Demand Forecasting

CHAPTER 1

INTRODUCTION

Demand forecasting refers to the prediction or estimation of a future situation

under given constraints.

Demand Forecasting is the activity of estimating the quantity of a product or

service that consumers will purchase. Demand forecasting involves techniques

including both

informal methods, such as educated guesses, and quantitative methods, such as the

use of historical sales data or current data from test markets. Demand forecasting

may be used in making pricing decisions, in assessing future capacity

requirements, or in making decisions on whether to enter a new market.

Pricing is one of the four Ps of the marketing mix. The other three aspects are

product, promotion, and place. It is also a key variable in microeconomic price

allocation theory. Price is the only revenue generating element amongst the 4ps,

the rest being cost centers. Pricing is the manual or automatic process of applying

prices to purchase and sales orders, based on factors such as: a fixed amount,

quantity break, promotion or sales campaign, specific vendor quote,

priceprevailing on entry, shipment or invoice date, combination of multiple orders

or lines, and many others. Automated systems require more setup and maintenance

but may prevent pricing errors.

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A market entry strategy is the planned method of delivering goods orservices

to a target market and distributing them there. When importing or exporting

services, it refers to establishing and managing contracts in a foreign country.

NECESSITY FOR FORECASTING DEMAND

Often forecasting demand is confused with forecasting sales. But, failing to

forecast demand ignores two important phenomena. There is a lot of debate in the

demand planning literature as how to measure and represent historical demand,

since the historical demand forms the basis of forecasting. Should we use the

history of outbound shipments or customer orders or a combination of the two to

proxy for demand.

Stock effects

The effects that inventor y levels have on sales. In the extreme case of stock-outs,

demand coming into your store is not converted to sales due to a lack of

availability. Demand is because the desired sizes are no longer available. For

example, when a consumer electronicsretailer does not display a particular flat-

screen TV, sales for that model are typically lower than the sales for models on

display. And in fashion retailing, once the stock level of a particular sweater falls

to the point where standard sizes are no longer available, sales of that item are

diminished.

Market response effects

The effect of market events that are within and beyond a retailer’s control. Demand

for an item will likely rise if a competitor increases the price or if you promote the

item in your weekly circular. The resulting sales increase reflects a change in

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demand as a result of consumers responding to stimuli that potentially drive

additional sales. Regardless of the stimuli, these forces need to be factored into

planning and managed within the demand forecast.

In this case demand forecasting uses techniques in causal modeling. Demand

forecast modeling considers the size of the market and the dynamics of market

share versus competitors and its effect on firm demand over a period of time. In the

manufacturer to retailer model, promotional events are an important causal factor

in influencing demand.These promotions can be modeled with intervention models

or use a consensus process to aggregate intelligence using internal collaboration

with the Sales and Marketing functions.

METHODS

METHODS OF FORECASTING

SURVEY METHOD STATISTICAL METHOD

1.Survey of buyer’s intentions 1.Trend projection method

2.Expert opinion method or Delphi Method 2.Moving averages method

3.Controlled Experiments 3.Regression analysis

4.Simulated market situations 4.Barometric method

No demand forecasting method is 100% accurate. Combined forecasts improve

accuracy and reduce the likelihood of large errors.

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Methods that rely on Qualitative

Forecasting demand based on expert opinion. Some of the types in this method are,

• Unaided judgment

• Prediction market

•Delph itechnique

•Game theory

•Judgmental bootstrapping

• Simulated interaction

• Intentions and expectations surveys

Conjoint analysis

Methods that rely on quantitative data

•Discrete Event Simulation

•Extrapolation

•Quantitative analogies

•Rule-based forecasting

•Neural networks

•Data mining

•Causal models

•Segmentation

FORECASTING

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The basic ingredient of any demand plan is a statistical forecast. Statistical models

and resulting forecasts are the building blocks of the planning process.

