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PRESENTATION
Market and Demand
     Analysis
Group- 02
Sl.
No.             Name                 ID       Program


1.    Md. Samiul Islam Chowdhury   10105063   BSEEE


2.           Abul Kalam            10105019   BSEEE


3.         Md. Masud Rana          10105059   BSEEE


4.        Md. Ashraful Haque       10105033   BSEEE


5.         Md.Rezaul Karim         09105087   BSEEE
Overview

• Situational Analysis & Specifications of Objective.
      • Collection of Secondary Information.
            • Conduct of Market Survey.
          • Characterization of the Market.
               • Demand Forecasting.
      • Uncertainties in Demand Forecasting.
                 • Market planning.



                                                        4
Key Step in Market & Demand Analysis and
             Their Inter-relationship
                    Collection of                         Demand
                    Secondary                             Forecasting
                    Information




                                    Characterization of
Situational
                                    the Market
Analysis and
Specifications of
Objectives


                                                          Market Planning
                    Conduct of
                    Market Survey
SITUATIONAL ANALYSIS AND
         SPECIFICATIONS OF OBJECTIVES
 Get a “feel” for the relationship between the product and it’s market,
  the project analyst may informally talk to customers, competitors,
  middlemen and other in the industry.
 Look at the experience of the company to learn about the purchasing
  power of customer, action & strategies of competitors.
 The objectives of market & Demand analysis, to answer the
  following question : (for air coolers)
 Who are the buyers of air cooler?
 What is the total current demand for air coolers?
 What price will the customer be willing to pay for the improved air
  cooler.
 What price & warranty will ensure its acceptance?
 What are the prospects of immediate sales? etc.
Collection of Secondary Information

 Secondary Information is information that has been gathered   in some
  other context and is already available.
 Secondary information provides the base and starting point for the
  market & Demand analysis.
 Also discussed on :
 General Sources of Secondary Information
 Industry Specific Sources of Secondary Information
 Evaluation of Secondary Information



                                                                   7
Conduct of Market Survey
 The market survey may be a census survey or a sample
  survey.
 Census survey are employed principally for intermediate
  goods & investment goods when such goods are used by a
  small number of firms.
• Steps in a Sample Survey
   – Define the Target Population
   – Select the Sampling Scheme and Sample Size
   – Develop the Questionnaire
   – Recruit and Train the Field Investigators
   – Obtain Information as Per the Questionnaire from the
     Sample of Respondents
   – Scrutinizes the Information Gathered
                                                          8
   – Analyze and interpret the Information
Conduct of Market Survey

Some Problems:
         – Heterogeneity of the Country
         – Multiplicity of the Languages
           – Design of Questionnaire




                                           9
Characterization of the Market
 Effective Demand in the Past and Present
 Production + Imports – Exports – Change in stock level
 Breakdown of Demand
   – Nature of Product
   – Consumer Groups
   – Geographical Division
 Price
 Methods of Distribution and Sales Promotion
 Consumers
 Supply and Competition
 Government Policy
                                                          10
Forecasting
Predicting the future
Qualitative forecast methods
  – subjective
Quantitative forecast methods
  – based on mathematical formulas
Depend on
  – time frame
  – demand behavior
  – causes of behavior
Demand Forecasting
Qualitative Methods
  – These methods rely essentially on the judgment
    of experts to translate qualitative information into
    quantitative estimates
  – Used to generate forecasts if historical data are
    not available (e.g., introduction of new product)
  – The important qualitative methods are:
     • Jury of Executive Method
     • Delphi Method


                                                       12
Jury of Executive Opinion Method
 Rationale
   – Upper-level management has best information on latest
     product developments and future product launches
 Approach
   – Small group of upper-level managers collectively develop
     forecasts – Opinion of Group
 Main advantages
   – Combine knowledge and expertise from various
     functional areas
   – People who have best information on future
     developments generate the forecasts

