Where m4 is the fourth moment about the mean, s is the standard deviation, and m2 is the

second moment about the mean.

For a normal distribution, = 3.

Using Microsoft excel we calculate the fourth and second moments of each product sold

after which we derive the moment coefficient of kurtosis.

Let d be the deviation from the mean.



L d d2 d4

141040 - 2,662.0 7,086,244.00 50,214,854,027,536.00

140004 - 3,698.0 13,675,204.00 187,011,204,441,616.00

142381 - 1,321.0 1,745,041.00 3,045,168,091,681.00

143605 - 97.0 9,409.00 88,529,281.00

145679 1,977.0 3,908,529.00 15,276,598,943,841.00

144873 1,171.0 1,371,241.00 1,880,301,880,081.00

143382 - 320.0 102,400.00 10,485,760,000.00

144691 989.0 978,121.00 956,720,690,641.00

145022 1,320.0 1,742,400.00 3,035,957,760,000.00

146343 2,641.0 6,974,881.00 48,648,964,964,161.00

Mean 143,702.00 3,759,347.00 31,008,034,508,883.80

Second moment 375,934.70

Fourth moment 3,100,803,450,888.38

a4 21.94



K d d2 d4

144042 - 2,811.1 7,902,283.21 62,446,079,931,048.40

150011 3,157.9 9,972,332.41 99,447,413,695,535.70

145273 - 1,580.1 2,496,716.01 6,233,590,834,590.41

146202 - 651.1 423,931.21 179,717,670,812.07

147213 359.9 129,528.01 16,777,505,374.56

147346 492.9 242,950.41 59,024,901,719.17

147458 604.9 365,904.01 133,885,744,534.08

146444 - 409.1 167,362.81 28,010,310,171.10

146523 - 330.1 108,966.01 11,873,591,335.32

148019 1,165.9 1,359,322.81 1,847,758,501,786.26

Mean 146,853.10 2,316,929.69 17,040,413,268,690.70


Fourth moment 1,704,041,326,869.07

a4 31.74



R d d2 d4

145093 - 1,580.4 2,497,664.16 6,238,326,256,148.41

147372 698.6 488,041.96 238,184,954,720.65

146365 - 308.4 95,110.56 9,046,018,623.51

144828 - 1,845.4 3,405,501.16 11,597,438,150,761.20

146369 - 304.4 92,659.36 8,585,756,995.61

147868 1,194.6 1,427,069.16 2,036,526,387,423.15

149453 2,779.6 7,726,176.16 59,693,798,055,352.90

146313 - 360.4 129,888.16 16,870,934,108.18

146001 - 672.4 452,121.76 204,414,085,865.49

147072 398.6 158,881.96 25,243,477,213.44

Mean 146,673.40 1,647,311.44 8,006,843,407,721.25


Fourth moment 800,684,340,772.13

a4 29.51

Since the value of a4 for all the products is well outside the normal range of 3, we can

conclude that the data does not follow a normal distribution at all.Since our data does not

follow the normal distribution, we resort to the use of the non-parametric test to achieve

our aims.



3.2.1. Test on the rate of sales using

Years (Xi) Y j - Yi Avg. Sales Yi i j

ve

i j

ve

1 j – (i=1) 142547.75 9 0

2 j – (i=2) 14427.4 6 2

3 j – (i=3) 143775.5 7 0

4 j – (i=4) 144210 6 0

5 j – (i=5) 145819.75 2 3

6 j – (i=6) 145046.5 4 0

7 j – (i=7) 145888 1 2

8 j – (i=8) 145339.5 1 1

9 j – (i=9) 145236.5 1 0

10 j – (i=10) 146473

37 8

Hypothesis:

Ho: =0 (There’s no sales increase over the years)

H1: <0 (There‘s sales increase the years).



Test Statistic = 2K

n(n – 1)

K =i j

ve

– i j

ve

K = 37 – 8

K =29

= 2(29)10(9)

= 0.6444

Kendall from table at n = 10 and at 5% level of significance is 0.467

Conclusion: Reject Ho and conclude that there’s an increase in the staff employment rate.



3.2.2. Test on Staff Employment Rate

Years Xi Number of Staff

(Yi)

Y j - Yi i j

ve

i j

ve

1 30 j-(i=1) 9 0

2 32 j-(i=2) 7 0

3 32 j-(i=3) 7 0

4 34 j-(i=4) 6 0

5 38 j-(i=5) 5 0

6 43 j-(i=6) 2 0

7 51 j-(i=7) 0 3

8 43 j-(i=8) 1 1

9 40 j-(i=9) 1 0

10 42 j-(i=10) 38 4

Hypothesis:

Ho: = 0 (There’s no increase in staff employment rate)

H1: <0 (There’s increase in the staff employment rate)



Test Statistic = 2K

n(n – 1)

K =i j

ve

– i j

ve

K = 38 – 4

K = 32

= 2 (32)10 (9)

= 0.7111

Kendall from table at n = 10 and at 5% level of significance is 0.467

Conclusion: Reject H0 and conclude that there’s an increase in the staff employment rate.



