Demand Forecasting: Steps, Features, Techniques, Method

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What is Demand Forecasting?

Demand forecasting is an attempt to estimate the future level of demand on the basis of past as well as present knowledge and experience, to avoid both under production and overproduction.

It may be based on estimates of demand potential of the entire industry. The demand forecasting serves as the reference point for all marketing control efforts. It is indispensable in modern business.

What is Forecasting?

Forecasting is an attempt to predict the future by examining the past. Business firms can estimate and minimise future risk and uncertainty through forecasting and forward planning. Without forecasting, forward planning will be directionless and meaningless.

Demand Forecasting Definition

Demand forecasting is an estimate of sales during a specified future period based on proposed marketing plan and a set of particular uncontrollable and competitive forces.

– Cundiff and Still

Demand forecasting may be defined as the process of finding values for demand in future time periods

Evan J. Douglas

Steps in Demand Forecasting

Demand forecasting is a scientific exercise. It has to go through a number of steps. At each step, critical considerations are required to be made.

Steps in demand forecasting are:

  1. Identification of Objective
  2. Nature of Product and Market
  3. Determinants of Demand
  4. Analysis of Factors
  5. Choice of Method
  6. Testing Accuracy
Steps in Demand Forecasting
Steps in Demand Forecasting

Identification of Objective

Economist first should be clear about the uses of forecast data and how it is related to forward planning by the firm. Depending upon the scenario, the economist has to choose the type of forecast: short-run, active or passive, conditional or non-conditional, etc.

Nature of Product and Market

Nature of the product or service is an important consideration for which we are attempting a demand forecast. Forecasting of demand must examine carefully whether the product is a consumer good or producer good, perishable or durable.

It should also consider the stage at which the product is i.e. introduction, growth, maturity and saturation, or obsolescence and decline.
Finally, the nature of competition in the market (perfect or imperfect) should not be overlooked.

Determinants of Demand

Different determinants will assume a different degree of importance in different demand functions, depending on the nature of product and nature of forecasts, In addition, it is important to consider socio-psychological determinants; especially demographic, sociological and psychological factors affecting the demand.

Analysis of Factors

In an analysis of statistical demand function, it is customary to classify the explanatory factors into

  • Trend factors
  • Cyclical factors
  • Seasonal factors
  • Random factors

An analysis of factors is especially important depending upon whether it is the aggregate demand in the economy or the industry’s demand or the company’s demand or the consumer’s demand which is being predicted.

Choice of Method

The economist has to choose a particular technique from among various techniques of demand forecasting, depending upon the nature of the product.

Testing Accuracy

There are various methods for testing statistical accuracy in a given forecast. Some of them are simple and inexpensive; others are quite complex and difficult.

This testing is needed to avoid/reduce the margin of forecasting error and thereby to improve the decision-making.

Read: Consumer Behaviour – Classification, Importance, Stages

Features of Demand Forecasting

Eight major features of demand forecasting method can be identified with forecasting methods (techniques) to identify key characteristics of a good demand forecasting method.

  1. Time Horizon
  2. Level of Detail
  3. Stability
  4. Pattern of Data
  5. Type of Model
  6. Cost
  7. Accuracy
  8. Ease of Application
Features of Demand Forecasting
Features of Demand Forecasting

Time Horizon

The length of time over which a decision is being made has a bearing on the appropriate technique to use. The probability of forecasting error generally decreases with an increase in the length of the time horizon.

Level of Detail

The level of detail needed should match the focus of the decision-making unit in the forecast.

For example, production planning must make its decision at the individual product level, whereas the corporate planning department is likely to be happy with aggregate demand forecasts by product categories.


Forecasting in situations that are relatively stable over time requires less attention than those that are in constant flux. In stable situations, the existing pattern is assumed to continue in the future and past patterns can be easily extrapolated in future.

Pattern of Data

Data required to use the underlying-relationships should be available on a timely basis. Each forecasting method is based on an underlying assumption about the data.

As different forecasting methods vary in their ability to identify different patterns, it is useful to make the pattern in the data fit with the method that suits it the most.

Type of Model

Other assumptions are also made in each forecasting technique that must fit the situation under consideration. The technique used should be easily comprehended by the management to give quick meaningful results.


Several costs are associated with adopting a forecasting procedure. The variation in costs affects the selection of the forecasting method. There is a need for an economic consideration of balancing the benefits against the extra cost of providing the improved forecasting.


It is measured by the degree of deviations between past forecasts and current actual performance or present forecasts and future performance. If the likely state comes close to the actual state, it means that the forecast is dependable.

