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Demand Demand Forecasting Forecasting
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Page 1: Demand forecasting

DemandDemand Forecasting Forecasting

Page 2: Demand forecasting

Meaning of Demand Forecasting

“An estimate of sales in dollars or physical units for a specified future period under a proposed marketing plan.”

American Marketing Association Demand forecasting is the scientific and

analytical estimation of demand for a product (service) for a particular period of time.

It is the process of determining how much of what products is needed when and where.

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Categorization of Demand Forecasting

By Level of ForecastingFirm (Micro) level: forecasting of demand for its

product by an individual firm. decisions related to production and marketing.

Industry level: for a product in an industry as a whole. insight in growth pattern of the industry in identifying the life cycle stage of the product relative contribution of the industry in national

income.

Page 4: Demand forecasting

Categorization of Demand Forecasting

Economy (Macro) level: forecasting of aggregate demand (or output) in the economy as a whole.

helps in various policy formulations at government level.

Page 5: Demand forecasting

Categorization of Demand Forecasting

By nature of goodsCapital Goods: Derived demand

demand for capital goods depends upon demand of consumer goods which they can produce.

Consumer Goods: Direct demanddurable consumer goods: new demand

or replacement demandNon durable consumer goods: FMCG

.

Page 6: Demand forecasting

Categorization of Demand Forecasting

By Time PeriodShort Term (0 to 3 months): for inventory

management and scheduling.Medium Term (3 months to 2 years): for

production planning, purchasing, and distribution.

Long Term (2 years and more) for capacity planning, long term capital requirement, and investment decisions

Page 7: Demand forecasting

Choice of a forecasting technique

depends on:Imminent objectives of forecast,

whether it is for a new product, or to gauge impact of a new advertisement, etc.

Cost involved, cost of forecasting should not be more than its benefits, here opportunity cost of resources will also be important.

Time perspective, whether the forecast is meant for the short run or the long run

Page 8: Demand forecasting

Choice of a forecasting technique

Complexity of the technique, vis-à-vis availability of expertise; this would determine whether the firm would look for experts “in house” or outsource it

Nature and quality of available data, i.e. does the time series show a clear trend or is it highly unstable.

Page 9: Demand forecasting

Techniques of Demand ForecastingSubjective (Qualitative) methods: rely

on human judgment and opinion.Buyers’ OpinionSales Force CompositeMarket SimulationTest MarketingExperts’ Opinion

Group DiscussionDelphi Method

Page 10: Demand forecasting

Techniques of Demand ForecastingQuantitative methods: use

mathematical or simulation models based on historical demand or relationships between variables.

Trend Projection

Smoothing Techniques

Barometric techniques

Econometric techniques

Page 11: Demand forecasting

Subjective Methods of Demand Forecasting

Consumers’ Opinion Survey Buyers are asked about future buying

intentions of products, brand preferences and quantities of purchase, response to an increase in the price, or an implied comparison with competitor’s products. Census Method: Involves contacting

each and every buyerSample Method: Involves only

representative sample of buyers

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Subjective Methods of Demand Forecasting

MeritsSimple to administer and comprehend.Suitable when no past data available.Suitable for short term decisions regarding

product and promotion.DemeritsExpensive both in terms of resources and time.Buyers may give incorrect responses. Investigators’ bias regarding choice of sample

and questions cannot be fully eliminated.

Page 13: Demand forecasting

Subjective Methods of Demand Forecasting

Sales Force Composite / Openion Survey

Salespersons are in direct contact with the customers. Salespersons are asked about estimated sales targets in their respective sales territories in a given period of time.

Contd…

Page 14: Demand forecasting

Subjective Methods of Demand Forecasting

MeritsCost effective as no additional cost is incurred

on collection of data.Estimated figures are more reliable, as they are

based on the notions of salespersons in direct contact with their customers.

DemeritsResults may be conditioned by the bias of optimism

(or pessimism) of salespersons.Salespersons may be unaware of the economic

environment of the business and may make wrong estimates.

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Subjective Methods of Demand Forecasting

Experts’ Opinion Methodi) Group Discussion: (developed by Osborn in 1953) Decisions may be taken with the help of brainstorming sessions or by structured discussions. ii) Delphi Technique: developed by the Rand Corporation at the beginning of the Cold War, to forecast impact of technology on warfare.

Way of getting repeated opinion of experts without their face to face interaction.

Consolidated opinions of experts is sent for revised views till conclusions converge on a point.

Contd…

Page 16: Demand forecasting

Subjective Methods of Demand Forecasting

MeritsDecisions are enriched with the experience of

competent experts.Firm need not spend time, resources in

collection of data by survey.Very useful when product is absolutely new to

all the markets.DemeritsExperts’ may involve some amount of bias.With external experts, risk of loss of

confidential information to rival firms.