Although consensus and collaboration are key ingredients of a successful demand

management program, statistical forecasting is the first-step to create the baseline

plan. To this end, a good process and software technologies become important.

One of the key things you look for when you prepare a Request for Proposal (RFP)

is to ensure that you cover all of the modeling algorithms and techniques which are

relevant for your process. This depends on your industry and your specific business

model.

Forecasting techniques can be broadly classified as:

1.Time Series Forecasting models consisting of exponential smoothing, Holt-

Winters Multiplicative Smoothing, ARIMA models and Box-Jenkins Models,

Logarithmic regression models.

2.Promotional Planning Models that typically use event modeling methodologies

and indicator variable models.

3.Causal models that include a variety of Multiple Linear Regression Models and

transfer function models.

4. Probabilistic Models that often forecast the probability of a particular event

happening in the future and these include Logit, Probit and Tobit models

DEMAND FORECASTING

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The Importance of Demand Forecasting

Forecasting product demand is crucial to any supplier, manufacturer, or retailer.

Forecasts of future demand will determine the quantities that should be purchased,

produced, and Shipped. Demand forecasts are necessary since the basic operations

process,moving from the suppliers' raw materials to finished goods in the

customers' hands, takes time. Most firms cannot simply wait for demand to emerge

and then react to it. Instead, they must anticipate and plan for future demand so that

they can react immediately to customer orders as they occur. In other words, most

manufacturers "make to stock" rather than

"make to order" – they plan ahead and then deploy inventories of finished goods

into field locations. Thus, once a customer order materializes, it can be fulfilled

immediately – since most customers are not willing to wait the time it would take

to actually process their order throughout the supply chain and make the product

based on their order. An order cycle could take weeks or months to go back

through part suppliers and sub- assemblers, through manufacture of the product,

and through to the eventual shipment of the order to the customer.

Firms that offer rapid delivery to their customers will tend to force all competitors

in the market to keep finished good inventories in order to provide fast order cycle

times. As a result, virtually every organization involved needs to manufacture or at

least order parts based on a forecast of future demand. The ability to accurately

forecast demand also affords the firm opportunities to control costs through

leveling its production quantities, rationalizing its transportation, and generally

planning for efficient logistics operations.In general practice, accurate demand

forecasts lead to efficient operations and high levels of customer service, while

inaccurate forecasts will inevitably lead to inefficient, high cost operations and/or

poor levels of customer service. In many supply chains, the mostimportant action

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we can take to improve the efficiency and effectiveness of the logistics

process is to improve the quality of the demand forecasts.

Forecasting Demand in a Logistics System Logistics professionals are typically

interested in where and when customer demand will

materialize. Consider a retailer selling through five superstores in Boston, New

York,Detroit, Miami, and Chicago. It is not sufficient to know that the total

demand will be

5,000 units per month, or, say, 1,000 units per month per store, on the average.

Rather it is important to know, for example, how much the Boston store will sell in

a specific

month, since specific stores must be supplied with goods at specific times. The

requirement might be to forecast the monthly demand for an item at the Boston

superstore for the first three months of the next year. Using available historical

data, without any further analysis, the best guess of monthly demand in the coming

months would probably be the average monthly sales over the last few years. The

analytic challenge is to come up with a better forecast than this simple average.

Since the logistics system must satisfy specific demand, in other words what is

needed, where and when, accurate forecasts must be generated at the Stock

Keeping Unit (SKU) level, by stocking location, and by time period. Thus, the

logistics information system must often generate thousands of individual forecasts

each week. This suggests that

useful forecasting procedures must be fairly "automatic"; that is, the forecasting

method should operate without constant manual intervention

Forecasting is a problem that arises in many economic and managerial contexts,

and hundreds of forecasting procedures have been developed over the years, for

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many different purposes, both in and outside of business enterprises. The

