1. 2nd module
Preliminary Screening
• Compatibility with the promoter
• Consistency with the governmental priorities
• Availability of inputs
• Adequacy of market
• Reasonableness of cost
• Acceptability of the risk level
2. Project Rating Index
• Identify factors relevant for project rating
• Assign weights to these factors
• Rate the project proposal on various
factors, using a suitable rate scaling(5-7)
• For each factor multiply the factor rating to
get factor score
• Add all the factor scores to get the overall
project rating index
3. Construction of a Rating Index
Factor Factor Rating Factor score
weight
VG 5 G4 A3 P2 VP 0
Input availability 0.25 y 0.75
Technical know-how 0.10 y 0.40
Reasonableness of cost 0.05 y 0.20
Adequacy of market 0.15 y 0.75
Complementary relationship with 0.05 y 0.20
other products
Stability 0.10 y 0.40
Dependence on firm’s strength 0.20 y 1.00
Consistency with government 0.10 y 0.30
policies
Total Rating Index 4.00
4. Sources of positive NPV
• Economies of scale
• Product differentiation
• effective Ad and superior market
• Exceptional service
• Innovative product features
• High quality and dependability
• Cost advantage
• Accumulated experience and comparative edge on
learning curve
• Monopolistic access to low cost material
• A favorable location
• More effective cost control and cost reduction
5. • Market reach
• ex.Avon market network
• HUL distribution network
• Technological edge
• IBM & Intel
• Government policy
• Restrictive licensing
• Import restriction
• High tariff walls
• Environmental controls
• Special tax releifs
7. Threat of substitute products
• Threat of substitute products means how easily
your customers can switch to your competitors
product. Threat of substitute is high when:
• There are many substitute products available
• Customer can easily find the product or service
that you’re offering at the same or less price
• Quality of the competitors’ product is better
• Substitute product is by a company earning high
profits so can reduce prices to the lowest level.
8. Threat of new entrants
• A new entry of a competitor into your market also
weakens your power. Threat of new entry depends
upon entry and exit barriers. Threat of new entry is
high when:
• Capital requirements to start the business are less
• Few economies of scale are in place
• Customers can easily switch (low switching cost)
• Your key technology is not hard to acquire or isn’t
protected well
• Your product is not differentiated
9. Industry Rivalry
• Industry rivalry mean the intensity of
competition among the existing competitors in
the market. Intensity of rivalry depends on the
number of competitors and their
capabilities. Industry rivalry is high when:
• There are number of small or equal competitors
and less when there’s a clear market leader.
• Customers have low switching costs
• Industry is growing
• Exit barriers are high and rivals stay and compete
• Fixed cost are high resulting huge production and
reduction in prices
10. Bargaining power of suppliers
• Bargaining Power of supplier means how strong
is the position of a seller. How much your
supplier have control over increasing the Price of
supplies. Suppliers are more powerful when
• Suppliers are concentrated and well organized
• a few substitutes available to supplies
• Their product is most effective or unique
• Switching cost, from one suppliers to another, is
high
• You are not an important customer to Supplier
11. Bargaining power of Buyers
• Bargaining Power of Buyers means, How much control
the buyers have to drive down your products price, Can
they work together in ordering large volumes. Buyers
have more bargaining power when:
• Few buyers chasing too many goods
• Buyer purchases in bulk quantities
• Product is not differentiated
• Buyer’s cost of switching to a competitors’ product is
