SlideShare une entreprise Scribd logo
1  sur  55
Télécharger pour lire hors ligne
PROJECT INDEX


    Demand Forecasting & its need for the Project
    Research method
    Research Methodology
    DATA Collection Method, Analysis & Implementation
    Marketing
          -Marketing Planning-mission
          -Marketing Planning-vision & values
   Market Analysis –Defining the market
                         -Types of Market
   Market Research –Introduction
                         -Market Segmentation
                         -Why segment the market?
   Product –Introduction
-Product Life Cycle
   Product Analysis
   Customer or Consumer
   Competitor Analysis kind of information
                         -Role of competitor analysis
   Pricing –Introduction
   Brand
   Demand Analysis of BHEL Products & Forecasting
                    -Total demand of products in domestic market
                    -Analysis of demand in domestic market
   SWOT Analysis of BHEL
   Findings
   Limitations
   Conclusion
   Recommendation & Suggestions
   Websites visited
   Bibliography
DEMAND FORECASTING

'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. ‟


Necessity for forecasting demand

Often forecasting demand is confused with forecasting sales. But, failing
to forecast demand ignores two important phenomena

Stock effects

The effects that inventory 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 also untapped when sales for an item
are decreased due to a poor display location, or because the desired sizes
are no longer available. For example, when a consumer electronics
retailer 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 ite m 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 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.
Methods that rely on judgment


     When using judgment, rely on structured procedures such as
    Delphi, simulated interaction, structured analogies, and conjoint
    analysis. Simulated interaction is useful to predict the decisions in
    conflict situations, such as in negotiations. In addition to seeking
    good feedback, forecasters should explicitly list all the things that
    might be wrong about their forecast. This will produce better
    calibrated prediction intervals.



   Unaided judgment : It is common practice to ask experts what will
    happen. This is a good procedure to use when

        • experts are unbiased
        • large changes are unlikely
        • relationships are well understood by experts (e.g., demand
           goes up when prices go down)
        • experts possess privileged information
        • experts receive accurate and well-summarized feedback
           about their forecasts.


   Prediction market : Prediction markets, also known as betting
    markets, information markets, and futures markets have a long
    history. Despite numerous attempts since the 1930s, no methods
    have been found to be superior to markets when forecasting prices.
    However, few people seem to believe this as they pay handsomely
    for advice about what to invest in. Some commercial organizations
    provide internet markets and software that to allow participants to
    bet by trading contracts. However, there are no empirical studies
    that compare forecasts from prediction markets with those from
    traditional groups or from other methods.

   Delphi technique: The Delphi technique was developed at RAND
    Corporation in the 1950s to help capture the knowledge of diverse
experts while avoiding the disadvantages of traditional group
    meetings. The latter include bullying and time-wasting. To forecast
    with Delphi the administrator should recruit between five and
    twenty suitable experts and poll them for their forecasts and
    reasons. The administrator then provides the experts with
    anonymous summary statistics on the forecasts, and experts‟
    reasons for their forecasts. The process is repeated until there is
    little change in forecasts between rounds – two or three rounds are
    usually sufficient. The Delphi forecast is the median or mode of the
    experts‟ final forecasts.



   Game theory:Simulated interaction is a form of role playing for
    predicting decisions by people who are interacting with others. It is
    especially useful when the situation involves conflict. For example,
    one might wish to forecast how best to secure an exclusive
    distribution arrangement with a major supplier. To use simulated
    interaction, an administrator prepares a description of the target
    situation, describes the main protagonists‟ roles, and provides a
    list of possible decisions. Role players adopt a role and read about
    the situation. They then improvise realistic interactions with the
    other role players until they reach a decision; for example to sign a
    trial one-year exclusive distribution agreement. The role players‟
    decisions are used to make the forecast.

   Judgmental bootstrapping : Judgmental bootstrapping converts
    subjective judgments into structured procedures. Experts are
    asked what information they use to make predictions about a class
    of situations. They are then asked to make predictions for diverse
    cases, which can be real or hypothetical. The resulting data are
    then converted to a model by estimating a regression equation
    relating the judgmental forecasts to the information used by the .


   Simulated interaction : Simulated interaction is a form of role
    playing for predicting decisions by people who are interacting with
    others. It is especially useful when the situation involves conflict.
    For example, one might wish to forecast how best to secure an
    exclusive distribution arrangement with a major supplier. To use
    simulated interaction, an administrator prepares a description of
the target situation, describes the main protagonists‟ roles, and
    provides a list of possible decisions. Role players adopt a role and
    read about the situation. They then improvise realistic interactions
    with the other role players until they reach a decision; for example
    to sign a trial one-year exclusive distribution agreement. The role
    players‟ decisions are used to make the forecast.


   Intentions and expectations surveys : With intentions surveys,
    people are asked how they intend to behave in specified situations.
    In a similar manner, an expectations survey asks people how they
    expect to behave. Expectations differ from intentions because
    people realize that unintended things happen



   Conjoint analysis : By surveying consumers about their
    preferences for alternative product designs in a structured way, it
    is possible to infer how different features will influence demand.




              Methods that rely on quantitative data

    With the proliferation of data, causal models play an increasingly
    important role in forecasting market size, market share, and sales.
    Methods should be developed primarily on the basis of theory, not
    data. Finally, efforts should be made to ensure forecasts are free of
    political considerations in a firm. To help with this, emphasis
    should be on gaining agreement about the forecasting methods.
    Also, for important forecasts, decisions on their use should be
    made before the forecasts are provided. Scenarios are helpful in
    guiding this process.



   Extrapolation : Extrapolation methods use historical data on that
    which one wishes to forecast. Exponential smoothing is the most
    popular and cost effective of the statistical extrapolation methods.
    It implements the principle that recent data should be weighted
more heavily and „smoothes‟ out cyclical fluctuations to forecast
    the trend. To use exponential smoothing to extrapolate, the
    administrator should first clean and deseasonalise the data, and
    select reasonable smoothing factors. The administrator then
    calculates an average and trend from the data and uses these to
    derive a forecast .



   Quantitative analogies : Experts can identify situations that are
    analogous to a given situation. These can be used to extrapolate
    the outcome of a target situation. For example, to assess the loss
    in sales when the patent protection for a drug is removed, one
    might examine the historical pattern of sales for analogous drugs.
    To forecast using quantitative analogies, ask experts to identify
    situations that are analogous to the target situation and for which
    data are available



   Rule-based forecasting : Rule-based forecasting (RBF) is a type of
    expert system that allows one to integrate managers‟ knowledge
    about the domain with time-series data in a structured and
    inexpensive way. For example, in many cases a useful guideline is
    that trends should be extrapolated only when they agree with
    managers‟ prior expectations


   Neural networks : Neural networks are computer intensive
    methods that use decision processes analogous to those of the
    human brain. Like the brain, they have the capability of learning
    as patterns change and updating their parameter estimates.
    However, much data is needed in order to estimate neural network
    models and to reduce the risk of over-fitting the data (Adya and
    Collopy 1998).
   Data mining : Data mining uses sophisticated statistical analyses
    to identify relationships. It is a popular approach. Data mining
    ignores theory and prior knowledge in a search for patterns.
    Despite ambitious claims and much research effort, we are not
    aware of evidence that data mining techniques provide benefits for
    forecasting.


   Causal models : Causal models are based on prior knowledge and
    theory. Time-series regression and cross-sectional regression are
    commonly used for estimating model parameters or coefficients.
    Causal models are most useful when (1) strong causal
    relationships are expected, (2) the direction of the relationship is
    known, (3) causal relationships are known or they can be
    estimated, (4) large changes are expected to occur in the causal
    variables over the forecast horizon, and (5) changes in the causal
    variables can be accurately forecast or controlled, especially with
    respect to their direction. Reviews of commercial software that can
    be used to develop causal models are provided at the
    forecastingprinciples.com site.

   Segmentation :Segmentation involves breaking a problem down
    into independent parts, using data for each part to make a
    forecast, and then combining the parts. For example, a company
    could forecast sales of wool carpet separately for each climatic
    region, and then add the forecasts.
NEED FOR MARKETING FORECASTING
CONCLUSIONS FOR DEMAND FORECASTING


Significant gains have been made in forecasting for marketing, especially
since 1960. Advances have occurred in the development of methods
based on judgment, such as Delphi, simulated interactions, intentions
studies, opinions surveys, bootstrapping, and combining. They have also
occurred for methods based on statistical data, such as extrapolation,
rule-based forecasting, and econometric methods. Most recently, gains
have come from the integration of statistical and judgmental forecasts.

General principles
  • Managers‟ domain knowledge should be incorporated into
     forecasting methods.
  • When making forecasts in highly uncertain situations, be
     conservative. For example, the trend should be dampened over the
     forecast horizon.
  • Complex methods have not proven to be more accurate than
     relatively simple methods. Given their added cost and the reduced
     understanding among users, highly complex procedures cannot be
     justified.
  • When possible, forecasting methods should use data on actual
     behaviour, rather than judgments or intentions, to predict
     behaviour.
  • Methods that integrate judgmental and statistical data and
     procedures (e.g., rule-based forecasting) can improve forecast
     accuracy in many situations.
  • Overconfidence occurs with quantitative and judgmental methods.
  • When making forecasts in situations with high uncertainty, use
     more than one method and combine the forecasts, generally using
     simple averages.

Methods based on statistical data
RESEARCH METHODS

I- Why Are Research Methods Important?

Science, at a basic level attempts to answer questions (such as “why are
we aggressive) through careful observation and collection of data. These
answers can then (at a more complex or higher level) are used to further
our knowledge of us and our world, as well as help us predict
subsequent     events     and    behavior.   But,    this   requires   a
systematic/universal way of collecting and understanding data –
otherwise there is chaos.

At a practical level, methodology helps us understand and evaluate the
merit of all the information we‟re confronted with every day. For example,
do you believe in the following studies?

      Study indicated that the life span of left-handed people is
       significantly shorter than those who are right hand dominant.

      Study demonstrated a link between smoking and poor grades.

There are many aspects of these studies that are necessary before one
can evaluate the validity of the results. However, most people do not
bother to find out the details (which are the keys to understanding the
studies) but only pay attention to the findings, even if the findings are
completely erroneous.


They are also practical in the workplace

      Mental Health Profession – relies on research to develop new
       therapies, and learn which therapies are appropriate and effective
       for different types of problems and people.

      Business World       –   marketing   strategies,   hiring,   employee
       productivity, etc.


II- Different Types of Research Methods

          Basic Research
          Applied Research
          Program Evaluation
III- How Do Non-Scientists Gather Information?

  We all observe our world and make conclusions. How do we do this:

     Seek an authority figure
     Intuition


IV- THE SCIENTIFIC METHOD

B. Why of Conducting Scientific Research

     Naturalistic Observation
     Case Study
     Survey
     Psychological Testing
     Experimental Research
Research Methodology


      Type or research ---------------- Exploratory Research
                                           Design.

      Method of Research------------- Data collection Method
       Through Customer enquiries
        Receive for submission of
       Tender from domestic market.


   Sampling method ---------------Through         statistical   and
Judgement method (Regression)

      Sampling unit--------------------BHEL Jhansi.

    Sampling element transformer------Power transformer,
                                       Dry Type, Instrument & HVR
Transformers.




DATA COLLECTION


There are very few hard and fast rules to define the task of data
collection. Each research project uses a data collection technique
appropriate to the particular research methodology. The two primary
goals for both quantitative and qualitative studies are to maximize
response and maximize accuracy.

When using an outside data collection service, researchers often validate
the data collection process by contacting a percentage of the respondents
to verify that they were actually interviewed. Data editing and cleaning
involves the process of checking for inadvertent errors in the data. This
usually entails using a computer to check for out-of-bounds data. Here
which I collected the datas from enquiry records & annual reports of
BHEL are mainly secondary data set.
DATA ANALYSIS


Modern computer software has made the analysis of quantitative data a
very easy task. It is no longer incumbent on the researcher to know the
formulas needed to calculate the desired statistics. However, this d oes
not obviate the need for the researcher to understand the theoretical and
conceptual foundations of the statistical techniques. Each statistical
technique has its own assumptions and limitations. Considering the ease
in which computers can calculate complex statistical problems, the
danger is that the researcher might be unaware of the assumptions and
limitations in the use and interpretation of a statistic.




DATA IMPLEMENTATION



The most important consideration in preparing any research report is the
nature of the audience. The purpose is to communicate information, and
therefore, the report should be prepared specifically for the readers of the
report. Sometimes the format for the report will be defined for the
researcher (e.g. a dissertation), while other times, the researcher will
have complete latitude regarding the structure of the report. At a
minimum, the report should contain an abstract, problem statement,
methods section, results section, discussions of the results, and a list of
references.
MARKETING


There are many definitions of marketing. Consider some of the following
alternative definitions:

“The all-embracing function that links the business with customer
needs and wants in order to get the right product to the place at the
right time”.

“The achievement of corporate goals through meeting                            and
exceeding customer needs better than the competition”.