procedures that we will discuss have proven to be very applicable to the task of

forecasting product demand in a logistics system. Other techniques, which can be

quite useful for other forecasting problems, have shown themselves to be

inappropriate or inadequate to the task of demand

forecasting in logistics systems. In many large firms, several organizations are

involved in generating forecasts. The marketing department, for example, will

generate high-level long-term forecasts of market demand and market share of

product families for planning purposes. Marketing will also often develop short-

term forecasts to help set sales targets or quotas. There is frequently strong

organizational pressure on the logistics group to simply use these forecasts, rather

than generating additional demand forecasts within the logistics system. After all,

the logic seems to go, these marketing forecasts cost money to develop, and who is

in a better position than marketing to assess future demand, and "shouldn’t we all

be working with the same game plan anyway…?"

In practice, however, most firms have found that the planning and operation of an

effective logistics system requires the use of accurate, dis-aggregated demand

forecasts.

The manufacturing organization may need a forecast of total product demand by

week, and the marketing organization may need to know what the demand may be

by region

GENERAL APPROACHES TO FORECASTING

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All firms forecast demand, but hardly any two firms forecast demand in exactly the

same way. Over the last few decades, many different forecasting techniques have

been developed in a number of different application areas, including engineering

and economics. Many such procedures have been applied to the practical problem

of forecasting demand in a logistics system, with varying degrees of success. Most

commercial software packages that support demand forecasting in a logistics

system include dozens of different forecasting algorithms that the analyst can use

to generate

alternative demand forecasts. While scores of different forecasting techniques

exist, almost any forecasting procedure can be broadly classified into one of the

following four

basic categories based on the fundamental approach towards the forecasting

problem that is employed by the technique.

1. Judgmental Approaches. The essence of the judgmental approach is to

address the forecasting issue by assuming that someone else knows and

can tell you the right answer. That is, in a judgment-based technique we

gather the knowledge and opinions of people who are in a position to

know what demand will be. For example, we might conduct a survey of

the customer base to estimate what our sales will be next month.

2. Experimental Approaches. Another approach to demand forecasting,

which is appealing when an item is "new" and when there is no other

information upon which to base a forecast, is to conduct a demand

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experiment on a small group of customers and to extrapolate the results to

a larger population. For example, firms will often test a new consumer

product in a geographically isolated "test market" to establish its probable

market share. This experience is then extrapolated to the national market

to plan the new product launch. Experimental approaches are very useful

and necessary for new products, but for existing products that have an

accumulated historical demand record it seems intuitive that demand

forecasts should somehow be based on this demand experience. For most

firms (with some very notable exceptions) the large majority of SKUs in

the product line have long demand histories.

3. Relational/Causal Approaches. The assumption behind a causal or

relational forecast is that, simply put, there is a reason why people buy our

product. If we can understand what that reason (or set of reasons) is, we

can use that understanding to develop a demand forecast. For example, if

we sell umbrellas at a sidewalk stand, we would probably notice that daily

demand is strongly correlated to the weather – we sell more umbrellas

when it rains. Once we have established this relationship, a good weather

forecast will help us order enough umbrellas to meet the expected demand.

4. "Time Series" Approaches. A time series procedure is fundamentally

different than the first three approaches we have discussed. In a pure time

series technique, no judgement or expertise or opinion is sought. We do

not look for "causes" or relationships or factors which somehow "drive"

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NEED FOR DEMAND FORECASTING

DETERMINANTS FOR DEMAND FORECASTING

. Capital goods – goods required for further production of goods

Demand for capital goods is derived demand

- Replacement demand

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- New demand

2. Durable consumer goods— goods used continuously for a period of time

- Replacement demand

- New demand

3. Non-durable consumer goods— commodities which are used in a single act of

consumption

Demand for these goods is influenced by

- Disposable income of people

- Price of the commodity

- Size and characteristics of population

CHAPTER 2

INTRODUCTION

Research can be defined as the search for knowledge or any systematic investigation to establish facts. The primary purpose for applied research is

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discovering, interpreting, and the development of methods and systems for the advancement of human knowledge.

