Summary Chapter Five Demand Forecasting Introduction

Summary

Chapter Five Demand Forecasting

Introduction ;

A forecast is an estimation or prediction about situations which are most likely to occur in near or distant future.

The firm must plan for the future. Planning for the future involves forecasting. The firm has to forecast the future level of demand for its products under different possible circumstances; such as prices, competition, promotional activities and general economic activities.

Forecasting does play a key role in managerial decisions and hence forecasting is emphasized in the study of managerial economics. The objective of business forecasting is to minimize risk and the margin of uncertainty.

Techniques :

Techniques of demand forecasting are categorized into qualitative and quantitative techniques.

The qualitative approach aims at obtaining information about the intentions of buyers through collecting experts’ opinion or by conducting interviews with the consumers.

The quantitative approach uses past experience as the guide and projects past statistical relationships to obtain the expected level of future demand.

For existing products, we can use any of the suitable methods or a combination of them; but for new products only qualitative survey methods have to be used in absence of any past data.

Forecasting Methods

► QUALITATIVE :- Expert opinions Consumers’ survey:- Complete enumeration. Sample survey. End – Use.

► Quantitative : - Time series. Moving average. Exponential Smoothing. Index numbers. Regression analysis. Econometric Models. Input-output analysis.

♠ Expert Opinion Method.

The firm makes an effort to obtain the opinion of experts with long standing experience in the field of enquiry related to the product. If results are based on inputs from several experts, it is known as forecasting through the panel consensus. Normally the forecast reflects opinion of the group, but it could get unfavorably influenced by personality of a key or a few members.

To counter this, another approach called Delphi method is adopted. In this method, a questionnaire pertaining to forecasting problem is presented to the panel members. Responses obtained from them are analyzed and results provided to the panel members for their feedback. Revised forecasts obtained from them are compared and re-circulated until consensus is reached. The method is quite expensive but simple and does not require extensive statistical calculations. If the consulted experts are genuinely reliable, then panel consensus could perhaps be the best method of forecasting.

♠ Consumers Survey Method.

For short term projections this method is well suited. Buyers’ intentions are surveyed by directly approaching them and getting their opinions. The questionnaire used for this purpose needs to be complete as well as interesting to evoke customer interest.

Consumers’ survey may assume three forms. i] Complete enumeration survey. ii] Sample survey. iii] End-use method. i] Complete enumeration survey:-

This survey covers all consumers hence resembles Census Data Collection. Information regarding the prospective demand for the product under consideration is obtained from all past, present and possible consumers.

The method provides unbiased authentic information as all buyers are covered. But the process involves high costs to cover every buyer and the to analyze huge data obtained. ii] Sample Survey :-

As against all in the above method, only few consumers are contacted in this sample survey. Care is exercised to ensure that, this sample group of respondents represents the entire population of consumers. Information collected from this group is used to prepare the forecast. The method is cost effective and provides quick results as the number of buyers and data collected from them is manageable. iii] End-use method:-

A given product may have different use for different consumers. Milk is used by a set of consumers to prepare sweetmeats, by others to make chocolates, third to make butter, milk powder. In this method data is collected from each segment of users and then consolidated into a forecast.

The method is easy to manage, if number of end users is limited, and buyers provide their inputs well ahead of their respective production schedules.

Joel Dean, however, criticizes survey method by stating that consumers are often inconsistent and there are formidable barriers to learning the buying intentions of the household consumers.

♠ Time Series

This method is based on obtaining historical data regarding the demand for the product so as to project future occurrences on the basis of what has happened in the past.

Time series data would indicate different types of fluctuations which can be classified as Secular Trends, Cyclical Variations, Seasonal Variations and random Fluctuations. Only secular trends are projected to obtain demand forecasts. The trend projections assume that that the historical relationships involved in the Time Series will continue in future, which is always not the case. The trend projections are used for long term forecasting.

♠ Moving average.

The method of moving averages is useful when the market demand is assumed to remain fairly steady over time. It is calculated by

Demand in the previous n months Moving Average = n

♠ Exponential Smoothing.

In this technique more recent data are given more weightage. This is based on the argument that the more recent the observations, more its impact on the future.

♠ Index numbers.

The index numbers offer a device to measure changes in a group of related variables over a number of years. We select a Base Year which is given the value of 100 and then express all subsequent changes as movement of this number.

♠ Regression analysis.

This statistical method is undertaken to measure the relationship between two variables where correlation appears to exist. For example demand for annual repairs of air conditioners can be established based on the age of machines under servicing.

♠ Econometric Models.

The econometric models used in fore casting take the form of an equation or system of equation which seems best to express the most probable interrelationship between a set of economic variables according to economic theory and statistical analysis. Models can be qualitatively or quantitatively formulated. Like in earlier methods the assumption is that the relationship established in the past will continue to prevail in future.

♠ Input-output analysis.

The input-output analysis provides perhaps the most complete of all the complex inter-relationships within an economic system. The input-output analysis, for example, will show how an increase or decrease in demand for cars affects increase in demand for steel, tyres or glass.

There is no unique method for forecasting the demand for any product. The forecaster has to use any one, or combination, of the methods discussed above after due consideration of The objective; Data availability; Urgency; Available resources ; and The nature of the commodity.

Forecasting Methods used during the Product Lifecycle.

Each stage needs an appropriate method. For development and introduction stage; market trial survey, Delphi or an in-house survey of experts are recommended methods. Time Series or Regression analysis are methods best suited for Rapid Growth stage in the product lifecycle. These two methods along with Econometric models are used for Steady Growth stage where there is slowing down of demand.

Criteria for selecting a good forecasting method.

Accuracy and reliability are prime requirements followed by data availability. The method selected needs to be economical and flexible, especially when economists are faced with a number of uncontrollable variables. The period by which products hit the market is long, hence forecasts must stand the test of durability. The process requires coverage of large correspondents and collected data, simplicity of the method helps in obtaining meaningful data in a short time.

Limitations of Demand Forecasting.

Even though the opinion surveys are simple and straight forward, there is an element of subjectivity involved.

As surveys are expensive and time consuming, there is a tendency to limit the size of sample consumers. This leads to data being not representative and therefore misleading.

When Time Series method is used results are biased as cycles have different intensities and timings.

Though scientific methods are adopted, there is difference between field experiments and laboratory experiments.

Despite limitations associated with forecasting, we all agree that forecasting by an appropriate technique is essential. No businessman can afford to do without it. Good forecasting constitutes the core of business management.