“The management process that identifies anticipates and supplies
customer requirements efficiently and profitably”.

“Marketing may be defined as a set of human activities directed at
facilitating and consummating exchanges”




     Marketing


             Why is the business’ attitude to marketing?
                             Marketing Orientation



                            Gain information on             Persuade
         Market                   The market:              customers to buy:
         Analysis            Market Research                Marketing Mix

                                    Quantitative                  Product
    Market Analysis                  Analysis
                                                              Price
        Market                   Qualitative
     Segmentation                    Analysis
                                                              Place
     Marketing
      Strategy                   Consumer
                                      Tests                   Promotion
Five Successful Marketing Techniques


1. Keep Adding Something New:
Every time you add something new to your business you create an
opportunity to get more sales. For example, something as simple as adding
new information on your web site creates another selling opportunity when
prospects and customers visit your site to see the new information.

  Adding a new product or service to the list of those you already offer
usually produces a big increase in sales. The added product increases your
sales in 3 different ways:

      It attracts mew customers who were not interested in your current
       products and services.

      It generates repeat sales from existing customers who also want to
       have your new product.

      It enables you to get bigger sales by combing two or more items into
       special package offers.


2. Become a Valuable Resource:
 Look for ways you can be a resource for your prospects and customers.
Supply them with free information. Help them do things faster, easier, less
expensively. You get another opportunity to sell something every time they
come back to you for help.


3. Separate Yourself from Your Competition:
 Find or create a reason for customers to do business with you instead of
with someone else offering the same or similar products. For example, do
you provide faster results, easier procedures, personal attention or a better
guarantee?

 Determine the unique advantage you offer to customers that your
competitors do not offer. Promote that advantage in all of your advertising.
Give your prospects a reason to do business with you instead of with your
competition and you‟ll automatically get more sales.




4. Promote the End Result:
Your customers don‟t really want your product
or service. They want the benefit produced by using it.

       For example, car buyers want convenient transportation with a
certain image. Dental patients want healthy and good-looking teeth without
suffering any pain. Business opportunity seekers want personal and
financial freedom for themselves and their family.

  Make sure your web pages, sales letters and other sales messages are
promoting the end result your customers want.


5. Anticipate Change:
                      Change is the biggest challenge to your business
success. The days are gone when a business could constantly grow by
simply repeating what It did successfully in the past… or even recently.
Aggressive, innovative competitors and rapidly changing technology make it
impossible.

 Expect change and prepare for it. Don‟t wait until your income declines to
take action. Develop the habit of looking for early signs that something is
changing. Then confront it before you start to lose business.


Tip:Insulate yourself against the impact of change by increasing the number
of products and services you offer and by using a variety of different
marketing methods. Only a small portion of your total business will be
affected if the sales of one product decline or the response to one marketing
method drops.




Marketing planning – Mission
Mission

“A mission describes the organization‟s basic function in society, in
terms of the products and services it produces for its customers”.

A clear business mission should have each of the following elements:




                          Purpose
                             Why the business
                          exists


 Strategy&
       Scope                                               Values
    What business                                     What management
 and how                                                Believes in



                             Standards &
                              Behaviors
                           The rules that guide
                          how the business
                          operates




            Marketing Planning – Values & Vision
Values from the foundation of a business management style.

Values provide the justification of behavior and, therefore, exert significant
influence on marketing decisions.




Market analysis – defining the market


All business operates in “markets”. But what is a market?
And how can it be defined?

Traditionally, a “market” was a physical place where buyers and sellers
gathered to buy and sell goods. Economists describe a market as a collection
of buyers and sellers who transact over a particular product or product
class (such as the housing market or the grain market).

 It is important to be careful about how a market is defined. The following
key marketing process relies on a relevant definition:

      Measuring market share
      Measuring market size and growth
      Specifying target customers
      Identifying relevant competitors
      Formulating a marketing strategy

A market can be defined as follows:

A market is the set of all actual and potential buyers of a product or
service.




Five basic markets & their connecting flows:
Resource
                   Market




Manufacturer                   Consumer
                  Government
 Market                          Market
                     Market




               Intermediary
                      Market
Types of market



Markets can be analysis via the product itself, or end-consumer, or both.
The most common distinction is between consumer and industrial
markets.



Consumer Markets
Consumer markets are the markets for products and services bought by
individuals for their own or family use. Goods bought in consumer markets
can be categorized in several ways:

    Fast-moving consumer goods (“FMCGs”)

    Consumer durables

    Soft goods


Industrial Markets

Industrial markets involve the sale of goods between business. These are
goods that are not aimed directly at consumers.
Industrial markets include

   Selling finished goods
Examples-office furniture, computer systems

   Selling raw materials or components
Example-steel, coal, gas timber

   Selling services to businesses
Example-waste disposal, security, accounting &legal services
MARKET RESEARCH

Market research answers questions in respect of different markets. The
purpose of this research is to gather facts about markets and the forces
operating therein, like competitors and government, so as to enhance the
competitive strength of the company in the market place. The areas of
market research broadly include:


   Determine the size of both current and potential market.

   Assessing the market trends.

   Ascertaining the strengths and weaknesses of competitors‟ marketing
    strategies.

   Determining the impact of current and contemplated legislative
    actions of the state on the marketing effort of the company.

   Demand and sales forecasting.




                  Market Segmentation


“Market Segmentation is the division of a market into those
subgroups which have special needs & preferences & which represent
sufficient pockets of demand to justify separate marketing
strategies”.

The concept of market segmentation is based on the fact that markets are
heterogeneous.

Bases for Segmentation

The major segmentation variables are:

  1.   Geographic segmentation
  2.   Demographic segmentation
  3.   Psychographic segmentation
  4.   Behavior segmentation
1. Geographic segmentation:
                               Geographic segmentation calls for division
of the market into different geographic units such as nation, states, regions,
countries, cities, neighbourhood, density of city, climate, etc.


   2. Demographic segmentation:
                               In demographic segmentation, we divide the
   market into groups on the basis of variables such as age, family size,
   gender, income, occupation, education religion, generation, nationality,
   etc.
    One reason, demographic variables are so popular with marketers is that
   they‟re often associated with consumer needs & wants. Another is that
   they‟re easy to measure.


   3. Psychographic segmentation:
                              Psychographics is the science of using
   psychology & demographics to better understand consumers. In
   Psychographic segmentation, buyers are divided into different groups on
   the basis of psychological/personality traits. Such as lifestyle, values,
   social class, etc.

   4. Behavior segmentation:
                              In Behavior segmentation, marketers divide
   buyers into groups on the basis of -use occasion, benefit sought, usage
   rate, loyalty status, readiness to purchase, attitude toward product, user
   status, etc.


Why Segment Market?


   There are several important reasons why business should attempt to
   segment their market carefully. These are summarized below:

   1.   Enhanced profits for business.
   2.   Better opportunities for growth.
   3.   Retain more customers.
   4.   Target marketing communications.
   5.   Gain share of the market segment.
Products – Introduction

A product is defined as:

“Anything that is capable of satisfying customer needs”


A product group (or product line) is a group of brands that are closely
related in terms of their functions and the benefits they provide (e.g. Dell‟s
range of personal computers or Sony‟s range of televisions).


There are two main types of product brand:

   (1) Manufacture brands
   (2) Own-label brands

Manufacturer brands are created by producers and use their chosen brand
name. The producer has the responsibility for marketing the brand, by
building distribution and gaining customer brand loyalty. Good examples
include Microsoft, Panasonic and Mercedes.

Own-label brands are created and owned by distributions.
Good examples include Tesco and Sainsbury‟s

Business need to regularly look for new products and markets for future
growth. A useful way of looking at growth opportunities is the An off Growth
matrix which suggests that there are four main ways in which growth can be
achieved through a product strategy:


   (1) Market penetration- Increase sales of an existing product in an
       existing market.

   (2) Product development – Improve present products and/or develop new
       products for the current market.


   (3) Market development – Sell existing products into new markets (e.g.
       developing export sales).

   (4) Diversification– Develop new products for new markets.
Products – Product life cycle


We define a product as “anything that is capable of satisfying customer
needs. This definition includes both physical products (e.g. cars, washing
machines, DVD players) as well as services (e.g. insurance, banking, private
health care).

Business should manage their products carefully over time to ensure that
they deliver products that continue to meet customer wants. The process of
managing groups of brands and product lines is called portfolio planning.

The stages through which individual products develop over time is called
commonly known as the “Product Life Cycle”.

The classic product life cycle has four stages (illustrated in the diagram
below): introduction; growth; maturity and decline




Introduction Stage
A period of slow sales growth as the product is introduced in the market.
Profits are non-existent because of the heavy expenses of product
introduction.




Growth Stage
The Growth Stage is characterized by rapid growth in sales and profits.

Maturity Stage

 The Maturity Stage is, perhaps, the most common stage for all markets, it is
in this stage that competition is most intense as companies fight to maintain
their market share.


Decline Stage

In the Decline Stage, the market is shrinking, reducing the overall amount
of profit that can be shared amongst the remaining competitors.



Object of Product Analysis

A Product Analysis refers to the study of:
   a) The raw materials used
   b) Components,
   c) Features like shape, size, colour, weight, design, etc.
   d) The merits of the product- its convenience, portability, style, comfort,
      durability, wholesomeness or purity.
   e) Packing.
   f) Branding

   Product Analysis


Those who are in the business of marketing, industrial products should be
continuously on the lookout of modifications in the existing products with a
view to:
 (a) improving the quality & functional performance of the products and
(b) ensuring that the products fulfills the changing requirements of the
customers.
The industrial marketers may also have to concern himself with the end
product and the profitability of his customer and if possible suggest to him
how these could be improved.

For this purpose, the Industrial Marketer will have to continuously subject
his own products to marketing research – to product analysis and to new
product ideas in particular. Product Analysis of his existing products would
include the study of the following aspects of his products:


 i.   Field performance of the products, and the quality, purity, fineness,
      etc. of the materials and parts used in their manufacture.
ii.   Design of the product and features like size, shape, weight,
       applicability, interchangeability, etc.


iii.   Benefits like convenience of operating or using, durability, portability,
       etc.

iv.    Other special features or benefits if any.


Since industrial customers are usually fewer, large, and geographically
concentrated, the problems relating to large populations and large territories
in the selection of a sample would get reduced. In some cases the number of
customers might be so few and well listed in the company record according
to area, type of business, sales turnover, etc.; that sample selection will be
much easier.




Customers or Consumers?

A common question that arises when studying marketing is the following:

What is the difference between a customer and a consumer?

The following distinction should help:

      A Customer – purchases and pays for a product or service.

      A Consumer – is the ultimate user of the product or service, the
       consumer may not have paid for the product or service.

Consider the following example:

      A Food manufacturing business makes own-label, Italian ready
       meals for the major supermarkets.

So far as the business is concerned, the customer is the supermarket to
whom it supplies meals.

      The consumer is the individual who eats the meal.

In terms of its marketing effort, who should the business above target?

In reality – it needs to understand the needs and wants of both the customer
and the consumer.
It needs to develop a strong understanding of the needs of the supermarkets
in terms of their requirements for ready meals (e.g. packaging, recipes, price
and delivery).

It also needs to understand (perhaps with the help of the supermarkets) the
needs and wants of the consumer. How are tastes changing? Are consumers
happy with the standard/taste of the product?




        Competitors analysis – kinds of
Information

The tables below lists the kinds of competitors‟ information that would help
business complete some good quality competitor analysis.

What business probably already know their competitors

Overall sales and profits
Sales and Profits by market
Sales by main brand
Cost structure
Market shares (revenues and volumes)
Organization Structure
Distribution system
Identity/profile of senior management.
The diagram below shows the impact of varying levels of competitor action
on the profits of a business:




                                         Weak competitors response



   Annual
   profits                               Moderate competitors response



                                         Strong competitor response




Role of competitor analysis



Competitor analysis has several important roles in marketing:

      To    help     management       understand       their            competitive
       advantages/disadvantages relative to competitors.

      To generate understanding of competitor‟s past, present (and most
       importantly) future strategies.

      To provide an informed basis to develop strategies to achieve
       competitive advantage in the future.

      To help forecast the returns that may be made from future
       investments (e.g. how will competitors respond to a new product or
       pricing strategy)?

What questions should be asked when undertaking competitor analysis?
The following is a useful list to bear in mind:

Who are our competitors? (See the section on identifying compe titors further
below)
What threats do they post?

What is the profile of our competitors?

What are the objectives of our competitors?

What strategies are our competitors pursuing and how successful are these
strategies?

What are the strength and weaknesses of our competitors?

How are our competitors likely to respond to any changes to the way we do
business?




Pricing – Introduction


Setting the right price is an important part of effective marketing. It is the
only part of the marketing mix that generates revenue (product, promotion
and place are all about marketing costs).

Price is also the marketing variable that can be changed most quickly,
perhaps in response to a competitor price change.

Put simply, price is the amount of money or goods for which a thing is
bought or sold.