3.3. Significance of the sold products

Years/Blocks A B C D

1 140016 (1) 141040 (2) 144042 (3) 145093 (4)

2 139709 (1) 140004 (2) 150011 (4) 147373 (3)

3 141083 (1) 142381 (2) 145273 (3) 146365 (4)

4 142205 (1) 143605 (2) 146202 (4) 144828 (3)

5 144018 (1) 145679 (2) 147213 (4) 146369 (3)

6 140099 (1) 144873 (2) 147346 (3) 147868 (4)

7 143259 (1) 143382 (2) 147458 (3) 149453 (4)

8 143910 (1) 144691 (2) 146444 (4) 146313 (3)

9 143400 (1) 145022 (2) 146523 (4) 146001 (3)

10 144458 (1) 146343 (2) 148019 (4) 147072 (3)

R j 10 20 36 34

A = Blue Brand, B = Lipton Tea ,C = Knorr tube and D = Royco

Note: The rank of each sale is in the bracket



3.4. Correlation study of the sales and the employment rate

Expressing average sale staff employment rate in percent, we have

X 9.84 9.96 9.93 9.96 10.01 10.04 10.09 10.03 10.03 10.11

Y 7.35 7.94 7.94 8.53 9.71 11.18 13.53 11.18 10.29 12.35

X = Average sales in percentage

Y = Employment rate in percentage

Hypothesis:

Ho: X and Y are not correlated ρ = 0

H1: X and Y are correlated ρ> 0

Decision Rule: Reject Ho of r > C or 2

1

n

i

i

d

< C2

R x 1 2.5 4 2.5 5 8 9 6.5 6.5 10

R y 1 2.5 2.5 4 5 7.5 10 7.5 6 9

di 0 0 2.25 2.25 0 0.25 1 1 0.25 1

di2

= R x – R y



2

1

n

i

i

d

= 8.5

Test Statistic r = 1 – 62

1

n

i

id

n(n2-1)

r = 1 – 6(8.5)

10(100-1)

r = 1 – 57

990

r = 0.9485

Conclusion: The sales rate and staff employment rate are highly correlated.



3.5. Determination of Significance of Correlation Value (r)

The significance can be tested using

tcal = r 2n ~ tn-2

21- r

H0: r = 0.9485 isn’t significant

H1: r = 0.9485 is significant

tcal = 0.9485 10 - 2 1 - .9485 = 8.4845

tn-2 = t10-2 = 2.31

Conclusion: Reject H0 and conclude that r = 0.9485 is significant at 5% level of significance.

0.05()

()



3.6. Trend study on the sales of product

Yrs X Y X Y X XY Trend (T) Error (e)

2000 0 142547.75 -4.5 -2323.5 20.25 10409.85 143384.37 -836.62

2001 1 144274 -3.5 -587.05 12.25 2054.68 143712.52 561.48

2002 2 143775.5 -2.5 -1085.55 6.25 2713.86 144040.67 -265.17

2003 3 144210 -1.5 -651.05 2.25 976.58 144368.82 -158.82

2004 4 145819.75 -0.5 958.7 0.25 -479.35 14496.97 1122.78

2005 5 145046.5 0.5 185.45 0.25 92.73 145025.12 21.38

2006 6 145888 1.5 1026.95 2.25 1540.43 145353.27 534.73

2007 7 145339.5 2.5 478.45 6.25 1196.13 145681.42 -341.92

2008 8 145236.5 3.5 375.45 12.25 1314.08 146009.57 -773.07

2009 9 146473 4.5 1611.95 20.25 7253.78 146337.72 135.28

Where Y =1

n

i

i

Y

n



Chapter 4. SUMMARY AND CONCLUSION

4.1. Summary

The analysis in chapter three as shown that the use of statistical models in assessing service

delivery in a business organization is imperative.

The Kendall’s k– test severed a good purpose in analysing the sales and staff employment rate

which both serves as the bases for analysing service delivery. Friedman Fr-test, Spearman

Rank correlation and the simple linear regression, compared the sales of the product, showed

the relationship between the sales of the product and employment rate and the trend of the

sales of the products respectively.

4.2. Conclusion

In conclusion, the food and nutrition department of Unilever Nigeria Plc Lagos has a good

and stable standard of the delivery of services. Their rate of service delivery depended on the

quality and quality of their production, numerical staff strength and some other administrative

factors. The level of relationship between the sales and the employment rate led to the

positive trend line graph which is bound to be positively – continuous except some drastic

change that will have a negative effect on the administration of the department.

But even with the commendation, the department still has some work to do as shown in the

comparative study of the sales of the product. The knorr and Royce brands are failing

compared to the Blue band and Lipton tea brands with their rather small sum of rank. The

administrative section should come up innovative ideas such market study and preference,

advert placement etc. to stir – up the sales of these brands.



4.3. Recommendation

It is highly recommended that the management of the company reorganize their supply and

sales operations. Also they should prepare an efficiency list and do away with inefficient

members of staff.



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