STATEMENT OF THE PROBLEM:

One of the core issues, companies are facing today is the increase in man power cost. Coupled with this is a pressure the downsize and manage with fewer people, thus increasing efficiency and employee productivity. Companies are also realising the need for insuring that competent people are available for performing various critical roles. There is recognition that technology, finance, customers and market system and process can all be set right or managed effectively with the right kind of human resources. Apart from this, there is a focus on performing roles, time management, mentoring of competence, increased emphasis on performance management system and recognition of the strategic advantage given by the employee competencies in building the core competencies of the organisation. All these factors are pushing up the value of competency mapping in enterprise.

The engineering industry requires highly skilled man power with specialised technical skills. It is very important that competent people are available for ensuring efficiency and productivity. In order to nurture competence and build core competencies, Competency Mapping has become an important function of the HR department.

Therefore the researcher has undertaken the study titled “Competency Mapping” in ASEA BROWN BOVERI PRIVATE LIMITED.

TITLE OF THE STUDY

The study titled “A STUDY ON DEMAND FORECASTING”

OBJECTIVES OF THE STUDY:

1. To understand the level of competencies for various functions.

2. To find out the gaps in competency for various functions.

3. To assess the training need for building required competencies for

a specific function.

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4. To assess whether the employees have a positive attitude towards

their job.

SCOPE OF THE STUDY:

This study covers all aspects of Demand forecasting as an important tool. It covers various aspects projection of future sales estimation such as various methods of demand forecasting, most importantly trend analysis. However the study does not include any other demand forecasting tools.

STATEMENT OF THE PROBLEM

In todays times sales forecasting plays a very important role in any industry. Mineral water industry requires sales forecasting crucially in order to meet the demands of the customers. Therefore, a study on Bharathi Aqua solutions gives a brief picture about the future sales of the company and also the various factors effecting its sales.

METHODOLOGY

1. Type of research : This study is a descriptive analytical study.

2. Sources of data : Primary and secondary sources of data were used for the

purpose of this study. Primary data was sourced with the help of an

interview schedule. Books and internet were the source of secondary data.

3. Tool for collection of data : Sales data of Bharathi enterprises

4. OBJECTIVES

To study the statistical tools of the graph

To analyse the changes in growth.

Trend projection for future

SWOT analysis

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5. Limitations:

a. Time was a major constraint in undertaking the study.

b. This study is conducted for academic purpose only.

c. The data was not exhaustive

6. Chapter scheme

CHAPTER 1: INTRODUCTION

This is a general introduction to demand forecasting.

CHAPTER 2: RESEARCH DESIGN

This chapter outlines the research design adopted, title of the study, research methodology, objectives, scope and significance of the study, source of data, data collection instruments and the limitations of the study.

CHAPTER 3: COMPANY PROFILE

This chapter studies the organisational profile of the company, achievements, product range, company philosophy and performance of the organisation.

CHAPTER 5: ANALYSIS AND INTERPRETATION

This chapter is about the analysis of relevant data over the study period and interpretation of the same.

CHAPTER 6: SUMMARY OF FINDINGS, SUGGESTIONS AND CONCLUSION.

This is the last chapter of the study, which gives the findings of analysis and conclusion drawn from the analysis.

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BHARATHI ENTERPRISES

Bharathi Enterprises, Kanakanagar, Bangalore-32Contact: 9845260197

About BHARATHI AQUA SOLUTIONS

Bharathi Aqua Solutions, a technology and customer service oriented premier Water & Waste Water treatment Company, where “Trust is a Tradition”. The company is powered and backed by professionals with rich experience and expertise in the water & Waste water treatment and allied fields. Presently we have operations in Bangalore. Shortly we are planning to commence branches in Tamil Nadu and Hyderabad.