 The price of a product may be seen as a financial expression of the value of
that product.

For a consumer, price is the monetary expression of the value to be enjoyed/
benefits of purchasing a product, as compared with other available items.

The concept of value can therefore be expressed as:

(Perceived)     VALUE = (perceived)           BENEFITS -        (perceived)
COSTS

A Customer‟s motivation to purchase a product comes firstly from a need
and a want: e.g.
   Need: “I need to eat.
      Want: I would like to go out for a meal tonight”

The second motivation comes from a perception of the value of a product in
satisfying that need/want (e.g. “I really fancy a McDonalds”).

The perception of the value of a product varies from customers to customer,
because perceptions of benefits and costs vary.

Perceived benefits are often largely dependent on personal taste (e.g. spicy
versus sweet or green verses blue). In order to obtain the maximum possible
value from the available market, business try to „segment‟ the market – that
is to divide up the market into groups of consumers whose preferences are
broadly similar – and to adapt their products to attract these customers.

In general a products perceived value may be increased in one of two ways –
either by:

   (1) Increasing the benefits that the product will deliver, or,
   (2) Reducing the cost.

For consumers, the PRICE of a product is the most obvious indicator of cost
– hence the need to get product pricing right.


Factors Affecting Demand:

Consider the factors affecting the demand for a product that are:

   (1) Within the control of a business and
   (2) Outside the control of a business.


Factors within a business control include:

      Price (assuming an imperfect market – i.e. not perfect competition).
      Product research and development.
      Advertising & Sales promotion.
      Training and organization of the sales force
      Effectiveness of distribution (e.g. access to retail outlets; trained
       distributor agents)
      Quality of after-sales services (e.g. which affects demand from repeat-
       business)



Factors outside the control of business include:
   The price of substitute goods and services.
      The price of complementary goods and services.
      Consumer‟s disposable income.
      Consumer tastes and fashions.


Price is therefore, a critically important element of the choices available to
businesses in trying to attract demand for their products.



BRANDS

Meaning of brands

Brands are a mean of differentiating a company‟s products and services
from those of its competitors.

There is plenty of evidence to prove that customers will pay a substantial
price premium for a good brand and remain loyal to that brand. It is
important, therefore, to understand what brands are and why they are
important.

“…. It is not factories that make profits, but relationships with
customers and it is company and brand names which secure those
relationships”.

Businesses that invest in and sustain leading brands prosper whereas those
that fail are left to fight for the lower profits available in commodity markets.
What is brand?

One definition of a brand is as follows:

“A name, term, sign, symbol or design, or a combination of these, that
is intended to identified the goods and services of one business or
group of businesses and to differentiated them from those of
competitors”.

Interbrand – a leading branding consultancy – defines a brand in this way:

“A mixture of tangible and intangible attributes symbolized in a
trademark, which if properly managed, creates influence and
generates value”.

Three other important terms relating to brands should be defined at this
stage:


      Brand equity
      Brand image
      Brand extension
      Brands and products
Analysis of Demand for transformers in Domestic
market of BHEL Jhansi Unit


The demand forecasting for the organizations like Bharat Heavy Electricals
Ltd.(BHEL), Jhansi is of great importance because it involves a big amount
of working capital. If we have some predictions about the future demand of
transformers we can make better plan for production to ensure the delivery
of right product at right time and at the right place. The demand forecasting
also helps to make allotment of proper working capital.

         The method used for demand forecasting is REGRESSION
ANALYSIS. This method is very useful for making demand forecast for the
product/products which have actually increasing trend of demand but
forecast goes downward or, conversely the trend for demand is downward
and the forecast goes upward. To minimize this effect a factor is added. This
procedure adjusts the forecast according to the trend. It has been observed
that the values of forecast come pretty close to the actual values.




REGRESSION METHOD


Meaning & Definition

The measurement of the mutual relations of two or more variables is got by
regression. Commonly, the question arises if there is some relation between
the weight and height of an infant, can its weight be calculated or if we
know its age can by this other magnitudes of it be declared .Can the
quantity of demand and supply be known for a definite value. What will be
the effect on the consumption quantity, if the tax on intoxicant is doubled.
For this & for many other measurements of relations the method of
regression is used.


According to Blair, “Regression is the measure of the average
relationship between two or more variables in the terms of the original
units of data”.
“In more popular sense we may call regression a trend, a line which
shows how many units of change in one variable are associated with
one unit of change in another Variable.”

According to Yule & Kendall, “The term regression is not a particular
happy one from the etymological point of view, but it is so firmly
embedded in statistical literature that we make no attempt to replace.
In general, the idea ordinarily attached to the word „regression, does
not touch upon the connotation, & it should be regarded merely a
convenient term”.


UTILITY OF REGRESSION


  1. To forecast the probable value : In the analytical studies of different
     kinds, there is great value of regression. By it we can know that if out
     of the two connected series the value of one has been given what may
     possibly be the value of the other series connected with it. If the rate
     of pay scale is increased what will be its effect on the efficiency; there
     having been an increase in the common price level how much will
     there be a change in the life leading expenditure, increase or decrease
     in the study will how much effect the result of student etc. are many
     questions that can be satisfactorily answered by regression method.

  2. To Know the Correlation & Co-Variation:              With the help of
     regression the correlation between the two series can be known. If the
     two lines of regression cover each other the correlation between the
     two series is complete but if they cross each other at 90˚ angle, the
     correlation is cipher. The more are the lines of regression inclined
     towards each, the quantity of correlation is the greater.
     When the two lines rise from the lower left to right upper the
     correlation is positive but opposite to it when the lines move from
     upper to the lower side the correlation is negative. Co-Variation too
     can be known by it.
TOTAL DEMAND OF PRODUCT (TRANSFORMERS)
       IN DOMESTIC MARKET (FROM YEAR 2005-2012)



YEAR      POWER         DRY-TYPE      INSTRUMENT    HVR
          TRANSFORMER   TRANSFORMER   TRANSFORMER   TRANSFORMER
2005-06   842           335           6822          1149
2006-07   948           873           7419          3684
2007-08   760           1200          5875          4611
2008-09   1192          927           10715         2803
2009-10   1150          794           8845          3043
2010-11   975           708           9702          4289
2011-12   855           769           7178          2451
FORMULAS USED IN REGRESSION:




x= Mean for the number of years used.

y= Mean for the demand collected in quantity.

X= Number of years used.

Y= Number of demands collected.

{Y= a+b*x} where a, b are constants & Y shows the trend for
demand.

b= sum(X-x)(Y-y)/sum(X-x)^2

a=y-b*x
TOTAL DEMAND OF BHEL PRODUCTS
IN DOMESTIC MARKET




POWER     TRANSFORMER

YEAR      X         Y           X-x         (X-x)^2        Y-y          (X-x)(Y-y)   Y=a+bx


2005-06        1         842           -3             9          -118          354        908
2006-07        2         948           -2             4           -12           24        925
2007-08        3         760           -1             1          -200          200        942
2008-09        4        1192            0             0           232            0        959
2009-10        5        1150           1              1          190           190        976
2010-11        6         975           2              4           15            30        993
2011-12        7         855           3              9          -105         -315       1010


               4         960                          28                       483

          b=            17.25          17
          a=              891         891


DEMAND    FORECAST

YEAR      X         Y


2012-13        8        1027
2013-14         9       1044
2014-15        10       1061
2015-16        11       1078
2016-17        12       1095
DEMAND
1400

1200

1000

 800

 600                                                             DEMAND
 400

 200

   0
       2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12




                  DEMAND FORECASTED
1120

1100

1080
1060

1040                                                   DEMAND FORECASTED
1020
1000

 980
       2012-13 2013-14 2014-15 2015-16 2016-17
1400

1200

1000

 800
                                                                    DEMAND
 600
                                                                    TREND
 400

 200

   0
       2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12




                      DEMAND FORECAST
1120

1100

1080

1060
1040                                                        DEMAND FORECAST
1020

1000

 980
        2012-13 2013-14 2014-15 2015-16 2016-17
DRY       TYPE        TRANSFORMER

YEAR             X            Y         X-x       (X-x)^2       Y-y     (X-x)(Y-y)   Y=a+bx


2005-06           1               335     -3                9    -466        1398        899
2006-07           2               873     -2                4      72        -144        919
2007-08           3              1200     -1                1     399        -399        939
2008-09           4               927      0                0     126           0        959
2009-10           5               794         1             1      -7           -7       979
2010-11           6               708         2             4     -93         -186       999
2011-12           7               769         3             9     -32          -96      1019

                  4               801                   28                     566


                 b=         20.21429      20
                 a=         879.1429     879


DEMAND           FORECAST

YEAR             X           Y


2012-13           8              1039
2013-14           9              1059
2014-15          10              1079
2015-16          11              1099
2016-17          12              1119
DEMAND
1400

1200

1000

 800

 600                                                             DEMAND
 400

 200
   0
       2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12




                   DEMAND FORECASTED
1140
1120
1100
1080
1060
                                                       DEMAND FORECASTED
1040
1020
1000
 980
       2012-13 2013-14 2014-15 2015-16 2016-17
1400

1200

1000

 800
                                                              TREND
 600
                                                              DEMAND
 400

 200

   0
       2005-062006-072007-082008-092009-102010-112011-12




                    DEMAND FORECAST
1140
1120
1100
1080
1060
                                                      DEMAND FORECAST
1040
1020
1000
 980
       2012-13 2013-14 2014-15 2015-16 2016-17
INSTRUMENT TRANSFORMER

YEAR       X             Y       X-x       (X-x)^2   Y-y      (X-x)(Y-y)   Y=a+bx


2005-06     1            6822      -3            9    -1257        3771        7157
2006-07     2            7419      -2            4     -660        1320        7464
2007-08     3            5875      -1            1    -2204        2204        7771
2008-09     4           10715          0         0    2636             0       8078
2009-10     5            8845          1         1     766          766        8385
2010-11     6            9702          2         4    1623         3246        8692
2011-12     7            7178          3         9     -901       -2703        8999


            4            8079                   28                 8604


           b=         307.2857    307
           a=         6849.857   6850


DEMAND     FORECAST


YEAR       X             Y


2012-13     8            9306
2013-14     9            9613
2014-15    10            9920
2015-16    11           10227
2016-17    12           10534
DEMAND
12000

10000

8000

6000
                                                                  DEMAND
4000

2000

   0
        2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12




                   DEMAND FORECASTED
10800
10600
10400
10200
10000
 9800
 9600                                                   DEMAND FORECASTED
 9400
 9200
 9000
 8800
 8600
        2012-13 2013-14 2014-15 2015-16 2016-17
12000

10000

8000

6000
                                                          TREND
4000                                                      DEMAND

2000

   0




                    DEMAND FORECAST
10800
10600
10400
10200
10000
 9800
 9600                                             DEMAND FORECAST
 9400
 9200
 9000
 8800
 8600
        2012-13 2013-14 2014-15 2015-16 2016-17
HVR       TRANSFORMER

YEAR       X            Y       X-x    (X-x)^2   Y-y     (X-x)(Y-y)   Y=a+bx


2005-06        1        1149      -3         9   -1998        5994        2767
2006-07        2        3684      -2         4    537        -1074        2894
2007-08        3        4611      -1         1   1464        -1464        3021
2008-09        4        2803      0          0    -344            0       3148
2009-10        5        3043      1          1    -104        -104        3275
2010-11        6        4289      2          4   1142         2284        3402
2011-12        7        2451      3          9    -696       -2088        3529


               4        3147                28                3548


          b=         126.7143   127
          a=         2640.143   2640


DEMAND    FORECAST


YEAR       X            Y


2012-13        8        3656
2013-14        9        3783
2014-15    10           3910
2015-16    11           4037
2016-17    12           4164
DEMAND
5000
4500
4000
3500
3000
2500
2000                                                             DEMAND
1500
1000
 500
   0
       2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12




                   DEMAND FORECASTED
4300
4200
4100
4000
3900
3800                                                   DEMAND FORECASTED
3700
3600
3500
3400
       2012-13 2013-14 2014-15 2015-16 2016-17
5000
4500
4000
3500
3000
2500                                                          TREND
2000                                                          DEMAND
1500
1000
 500
   0
       2005-062006-072007-082008-092009-102010-112011-12




                    DEMAND FORECAST
4300
4200
4100
4000
3900
3800                                                  DEMAND FORECAST
3700
3600
3500
3400
       2012-13 2013-14 2014-15 2015-16 2016-17
Analysis of Demand in Domestic Market

1. Power Transformer:-
It is clear from data and graph that the demand of power transformer is
fluctuating in nature. In 2005 to 2012, demand was 842, 948, 760, 1192,
1150, 975 & 855 in quantity. The reasons for fluctuating & decrease in
trend from 2008-12 may be due to role of recession, FDI, China equipment‟s
are imported & tenders go to Foreign market so no role for Indian parties to
involve for demand.
                   After Forecasting, from 2012-2017, the demand is
continuously increasing in a very small amount (1027, 1044, 1061, 1078 &
1095) in quantity.

