MARKET AND DEMAND ANALYSIS

1. MARKET AND DEMAND ANALYSIS

2. Demand Forecasting Collection of Secondary Information Situational Analysis and Specifications of Objectives Characterization of the Market Market Planning Conduct of Market Survey

3. SITUATIONAL ANALYSIS AND SPECIFICATIONS OF OBJECTIVES

4. COLLECTION OF SECONDARY INFORMATION • General Sources of Secondary Information • Industry Specific Sources of Secondary Information • Evaluation of Secondary Information

5. SECONDARY SOURCES OF DATA • Pakistan Economic Survey • Pakistan Basic Facts • Reports of Export Working Groups on Various Industries • Census of Manufacturing Industries • Pakistan Statistical Yearbook • Monthly Statistical Bulletin • Annual Report of State Bank of Pakistan • Annual Reports and Accounts of the Companies Listed on the Stock Exchange • Annual Reports of the Various Associations of Manufacturers

6. 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

7. CONDUCT OF MARKET SURVEY • Some Problems • Heterogeneity of the Country • Multiplicity of the Languages • Design of Questionnaire

8. 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

9. CHARACTERISATION OF THE MARKET • Price • Methods of Distribution and Sales Promotion • Consumers • Supply and Competition • Government Policy

10. 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

11. 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 • Main advantages • Combine knowledge and expertise from various functional areas • People who have best information on future developments generate the forecasts

12. JURY OF EXECUTIVE OPINION METHOD • Main drawbacks • Expensive • No individual responsibility for forecast quality • Risk that few people dominate the group • Typical applications • Short-term and medium-term demand forecasting

13. DELPHI METHOD • Rationale • Anonymous written responses encourage honesty and avoid that a group of experts are dominated by only a few members

14. Consensus reached? DELPHI METHOD • Approach Coordinator Sends Initial Questionnaire Each expert writes response (anonymous) Coordinator performs analysis Coordinator sends updated questionnaire Coordinator summarizes forecast No Yes

15. 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

16. DELPHI METHOD • 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. • The important time series projection methods are: • Trend Projection Method • Exponential Smoothing Method • Moving Average Method

18. CASUAL METHODS • Casual 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

19. 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

20. CHAIN RATIO METHOD • Market Potential for heated coats in the U.S.: Market Sales Potential = U x A x M x I x C x S x F x E x Y = 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

21. 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

22. 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 demandQ1 = quantity demanded in the base yearQ2 = quantity demanded in the following yearI1 = income level in the base year I2 = income level in the following year

23. 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

24. END USE METHOD • This method forecasts the demand based on the consumption coefficient of the various uses of the product.

25. LEADING INDICATOR METHOD • This method uses the changes in the leading indicators to predict the changes in the lagging indicators. • Two basic steps: • Identify the appropriate leading indicator(s) • Establish the relationship between the leading indicator(s) and the variable to forecast.

26. ECONOMETRIC METHOD • An advanced forecasting tool, it is a mathematical expression of economic relationships derived from economic theory. • 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.

27. ECONOMETRIC METHOD • 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.

28. UNCERTANITIES IN DEMAND FORECASTING • Data about past and present markets. • Lack of standardization • Few observations • Influence of abnormal factors • Methods of forecasting • Inability to handle unquantifiable factors • Unrealistic assumptions • Excessive data requirement

29. 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

30. 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