                                                             13
Jury of Executive Opinion Method
Main drawbacks
  – Expensive
  – No individual responsibility for forecast quality
  – Risk that few people dominate the group
  – Subjective
  – Reliability is questionable
Typical applications
  – Short-term and medium-term demand forecasting


                                                        14
Delphi Method
 Rationale

  – Eliciting the opinions of a group of experts with
    the help of mail survey

  – Anonymous written responses encourage honesty
    and avoid that a group of experts are dominated by
    only a few members


                                                        15
Delphi Method
   Approach

Coordinator     Each expert            Coordinator
Sends Initial   writes response        performs
Questionnaire   (anonymous)            analysis


                Coordinator       No
                                                           Coordinator
                sends updated           Consensus    Yes
                                                           summarizes
                questionnaire           reached?           forecast




                                                                   16
Delphi Method
 Main advantages
   – Generate consensus
   – Can forecast long-term trend without availability of
     historical data
 Main drawbacks
   – Slow process
   – Experts are not accountable for their responses
   – Little evidence that reliable long-term forecasts can be
     generated with Delphi or other methods
 Typical application
                     – Long-term forecasting
                    – Technology forecasting
                                                            17
Time Series Projection Methods
• These methods generate forecasts on the basis of an
  analysis of the historical time series.
• Assume that what has occurred in the past will
  continue to occur in the future
• Relate the forecast to only one factor - time
The important time series projection methods are:
   – Trend Projection Method
   – Exponential Smoothing Method
   – Moving Average Method

                                                        18
Trend Projection Method
Advantages
• It uses all observations
• The straight line is derived by statistical procedure
• A measure of goodness fit is available

Disadvantages
• More complicated
• The results are valid only when certain conditions are
  satisfied

                                                           19
Exponential Smoothing
 Exponential smoothing, forecasts are modified in the
 light of observed errors.
 If the forecast value for year t, Ft, is less than the
 actual value for year t, St, the forecast for the year
 t+1, Ft + 1 ..
                Ft + 1 = Ft + α et
Where Ft + 1 = forecast for year )
α = smoothing parameter
et = error in the forecast for year t = St = Ft
Solution of problem for Exponential
             Smoothing
Moving Average
 Naive forecast
    – demand in current period is used as next period’s forecast
 Simple moving average
    – uses average demand for a fixed sequence of periods
    – stable demand with no pronounced behavioral patterns
 Weighted moving average
    – weights are assigned to most recent data
   According to the moving average method
         St + S t – 1 +…+ S t – n +1
Ft + 1 =
                    n
where Ft + 1 = forecast for the next period
         St = sales for the current period
         n = period over which averaging is done
                                                                      22
                                                                   12-22
Weighted Moving Average
                                n

 Adjusts moving WMAn = i1 Wi Di
                           =
  average
  method to      where
  more closely     Wi = the weight for period i,
  reflect data           between 0 and 100
                         percent
  fluctuations
                         Wi = 1.00

                                                      23
                                                   12-23
Weighted Moving Average Example

    MONTH               WEIGHT          DATA
    August                17%            130
    September             33%            110
    October               50%            90
                                        3
  November Forecast         WMA3 =      1 Wi Di
                                       i=

     = (0.50)(90) + (0.33)(110) + (0.17)(130)

                  = 103.4 orders
                                                      24
                                                   12-24
Causal Methods

 Causal methods seek to develop forecasts on
 the basis of cause-effects relationships
 specified in an explicit, quantitative manner.
  – Chain Ratio Method
  – Consumption Level Method
  – End Use Method
  – Leading Indicator Method
  – Econometric Method
                                             25
Chain Ratio Methods
 Market Potential for heated coats in the U.S.:
   – Population (U) = 280,000,000
   – Proportion of U that are age over 16 (A) = 75%
   – Proportion of A that are men (M) = 50%
   – Proportion of M that have incomes over $65k (I) = 50%
   – Proportion of I that live in cold states (C) = 50%
   – Proportion of C that ski regularly (S) = 10%
   – Proportion of S that are fashion conscious (F) = 30%
   – Proportion of F that are early adopters (E) = 10%
   – Average number of ski coats purchased per year (Y) = .5
     coats
   – Average price per coat (P) = $ 200

                                                          26
Chain Ratio Methods
 Market Potential for heated coats in the U.S.:
  Market Sales Potential =
  UxAxM xI xCxS xF xExY
  = 280 Million x 0.75 x 0.50 x 0.50 x 0.50 x 0.10 x
    0.30 x 0.10 x200
  = $7.88 Million




                                                       27
Consumption Level Method

This method is used for those products that are
 directly consumed. This method measures the
 consumption level on the basis of elasticity
 coefficients.