2. Dry Type Transformer:-
In this type of transformer, In 2005 to 2012, the actual demand was 335,
873, 1200, 927, 794, 708 & 769 in quantity. The reasons for fluctuating
nature in trend from 2005-12 may be due to role of recession, FDI, China
equipment‟s are imported, costlier design so less demand & no coils filled so
less dangerous used mainly in Small scale industries, Townships etc., so
more demand for Dry Type Transformers.
                    After forecasting, from 2012-2017, the demand is
continuously increasing in a very small amount (1039, 1059, 1079, 1099 &
1119) in quantity.

3. HVR Transformer:-
In this type of transformer, In 2005 to 2012, the actual demand was 1149,
3684, 4611, 2803, 3043, 4289 & 2451 in quantity. The reasons for
fluctuations may be due to role of recession, FDI, China equipment‟s are
imported & technology has changed drastically.
          After forecasting, In 2012-17 the demand is increasing
continuously increasing in good amount (3656, 3783, 3910, 4037 & 4164)
in quantity.

4. Instrument Transformer:-
                              In this type of transformer, In 2005 to 2012,
the actual demand was 6822, 7419, 5875, 10715, 8845, 9702 & 7178 in
quantity. The reasons for fluctuations may be due to role of recession, FDI,
China equipment‟s are imported, decrease in trend due to Indian market
tenders doesn‟t float and it goes to Foreign market & less technological.
Increase trend shows indications of power shortage increase, population
increase, more standard of living so more power instruments are required &
some new customers are coming up due to liberalization of Govt. policies for
captive power plant.
        After forecasting, from 2012 to 2017, the demand is continuously
increasing in a very large amount (9306, 9613, 9920, 10227 & 10534) in
quantity.
SWOT ANALYSIS OF BHEL

STRENGTH:-

  1. Manufacturing Capacity:- The manufacturing capacity of BHEL is
     105 transformer per year . However the demand in market is 900 per
     year.
  2. Mixed Product:- BHEL manufacture mixed product such as power
     transformers, DTT , INST transformer, HVR, etc. That‟s why it can
     meet mixed demand also compared to other manufacturers
  3. EPC contractor (Engineering Procurement & Construction):- It
     has 14 manufacturing units. BHEL can design, procure raw material
     & do construct transformers.

WEAKNESS:-

 1. Long Procurement Cycle:- Being a Government organization
    everything is goes in a systematic manner & it takes more & more
    time.
 2. Delay in Response:- Because of long procurement cycle the response
    is also delay.

OPPORTUNITY:-

 1. High Demand:- Because of high demand it can takes more orders &
    do more business.
 2. It is established supplies so some government parties also prefer BHEL
 3. Being an EPC Contractor it can get more EPC contract.
 4. Joint Venture with Siemens in the name of Power Plant Performance
    Improvement Limited (PPIL), is a major strength for the company. This
    tie-up will be beneficial as there is a lot of scope for business.

THREAT:-

 1. Competition with Siemen‟s, Vijay, BL, EMG, etc.
 2. New entrance of Firms in Market Such as Kanohar, Victory, IMP, ECE,
    etc.
FINDINGS


  A Demand of BHEL Transformers has been increased in the last two
   years.



  Less technological in comparison to their competitors.



  At this time BHEL has good number of customers, this shows the
   progress of BHEL in the near future.
LIMITATIONS



Nobody is perfect in the world. Everybody makes some mistakes. If
somebody doesn‟t makes mistakes that means he or she doesn‟t work
because when you do some work you are bound to make some mistakes &
there is always room for improvements. So this study may also not be free of
mistakes. But I have tried my level best to make this project BEST. There
may be some mistakes in this study. They may be as follows:-




    The DATA has been mainly collected from Transformer & Commercial
     Department (TRC) of BHEL Jhansi, mainly it comes under the
     SECONDARY DATA (from BHEL annual reports, records & books)
CONCLUSION


After studying and analyzing various aspects of this project, I have
concluded that I have gained lot of knowledge about this unit and BHEL
Company. My project which is based on the topic of “Demand Analysis of
Transformers” is based the export-import procedure and demand analysis
of BHEL.


During my training period I have done rotation work in which I know about
its working routine and collected lots of information about its product like
transformers and Locomotive. I have done my project on “Demand Analysis
of transformers” such as power transformer, dry type transformers, HVR
transformers & Instrument transformer.



So, through this project I have learned:

    Analysis of Future demand of BHEL transformers in domestic market

    Export & Import Procedure

    Specific requirement of export & import
RECOMMENDATION & SUGGESTIONS



  BHEL must try to find out the reasons of decreasing demand of
   transformers such as power transformers, Instrument transformers &
   HVR transformers in domestic market.


  BHEL must try to change their marketing strategies.


  There should be optimum utilization of all factors of production.


  Modernization of techniques and up gradation of existing machinery.


  Avoid indigenization.


  They should try to motivate the employee and try to change their work
   so they get the interest against their work and enjoy the work also
   increase the knowledge.



  The main products of BHEL JHANSI are Transformers &
   Locomotives.To expand the market for these products of BHEL,
   regular seminars should be conducted. These seminars should
   emphases on the awareness & advertisement of BHEL‟s product &
   their characteristic, features etc. among the customers related to that
   region this will in turn help in advertising of BHEL‟s product in the
   region of immense competitors where the other players are situated.
WEBSITES VISITED



www.Bhel.com

www.google.com

www.Ask.com

www.wikipedia.in


BIBLOGRAPHY


   Marketing Management (Kotler)

   Marketing Research (C.R. Kothari)

   Business Statistics (R.P. Varshney)

   Annual REPORTS of BHEL

Contenu connexe

Tendances

3 demand-forecasting
3 demand-forecasting3 demand-forecasting
3 demand-forecastingSatish Raju
 
Risk measurement & efficient market hypothesis
Risk measurement & efficient market hypothesisRisk measurement & efficient market hypothesis
Risk measurement & efficient market hypothesisJatin Pancholi
 
Market and demand analysis 2
Market and demand analysis 2Market and demand analysis 2
Market and demand analysis 2joybutt5033
 
Conducting market research
Conducting market researchConducting market research
Conducting market researchmartinwuest
 
Demand forecasting
Demand  forecasting Demand  forecasting
Demand forecasting Rohit Parkar
 
Demand forecasting
Demand forecastingDemand forecasting
Demand forecastingPraveen Ojha
 
demand forecasting
demand forecastingdemand forecasting
demand forecastingarjunchand
 
04 demand forecasting
04 demand forecasting04 demand forecasting
04 demand forecastingSunil Yadav
 
OpLossModels_A2015
OpLossModels_A2015OpLossModels_A2015
OpLossModels_A2015WenSui Liu
 
Demand Forecasting and Market planning
Demand Forecasting and Market planningDemand Forecasting and Market planning
Demand Forecasting and Market planningAmrutha Raghu
 
Demand forecasting
Demand forecastingDemand forecasting
Demand forecastingAkshismruti
 
Demand estimation and forecasting
Demand estimation and forecastingDemand estimation and forecasting
Demand estimation and forecastingshivraj negi
 
Demand analysis PPT OF MANAGERIAL ECONOMICS MBA
Demand analysis PPT OF MANAGERIAL ECONOMICS MBADemand analysis PPT OF MANAGERIAL ECONOMICS MBA
Demand analysis PPT OF MANAGERIAL ECONOMICS MBABabasab Patil
 
Strategy under uncertainty
Strategy under uncertaintyStrategy under uncertainty
Strategy under uncertaintyMohamed Fahmy
 

Tendances (20)

3 demand-forecasting
3 demand-forecasting3 demand-forecasting
3 demand-forecasting
 
Risk measurement & efficient market hypothesis
Risk measurement & efficient market hypothesisRisk measurement & efficient market hypothesis
Risk measurement & efficient market hypothesis
 
Strategy under uncertainty
Strategy under uncertaintyStrategy under uncertainty
Strategy under uncertainty
 
Market and demand analysis 2
Market and demand analysis 2Market and demand analysis 2
Market and demand analysis 2
 
Conducting market research
Conducting market researchConducting market research
Conducting market research
 
Demand forecasting
Demand  forecasting Demand  forecasting
Demand forecasting
 
Demand forecasting
Demand forecastingDemand forecasting
Demand forecasting
 
demand forecasting
demand forecastingdemand forecasting
demand forecasting
 
04 demand forecasting
04 demand forecasting04 demand forecasting
04 demand forecasting
 
OpLossModels_A2015
OpLossModels_A2015OpLossModels_A2015
OpLossModels_A2015
 
Demand Forecasting and Market planning
Demand Forecasting and Market planningDemand Forecasting and Market planning
Demand Forecasting and Market planning
 
Fundamental n Technical analysis
Fundamental n Technical analysisFundamental n Technical analysis
Fundamental n Technical analysis
 
Demand forecasting
Demand forecastingDemand forecasting
Demand forecasting
 
Demand Forecasting
Demand ForecastingDemand Forecasting
Demand Forecasting
 
6 Demand forecasting
6 Demand forecasting6 Demand forecasting
6 Demand forecasting
 
Demand estimation and forecasting
Demand estimation and forecastingDemand estimation and forecasting
Demand estimation and forecasting
 
Demand analysis PPT OF MANAGERIAL ECONOMICS MBA
Demand analysis PPT OF MANAGERIAL ECONOMICS MBADemand analysis PPT OF MANAGERIAL ECONOMICS MBA
Demand analysis PPT OF MANAGERIAL ECONOMICS MBA
 
Mkt
MktMkt
Mkt
 
Strategy under uncertainty
Strategy under uncertaintyStrategy under uncertainty
Strategy under uncertainty
 
Demand forcasting
Demand forcastingDemand forcasting
Demand forcasting
 

En vedette

case study on product life cycle of pepsi
case study on product life cycle of pepsicase study on product life cycle of pepsi
case study on product life cycle of pepsianishaa95
 
Product life cycle of nokia mobiles
Product life cycle of nokia mobilesProduct life cycle of nokia mobiles
Product life cycle of nokia mobilesTanmoy Roy
 
Nokia product life cycle
Nokia product life cycleNokia product life cycle
Nokia product life cycleTasheen Sheikh
 
Product life cycle & marketing strategy
Product life cycle & marketing strategyProduct life cycle & marketing strategy
Product life cycle & marketing strategyHitesh Sunny
 
1. maggi the-product-life-cycle
1. maggi the-product-life-cycle1. maggi the-product-life-cycle
1. maggi the-product-life-cycleSwati Sharma
 
Product planning & development
Product planning & developmentProduct planning & development
Product planning & developmentSoma Giri
 

En vedette (9)

Bhel ppt
Bhel pptBhel ppt
Bhel ppt
 
demand forecasting techniques
demand forecasting techniquesdemand forecasting techniques
demand forecasting techniques
 
Case Study on Nokia
Case Study on NokiaCase Study on Nokia
Case Study on Nokia
 
case study on product life cycle of pepsi
case study on product life cycle of pepsicase study on product life cycle of pepsi
case study on product life cycle of pepsi
 
Product life cycle of nokia mobiles
Product life cycle of nokia mobilesProduct life cycle of nokia mobiles
Product life cycle of nokia mobiles
 
Nokia product life cycle
Nokia product life cycleNokia product life cycle
Nokia product life cycle
 
Product life cycle & marketing strategy
Product life cycle & marketing strategyProduct life cycle & marketing strategy
Product life cycle & marketing strategy
 
1. maggi the-product-life-cycle
1. maggi the-product-life-cycle1. maggi the-product-life-cycle
1. maggi the-product-life-cycle
 
Product planning & development
Product planning & developmentProduct planning & development
Product planning & development
 

Similaire à bhel forcasting

Enterprations Weekly Strategy, Number 2, December 2016
Enterprations Weekly Strategy, Number 2, December 2016Enterprations Weekly Strategy, Number 2, December 2016
Enterprations Weekly Strategy, Number 2, December 2016Mutiu Iyanda, mMBA, ASM
 
Demand forecasting
Demand forecastingDemand forecasting
Demand forecastingKeval Patel
 
Demand estimating and forcasting
Demand estimating and forcastingDemand estimating and forcasting
Demand estimating and forcastingMuntaquir Hasnain
 
Deman forcasting
Deman forcastingDeman forcasting
Deman forcastingTinku Kumar
 
ForecastingDiscuss the different types of forecasts to include tim.pdf
ForecastingDiscuss the different types of forecasts to include tim.pdfForecastingDiscuss the different types of forecasts to include tim.pdf
ForecastingDiscuss the different types of forecasts to include tim.pdfamolmahale23
 
Introduction toDemand Forecasting part one
Introduction toDemand Forecasting part oneIntroduction toDemand Forecasting part one
Introduction toDemand Forecasting part oneErichViray
 
Introduction to demand forecasting
Introduction to demand forecastingIntroduction to demand forecasting
Introduction to demand forecastingAmandaBvera
 
