market and demand analysis (part 2)
TRANSCRIPT
Market And Demand Analysis - 2
Presented By: Rashedul Kabir
Sr. Asst. Secretary, R&DSEIP Project, BKMEA
Theoretical Part
Pattern Prediction
Predict the next number in the pattern• 1, 4, 7, 10, 13, ………?
•
• 1, 3, 9, …………..?
...?
Pattern Prediction
• Predict the next number in the pattern (Solution): 1. 2.
3.
Demand Forecasting MethodsForecasting Methods
QuantitativeCasual
Consumption Level
Chain Ratio
End Use
Bass Diffusion
Leading Indicator
Econometric
Time SeriesSmoothing
Moving Average
Weighted Moving Average
Exponential Smoothing
Trend Projection
Trend Projection Adjusted for Seasonal Influence
QualitativeDelphi
Expert Judgment
Scenario Writing
Intuitive Approaches
Forecasting Horizon
Range Horizon Application Method
Long >5 years1. Facility planning2. Capacity planning3. Product planning
1. Economic2. Demographic3. Market
Information
Medium 1-5 years1. Staffing plan2. Aggregate
production plan
1. Time series2. Regression
analysis
Short1 day to 1 year
1. Purchasing2. Detail job
schedule
1. Exponential2. Smoothing3. Trend exploration4. Graphical
methods
Forecasting Methods
Qualitative method Quantitative method
1. Characteristics Based on human judgment, opinions; subjective and nonmathematical
Based on mathematics;quantitative in nature
2. Strength Can incorporate latest changes in the environment and “inside information.”
Consistent and objective; able to consider much information and data at one time
3. Weakness Can bias the forecast and reduce forecast accuracy
Often quantifiable data are not available. Only as good as the data on which they are based
Forecasting methods are classified into two groups
Qualitative Methods1. Jury of executive methods/Expert Judgment/Jury of Executive opinion method: This method involves asking the opinions of a group of managers on expected future sales and combining them in to a sales estimate.
2. Delphi method: This method is used for producing the opinions of a group of experts with the help of a mail survey.
Steps of Delphi method:• A group of experts is sent a questionnaire by mail and asked to express their views.• Received responses are summarized without disclosing identity and send back to
the experts to prove further reasons.• The process may be continued for one or more rounds till a reasonable agreement
emerges in the views of the experts
Continued
Qualitative Methods3. Scenario Writing:
Different sets of assumptions lead to different scenarios. The job of the decision maker is to decide how likely each scenario is and then to make decisions accordingly.
4. Intuitive Approaches
Subjective or intuitive qualitative approaches are based on the ability of human mind to process a variety of information that, in most cases, is difficult to quantify. In brainstorming sessions, individuals are freed from usual group restrictions of peer pressure and criticism.
Quantitative Methods
1. Time Series Methodsa) Trend projection method: Trend projection method involves • Determining the trend of future value by analyzing
past value statistics• Projecting future value by extrapolating the trendLinear relationship is used as most commonly employed relationships i. e.
tbXa tYContinued
Quantitative Methods
1. Time Series Methodsb)Trend Projection Adjusted Seasonal Influence
[Use SPSS software]Y(2016)Q1(1st Quarter)=7.91000+(-.44427)
=7.4673Sales Price forecast for Year 2016, 1st Quarter
Continued
Quantitative Methods
1. Time Series Methodsc) Smoothing Model:i) Exponential smoothing method:Note that the value we entered in the Damping
factor box is α=0-1; forecasts for other smoothing constants can be computed easily by entering a different value for 0-1 in the Damping factor box.
Continued
Quantitative Methods1. Time Series Methodsc) Smoothing Model:ii) Moving average method: As per the moving average method of sales forecasting the forecast for the next period is equal to the average of the sales for several preceding periods.
Where Ft+1 is the forecast for the next period, St is the sales for the current period, and n is the period over which averaging is done.