                                               28
Consumption Level Method

 Income Elasticity: This reflects the responsiveness
  of demand to variations in income. It is calculated
  as:
      E1 = [Q2 - Q1/ I2- I1] * [I1+I2/ Q2 +Q1]
• Where
  E1 = Income elasticity of demand
  Q1 = quantity demanded in the base year
  Q2 = quantity demanded in the following year
  I1 = income level in the base year
  I2 = income level in the following year
                                                   29
Consumption Level Method

Price Elasticity: This reflects the responsiveness of
  demand to variations in price. It is calculated as:
     EP = [Q2 - Q1/ P2- P1] * [P1+P2/ Q2 +Q1]
• Where
   EP = Price elasticity of demand
   Q1 = quantity demanded in the base year
   Q2 = quantity demanded in the following year
   P1 = price level in the base year
   P2 = price level in the following year
                                                    30
End Use Method
 Suitable for estimating demand for intermediate
    products
 Also called as consumption coefficient method
Steps
1. Identify the possible uses of the products
2. Define the consumption coefficient of the product
    for various uses
3. Project the output levels for the consuming
    industries
4. Derive the demand for the project
                                                       31
End Use Method
  This method forecasts the demand based on the
  consumption coefficient of the various uses of the
  product.


          Projected Demand for Indchem
             Consumption    Projected Output   Projected Demand for
              Coefficient       in Year X       Indchem in Year X
Alpha            2.0            10,000               20,000
Beta             1.2            15,000               18,000
Kappa            0.8            20,000               16,000
Gamma            0.5            30,000               15,000
                                 Total               69,000
                                                               32
Leading Indicator Method
 This method uses the changes in the leading
  indicators to predict the changes in the
  lagging indicators.
 Two basic steps:
  1. Identify the appropriate leading indicator(s)
  2. Establish the relationship between the leading
     indicator(s) and the variable to forecast.



                                                      33
Econometric Method
An advanced forecasting tool, it is a mathematical
   expression of economic relationships derived from
   economic theory.
Economic variables incorporated in the model
1. Single Equation Model
      Dt = a0 + a1 Pt + a2 Nt
Where
   Dt = demand for a certain product in year t.
   Pt = price of the product in year t.
   Nt = income in year t.
                                                   34
Econometric Method
2. Simultaneous equation method
  GNPt = Gt + It + Ct
      It = a0 + a1 GNPt
      Ct = b0 + b1 GNPt
• Where
  GNPt = gross national product for year t.
     Gt = Governmental purchase for year t.
     It = Gross investment for year t.
     Ct= Consumption for year t.
                                              35
Econometric Method
Advantages
• The process sharpens the understanding of
  complex cause – effect relationships
• This method provides basis for testing
  assumptions
Disadvantages
• It is expensive and data demanding
• To forecast the behaviour of dependant
  variable, one needs the projected values of
  independent variables
                                                36
Uncertainties in Demand Forecasting

 Data about past and present markets.
   – Lack of standardization:- product, price, quantity,
     cost, income….
   – Few observations
   – Influence of abnormal factors:- war, natural
     calamity
  Methods of forecasting
   – Inability to handle unquantifiable factors
   – Unrealistic assumptions
   – Excessive data requirement                      37
Uncertainties in Demand Forecasting

 Environmental changes
  – Technological changes
  – Shift in government policy
  – Developments on the international scene
  – Discovery of new source of raw material
  – Vagaries of monsoon