Demand Forcasting
Demand ForcastingDemand Forcasting
Demand ForcastingAjilal
 
Demand Forecasting in the restaurant management
Demand Forecasting in the restaurant managementDemand Forecasting in the restaurant management
Demand Forecasting in the restaurant managementErichViray
 
Demand forecasting ppt
Demand forecasting pptDemand forecasting ppt
Demand forecasting pptSusheel Tiwari
 
A study on after sales and services in tvs
A study on after sales and services in tvsA study on after sales and services in tvs
A study on after sales and services in tvsProjects Kart
 

Similaire à bhel forcasting (20)

SLE ECONOMICS
SLE ECONOMICS SLE ECONOMICS
SLE ECONOMICS
 
Forecasting in OPM.pptx
Forecasting in OPM.pptxForecasting in OPM.pptx
Forecasting in OPM.pptx
 
Enterprations Weekly Strategy, Number 2, December 2016
Enterprations Weekly Strategy, Number 2, December 2016Enterprations Weekly Strategy, Number 2, December 2016
Enterprations Weekly Strategy, Number 2, December 2016
 
Demand forecasting
Demand forecastingDemand forecasting
Demand forecasting
 
Advertising and Campaign planning
Advertising and Campaign planningAdvertising and Campaign planning
Advertising and Campaign planning
 
Demand estimating and forcasting
Demand estimating and forcastingDemand estimating and forcasting
Demand estimating and forcasting
 
Unit 2
Unit  2Unit  2
Unit 2
 
Deman forcasting
Deman forcastingDeman forcasting
Deman forcasting
 
ForecastingDiscuss the different types of forecasts to include tim.pdf
ForecastingDiscuss the different types of forecasts to include tim.pdfForecastingDiscuss the different types of forecasts to include tim.pdf
ForecastingDiscuss the different types of forecasts to include tim.pdf
 
Forecasting
ForecastingForecasting
Forecasting
 
Introduction toDemand Forecasting part one
Introduction toDemand Forecasting part oneIntroduction toDemand Forecasting part one
Introduction toDemand Forecasting part one
 
UNIT - II.pptx
UNIT - II.pptxUNIT - II.pptx
UNIT - II.pptx
 
Introduction to demand forecasting
Introduction to demand forecastingIntroduction to demand forecasting
Introduction to demand forecasting
 
Segmentation
SegmentationSegmentation
Segmentation
 
Segmentation
SegmentationSegmentation
Segmentation
 
Demand Forcasting
Demand ForcastingDemand Forcasting
Demand Forcasting
 
Demand Forecasting in the restaurant management
Demand Forecasting in the restaurant managementDemand Forecasting in the restaurant management
Demand Forecasting in the restaurant management
 
Demand forecasting ppt
Demand forecasting pptDemand forecasting ppt
Demand forecasting ppt
 
The Analyst Conversation
The Analyst ConversationThe Analyst Conversation
The Analyst Conversation
 
A study on after sales and services in tvs
A study on after sales and services in tvsA study on after sales and services in tvs
A study on after sales and services in tvs
 

Dernier

Call Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service AvailableDipal Arora
 
FULL ENJOY Call Girls In Majnu Ka Tilla, Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Majnu Ka Tilla, Delhi Contact Us 8377877756FULL ENJOY Call Girls In Majnu Ka Tilla, Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Majnu Ka Tilla, Delhi Contact Us 8377877756dollysharma2066
 
Value Proposition canvas- Customer needs and pains
Value Proposition canvas- Customer needs and painsValue Proposition canvas- Customer needs and pains
Value Proposition canvas- Customer needs and painsP&CO
 
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...Dave Litwiller
 
Cracking the Cultural Competence Code.pptx
Cracking the Cultural Competence Code.pptxCracking the Cultural Competence Code.pptx
Cracking the Cultural Competence Code.pptxWorkforce Group
 
RSA Conference Exhibitor List 2024 - Exhibitors Data
RSA Conference Exhibitor List 2024 - Exhibitors DataRSA Conference Exhibitor List 2024 - Exhibitors Data
RSA Conference Exhibitor List 2024 - Exhibitors DataExhibitors Data
 
Boost the utilization of your HCL environment by reevaluating use cases and f...
Boost the utilization of your HCL environment by reevaluating use cases and f...Boost the utilization of your HCL environment by reevaluating use cases and f...
Boost the utilization of your HCL environment by reevaluating use cases and f...Roland Driesen
 
M.C Lodges -- Guest House in Jhang.
M.C Lodges --  Guest House in Jhang.M.C Lodges --  Guest House in Jhang.
M.C Lodges -- Guest House in Jhang.Aaiza Hassan
 
Ensure the security of your HCL environment by applying the Zero Trust princi...
Ensure the security of your HCL environment by applying the Zero Trust princi...Ensure the security of your HCL environment by applying the Zero Trust princi...
Ensure the security of your HCL environment by applying the Zero Trust princi...Roland Driesen
 
John Halpern sued for sexual assault.pdf
John Halpern sued for sexual assault.pdfJohn Halpern sued for sexual assault.pdf
John Halpern sued for sexual assault.pdfAmzadHosen3
 
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756dollysharma2066
 
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...Lviv Startup Club
 
Regression analysis: Simple Linear Regression Multiple Linear Regression
Regression analysis:  Simple Linear Regression Multiple Linear RegressionRegression analysis:  Simple Linear Regression Multiple Linear Regression
Regression analysis: Simple Linear Regression Multiple Linear RegressionRavindra Nath Shukla
 
Call Girls Navi Mumbai Just Call 9907093804 Top Class Call Girl Service Avail...
Call Girls Navi Mumbai Just Call 9907093804 Top Class Call Girl Service Avail...Call Girls Navi Mumbai Just Call 9907093804 Top Class Call Girl Service Avail...
Call Girls Navi Mumbai Just Call 9907093804 Top Class Call Girl Service Avail...Dipal Arora
 
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRL
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRLMONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRL
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRLSeo
 
7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...Paul Menig
 
The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Commun...
The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Commun...The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Commun...
The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Commun...Aggregage
 

Dernier (20)

Call Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service AvailableCall Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
Call Girls Pune Just Call 9907093804 Top Class Call Girl Service Available
 
FULL ENJOY Call Girls In Majnu Ka Tilla, Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Majnu Ka Tilla, Delhi Contact Us 8377877756FULL ENJOY Call Girls In Majnu Ka Tilla, Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Majnu Ka Tilla, Delhi Contact Us 8377877756
 
Value Proposition canvas- Customer needs and pains
Value Proposition canvas- Customer needs and painsValue Proposition canvas- Customer needs and pains
Value Proposition canvas- Customer needs and pains
 
Mifty kit IN Salmiya (+918133066128) Abortion pills IN Salmiyah Cytotec pills
Mifty kit IN Salmiya (+918133066128) Abortion pills IN Salmiyah Cytotec pillsMifty kit IN Salmiya (+918133066128) Abortion pills IN Salmiyah Cytotec pills
Mifty kit IN Salmiya (+918133066128) Abortion pills IN Salmiyah Cytotec pills
 
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...
Enhancing and Restoring Safety & Quality Cultures - Dave Litwiller - May 2024...
 
Cracking the Cultural Competence Code.pptx
Cracking the Cultural Competence Code.pptxCracking the Cultural Competence Code.pptx
Cracking the Cultural Competence Code.pptx
 
RSA Conference Exhibitor List 2024 - Exhibitors Data
RSA Conference Exhibitor List 2024 - Exhibitors DataRSA Conference Exhibitor List 2024 - Exhibitors Data
RSA Conference Exhibitor List 2024 - Exhibitors Data
 
Boost the utilization of your HCL environment by reevaluating use cases and f...
Boost the utilization of your HCL environment by reevaluating use cases and f...Boost the utilization of your HCL environment by reevaluating use cases and f...
Boost the utilization of your HCL environment by reevaluating use cases and f...
 
M.C Lodges -- Guest House in Jhang.
M.C Lodges --  Guest House in Jhang.M.C Lodges --  Guest House in Jhang.
M.C Lodges -- Guest House in Jhang.
 
Ensure the security of your HCL environment by applying the Zero Trust princi...
Ensure the security of your HCL environment by applying the Zero Trust princi...Ensure the security of your HCL environment by applying the Zero Trust princi...
Ensure the security of your HCL environment by applying the Zero Trust princi...
 
John Halpern sued for sexual assault.pdf
John Halpern sued for sexual assault.pdfJohn Halpern sued for sexual assault.pdf
John Halpern sued for sexual assault.pdf
 
Forklift Operations: Safety through Cartoons
Forklift Operations: Safety through CartoonsForklift Operations: Safety through Cartoons
Forklift Operations: Safety through Cartoons
 
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756
FULL ENJOY Call Girls In Mahipalpur Delhi Contact Us 8377877756
 
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...
Yaroslav Rozhankivskyy: Три складові і три передумови максимальної продуктивн...
 
VVVIP Call Girls In Greater Kailash ➡️ Delhi ➡️ 9999965857 🚀 No Advance 24HRS...
VVVIP Call Girls In Greater Kailash ➡️ Delhi ➡️ 9999965857 🚀 No Advance 24HRS...VVVIP Call Girls In Greater Kailash ➡️ Delhi ➡️ 9999965857 🚀 No Advance 24HRS...
VVVIP Call Girls In Greater Kailash ➡️ Delhi ➡️ 9999965857 🚀 No Advance 24HRS...
 
Regression analysis: Simple Linear Regression Multiple Linear Regression
Regression analysis:  Simple Linear Regression Multiple Linear RegressionRegression analysis:  Simple Linear Regression Multiple Linear Regression
Regression analysis: Simple Linear Regression Multiple Linear Regression
 
Call Girls Navi Mumbai Just Call 9907093804 Top Class Call Girl Service Avail...
Call Girls Navi Mumbai Just Call 9907093804 Top Class Call Girl Service Avail...Call Girls Navi Mumbai Just Call 9907093804 Top Class Call Girl Service Avail...
Call Girls Navi Mumbai Just Call 9907093804 Top Class Call Girl Service Avail...
 
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRL
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRLMONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRL
MONA 98765-12871 CALL GIRLS IN LUDHIANA LUDHIANA CALL GIRL
 
7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...7.pdf This presentation captures many uses and the significance of the number...
7.pdf This presentation captures many uses and the significance of the number...
 
The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Commun...
The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Commun...The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Commun...
The Path to Product Excellence: Avoiding Common Pitfalls and Enhancing Commun...
 

