The activity of estimating the quantity of a product or service that consumers will purchase. Demand forecasting involves techniques including both informal methods, such as educated guesses, and quantitative methods, such as the use of historical sales data or current data from test markets. Demand forecasting may be used in making pricing decisions, in assessing future capacity requirements, or in making decisions on whether to enter a new market.

— according to Cundiff and Still, "Demand Forecasting is an estimate of Demand during a specified period. Which estimate is tied to a proposed marketing plan and which assumes a particular set of uncontrollable and competitive forces."

— In the words of Prof. Philip Kotler. The company (sales) forecast is the expected level of company sales based on a chosen marketing plan and assumed marketing environment"

— According to Evan J. Douglas, "Demand forecasting may be defined as the process of finding values for demand in future time periods."

Demand Forecasting

The cost should be controlled by producing correct level of goods in the firm and also according to the demand for those goods in the market. For the estimation of demand, demand forecasting is to be done by the firm.

  • Forecasting = estimation of future situations.

  • Forecasting reduces or minimizes the uncertainty.

  • By forecasting effective decisions can be taken for tomorrow.

  • Demand forecasting is based on the determinants of the demand.

  • Demand for goods increases and gives sales.

  • Sales are the primary source of the income for a firm.


1. Identification of business objectives:

In the first stage we should know what is the aim of forecasting? What we get or know from the forecasting? Estimation of factors like quantity and composition of demand for goods, price to be quoted, sales planning and inventory control etc., are done in the first stage.

2. Determining the nature of goods under consideration:

Different category of goods has their own distinctive demand. Example capital goods, consumer durables and non-durables goods in which category our goods fall we should estimate.

3. Selecting a proper method of forecasting:

There are different methods for demand forecasting. Which is best suited method that we should select for doing demand forecasting?

4. Interpretation of results:

The forecasting which is done by the managerial economist should be interpreted in detailed manner. That means it should be easy to understand by the top management.

Demand Forecasting Techniques

To invest money and others factors in business; we require a reasonable accurate forecast of demand. Starting with qualitative methods like survey of collective opinions, buyers' intention, Delphi approach and its variant, a number of quantitative methods are used for computing demand forecasts as detailed below:

Opinion polling method

a) Collective opinion Survey:

Sales personnel are closest to the customers and have an intimate feel of the market. Thus they are most suited to assess consumer’s reaction to company's products. Herein each salesperson makes an estimate of the expected sales in their respective area, territory, state and/or region, These estimates are collated, reviewed and revised to take into account changes in design/features of products, changes in selling prices, Projected advertising and sales promotion campaigns and anticipated changes in Competitors: marketing policies covering product, people, price, promotion and place.

Opinions of all managers involved at various levels of sales organization are also included in the survey. Thus "collective opinion survey forms the basic of market Analysis and demand forecasting.

Although this method is simple, direct, first hand and most acceptable, it suffers from following weaknesses.

  1. Estimates are based n personal judgment which may not be free from bias

  2. Adding together demand estimates of individual salespersons to obtain total demand of the country maybe risky as each person has knowledge about a small portion of market only

  3. Salesperson may not prepare the demand estimates with the requisite seriousness and care

  4. Owing to limited experience, usually in their employment, salesperson may not have the requisite knowledge and experience

This method may be useful for long-term forecasts. It is also used for new products or new variants of existing products.

b) Survey of Customers Intention

Another method of demand forecasting is to carry out a survey of what consumers prefer and intend to buy. If the product is sold to a few large industrial buyers, survey would involve interviewing them.

If it is a consumer durable product, a sample survey is carried out about what they are planning or intending to buy. It is not east to query all consumers through direct contact or through printed questionnaire by mail. These surveys serve useful purpose in establishing relationships between

  • demand and price

  • demand and income of consumers

  • demand and expenditure on advertisement etc.

This method is preferred when bulk sales are made by institutions and industrial buyers and only a few of them have to be contacted.