Ease of Application

Models must be chosen within the abilities of the users to understand them and within the time allowed for using them. This will enable management to properly interpret the results. The simplicity of handling the method matters in the selection of the method.

Read: 4Ps of Marketing Mix

Methods & Techniques of Demand Forecasting

The choice of choosing techniques of demand forecasting is complicated because each situation might require a different method. Management should be aware of the factors favouring one method over another in a given demand-forecasting situation.

Some of the methods of demand forecasting are discussed below:

  1. Survey Methods
    1. Consumer Survey Method
    2. Collective Opinion Method
    3. Delphi Method
    4. Market Experiment Method

  2. Statistical Methods
    1. Time Series Analysis
    2. Regression Analysis
Methods of Demand Forecasting
Methods & Techniques of Demand Forecasting

Survey Methods

Under this approach, surveys are conducted about the intentions of consumers (individuals, firms or industries), opinion of experts or of markets.

When taking sample surveys, a selected subset is surveyed and through study, inferences are drawn. These methods are usually suitable for short-term forecasts due to the nature of consumers’ intentions.

A few important survey methods:

Consumer Survey Method

A firm can ask consumers, what and how much they are planning to buy at various prices of the product for the forthcoming time period, usually a year.

Collective Opinion Method

Also called sales-force polling), salesmen or experts are required to estimate expected future demand of the product in their respective territories and sections.

Delphi Method

It is also known as Reasoned Opinion. A variant of opinion poll and survey method is a Delphi method, developed by Rand Corporation of USA in the late 1940s for predicting technical changes.

Market Experiment Method

Under this method, the main determinants of the demand of a product like price, advertising, product design, packaging, quality, etc., are identified.

These factors are then varied separately over different markets or over different time periods, holding other factors constant. The effect of the experiment on consumer behaviour is studied under actual or controlled market conditions, which is used for overall forecasting purpose.

Statistical Methods

These methods make use of historical data (time series or cross-section) as a basis for extrapolating quantitative relationships to arrive at the future demand patterns and trends. The data may also be analysed through econometric models.

These are useful for long-term forecasting, for old products and for larger levels of aggregation. They are based on scientific ways of estimation, which are logical, unbiased and proved to be useful. However, the biggest disadvantage is that it is difficult to apply these methods.

Time Series Analysis

It is an arrangement of statistical data in chronological order, i.e., in accordance with its time of occurrence. It reflects the dynamic pace of steady movements of a phenomenon, over a period of time.

Regression Analysis

Regression analysis is perhaps the most popular method of forecasting among economists. It is a mathematical analysis of the average relation between two or more variables, in terms of the original units of the data.

Read: What is Marketing Environment?

Importance of Demand Forecasting

Importance of demand forecasting are given below:

  1. Distribution of resources
  2. Helps in avoiding wastages of resources
  3. Serves as a direction to production
  4. Pricing
  5. Sales policy
  6. Decrease of business risk
  7. Inventory management
Demand Forecasting Importance
Demand Forecasting Importance

Distribution of resources

We know that inputs are processed to result into output. These inputs include resources like materials, machinery and of course human resources.

The business firm also has to make decisions regarding capital arrangement, manpower planning and so on. In short, the estimation of demand enables the firm to undertake critical business decisions.

Helps in avoiding wastages of resources

Demand forecasting is not an option but compulsion in today’s competitive environment. In order to avoid wastages, it is always beneficial to have a sense of future demand for products and services.

Serves as a direction to production

If there is a proper prediction of the demand, then it serves as a handy tool for the businesses to undertake future production activities. According to the demand in the market, the company can control their production.


The decision regarding the pricing of goods and services is perhaps one of the most critical business decisions. If there are sincere predictions about the future sales of the firm’s product then it could serve as a good aid to devise pricing strategies.

Sales policy

Production is followed by sales. The business firms can plan their sales policy effectively on the backdrop of demand forecasting.

This also implies that the distribution of goods and services can be done appropriately depending upon the predictions of the demand for the product.

Decrease of business risk

Where there is a business there is a risk. Demand forecasting though does not completely remove the business uncertainties, helps in reducing the risks and uncertainties to a certain extent.

Inventory management

Inventories is one of those aspects which is closely associated with demand. This is because inventories are kept by the producers to meet the demand in the coming times.

Factors Affecting Demand Forecasting

  1. Prevailing economic conditions
  2. Existing conditions of the industry
  3. Existing condition of an organisation
  4. Prevailing market conditions
  5. Sociological conditions
  6. Psychological conditions
  7. Competitive conditions
  8. Import-export policies
Factors Influencing Demand Forecasting 1
Factors Influencing Demand Forecasting


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