bhel forcasting

  • 1. PROJECT INDEX  Demand Forecasting & its need for the Project  Research method  Research Methodology  DATA Collection Method, Analysis & Implementation  Marketing -Marketing Planning-mission -Marketing Planning-vision & values  Market Analysis –Defining the market -Types of Market  Market Research –Introduction -Market Segmentation -Why segment the market?  Product –Introduction -Product Life Cycle  Product Analysis  Customer or Consumer  Competitor Analysis kind of information -Role of competitor analysis  Pricing –Introduction  Brand  Demand Analysis of BHEL Products & Forecasting -Total demand of products in domestic market -Analysis of demand in domestic market  SWOT Analysis of BHEL  Findings  Limitations  Conclusion  Recommendation & Suggestions  Websites visited  Bibliography
  • 2. DEMAND FORECASTING '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. ‟ Necessity for forecasting demand Often forecasting demand is confused with forecasting sales. But, failing to forecast demand ignores two important phenomena Stock effects The effects that inventory 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 also untapped when sales for an item are decreased due to a poor display location, or because the desired sizes are no longer available. For example, when a consumer electronics retailer 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 ite m 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 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.
  • 3. Methods that rely on judgment When using judgment, rely on structured procedures such as Delphi, simulated interaction, structured analogies, and conjoint analysis. Simulated interaction is useful to predict the decisions in conflict situations, such as in negotiations. In addition to seeking good feedback, forecasters should explicitly list all the things that might be wrong about their forecast. This will produce better calibrated prediction intervals.  Unaided judgment : It is common practice to ask experts what will happen. This is a good procedure to use when • experts are unbiased • large changes are unlikely • relationships are well understood by experts (e.g., demand goes up when prices go down) • experts possess privileged information • experts receive accurate and well-summarized feedback about their forecasts.  Prediction market : Prediction markets, also known as betting markets, information markets, and futures markets have a long history. Despite numerous attempts since the 1930s, no methods have been found to be superior to markets when forecasting prices. However, few people seem to believe this as they pay handsomely for advice about what to invest in. Some commercial organizations provide internet markets and software that to allow participants to bet by trading contracts. However, there are no empirical studies that compare forecasts from prediction markets with those from traditional groups or from other methods.  Delphi technique: The Delphi technique was developed at RAND Corporation in the 1950s to help capture the knowledge of diverse
  • 4. experts while avoiding the disadvantages of traditional group meetings. The latter include bullying and time-wasting. To forecast with Delphi the administrator should recruit between five and twenty suitable experts and poll them for their forecasts and reasons. The administrator then provides the experts with anonymous summary statistics on the forecasts, and experts‟ reasons for their forecasts. The process is repeated until there is little change in forecasts between rounds – two or three rounds are usually sufficient. The Delphi forecast is the median or mode of the experts‟ final forecasts.  Game theory:Simulated interaction is a form of role playing for predicting decisions by people who are interacting with others. It is especially useful when the situation involves conflict. For example, one might wish to forecast how best to secure an exclusive distribution arrangement with a major supplier. To use simulated interaction, an administrator prepares a description of the target situation, describes the main protagonists‟ roles, and provides a list of possible decisions. Role players adopt a role and read about the situation. They then improvise realistic interactions with the other role players until they reach a decision; for example to sign a trial one-year exclusive distribution agreement. The role players‟ decisions are used to make the forecast.  Judgmental bootstrapping : Judgmental bootstrapping converts subjective judgments into structured procedures. Experts are asked what information they use to make predictions about a class of situations. They are then asked to make predictions for diverse cases, which can be real or hypothetical. The resulting data are then converted to a model by estimating a regression equation relating the judgmental forecasts to the information used by the .  Simulated interaction : Simulated interaction is a form of role playing for predicting decisions by people who are interacting with others. It is especially useful when the situation involves conflict. For example, one might wish to forecast how best to secure an exclusive distribution arrangement with a major supplier. To use simulated interaction, an administrator prepares a description of
  • 5. the target situation, describes the main protagonists‟ roles, and provides a list of possible decisions. Role players adopt a role and read about the situation. They then improvise realistic interactions with the other role players until they reach a decision; for example to sign a trial one-year exclusive distribution agreement. The role players‟ decisions are used to make the forecast.  Intentions and expectations surveys : With intentions surveys, people are asked how they intend to behave in specified situations. In a similar manner, an expectations survey asks people how they expect to behave. Expectations differ from intentions because people realize that unintended things happen  Conjoint analysis : By surveying consumers about their preferences for alternative product designs in a structured way, it is possible to infer how different features will influence demand. Methods that rely on quantitative data With the proliferation of data, causal models play an increasingly important role in forecasting market size, market share, and sales. Methods should be developed primarily on the basis of theory, not data. Finally, efforts should be made to ensure forecasts are free of political considerations in a firm. To help with this, emphasis should be on gaining agreement about the forecasting methods. Also, for important forecasts, decisions on their use should be made before the forecasts are provided. Scenarios are helpful in guiding this process.  Extrapolation : Extrapolation methods use historical data on that which one wishes to forecast. Exponential smoothing is the most popular and cost effective of the statistical extrapolation methods. It implements the principle that recent data should be weighted
  • 6. more heavily and „smoothes‟ out cyclical fluctuations to forecast the trend. To use exponential smoothing to extrapolate, the administrator should first clean and deseasonalise the data, and select reasonable smoothing factors. The administrator then calculates an average and trend from the data and uses these to derive a forecast .  Quantitative analogies : Experts can identify situations that are analogous to a given situation. These can be used to extrapolate the outcome of a target situation. For example, to assess the loss in sales when the patent protection for a drug is removed, one might examine the historical pattern of sales for analogous drugs. To forecast using quantitative analogies, ask experts to identify situations that are analogous to the target situation and for which data are available  Rule-based forecasting : Rule-based forecasting (RBF) is a type of expert system that allows one to integrate managers‟ knowledge about the domain with time-series data in a structured and inexpensive way. For example, in many cases a useful guideline is that trends should be extrapolated only when they agree with managers‟ prior expectations  Neural networks : Neural networks are computer intensive methods that use decision processes analogous to those of the human brain. Like the brain, they have the capability of learning as patterns change and updating their parameter estimates. However, much data is needed in order to estimate neural network models and to reduce the risk of over-fitting the data (Adya and Collopy 1998).
  • 7. Data mining : Data mining uses sophisticated statistical analyses to identify relationships. It is a popular approach. Data mining ignores theory and prior knowledge in a search for patterns. Despite ambitious claims and much research effort, we are not aware of evidence that data mining techniques provide benefits for forecasting.  Causal models : Causal models are based on prior knowledge and theory. Time-series regression and cross-sectional regression are commonly used for estimating model parameters or coefficients. Causal models are most useful when (1) strong causal relationships are expected, (2) the direction of the relationship is known, (3) causal relationships are known or they can be estimated, (4) large changes are expected to occur in the causal variables over the forecast horizon, and (5) changes in the causal variables can be accurately forecast or controlled, especially with respect to their direction. Reviews of commercial software that can be used to develop causal models are provided at the forecastingprinciples.com site.  Segmentation :Segmentation involves breaking a problem down into independent parts, using data for each part to make a forecast, and then combining the parts. For example, a company could forecast sales of wool carpet separately for each climatic region, and then add the forecasts.
  • 8. NEED FOR MARKETING FORECASTING
  • 9. CONCLUSIONS FOR DEMAND FORECASTING Significant gains have been made in forecasting for marketing, especially since 1960. Advances have occurred in the development of methods based on judgment, such as Delphi, simulated interactions, intentions studies, opinions surveys, bootstrapping, and combining. They have also occurred for methods based on statistical data, such as extrapolation, rule-based forecasting, and econometric methods. Most recently, gains have come from the integration of statistical and judgmental forecasts. General principles • Managers‟ domain knowledge should be incorporated into forecasting methods. • When making forecasts in highly uncertain situations, be conservative. For example, the trend should be dampened over the forecast horizon. • Complex methods have not proven to be more accurate than relatively simple methods. Given their added cost and the reduced understanding among users, highly complex procedures cannot be justified. • When possible, forecasting methods should use data on actual behaviour, rather than judgments or intentions, to predict behaviour. • Methods that integrate judgmental and statistical data and procedures (e.g., rule-based forecasting) can improve forecast accuracy in many situations. • Overconfidence occurs with quantitative and judgmental methods. • When making forecasts in situations with high uncertainty, use more than one method and combine the forecasts, generally using simple averages. Methods based on statistical data
  • 10. RESEARCH METHODS I- Why Are Research Methods Important? Science, at a basic level attempts to answer questions (such as “why are we aggressive) through careful observation and collection of data. These answers can then (at a more complex or higher level) are used to further our knowledge of us and our world, as well as help us predict subsequent events and behavior. But, this requires a systematic/universal way of collecting and understanding data – otherwise there is chaos. At a practical level, methodology helps us understand and evaluate the merit of all the information we‟re confronted with every day. For example, do you believe in the following studies?  Study indicated that the life span of left-handed people is significantly shorter than those who are right hand dominant.  Study demonstrated a link between smoking and poor grades. There are many aspects of these studies that are necessary before one can evaluate the validity of the results. However, most people do not bother to find out the details (which are the keys to understanding the studies) but only pay attention to the findings, even if the findings are completely erroneous. They are also practical in the workplace  Mental Health Profession – relies on research to develop new therapies, and learn which therapies are appropriate and effective for different types of problems and people.  Business World – marketing strategies, hiring, employee productivity, etc. II- Different Types of Research Methods  Basic Research  Applied Research  Program Evaluation
  • 11. III- How Do Non-Scientists Gather Information? We all observe our world and make conclusions. How do we do this:  Seek an authority figure  Intuition IV- THE SCIENTIFIC METHOD B. Why of Conducting Scientific Research  Naturalistic Observation  Case Study  Survey  Psychological Testing  Experimental Research
  • 12. Research Methodology  Type or research ---------------- Exploratory Research Design.  Method of Research------------- Data collection Method Through Customer enquiries Receive for submission of Tender from domestic market.  Sampling method ---------------Through statistical and Judgement method (Regression)  Sampling unit--------------------BHEL Jhansi.  Sampling element transformer------Power transformer, Dry Type, Instrument & HVR Transformers. DATA COLLECTION There are very few hard and fast rules to define the task of data collection. Each research project uses a data collection technique appropriate to the particular research methodology. The two primary goals for both quantitative and qualitative studies are to maximize response and maximize accuracy. When using an outside data collection service, researchers often validate the data collection process by contacting a percentage of the respondents to verify that they were actually interviewed. Data editing and cleaning involves the process of checking for inadvertent errors in the data. This usually entails using a computer to check for out-of-bounds data. Here which I collected the datas from enquiry records & annual reports of BHEL are mainly secondary data set.
  • 13. DATA ANALYSIS Modern computer software has made the analysis of quantitative data a very easy task. It is no longer incumbent on the researcher to know the formulas needed to calculate the desired statistics. However, this d oes not obviate the need for the researcher to understand the theoretical and conceptual foundations of the statistical techniques. Each statistical technique has its own assumptions and limitations. Considering the ease in which computers can calculate complex statistical problems, the danger is that the researcher might be unaware of the assumptions and limitations in the use and interpretation of a statistic. DATA IMPLEMENTATION The most important consideration in preparing any research report is the nature of the audience. The purpose is to communicate information, and therefore, the report should be prepared specifically for the readers of the report. Sometimes the format for the report will be defined for the researcher (e.g. a dissertation), while other times, the researcher will have complete latitude regarding the structure of the report. At a minimum, the report should contain an abstract, problem statement, methods section, results section, discussions of the results, and a list of references.
  • 14. MARKETING There are many definitions of marketing. Consider some of the following alternative definitions: “The all-embracing function that links the business with customer needs and wants in order to get the right product to the place at the right time”. “The achievement of corporate goals through meeting and exceeding customer needs better than the competition”. “The management process that identifies anticipates and supplies customer requirements efficiently and profitably”. “Marketing may be defined as a set of human activities directed at facilitating and consummating exchanges” Marketing Why is the business’ attitude to marketing? Marketing Orientation Gain information on Persuade Market The market: customers to buy: Analysis Market Research Marketing Mix Quantitative Product Market Analysis Analysis Price Market Qualitative Segmentation Analysis Place Marketing Strategy Consumer Tests Promotion