We draw vast experience in our operations from the various types of projects handled. This confidence and experience makes us competent both technically and commercially to provide Detailed engineering, Design, Erection, Commissioning of Hi -tech Water & Waste Water treatment Projects to customers ranging from Central & State Government Organisations, Indian Islands.

Lat

BHARATHI AQUA SOLUTIONS   Bharathi a vibrant, proactive, technology-driven and committed organization initiates with full pledge efforts to improve on International Quality Standard and accomplish methodological distinction.    In the process of existence, we have gained a wealth of experience and expertise

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80.206869 12.938482 E-6, SAKTHI APP

that has earned us the reputation as one of the “premier solution provider” in the water & Waste Water treatment field. This facilitated us to incorporate to manufacture various water

We are in water treatment since 1995, and establish a chain of products from de-mineralized water packaged drinking water, distilled water, electroplating water, phosphating water coolant water, water for pharmaceuticals, food products, and steam iron, for boiler, for printing purpose, for water base emulsion /distemper & microbiological activity.

In our endeavour to maintain strict quality controls each unit purchases performs & caps only from approved vendors. We produce our own bottles in-house. We have recently procured the latest world class state of the art machineries that puts us at par with International standards. This has not only helped us improve packaging quality but has also reduced raw material wastage & doubled production capacity. You can be rest assured that you are drinking safe & pure water when you consume our mineral water. Bharathi is free of impurities & 100% safe. Enjoy the Sweet taste of Purity !

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AN INSIGHT INTO BOTTLED WATER INDUSTRY IN INDIA

The bottled water industry is one of the most thriving sectors in India. The market is growing at a whopping rate of about 55 per cent annually and is expected to cross Rs. 1000-crore mark within the next couple of years.

Almost all major national and international brands have taken a plunge. Parle's Bisleri that virtually monopolized the bottled water market is now vying with Nestle, Coca Cola, PepsiCo, Manikchand, UB and Britannia. According to a national-level study, there are close to 200 bottled water brands in India. Nearly 80% of these are local brands.

In India, the per capita bottled water consumption is still quite low - less than five litres a year as compared to the global average of 24 litres. However, the total annual bottled water consumption has risen rapidly in recent times - it has tripled between 1999 and 2004 - from about 1.5 billion litres to five billion litres.

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The rise of the Indian bottled water industry began with the economic liberalisation process in 1991. The market was virtually stagnant until 1991, when the demand for bottled water was less than two million cases a year. However, since 1991-1992 it has not looked back, and the demand in 2004-05 was a staggering 82 million cases. India is the tenth largest bottled water consumer in the world. In 2002, the industry had an estimated turnover of Rs.10 billion (Rs.1,000 crores). Today it is one of India's fastest growing industrial sectors. Between 1999 and 2004, the Indian bottled water market grew at a compound annual growth rate (CAGR) of 25 per cent - the highest in the world.

With over a thousand bottled water producers, the Indian bottled water industry is big by even international standards. There are more than 200 brands, nearly 80 per cent of which are local. Most of the small-scale producers sell non-branded products and serve small markets. In fact, making bottled water is today a cottage industry in the country. Leave alone the metros, where a bottled-water manufacturer can be found even in a one-room shop, in every medium and small city and even some prosperous rural areas there are bottled water manufacturers.

Despite the large number of small producers, this industry is dominated by the big players - Parle Bisleri, Coca-Cola, PepsiCo, Parle Agro, Mohan Meakins, SKN Breweries and so on. Parle was the first major Indian company to enter the bottled water market in the country when it introduced Bisleri in India 25 years ago.

Bottled water is sold in a variety of packages: pouches and glasses, 330 ml bottles, 500 ml bottles, one-litre bottles and even 20- to 50-litre bulk water packs. The formal bottled water business in India can be divided broadly into three segments in terms of cost: premium natural mineral water, natural mineral water and packaged drinking water.