nSS ntt 11t
1t....SF
Continued
Quantitative Methods
1. Time Series Methodsc) Smoothing Model:iii) Weighted Moving Average : Weighted moving average involves selecting a different weight for each data value and then computing a weighted average of the most recent n values as the forecast.e.g. WMA=1/6*(B2)+2/6*(B3)+3/6*(B4)
Quantitative Methods
2. Causal Methodsa) Chain Ratio MethodThe potential sales of a product may be estimated by applying a series of factors to a measure of aggregate demand.For instance a firm planning to manufacture T-shirt in Bangladesh tried to estimate its potential sales in the following manner –
Adult male population in the country :150 millionProportion of adult male wearing T-shirt : 60%So Adult male population wearing T-shirt : 90 millionNumber of T-shirt one buys per year: 15 pieceTotal T-shirt needed per year: 1315 millionProportion of market capture capacity : 9%Potential sales : 121.5 million piece per year
It is a simple analytical approach to demand estimation but its success rate significantly depended on the information that uses in the estimation process. Continued
Quantitative Methods
2. Causal Methodsb) Consumption level methodThis types of estimation is useful for a product that is directly consumed. The method is basis of elasticity coefficients, the important ones being the income elasticity of demand and the price elasticity of demand.• Income Elasticity of Demand: The income elasticity of demand reflects the responsiveness of
demand to variation in income. Mathematically –
• Price Elasticity of Demand: The price elasticity of demand reflects the responsiveness of demand to variation in price. Mathematically –
-The price elasticity coefficient is applicable to only small variations-The price elasticity measure assumes that the pattern of consumer behavior remain unchanged
12
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12QQII
IIQQ
i XE
12
12
12
12QQPP
PPQQ
p XE
Continued
Quantitative Methods
2. Causal Methodsc) End use methodSuitable for estimating the demand for intermediate products, the end use method, also called the consumption behavior methods, involving the possible steps:• Identify the possible uses of the product• Define the consumption coefficient of the product for various uses• Project the output levels for the consuming industries• Derive the demand for the product
Continued
Quantitative Methods
2. Causal Methodsd) Bass diffusion modelDeveloped by Frank Bass, the Bass diffusion model seeks to estimate the pattern of sales growth for new products, in terms of two factors: p: The coefficient of innovation. It reflects the likelihood that a potential customer would adopt the product because of its innovative features.q: The coefficient of imitation. It reflects the tendency of a potential customer to buy the product because many others have bought it. It can be regarded as a network effect.According to a linear approximation of the model:
Where nt is the sales in period t, p is the coefficient of innovation, N is the potential size of the market, q is the coefficient of imitation, and Nt is the accumulative sales made until period.
211 )()/()( ttt NXNqNpqpNn
Continued
Quantitative Methods2. Causal Methodse) Leading indicator methodSteps:
• Identify the appropriate leading indicator(s): change ahead of other variables
• The lead-lag relationship: lagging variables
For example, the change in the level of urbanization (a leading indicator) may be used to predict the change in the demand for air conditions (a lagging variable).
Continued
Quantitative Methods
2. Causal Methodsf) Econometric methodAn econometric model is a mathematical representation of economic relationship(s) derived from economic theory. The primary objective of econometric analysis is to forecast the future behavior of the economic variables incorporated in the model.An example of the single equation model is given below:
Where Dt is demand for a certain product for year t, Pt is price for the product in year t, and Nt=income in year t.>The simultaneous equation model portrays economic relationships in terms of two or more equations.
ttt NaPaaD 210
Uncertainties in Forecasting(i) Data about past and present market-Lack of standardization-Few observations-Influence of abnormal factors(ii) Methods of forecasting-Inability to handle unquantifiable factors-Unrealistic assumptions-Excessive data requirement(iii) Environmental changes-Technological change-Shift in governmental policy-Developments on the international scene-Discovery of new sources of raw material-Vagaries of monsoon
Coping with Uncertainties• Conduct analysis with data based on uniform and standard definitions.• In identifying trends, coefficients, and relationships, ignore the abnormal
or out-of-the-ordinary observations.• Critically evaluate the assumptions of the forecasting methods and
choose a method which is appropriate to the situation.• Adjust the projections derived from quantitative analysis in the light of a
due consideration of unquantifiable, but significant influences.• Monitor the environment imaginatively to identify important changes.• Consider likely alternative scenarios and their impact on market and
competition.• Conduct sensitivity analysis to assess the impact on the size of demand
for unfavorable and favorable variations of the determining factors from their most likely levels.
Source/Reference• PROJECS Planning Analysis, Selection, Financing, Implementation, and
Review (8th edition), by Prasanna Chandra• Statistics for Business and Economics (11th edition), by Anderson,
Sweeny, and Williams• Sourcing and Supply Chain Management (5th edition), by Handfield,
Monczka, Giunipero, and Patterson• Fundamentals of Statistics (7th edition), S.C. Gupta• Basic Econometrics (4th edition), by Damodar N. Gujarati• Introductory Econometrics: A Modern Approach (5th edition), by
Jeffrey Wooldridge• An Introduction to Statistics (4th edition) ,By Mian & Miyan
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