  • 15. Five Successful Marketing Techniques 1. Keep Adding Something New: Every time you add something new to your business you create an opportunity to get more sales. For example, something as simple as adding new information on your web site creates another selling opportunity when prospects and customers visit your site to see the new information. Adding a new product or service to the list of those you already offer usually produces a big increase in sales. The added product increases your sales in 3 different ways:  It attracts mew customers who were not interested in your current products and services.  It generates repeat sales from existing customers who also want to have your new product.  It enables you to get bigger sales by combing two or more items into special package offers. 2. Become a Valuable Resource: Look for ways you can be a resource for your prospects and customers. Supply them with free information. Help them do things faster, easier, less expensively. You get another opportunity to sell something every time they come back to you for help. 3. Separate Yourself from Your Competition: Find or create a reason for customers to do business with you instead of with someone else offering the same or similar products. For example, do you provide faster results, easier procedures, personal attention or a better guarantee? Determine the unique advantage you offer to customers that your competitors do not offer. Promote that advantage in all of your advertising. Give your prospects a reason to do business with you instead of with your competition and you‟ll automatically get more sales. 4. Promote the End Result:
  • 16. Your customers don‟t really want your product or service. They want the benefit produced by using it. For example, car buyers want convenient transportation with a certain image. Dental patients want healthy and good-looking teeth without suffering any pain. Business opportunity seekers want personal and financial freedom for themselves and their family. Make sure your web pages, sales letters and other sales messages are promoting the end result your customers want. 5. Anticipate Change: Change is the biggest challenge to your business success. The days are gone when a business could constantly grow by simply repeating what It did successfully in the past… or even recently. Aggressive, innovative competitors and rapidly changing technology make it impossible. Expect change and prepare for it. Don‟t wait until your income declines to take action. Develop the habit of looking for early signs that something is changing. Then confront it before you start to lose business. Tip:Insulate yourself against the impact of change by increasing the number of products and services you offer and by using a variety of different marketing methods. Only a small portion of your total business will be affected if the sales of one product decline or the response to one marketing method drops. Marketing planning – Mission
  • 17. Mission “A mission describes the organization‟s basic function in society, in terms of the products and services it produces for its customers”. A clear business mission should have each of the following elements: Purpose Why the business exists Strategy& Scope Values What business What management and how Believes in Standards & Behaviors The rules that guide how the business operates Marketing Planning – Values & Vision
  • 18. Values from the foundation of a business management style. Values provide the justification of behavior and, therefore, exert significant influence on marketing decisions. Market analysis – defining the market All business operates in “markets”. But what is a market? And how can it be defined? Traditionally, a “market” was a physical place where buyers and sellers gathered to buy and sell goods. Economists describe a market as a collection of buyers and sellers who transact over a particular product or product class (such as the housing market or the grain market). It is important to be careful about how a market is defined. The following key marketing process relies on a relevant definition:  Measuring market share  Measuring market size and growth  Specifying target customers  Identifying relevant competitors  Formulating a marketing strategy A market can be defined as follows: A market is the set of all actual and potential buyers of a product or service. Five basic markets & their connecting flows:
  • 19. Resource Market Manufacturer Consumer Government Market Market Market Intermediary Market
  • 20. Types of market Markets can be analysis via the product itself, or end-consumer, or both. The most common distinction is between consumer and industrial markets. Consumer Markets Consumer markets are the markets for products and services bought by individuals for their own or family use. Goods bought in consumer markets can be categorized in several ways:  Fast-moving consumer goods (“FMCGs”)  Consumer durables  Soft goods Industrial Markets Industrial markets involve the sale of goods between business. These are goods that are not aimed directly at consumers. Industrial markets include  Selling finished goods Examples-office furniture, computer systems  Selling raw materials or components Example-steel, coal, gas timber  Selling services to businesses Example-waste disposal, security, accounting &legal services
  • 21. MARKET RESEARCH Market research answers questions in respect of different markets. The purpose of this research is to gather facts about markets and the forces operating therein, like competitors and government, so as to enhance the competitive strength of the company in the market place. The areas of market research broadly include:  Determine the size of both current and potential market.  Assessing the market trends.  Ascertaining the strengths and weaknesses of competitors‟ marketing strategies.  Determining the impact of current and contemplated legislative actions of the state on the marketing effort of the company.  Demand and sales forecasting. Market Segmentation “Market Segmentation is the division of a market into those subgroups which have special needs & preferences & which represent sufficient pockets of demand to justify separate marketing strategies”. The concept of market segmentation is based on the fact that markets are heterogeneous. Bases for Segmentation The major segmentation variables are: 1. Geographic segmentation 2. Demographic segmentation 3. Psychographic segmentation 4. Behavior segmentation
  • 22. 1. Geographic segmentation: Geographic segmentation calls for division of the market into different geographic units such as nation, states, regions, countries, cities, neighbourhood, density of city, climate, etc. 2. Demographic segmentation: In demographic segmentation, we divide the market into groups on the basis of variables such as age, family size, gender, income, occupation, education religion, generation, nationality, etc. One reason, demographic variables are so popular with marketers is that they‟re often associated with consumer needs & wants. Another is that they‟re easy to measure. 3. Psychographic segmentation: Psychographics is the science of using psychology & demographics to better understand consumers. In Psychographic segmentation, buyers are divided into different groups on the basis of psychological/personality traits. Such as lifestyle, values, social class, etc. 4. Behavior segmentation: In Behavior segmentation, marketers divide buyers into groups on the basis of -use occasion, benefit sought, usage rate, loyalty status, readiness to purchase, attitude toward product, user status, etc. Why Segment Market? There are several important reasons why business should attempt to segment their market carefully. These are summarized below: 1. Enhanced profits for business. 2. Better opportunities for growth. 3. Retain more customers. 4. Target marketing communications. 5. Gain share of the market segment.
  • 23. Products – Introduction A product is defined as: “Anything that is capable of satisfying customer needs” A product group (or product line) is a group of brands that are closely related in terms of their functions and the benefits they provide (e.g. Dell‟s range of personal computers or Sony‟s range of televisions). There are two main types of product brand: (1) Manufacture brands (2) Own-label brands Manufacturer brands are created by producers and use their chosen brand name. The producer has the responsibility for marketing the brand, by building distribution and gaining customer brand loyalty. Good examples include Microsoft, Panasonic and Mercedes. Own-label brands are created and owned by distributions. Good examples include Tesco and Sainsbury‟s Business need to regularly look for new products and markets for future growth. A useful way of looking at growth opportunities is the An off Growth matrix which suggests that there are four main ways in which growth can be achieved through a product strategy: (1) Market penetration- Increase sales of an existing product in an existing market. (2) Product development – Improve present products and/or develop new products for the current market. (3) Market development – Sell existing products into new markets (e.g. developing export sales). (4) Diversification– Develop new products for new markets.
  • 24. Products – Product life cycle We define a product as “anything that is capable of satisfying customer needs. This definition includes both physical products (e.g. cars, washing machines, DVD players) as well as services (e.g. insurance, banking, private health care). Business should manage their products carefully over time to ensure that they deliver products that continue to meet customer wants. The process of managing groups of brands and product lines is called portfolio planning. The stages through which individual products develop over time is called commonly known as the “Product Life Cycle”. The classic product life cycle has four stages (illustrated in the diagram below): introduction; growth; maturity and decline Introduction Stage A period of slow sales growth as the product is introduced in the market. Profits are non-existent because of the heavy expenses of product introduction. Growth Stage
  • 25. The Growth Stage is characterized by rapid growth in sales and profits. Maturity Stage The Maturity Stage is, perhaps, the most common stage for all markets, it is in this stage that competition is most intense as companies fight to maintain their market share. Decline Stage In the Decline Stage, the market is shrinking, reducing the overall amount of profit that can be shared amongst the remaining competitors. Object of Product Analysis A Product Analysis refers to the study of: a) The raw materials used b) Components, c) Features like shape, size, colour, weight, design, etc. d) The merits of the product- its convenience, portability, style, comfort, durability, wholesomeness or purity. e) Packing. f) Branding Product Analysis Those who are in the business of marketing, industrial products should be continuously on the lookout of modifications in the existing products with a view to: (a) improving the quality & functional performance of the products and (b) ensuring that the products fulfills the changing requirements of the customers. The industrial marketers may also have to concern himself with the end product and the profitability of his customer and if possible suggest to him how these could be improved. For this purpose, the Industrial Marketer will have to continuously subject his own products to marketing research – to product analysis and to new product ideas in particular. Product Analysis of his existing products would include the study of the following aspects of his products: i. Field performance of the products, and the quality, purity, fineness, etc. of the materials and parts used in their manufacture.
  • 26. ii. Design of the product and features like size, shape, weight, applicability, interchangeability, etc. iii. Benefits like convenience of operating or using, durability, portability, etc. iv. Other special features or benefits if any. Since industrial customers are usually fewer, large, and geographically concentrated, the problems relating to large populations and large territories in the selection of a sample would get reduced. In some cases the number of customers might be so few and well listed in the company record according to area, type of business, sales turnover, etc.; that sample selection will be much easier. Customers or Consumers? A common question that arises when studying marketing is the following: What is the difference between a customer and a consumer? The following distinction should help:  A Customer – purchases and pays for a product or service.  A Consumer – is the ultimate user of the product or service, the consumer may not have paid for the product or service. Consider the following example:  A Food manufacturing business makes own-label, Italian ready meals for the major supermarkets. So far as the business is concerned, the customer is the supermarket to whom it supplies meals.  The consumer is the individual who eats the meal. In terms of its marketing effort, who should the business above target? In reality – it needs to understand the needs and wants of both the customer and the consumer.
  • 27. It needs to develop a strong understanding of the needs of the supermarkets in terms of their requirements for ready meals (e.g. packaging, recipes, price and delivery). It also needs to understand (perhaps with the help of the supermarkets) the needs and wants of the consumer. How are tastes changing? Are consumers happy with the standard/taste of the product? Competitors analysis – kinds of Information The tables below lists the kinds of competitors‟ information that would help business complete some good quality competitor analysis. What business probably already know their competitors Overall sales and profits Sales and Profits by market Sales by main brand Cost structure Market shares (revenues and volumes) Organization Structure Distribution system Identity/profile of senior management.
  • 28. The diagram below shows the impact of varying levels of competitor action on the profits of a business: Weak competitors response Annual profits Moderate competitors response Strong competitor response Role of competitor analysis Competitor analysis has several important roles in marketing:  To help management understand their competitive advantages/disadvantages relative to competitors.  To generate understanding of competitor‟s past, present (and most importantly) future strategies.  To provide an informed basis to develop strategies to achieve competitive advantage in the future.  To help forecast the returns that may be made from future investments (e.g. how will competitors respond to a new product or pricing strategy)? What questions should be asked when undertaking competitor analysis? The following is a useful list to bear in mind: Who are our competitors? (See the section on identifying compe titors further below)
  • 29. What threats do they post? What is the profile of our competitors? What are the objectives of our competitors? What strategies are our competitors pursuing and how successful are these strategies? What are the strength and weaknesses of our competitors? How are our competitors likely to respond to any changes to the way we do business? Pricing – Introduction Setting the right price is an important part of effective marketing. It is the only part of the marketing mix that generates revenue (product, promotion and place are all about marketing costs). Price is also the marketing variable that can be changed most quickly, perhaps in response to a competitor price change. Put simply, price is the amount of money or goods for which a thing is bought or sold. The price of a product may be seen as a financial expression of the value of that product. For a consumer, price is the monetary expression of the value to be enjoyed/ benefits of purchasing a product, as compared with other available items. The concept of value can therefore be expressed as: (Perceived) VALUE = (perceived) BENEFITS - (perceived) COSTS A Customer‟s motivation to purchase a product comes firstly from a need and a want: e.g.