                                              38
Coping With Uncertainties
 Conduct analysis with data based on uniform
 and standard definitions.
 Ignore the abnormal or out-of-ordinary
 observations.
 Critically evaluate the assumptions
 Adjust the projections.
 Monitor the environment.
 Consider likely alternative scenarios.
 Conduct sensitivity analysis
                                            39
Market planning
Current marketing situation
 - Market, Competition, Distribution, PEST.
Opportunity and issue analysis - SWOT
Objectives- Break even, % market share…
Marketing strategy- target segment,
 positioning, 4 Ps
Action program- Quarter 1, Q2, Q3….



                                              40
Thank You

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Group 02's Market and Demand Analysis Presentation

  • 2. Market and Demand Analysis
  • 3. Group- 02 Sl. No. Name ID Program 1. Md. Samiul Islam Chowdhury 10105063 BSEEE 2. Abul Kalam 10105019 BSEEE 3. Md. Masud Rana 10105059 BSEEE 4. Md. Ashraful Haque 10105033 BSEEE 5. Md.Rezaul Karim 09105087 BSEEE
  • 4. Overview • Situational Analysis & Specifications of Objective. • Collection of Secondary Information. • Conduct of Market Survey. • Characterization of the Market. • Demand Forecasting. • Uncertainties in Demand Forecasting. • Market planning. 4
  • 5. Key Step in Market & Demand Analysis and Their Inter-relationship Collection of Demand Secondary Forecasting Information Characterization of Situational the Market Analysis and Specifications of Objectives Market Planning Conduct of Market Survey
  • 6. SITUATIONAL ANALYSIS AND SPECIFICATIONS OF OBJECTIVES  Get a “feel” for the relationship between the product and it’s market, the project analyst may informally talk to customers, competitors, middlemen and other in the industry.  Look at the experience of the company to learn about the purchasing power of customer, action & strategies of competitors.  The objectives of market & Demand analysis, to answer the following question : (for air coolers)  Who are the buyers of air cooler?  What is the total current demand for air coolers?  What price will the customer be willing to pay for the improved air cooler.  What price & warranty will ensure its acceptance?  What are the prospects of immediate sales? etc.
  • 7. Collection of Secondary Information  Secondary Information is information that has been gathered in some other context and is already available.  Secondary information provides the base and starting point for the market & Demand analysis.  Also discussed on :  General Sources of Secondary Information  Industry Specific Sources of Secondary Information  Evaluation of Secondary Information 7
  • 8. Conduct of Market Survey  The market survey may be a census survey or a sample survey.  Census survey are employed principally for intermediate goods & investment goods when such goods are used by a small number of firms. • Steps in a Sample Survey – Define the Target Population – Select the Sampling Scheme and Sample Size – Develop the Questionnaire – Recruit and Train the Field Investigators – Obtain Information as Per the Questionnaire from the Sample of Respondents – Scrutinizes the Information Gathered 8 – Analyze and interpret the Information
  • 9. Conduct of Market Survey Some Problems: – Heterogeneity of the Country – Multiplicity of the Languages – Design of Questionnaire 9
  • 10. Characterization of the Market  Effective Demand in the Past and Present Production + Imports – Exports – Change in stock level  Breakdown of Demand – Nature of Product – Consumer Groups – Geographical Division  Price  Methods of Distribution and Sales Promotion  Consumers  Supply and Competition  Government Policy 10
  • 11. Forecasting Predicting the future Qualitative forecast methods – subjective Quantitative forecast methods – based on mathematical formulas Depend on – time frame – demand behavior – causes of behavior
  • 12. Demand Forecasting Qualitative Methods – These methods rely essentially on the judgment of experts to translate qualitative information into quantitative estimates – Used to generate forecasts if historical data are not available (e.g., introduction of new product) – The important qualitative methods are: • Jury of Executive Method • Delphi Method 12