low
• Shopping cost is low
• Buyers are price sensitive
• Credible Threat of integration
12. Qualities of successful Entrepreneur
• Willingness to make sacrifices
• Leadership
• Decisiveness
• Confidence in the project
• Market orientation ex.Edwin Land Polaroid
• Strong ego
14. Collection of Demand
Secondary Forecasting
Information
Situational
Characterization of
Analysis and
the Market
Specifications of
Objectives
Conduct of Market Planning
Market Survey
14
16. COLLECTION OF SECONDARY
INFORMATION
• General Sources of Secondary Information
• Industry Specific Sources of Secondary
Information
• Evaluation of Secondary Information
16
17. SECONDARY SOURCES
OF DATA
1. Indian Economic Survey
2. Indian Basic Facts
3. Reports of Export Working Groups on Various
Industries
4. Census of Manufacturing Industries
5. Indian Statistical Yearbook
6. Monthly Statistical Bulletin
7. Annual Report of RBI
8. Annual Reports and Accounts of the Companies
Listed on the Stock Exchange
9. Annual Reports of the Various Associations of
Manufacturers
17
18. CONDUCT OF
MARKET SURVEY
• Census Survey
• Sample Survey
• 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
– Analyze and interpret the Information
18
19. CONDUCT OF
MARKET SURVEY
• Some Problems
– Heterogeneity of the Country
– Multiplicity of the Languages
– Design of Questionnaire
19
20. CHARACTERISATION
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
20
21. CHARACTERISATION
OF THE MARKET
• Price
• Methods of Distribution and Sales Promotion
• Consumers
• Supply and Competition
• Government Policy
21
22. Forecasting
• Predicting the future
• Qualitative forecast
methods
– subjective
• Quantitative forecast
methods
– based on mathematical
formulas
22
12-22
23. Types of Forecasting Methods
• Depend on
– time frame
– demand behavior
– causes of behavior
23
12-23
24. Time Frame
• Indicates how far into the future is forecast
– Short- to mid-range forecast
• typically encompasses the immediate future
• daily up to two years
– Long-range forecast
• usually encompasses a period of time longer than two
years
24
12-24
25. Demand Behavior
• Trend
– a gradual, long-term up or down movement of demand
• Random variations
– movements in demand that do not follow a pattern
• Cycle
– an up-and-down repetitive movement in demand
• Seasonal pattern
– an up-and-down repetitive movement in demand
occurring periodically
25
12-25
26. Causes of Behavior
• Analytical
• Cause effect relationship basis
• Quantitative
• Explicit
26
27. 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
27
28. 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
28
29. 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
29
30. 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
30
32. 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
32
34. 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
34
35. Linear Trend Line
xy - nxy
y = a + bx b =
x2 - nx2
a = y-bx
where
a = intercept of the where
relationship n = number of periods
b = slope of the line
x = time period x
x = = mean of the x values
y = forecast for n
demand for period x y
y = n = mean of the y values
35
12-35
37. Least Squares Example (cont.)
78
x = = 6.5
12
557
y = = 46.42
12
xy - nxy 3867 - (12)(6.5)(46.42)
b = 2 - nx2
= =1.72
x 650 - 12(6.5)2
a = y - bx
= 46.42 - (1.72)(6.5) = 35.2
37
12-37
38. Linear trend line y = 35.2 + 1.72x
Forecast for period 13 y = 35.2 + 1.72(13) = 57.56 units
70 –
60 –
Actual
50 –
Demand
40 –
Linear trend line
30 –
20 –
10 – | | | | | | | | | | | | |
1 2 3 4 5 6 7 8 9 10 11 12 13
0– Period
38
12-38
39. 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
39
40. Exponential Smoothing
Averaging method
Weights most recent data more strongly
Reacts more to recent changes
Widely used, accurate method
40
12-40
41. Exponential Smoothing (cont.)
Ft +1 = Dt + (1 - )Ft
where:
Ft +1 = forecast for next period
Dt = actual demand for present period
Ft = previously determined forecast for present
period
= weighting factor, smoothing constant
41
12-41
42. Effect of Smoothing Constant
0.0 1.0
If = 0.20, then Ft +1 = 0.20 Dt + 0.80 Ft
If = 0, then Ft +1 = 0 Dt + 1 Ft = Ft
Forecast does not reflect recent data
If = 1, then Ft +1 = 1 Dt + 0 Ft = Dt
Forecast based only on most recent data
42
12-42
43. Exponential Smoothing (α=0.30)
PERIOD MONTH DEMAND F2 = D1 + (1 - )F1
1 Jan 37 = (0.30)(37) + (0.70)(37)
2 Feb 40 = 37
3 Mar 41
4 Apr 37 F3 = D2 + (1 - )F2
5 May 45 = (0.30)(40) + (0.70)(37)
6 Jun 50
= 37.9
7 Jul 43
8 Aug 47
F13 = D12 + (1 - )F12
9 Sep 56
10 Oct 52 = (0.30)(54) + (0.70)(50.84)
11 Nov 55 = 51.79
12 Dec 54
43
12-43
44. Exponential Smoothing (cont.)
FORECAST, Ft + 1
PERIOD MONTH DEMAND ( = 0.3) ( = 0.5)
1 Jan 37 – –
2 Feb 40 37.00 37.00
3 Mar 41 37.90 38.50
4 Apr 37 38.83 39.75
5 May 45 38.28 38.37
6 Jun 50 40.29 41.68
7 Jul 43 43.20 45.84
8 Aug 47 43.14 44.42
9 Sep 56 44.30 45.71
10 Oct 52 47.81 50.85
11 Nov 55 49.06 51.42
12 Dec 54 50.84 53.21
13 Jan – 51.79 53.61
44
12-44
46. 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
46
12-46
47. Moving Average:
Naïve Approach
ORDERS
MONTH PER MONTH FORECAST
Jan 120 -
Feb 90 120
Mar 100 90
Apr 75 100
May 110 75
June 50 110
July 75 50
Aug 130 75
Sept 110 130
Oct 90 110
Nov - 90
47
12-47
48. Simple Moving Average
n
Di
i=1
MAn =
n
where
n = number of periods in
the moving average
Di = demand in period i
48
12-48
49. 3-month Simple Moving Average
3
ORDERS MOVING Di
MONTH PER MONTH AVERAGE i=1
MA3 =
Jan 120 – 3
Feb 90 –
Mar 100 – 90 + 110 + 130
Apr 75 103.3 = 3
May 110 88.3
June 50 95.0
July 75 78.3 = 110 orders
Aug 130 78.3 for Nov
Sept 110 85.0
Oct 90 105.0
Nov - 110.0
49
12-49
50. 5-month Simple Moving Average
ORDERS MOVING
MONTH PER MONTH AVERAGE 5
Di
Jan 120 – i=1
Feb 90 – MA5 =
Mar 100 –
5
Apr 75 –
90 + 110 + 130+75+50
May 110 – =
June 50 99.0
5
July 75 85.0
Aug 130 82.0 = 91 orders
Sept 110 88.0 for Nov
Oct 90 95.0
Nov - 91.0
50
12-50
51. Smoothing Effects
150 –
125 – 5-month
100 –
Orders
75 –
50 – 3-month
Actual
25 –
0– | | | | | | | | | | |
Jan Feb Mar Apr May June July Aug Sept Oct Nov
Month
51
12-51
52. 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
52
12-52
53. Weighted Moving Average Example
MONTH WEIGHT DATA
August 17% 130
September 33% 110
October 50% 90
3
November Forecast WMA3 = Wi Di
i=1
= (0.50)(90) + (0.33)(110) + (0.17)(130)
= 103.4 orders
53
12-53
54. 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
54
55. CHAIN RATIO METHOD
• 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
55
56. CHAIN RATIO METHOD
• Market Potential for heated coats in the U.S.:
Market Sales Potential =
UxAxMxIxCxSxFxExY
= 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
56
57. 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. The important ones are
57
58. 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
58
59. 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
59
60. 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
60
61. 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
61
62. 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.
62
63. 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.
63
64. 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.
64
65. 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
65
66. UNCERTANITIES 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 66
67. UNCERTANITIES 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
67
68. 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
68
70. Technical Analysis
• Manufacturing process/technology
– Choice of technology
– Plant capacity
– Principals inputs
– Investment outlay and production cost
– Use by other units
– Product mix
– Latest developments
– Ease of absorption
• Appropriate technology
71. Material Input and Utilities
• Raw material
• Processed industrial materials and
components
• Auxiliary material and factory supply
• Utilities
Product Mix
73. Location and site
• Proximity to raw material and markets
• Availability of infrastructure
• Labour situation
• Governmental policies
• Other factors
• Climate conditions
• General living condition proximity to ancillary units
• Ease in coping with environmental pollution
• Site selection
74. • Machinery and equipments
– Constraints in selecting machineries and
equipment
– Procurement of plant and machine
• Structure and civil work
• Site preparation and development
• Building and development
• Building and structure
• Other works