  • 30. Need: “I need to eat.  Want: I would like to go out for a meal tonight” The second motivation comes from a perception of the value of a product in satisfying that need/want (e.g. “I really fancy a McDonalds”). The perception of the value of a product varies from customers to customer, because perceptions of benefits and costs vary. Perceived benefits are often largely dependent on personal taste (e.g. spicy versus sweet or green verses blue). In order to obtain the maximum possible value from the available market, business try to „segment‟ the market – that is to divide up the market into groups of consumers whose preferences are broadly similar – and to adapt their products to attract these customers. In general a products perceived value may be increased in one of two ways – either by: (1) Increasing the benefits that the product will deliver, or, (2) Reducing the cost. For consumers, the PRICE of a product is the most obvious indicator of cost – hence the need to get product pricing right. Factors Affecting Demand: Consider the factors affecting the demand for a product that are: (1) Within the control of a business and (2) Outside the control of a business. Factors within a business control include:  Price (assuming an imperfect market – i.e. not perfect competition).  Product research and development.  Advertising & Sales promotion.  Training and organization of the sales force  Effectiveness of distribution (e.g. access to retail outlets; trained distributor agents)  Quality of after-sales services (e.g. which affects demand from repeat- business) Factors outside the control of business include:
  • 31. The price of substitute goods and services.  The price of complementary goods and services.  Consumer‟s disposable income.  Consumer tastes and fashions. Price is therefore, a critically important element of the choices available to businesses in trying to attract demand for their products. BRANDS Meaning of brands Brands are a mean of differentiating a company‟s products and services from those of its competitors. There is plenty of evidence to prove that customers will pay a substantial price premium for a good brand and remain loyal to that brand. It is important, therefore, to understand what brands are and why they are important. “…. It is not factories that make profits, but relationships with customers and it is company and brand names which secure those relationships”. Businesses that invest in and sustain leading brands prosper whereas those that fail are left to fight for the lower profits available in commodity markets.
  • 32. What is brand? One definition of a brand is as follows: “A name, term, sign, symbol or design, or a combination of these, that is intended to identified the goods and services of one business or group of businesses and to differentiated them from those of competitors”. Interbrand – a leading branding consultancy – defines a brand in this way: “A mixture of tangible and intangible attributes symbolized in a trademark, which if properly managed, creates influence and generates value”. Three other important terms relating to brands should be defined at this stage:  Brand equity  Brand image  Brand extension  Brands and products
  • 33. Analysis of Demand for transformers in Domestic market of BHEL Jhansi Unit The demand forecasting for the organizations like Bharat Heavy Electricals Ltd.(BHEL), Jhansi is of great importance because it involves a big amount of working capital. If we have some predictions about the future demand of transformers we can make better plan for production to ensure the delivery of right product at right time and at the right place. The demand forecasting also helps to make allotment of proper working capital. The method used for demand forecasting is REGRESSION ANALYSIS. This method is very useful for making demand forecast for the product/products which have actually increasing trend of demand but forecast goes downward or, conversely the trend for demand is downward and the forecast goes upward. To minimize this effect a factor is added. This procedure adjusts the forecast according to the trend. It has been observed that the values of forecast come pretty close to the actual values. REGRESSION METHOD Meaning & Definition The measurement of the mutual relations of two or more variables is got by regression. Commonly, the question arises if there is some relation between the weight and height of an infant, can its weight be calculated or if we know its age can by this other magnitudes of it be declared .Can the quantity of demand and supply be known for a definite value. What will be the effect on the consumption quantity, if the tax on intoxicant is doubled. For this & for many other measurements of relations the method of regression is used. According to Blair, “Regression is the measure of the average relationship between two or more variables in the terms of the original units of data”.
  • 34. “In more popular sense we may call regression a trend, a line which shows how many units of change in one variable are associated with one unit of change in another Variable.” According to Yule & Kendall, “The term regression is not a particular happy one from the etymological point of view, but it is so firmly embedded in statistical literature that we make no attempt to replace. In general, the idea ordinarily attached to the word „regression, does not touch upon the connotation, & it should be regarded merely a convenient term”. UTILITY OF REGRESSION 1. To forecast the probable value : In the analytical studies of different kinds, there is great value of regression. By it we can know that if out of the two connected series the value of one has been given what may possibly be the value of the other series connected with it. If the rate of pay scale is increased what will be its effect on the efficiency; there having been an increase in the common price level how much will there be a change in the life leading expenditure, increase or decrease in the study will how much effect the result of student etc. are many questions that can be satisfactorily answered by regression method. 2. To Know the Correlation & Co-Variation: With the help of regression the correlation between the two series can be known. If the two lines of regression cover each other the correlation between the two series is complete but if they cross each other at 90˚ angle, the correlation is cipher. The more are the lines of regression inclined towards each, the quantity of correlation is the greater. When the two lines rise from the lower left to right upper the correlation is positive but opposite to it when the lines move from upper to the lower side the correlation is negative. Co-Variation too can be known by it.
  • 35. TOTAL DEMAND OF PRODUCT (TRANSFORMERS) IN DOMESTIC MARKET (FROM YEAR 2005-2012) YEAR POWER DRY-TYPE INSTRUMENT HVR TRANSFORMER TRANSFORMER TRANSFORMER TRANSFORMER 2005-06 842 335 6822 1149 2006-07 948 873 7419 3684 2007-08 760 1200 5875 4611 2008-09 1192 927 10715 2803 2009-10 1150 794 8845 3043 2010-11 975 708 9702 4289 2011-12 855 769 7178 2451
  • 36. FORMULAS USED IN REGRESSION: x= Mean for the number of years used. y= Mean for the demand collected in quantity. X= Number of years used. Y= Number of demands collected. {Y= a+b*x} where a, b are constants & Y shows the trend for demand. b= sum(X-x)(Y-y)/sum(X-x)^2 a=y-b*x
  • 37. TOTAL DEMAND OF BHEL PRODUCTS IN DOMESTIC MARKET POWER TRANSFORMER YEAR X Y X-x (X-x)^2 Y-y (X-x)(Y-y) Y=a+bx 2005-06 1 842 -3 9 -118 354 908 2006-07 2 948 -2 4 -12 24 925 2007-08 3 760 -1 1 -200 200 942 2008-09 4 1192 0 0 232 0 959 2009-10 5 1150 1 1 190 190 976 2010-11 6 975 2 4 15 30 993 2011-12 7 855 3 9 -105 -315 1010 4 960 28 483 b= 17.25 17 a= 891 891 DEMAND FORECAST YEAR X Y 2012-13 8 1027 2013-14 9 1044 2014-15 10 1061 2015-16 11 1078 2016-17 12 1095
  • 38. DEMAND 1400 1200 1000 800 600 DEMAND 400 200 0 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 DEMAND FORECASTED 1120 1100 1080 1060 1040 DEMAND FORECASTED 1020 1000 980 2012-13 2013-14 2014-15 2015-16 2016-17
  • 39. 1400 1200 1000 800 DEMAND 600 TREND 400 200 0 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 DEMAND FORECAST 1120 1100 1080 1060 1040 DEMAND FORECAST 1020 1000 980 2012-13 2013-14 2014-15 2015-16 2016-17
  • 40. DRY TYPE TRANSFORMER YEAR X Y X-x (X-x)^2 Y-y (X-x)(Y-y) Y=a+bx 2005-06 1 335 -3 9 -466 1398 899 2006-07 2 873 -2 4 72 -144 919 2007-08 3 1200 -1 1 399 -399 939 2008-09 4 927 0 0 126 0 959 2009-10 5 794 1 1 -7 -7 979 2010-11 6 708 2 4 -93 -186 999 2011-12 7 769 3 9 -32 -96 1019 4 801 28 566 b= 20.21429 20 a= 879.1429 879 DEMAND FORECAST YEAR X Y 2012-13 8 1039 2013-14 9 1059 2014-15 10 1079 2015-16 11 1099 2016-17 12 1119
  • 41. DEMAND 1400 1200 1000 800 600 DEMAND 400 200 0 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 DEMAND FORECASTED 1140 1120 1100 1080 1060 DEMAND FORECASTED 1040 1020 1000 980 2012-13 2013-14 2014-15 2015-16 2016-17
  • 42. 1400 1200 1000 800 TREND 600 DEMAND 400 200 0 2005-062006-072007-082008-092009-102010-112011-12 DEMAND FORECAST 1140 1120 1100 1080 1060 DEMAND FORECAST 1040 1020 1000 980 2012-13 2013-14 2014-15 2015-16 2016-17
  • 43. INSTRUMENT TRANSFORMER YEAR X Y X-x (X-x)^2 Y-y (X-x)(Y-y) Y=a+bx 2005-06 1 6822 -3 9 -1257 3771 7157 2006-07 2 7419 -2 4 -660 1320 7464 2007-08 3 5875 -1 1 -2204 2204 7771 2008-09 4 10715 0 0 2636 0 8078 2009-10 5 8845 1 1 766 766 8385 2010-11 6 9702 2 4 1623 3246 8692 2011-12 7 7178 3 9 -901 -2703 8999 4 8079 28 8604 b= 307.2857 307 a= 6849.857 6850 DEMAND FORECAST YEAR X Y 2012-13 8 9306 2013-14 9 9613 2014-15 10 9920 2015-16 11 10227 2016-17 12 10534
  • 44. DEMAND 12000 10000 8000 6000 DEMAND 4000 2000 0 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 DEMAND FORECASTED 10800 10600 10400 10200 10000 9800 9600 DEMAND FORECASTED 9400 9200 9000 8800 8600 2012-13 2013-14 2014-15 2015-16 2016-17
  • 45. 12000 10000 8000 6000 TREND 4000 DEMAND 2000 0 DEMAND FORECAST 10800 10600 10400 10200 10000 9800 9600 DEMAND FORECAST 9400 9200 9000 8800 8600 2012-13 2013-14 2014-15 2015-16 2016-17
  • 46. HVR TRANSFORMER YEAR X Y X-x (X-x)^2 Y-y (X-x)(Y-y) Y=a+bx 2005-06 1 1149 -3 9 -1998 5994 2767 2006-07 2 3684 -2 4 537 -1074 2894 2007-08 3 4611 -1 1 1464 -1464 3021 2008-09 4 2803 0 0 -344 0 3148 2009-10 5 3043 1 1 -104 -104 3275 2010-11 6 4289 2 4 1142 2284 3402 2011-12 7 2451 3 9 -696 -2088 3529 4 3147 28 3548 b= 126.7143 127 a= 2640.143 2640 DEMAND FORECAST YEAR X Y 2012-13 8 3656 2013-14 9 3783 2014-15 10 3910 2015-16 11 4037 2016-17 12 4164
  • 47. DEMAND 5000 4500 4000 3500 3000 2500 2000 DEMAND 1500 1000 500 0 2005-06 2006-07 2007-08 2008-09 2009-10 2010-11 2011-12 DEMAND FORECASTED 4300 4200 4100 4000 3900 3800 DEMAND FORECASTED 3700 3600 3500 3400 2012-13 2013-14 2014-15 2015-16 2016-17
  • 48. 5000 4500 4000 3500 3000 2500 TREND 2000 DEMAND 1500 1000 500 0 2005-062006-072007-082008-092009-102010-112011-12 DEMAND FORECAST 4300 4200 4100 4000 3900 3800 DEMAND FORECAST 3700 3600 3500 3400 2012-13 2013-14 2014-15 2015-16 2016-17
  • 49. Analysis of Demand in Domestic Market 1. Power Transformer:- It is clear from data and graph that the demand of power transformer is fluctuating in nature. In 2005 to 2012, demand was 842, 948, 760, 1192, 1150, 975 & 855 in quantity. The reasons for fluctuating & decrease in trend from 2008-12 may be due to role of recession, FDI, China equipment‟s are imported & tenders go to Foreign market so no role for Indian parties to involve for demand. After Forecasting, from 2012-2017, the demand is continuously increasing in a very small amount (1027, 1044, 1061, 1078 & 1095) in quantity. 2. Dry Type Transformer:- In this type of transformer, In 2005 to 2012, the actual demand was 335, 873, 1200, 927, 794, 708 & 769 in quantity. The reasons for fluctuating nature in trend from 2005-12 may be due to role of recession, FDI, China equipment‟s are imported, costlier design so less demand & no coils filled so less dangerous used mainly in Small scale industries, Townships etc., so more demand for Dry Type Transformers. After forecasting, from 2012-2017, the demand is continuously increasing in a very small amount (1039, 1059, 1079, 1099 & 1119) in quantity. 3. HVR Transformer:- In this type of transformer, In 2005 to 2012, the actual demand was 1149, 3684, 4611, 2803, 3043, 4289 & 2451 in quantity. The reasons for fluctuations may be due to role of recession, FDI, China equipment‟s are imported & technology has changed drastically. After forecasting, In 2012-17 the demand is increasing continuously increasing in good amount (3656, 3783, 3910, 4037 & 4164) in quantity. 4. Instrument Transformer:- In this type of transformer, In 2005 to 2012, the actual demand was 6822, 7419, 5875, 10715, 8845, 9702 & 7178 in quantity. The reasons for fluctuations may be due to role of recession, FDI, China equipment‟s are imported, decrease in trend due to Indian market tenders doesn‟t float and it goes to Foreign market & less technological. Increase trend shows indications of power shortage increase, population increase, more standard of living so more power instruments are required & some new customers are coming up due to liberalization of Govt. policies for captive power plant. After forecasting, from 2012 to 2017, the demand is continuously increasing in a very large amount (9306, 9613, 9920, 10227 & 10534) in quantity.
  • 50. SWOT ANALYSIS OF BHEL STRENGTH:- 1. Manufacturing Capacity:- The manufacturing capacity of BHEL is 105 transformer per year . However the demand in market is 900 per year. 2. Mixed Product:- BHEL manufacture mixed product such as power transformers, DTT , INST transformer, HVR, etc. That‟s why it can meet mixed demand also compared to other manufacturers 3. EPC contractor (Engineering Procurement & Construction):- It has 14 manufacturing units. BHEL can design, procure raw material & do construct transformers. WEAKNESS:- 1. Long Procurement Cycle:- Being a Government organization everything is goes in a systematic manner & it takes more & more time. 2. Delay in Response:- Because of long procurement cycle the response is also delay. OPPORTUNITY:- 1. High Demand:- Because of high demand it can takes more orders & do more business. 2. It is established supplies so some government parties also prefer BHEL 3. Being an EPC Contractor it can get more EPC contract. 4. Joint Venture with Siemens in the name of Power Plant Performance Improvement Limited (PPIL), is a major strength for the company. This tie-up will be beneficial as there is a lot of scope for business. THREAT:- 1. Competition with Siemen‟s, Vijay, BL, EMG, etc. 2. New entrance of Firms in Market Such as Kanohar, Victory, IMP, ECE, etc.
  • 51. FINDINGS  A Demand of BHEL Transformers has been increased in the last two years.  Less technological in comparison to their competitors.  At this time BHEL has good number of customers, this shows the progress of BHEL in the near future.
  • 52. LIMITATIONS Nobody is perfect in the world. Everybody makes some mistakes. If somebody doesn‟t makes mistakes that means he or she doesn‟t work because when you do some work you are bound to make some mistakes & there is always room for improvements. So this study may also not be free of mistakes. But I have tried my level best to make this project BEST. There may be some mistakes in this study. They may be as follows:-  The DATA has been mainly collected from Transformer & Commercial Department (TRC) of BHEL Jhansi, mainly it comes under the SECONDARY DATA (from BHEL annual reports, records & books)
  • 53. CONCLUSION After studying and analyzing various aspects of this project, I have concluded that I have gained lot of knowledge about this unit and BHEL Company. My project which is based on the topic of “Demand Analysis of Transformers” is based the export-import procedure and demand analysis of BHEL. During my training period I have done rotation work in which I know about its working routine and collected lots of information about its product like transformers and Locomotive. I have done my project on “Demand Analysis of transformers” such as power transformer, dry type transformers, HVR transformers & Instrument transformer. So, through this project I have learned:  Analysis of Future demand of BHEL transformers in domestic market  Export & Import Procedure  Specific requirement of export & import
  • 54. RECOMMENDATION & SUGGESTIONS  BHEL must try to find out the reasons of decreasing demand of transformers such as power transformers, Instrument transformers & HVR transformers in domestic market.  BHEL must try to change their marketing strategies.  There should be optimum utilization of all factors of production.  Modernization of techniques and up gradation of existing machinery.  Avoid indigenization.  They should try to motivate the employee and try to change their work so they get the interest against their work and enjoy the work also increase the knowledge.  The main products of BHEL JHANSI are Transformers & Locomotives.To expand the market for these products of BHEL, regular seminars should be conducted. These seminars should emphases on the awareness & advertisement of BHEL‟s product & their characteristic, features etc. among the customers related to that region this will in turn help in advertising of BHEL‟s product in the region of immense competitors where the other players are situated.
  • 55. WEBSITES VISITED www.Bhel.com www.google.com www.Ask.com www.wikipedia.in BIBLOGRAPHY  Marketing Management (Kotler)  Marketing Research (C.R. Kothari)  Business Statistics (R.P. Varshney)  Annual REPORTS of BHEL