  • 13. Jury of Executive Opinion Method Rationale – Upper-level management has best information on latest product developments and future product launches Approach – Small group of upper-level managers collectively develop forecasts – Opinion of Group Main advantages – Combine knowledge and expertise from various functional areas – People who have best information on future developments generate the forecasts 13
  • 14. Jury of Executive Opinion Method Main drawbacks – Expensive – No individual responsibility for forecast quality – Risk that few people dominate the group – Subjective – Reliability is questionable Typical applications – Short-term and medium-term demand forecasting 14
  • 15. Delphi Method  Rationale – Eliciting the opinions of a group of experts with the help of mail survey – Anonymous written responses encourage honesty and avoid that a group of experts are dominated by only a few members 15
  • 16. Delphi Method  Approach Coordinator Each expert Coordinator Sends Initial writes response performs Questionnaire (anonymous) analysis Coordinator No Coordinator sends updated Consensus Yes summarizes questionnaire reached? forecast 16
  • 17. Delphi Method  Main advantages – Generate consensus – Can forecast long-term trend without availability of historical data  Main drawbacks – Slow process – Experts are not accountable for their responses – Little evidence that reliable long-term forecasts can be generated with Delphi or other methods  Typical application – Long-term forecasting – Technology forecasting 17
  • 18. Time Series Projection Methods • These methods generate forecasts on the basis of an analysis of the historical time series. • Assume that what has occurred in the past will continue to occur in the future • Relate the forecast to only one factor - time The important time series projection methods are: – Trend Projection Method – Exponential Smoothing Method – Moving Average Method 18
  • 19. Trend Projection Method Advantages • It uses all observations • The straight line is derived by statistical procedure • A measure of goodness fit is available Disadvantages • More complicated • The results are valid only when certain conditions are satisfied 19
  • 20. Exponential Smoothing  Exponential smoothing, forecasts are modified in the light of observed errors.  If the forecast value for year t, Ft, is less than the actual value for year t, St, the forecast for the year t+1, Ft + 1 .. Ft + 1 = Ft + α et Where Ft + 1 = forecast for year ) α = smoothing parameter et = error in the forecast for year t = St = Ft
  • 21. Solution of problem for Exponential Smoothing
  • 22. Moving Average  Naive forecast – demand in current period is used as next period’s forecast  Simple moving average – uses average demand for a fixed sequence of periods – stable demand with no pronounced behavioral patterns  Weighted moving average – weights are assigned to most recent data  According to the moving average method St + S t – 1 +…+ S t – n +1 Ft + 1 = n where Ft + 1 = forecast for the next period St = sales for the current period n = period over which averaging is done 22 12-22
  • 23. Weighted Moving Average n  Adjusts moving WMAn = i1 Wi Di = average method to where more closely Wi = the weight for period i, reflect data between 0 and 100 percent fluctuations  Wi = 1.00 23 12-23
  • 24. Weighted Moving Average Example MONTH WEIGHT DATA August 17% 130 September 33% 110 October 50% 90 3 November Forecast WMA3 = 1 Wi Di i= = (0.50)(90) + (0.33)(110) + (0.17)(130) = 103.4 orders 24 12-24
  • 25. Causal Methods  Causal methods seek to develop forecasts on the basis of cause-effects relationships specified in an explicit, quantitative manner. – Chain Ratio Method – Consumption Level Method – End Use Method – Leading Indicator Method – Econometric Method 25
  • 26. Chain Ratio Methods  Market Potential for heated coats in the U.S.: – Population (U) = 280,000,000 – Proportion of U that are age over 16 (A) = 75% – Proportion of A that are men (M) = 50% – Proportion of M that have incomes over $65k (I) = 50% – Proportion of I that live in cold states (C) = 50% – Proportion of C that ski regularly (S) = 10% – Proportion of S that are fashion conscious (F) = 30% – Proportion of F that are early adopters (E) = 10% – Average number of ski coats purchased per year (Y) = .5 coats – Average price per coat (P) = $ 200 26