Premium natural mineral water includes brands such as Evian, San Pelligrino and Perrier, which are imported and priced between Rs.80 and Rs.110 a litre. Natural mineral water, with brands such as Himalayan and Catch, is priced around Rs.20 a litre. Packaged drinking water, which is nothing but treated water, is the biggest segment and includes brands such as Parle Bisleri, Coca-Cola's Kinley and PepsiCo's Aquafina. They are priced in the range of Rs.10-12 a litre.

Attracted by the huge potential, that India's vast middle class offers, multinational players such as Coca-Cola and PepsiCo have been trying for the past decade to capture the Indian bottled water market.

Today they have captured a significant portion of it. However, Parle Bisleri continues to hold 40 per cent of the market share. Kinley and Aquafina are fast catching up, with Kinley holding 20-25 per cent of the market and Aquafina approximately 10 per cent. The rest, including the smaller players, have 20-25 per cent of the market share.

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market share of different companies

40%

25%

10%

25%

bisleri

kinley

aquafina

others

Consumption of bottled water in India is linked to the level of prosperity in the different regions. The western region accounts for 40 per cent of the market and the eastern region just 10. However, the bottling plants are concentrated in the southern region - of the approximately 1,200 bottling water plants in India, 600 are in Tamil Nadu. This is a major problem because southern India, especially Tamil Nadu, is water starved.

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The majority of the bottling plants - whether they produce bottled water or soft drinks - are dependent on groundwater. They create huge water stress in the areas where they operate because groundwater is also the main source - in most places the only source - of drinking water in India. This has created huge conflict between the community and the bottling plants.

Private companies in India can siphon out, exhaust and export groundwater free because the groundwater law in the country is archaic and not in tune with the realities of modern capitalist societies.

Treatment and purification account for the major cost. Even with the state-of-the-art treatment system with reverse osmosis and membranes, the cost of treatment is a maximum of 25 paise a litre (Rs.0.25/litre). Therefore, the cost of producing 1 litre of packaged drinking water in India, without including the labour cost, is just Rs.0.25. In a nutshell, in manufacturing bottled water, the major costs are not in the production of treated and purified water but in the packaging and marketing of it.

The cost of a bottle, along with the cap and the carton, is the single biggest cost - between Rs.2.50 and Rs.3.75 for a one-litre bottle. For water sold in big plastic jars (20-50 litres), which are also reused, or in pouches, this cost is much lower. It is precisely owing to this that companies sell water at even Re.1 a litre in a 20-50 litre jar and still make profits. Labour and establishment and marketing costs are highly variable and depend on the location and size of

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companies. Informal discussions with industry members reveal that the gross profit of this industry can be as much as between 25 and 50 per cent.

The reason that companies do not have to bear the cost of the main raw material - water - has made this industry highly profitable. But the real cost of the industry is huge.

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CHAPTER 4

ANALYSIS AND INTERPRRETATION

Analysis of data is a process of inspecting, cleaning, transforming, and modeling data with the goal of highlighting useful information, suggesting conclusions, and supporting decision making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.

Data mining is a particular data analysis technique that focuses on modeling and knowledge discovery for predictive rather than purely descriptive purposes. Business intelligence covers data analysis that relies heavily on aggregation, focusing on business information. In statistical applications, some people divide data analysis into descriptive statistics, exploratory data analysis, and confirmatory data analysis. EDA focuses on discovering new features in the data and CDA on confirming or falsifying existing hypotheses. Predictive analytics focuses on application of statistical or structural models for predictive forecasting or classification, while text analytics applies statistical, linguistic, and structural techniques to extract and classify information from textual sources, a species of unstructured data. All are varieties of data analysis.

SALES RECORD OF MINERAL WATER OF BHARATHI MINERAL WATER

YEARS SALES (IN lakhs)

2005 45

2006 52

2007 48

2008 55

2009 60

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2005 2006 2007 2008 20090

10

20

30

40

50

60

70

sales

ANALYSIS

The sales of Bharathi nenterprises in the year 2005 is Rs. 45,000 and there is an increase of sales upto 52,000 and there is a dip a sales to 48,000 and again there is a rise in sales to 60,000 in 2009.

