MARKET AND DEMAND ANALYSIS

Situational Analysis and Specifications of ObjectivesCollection of Secondary InformationConduct of Market SurveyCharacterization of the MarketDemand ForecastingMarket Planning

SITUATIONAL ANALYSIS AND SPECIFICATIONS OF OBJECTIVES

COLLECTION OF SECONDARY INFORMATIONGeneral Sources of Secondary InformationIndustry Specific Sources of Secondary InformationEvaluation of Secondary Information

CONDUCT OF MARKET SURVEYCensus SurveySample SurveySteps in a Sample SurveyDefine the Target PopulationSelect the Sampling Scheme and Sample SizeDevelop the QuestionnaireRecruit and Train the Field InvestigatorsObtain Information as Per the Questionnaire from the Sample of RespondentsScrutinizes the Information GatheredAnalyze and interpret the Information

CONDUCT OF MARKET SURVEYSome ProblemsHeterogeneity of the CountryMultiplicity of the LanguagesDesign of Questionnaire

CHARACTERISATION OF THE MARKETEffective Demand in the Past and Present Production + Imports Exports Change in stock levelBreakdown of DemandNature of ProductConsumer GroupsGeographical Division

CHARACTERISATION OF THE MARKETPriceMethods of Distribution and Sales PromotionConsumersSupply and CompetitionGovernment Policy

DEMAND FORECASTINGQualitative MethodsThese methods rely essentially on the judgment of experts to translate qualitative information into quantitative estimatesUsed to generate forecasts if historical data are not available (e.g., introduction of new product)The important qualitative methods are:Jury of Executive MethodDelphi Method

JURY OF EXECUTIVE OPINION METHODRationaleUpper-level management has best information on latest product developments and future product launchesApproachSmall group of upper-level managers collectively develop forecastsMain advantages Combine knowledge and expertise from various functional areasPeople who have best information on future developments generate the forecasts

JURY OF EXECUTIVE OPINION METHODMain drawbacks ExpensiveNo individual responsibility for forecast qualityRisk that few people dominate the groupTypical applicationsShort-term and medium-term demand forecasting

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

DELPHI METHODApproach Coordinator Sends Initial QuestionnaireEach expertwrites response(anonymous)CoordinatorperformsanalysisCoordinatorsends updatedquestionnaireCoordinatorsummarizesforecastYesNo

DELPHI METHODMain advantagesGenerate consensusCan forecast long-term trend without availability of historical dataMain drawbacks Slow process Experts are not accountable for their responsesLittle evidence that reliable long-term forecasts can be generated with Delphi or other methods

DELPHI METHODTypical applicationLong-term forecastingTechnology forecasting

TIME SERIES PROJECTION METHODSThese methods generate forecasts on the basis of an analysis of the historical time series.The important time series projection methods are:Trend Projection MethodExponential Smoothing MethodMoving Average Method

CASUAL METHODSCasual methods seek to develop forecasts on the basis of cause-effects relationships specified in an explicit, quantitative manner.Chain Ratio MethodConsumption Level MethodEnd Use MethodLeading Indicator MethodEconometric Method

CHAIN RATIO METHODMarket Potential for heated coats in the U.S.:Population (U) = 280,000,000Proportion 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 coatsAverage price per coat (P) = $ 200

CHAIN RATIO METHODMarket 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

CONSUMPTION LEVEL METHODThis 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

CONSUMPTION LEVEL METHODIncome 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

CONSUMPTION LEVEL METHODPrice 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

END USE METHODThis method forecasts the demand based on the consumption coefficient of the various uses of the product.

Projected Demand for IndchemConsumption CoefficientProjected Output in Year XProjected Demand for Indchem in Year XAlphaBetaKappaGamma2.01.20.80.510,00015,00020,00030,000Total20,00018,00016,00015,00069,000

LEADING INDICATOR METHODThis 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.

ECONOMETRIC METHODAn advanced forecasting tool, it is a mathematical expression of economic relationships derived from economic theory. Single Equation ModelDt = a0 + a1 Pt + a2 NtWhereDt = demand for a certain product in year t.Pt = price of the product in year t.Nt = income in year t.

ECONOMETRIC METHODSimultaneous equation methodGNPt = Gt + It + Ct It = a0 + a1 GNPt Ct = b0 + b1 GNPtWhereGNPt = gross national product for year t. Gt = Governmental purchase for year t. It = Gross investment for year t. Ct= Consumption for year t.

UNCERTANITIES IN DEMAND FORECASTINGData about past and present markets.Lack of standardizationFew observationsInfluence of abnormal factorsMethods of forecastingInability to handle unquantifiable factorsUnrealistic assumptionsExcessive data requirement

UNCERTANITIES IN DEMAND FORECASTINGEnvironmental changesTechnological changesShift in government policyDevelopments on the international sceneDiscovery of new source of raw materialVagaries of monsoon

COPING WITH UNCERTAINTIESConduct analysis with data based on uniform and standard definitions.Ignore the abnormal or out-of-ordinary observations.Critically evaluate the assumptionsAdjust the projections.Monitor the environment.Consider likely alternative scenarios.Conduct sensitivity analysis