Page 17: Demand forecasting

Subjective Methods of Demand Forecasting

Market Simulation

Firms create “artificial market”, consumers are instructed to shop with some money. “Laboratory experiment” ascertains consumers’ reactions to changes in price, packaging, and even location of the product in the shop. Grabor-Granger test:

Half of members are shown new product to see whether they would actually buy it at various prices on a random price list and then are shown the existing product. Other half is shown the existing product first and then the new product to ascertain if a product would be bought at different prices.

Contd…..

Page 18: Demand forecasting

Subjective Methods of Demand Forecasting

MeritsMarket experiments provide information on

consumer behaviour regarding a change in any of the determinants of demand.

Experiments are very useful in case of an absolutely new product.

DemeritsPeople behave differently when they are

being observed.In Grabor-Granger tests consumers may not

quote the price they may pay.

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Subjective Methods of Demand Forecasting

Test Marketing Involves real markets in which consumers

actually buy a product without the consciousness of being observed.

product is actually sold in certain segments of the market, regarded as the “test market”.

Choice and number of test market(s) and duration of test are very crucial to the success of the results.

Contd….

Page 20: Demand forecasting

Subjective Methods of Demand Forecasting

MeritsMost reliable among qualitative methods.Very suitable for new products. Considered less risky than launching the

product across a wide region.Demerits Very costly as it requires actual production of the

product, and in event of failure of the product the entire cost of test is sunk.

Time consuming to observe the actual buying pattern of consumers..

Page 21: Demand forecasting

Quantitative Methods of Demand Forecasting

Trend ProjectionStatistical tool to predict future values of a variable on the basis of time series data.

Time series data are composed of:Secular trend (T): change occurring consistently over a

long time and is relatively smooth in its path. Seasonal trend (S): seasonal variations of the data

within a year Cyclical trend (C): cyclical movement in the demand for

a product that may have a tendency to recur in a few years

Random events (R): have no trend of occurrence hence they create random variation in the series.

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Quantitative Methods: Methods of Trend Projection

Graphical methodPast values of the variable on vertical axis

and time on horizontal axis and line is plotted.

Movement of the series is assessed and future values of the variable are forecasted

simple but provides a general indication and fails to predict future value of demand

Contd…

Page 23: Demand forecasting

Quantitative Methods: Methods of Trend Projection

Least squares method based on the minimization of squared deviations

between the best fitting line and the original observations given.

Estimates coefficients of a linear function. Y=a+bX where a =intercept and b =slope

The normal equations:ΣY=na + bΣXΣXY= aΣX+ bΣX2

Once the coefficients of the trend equation are estimated, we can easily project the trend for future periods.

Contd…

Page 24: Demand forecasting

Quantitative Methods : Barometric Techniques

Barometric Technique alerts businesses to changes in the overall economic conditions.

Helps in predicting future trends on the basis of index of relevant economic indicators especially when the past data do not show a clear tendency of movement in a particular direction.

Contd….

Page 25: Demand forecasting

Quantitative Methods

Simple (or Bivariate) Regression Analysis: deals with a single independent

variable that determines the value of a dependent variable.

Demand Function: D = a+bP, where b is negative.

Contd…..

Page 26: Demand forecasting

Quantitative Methods

Problems Associated with Regression Analysis

Multicollinearity: when two or more explanatory variables in the regression model are found to be highly correlated the estimated coefficients may not be accurately determined.

Heteroscedasticity: Classical regression models assume that the variance of error terms is constant for all values of the independent variables

Contd…

Page 27: Demand forecasting

Specification errors: Omission of one or more of the independent variables, or when the functional form itself is wrongly constructed or estimate a demand function in linear form, though the function should have been nonlinear.

Identification problem: where the equations have common variables, like a demand supply model.

Problems Associated with Regression Analysis

Page 28: Demand forecasting

Limitations of Demand Forecasting

Change in Fashion: Is an inevitable consequence of advancement of civilization. Results of demand forecasting have short lasting impacts especially in a dynamic business environment.

Consumers’ Psychology: Results of forecasting depend largely on consumers’ psychology, understanding which itself is difficult.

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Lack of Past Data: Requires past sales data, which may not be correctly available. Typical problem in case for a new product. Limitations of Demand ForecastingLimitations of Demand Forecasting

Limitations of Demand Forecasting

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Uneconomical: Requires collection of data in huge volumes and their analysis, which may be too expensive for small firms to afford. Estimation process may take a lot of time, which may not be affordable.

Lack of Experienced Experts: Accurate forecasting necessitates experienced experts, who may not be easily available. Forecasting by less experienced individuals may lead to erroneous estimates.

Limitations of Demand Forecasting