INTERPRETATION

The above graph shows a fluctuations in the sales of the company due to intense competition in the market.

B. LEAST SQUARE METHOD

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CALCULATION OF LEAST SQUARE METHOD

YEARS SALES Rs. thousand (Y)

X X2 XY

2005 45 1 1 45

2006 52 2 4 104

2007 48 3 9 144

2008 55 4 16 220

2009 60 5 25 300

N=5 ∑Y=260 ∑X=15 ∑

X2=55 ∑XY=813

• The equation for the straight line trend is

Y = a + bx

a-intercept

b-shows impact of independent variable.

Therefore, the equation for the straight line trend is Y=42.1 + 3.3X

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TREND VALUES PROJECTED DEMAND

Y 2010 = 42.1+3.3(6) = 61.9

Y 2011 = 42.1+3.3(7) = 65.2

Y 2012 = 42.1+3.3(8) = 68.5

Y 2013 = 42.1+3.3(9) = 71.8

Y 2014 = 42.1+3.3(10) = 72.1

PROJECTED SALES OF BHARTHI AQUA SOLUTIONS

YEAR TREND PROJECTED SALES(IN LAKHS)

Y 2010 61.9

Y 2011 65.2

Y 2012 68.5Y 2013 71.8

Y 2014 72.1

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2010 2011 2012 2014 201556

58

60

62

64

66

68

70

72

74

SALES

ANALYSIS

The above table shows the estimated sales is in 2010 is 61.9 lakhs, in 2011 is 65.2, in 2011 it is 65.2 in 2012 it is 68.5 in 2013 it is 71.8, in 2014 it is 72.1.

INTEPRETATION

The sales of Bharathi enterprises has evidently on the growth spurt and the figures of estimated sales shows that the company will remain in good standing for next how the company will at 5 years. It depends on how the company will adapt itself with the environment and its competitors.

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SUMMARY OF FINDINGS

The sales of Bharathi aqua solutions in the year 2005 is Rs. 45 lakhs. Compare to 2005 in 2006, there is an increase in sales by 8% Compared to 2007, there is a dip in sales by 8% lakhs due to intense

competition by other already established mineral water brands. In 2008, there is an increase in sales to 55 lakhs compared to 2007. Compared to 2009, there is an increase in sales by 5% . It is seen that there are fluctuations in the sales of the company due to

intense competition in the market. The sales of Bharathi aqua solutions enterprises has evidently on the growth

spurt and the figures of estimated sales shows that the company will remain in good standing for next coming 5 years. It depends on how the company will adapt itself with the environment and its competitors.

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SUGGESTIONS

the company is facing intense competion from the already established brands like bisleri, kinley, aquafina etc therefore it has to work upon its marketing stratergies

the company has a few local permenent customers which is a big advantage of the company. it has to strenthen local customers.

the company has to expand its product line in order to survive in the market.

the company is not well known to most of the people and therefore it is one of the biggest drawbacks

CONCLUSIONS:

These are boom times for the Indian Bottled Water Industry - more so because the economics are sound, the bottom line is fat and the Indian government hardly cares for what happens to the nation's water resources.

The majority of the bottling plants - whether they produce bottled water or soft drinks - are dependent on groundwater. They create huge water stress in the areas where they operate because groundwater is also the main source - in most places the only source - of drinking water in India. This has created huge conflict between the community and the bottling plants.

Private companies in India can siphon out, exhaust and export groundwater free because the groundwater law in the country is archaic and not in tune with the realities of modern capitalist societies.

The existing law says that "the person who owns the land owns the groundwater beneath". This means that, theoretically, a person can buy one square meter of land and take all the groundwater of the surrounding areas and the law of land cannot object to it. This law is the core of the conflict between the community and

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the companies and the major reason for making the business of bottled water in the country highly lucrative.

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