  • 27. Chain Ratio Methods  Market Potential for heated coats in the U.S.: Market Sales Potential = UxAxM xI xCxS xF xExY = 280 Million x 0.75 x 0.50 x 0.50 x 0.50 x 0.10 x 0.30 x 0.10 x200 = $7.88 Million 27
  • 28. Consumption Level Method This method is used for those products that are directly consumed. This method measures the consumption level on the basis of elasticity coefficients. 28
  • 29. Consumption Level Method  Income Elasticity: This reflects the responsiveness of demand to variations in income. It is calculated as: E1 = [Q2 - Q1/ I2- I1] * [I1+I2/ Q2 +Q1] • Where E1 = Income elasticity of demand Q1 = quantity demanded in the base year Q2 = quantity demanded in the following year I1 = income level in the base year I2 = income level in the following year 29
  • 30. Consumption Level Method Price Elasticity: This reflects the responsiveness of demand to variations in price. It is calculated as: EP = [Q2 - Q1/ P2- P1] * [P1+P2/ Q2 +Q1] • Where EP = Price elasticity of demand Q1 = quantity demanded in the base year Q2 = quantity demanded in the following year P1 = price level in the base year P2 = price level in the following year 30
  • 31. End Use Method  Suitable for estimating demand for intermediate products  Also called as consumption coefficient method Steps 1. Identify the possible uses of the products 2. Define the consumption coefficient of the product for various uses 3. Project the output levels for the consuming industries 4. Derive the demand for the project 31
  • 32. End Use Method  This method forecasts the demand based on the consumption coefficient of the various uses of the product. Projected Demand for Indchem Consumption Projected Output Projected Demand for Coefficient in Year X Indchem in Year X Alpha 2.0 10,000 20,000 Beta 1.2 15,000 18,000 Kappa 0.8 20,000 16,000 Gamma 0.5 30,000 15,000 Total 69,000 32
  • 33. Leading Indicator Method  This method uses the changes in the leading indicators to predict the changes in the lagging indicators.  Two basic steps: 1. Identify the appropriate leading indicator(s) 2. Establish the relationship between the leading indicator(s) and the variable to forecast. 33
  • 34. Econometric Method An advanced forecasting tool, it is a mathematical expression of economic relationships derived from economic theory. Economic variables incorporated in the model 1. Single Equation Model Dt = a0 + a1 Pt + a2 Nt Where Dt = demand for a certain product in year t. Pt = price of the product in year t. Nt = income in year t. 34
  • 35. Econometric Method 2. Simultaneous equation method GNPt = Gt + It + Ct It = a0 + a1 GNPt Ct = b0 + b1 GNPt • Where GNPt = gross national product for year t. Gt = Governmental purchase for year t. It = Gross investment for year t. Ct= Consumption for year t. 35
  • 36. Econometric Method Advantages • The process sharpens the understanding of complex cause – effect relationships • This method provides basis for testing assumptions Disadvantages • It is expensive and data demanding • To forecast the behaviour of dependant variable, one needs the projected values of independent variables 36
  • 37. Uncertainties in Demand Forecasting Data about past and present markets. – Lack of standardization:- product, price, quantity, cost, income…. – Few observations – Influence of abnormal factors:- war, natural calamity  Methods of forecasting – Inability to handle unquantifiable factors – Unrealistic assumptions – Excessive data requirement 37
  • 38. Uncertainties in Demand Forecasting  Environmental changes – Technological changes – Shift in government policy – Developments on the international scene – Discovery of new source of raw material – Vagaries of monsoon 38
  • 39. Coping With Uncertainties  Conduct analysis with data based on uniform and standard definitions.  Ignore the abnormal or out-of-ordinary observations.  Critically evaluate the assumptions  Adjust the projections.  Monitor the environment.  Consider likely alternative scenarios.  Conduct sensitivity analysis 39
  • 40. Market planning Current marketing situation - Market, Competition, Distribution, PEST. Opportunity and issue analysis - SWOT Objectives- Break even, % market share… Marketing strategy- target segment, positioning, 4 Ps Action program- Quarter 1, Q2, Q3…. 40