Market and demand analysis 2

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


 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


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

Market and demand analysis 2

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