Disadvantages in this forecasting technique is that the customers may not know total requirements; in some cases they are not certain about quantity to be purchased. Besides there may be a tendency to inflate their requirements during shortages. This survey method is not useful for households - interviewing them is not only difficult out but also expensive. They are not able to give precise idea about their intentions particularly when alternative products are available in the market.

c) Delphi Method

The Delphi technique was developed at RAND Corporation in the 1950s. Delphi method is a group (members) process and aims at achieving an collective opinion of the members on the subject. Herein experts in the field of marketing research and demand forecasting are engaged in

  • analyzing economic conditions

  • carrying out sample surveys of market

  • conducting opinion polls

Based on the above, demand forecast is worked out in following steps:

  1. Co-ordinator sends out a set of questions in writing to all the experts co-opted on the panel who are requested to write back a brief prediction.

  2. Written predictions of experts are collated, edited and summarized together by the Co-ordinator.

  3. Based on the summary, Co-ordinator designs a new set of questions and gives them to the same experts who answer back again in writing.

  4. Co-ordinator repeats the process of collating, editing and summarizing the responses.

  5. Steps 3 and 4 are repeated by the Co-ordinator to experts with diverse backgrounds until consensus is reached.

If there is divergence of opinions and hence conclusions, Co-ordinator has to sort it out through mutual discussions. Co-ordinator has to have the necessary experience and background as he plays a key role in designing structured 'questionnaires and synthesizing the data. Direct interaction among experts is avoided nor their identify is disclosed. Procedures also neither avoid inter-personnel conflicts nor are strong-willed experts able to dominate the group. This method is also used for technology forecasting

d) Nominal Group Technique

This technique was originally developed by Delbecq and VandeVen. This is a further modification of Delphi method of forecasting. A panel of 3-4 groups of up to 10 experts are formed and allowed to interact, discuss 'and rank all the suggestions in descending (highest to lowest) order as per the following procedure:

Experts sit around a table in full view of one another and are asked to speak to each other. An administrator hand over copies of questionnaire needing a forecast and each expert is expected to write down a list of ideas about the questions. After everyone has written down their ideas, administrator asks each expert to share one idea, out of own list. The idea shared is written on the `flip chart' which everyone can see. Experts give ideas in rotation until all of them are written on the `flip chart'. No discussion takes place in this phase and usually 15 to 25 ideas emerge from this format.

In the next phase, experts discuss ideas presented by them. Administrator ensures that all ideas have been adequately discussed. During discussions similar ideas are combined. This reduces the number of ideas. After completing group discussions, experts are asked to give in writing ranks to ideas according to their perception of priority

Statistical methods

  • Trend projection method

This technique assumes that whatever past years demand pattern will be continued in the future also. Basing on the historical data that means previous year’s data is used to predict the demand for the future. In this trend projection method, previous year’s data is presented on the graph and future demand is estimated.

  • Regression Analysis

Past data is used to establish a functional relationship between two variables. For Example, demand for consumer goods has a relationship with income of Individuals and family; demand for tractors is linked to the agriculture income and demand for cement, bricks etc. are dependent upon value of construction contracts at any time. Forecasters collect data and build relationship through co-relation and regression analysis of variables.

Deficit monsoon hits tractor sales as farm operations see a decline

Our annual sale is pegged around 40,000 units. But, we are unlikely to touch sales in excess of 20,000 units, says official of automotive major Mahindra & Mahindra

Deficit rain during monsoon this year has brought down paddy acreage during the kharif season. But the shortfall in rains has hit one segment of the industry very hard.

The sale of tractors, used extensively in the agriculture operations, has shown a steep dip during the current year. Automotive major Mahindra & Mahindra has witnessed a significant de-growth in the overall tractor sales in the State that, in turn, had its echo on the company’s overall performance in the segment.

Mahindra & Mahindra president automotive and farm equipment sectors Pawan Goenka said the company enjoys over 50 per cent market share in the tractor sales in Andhra Pradesh where the total annual sale is pegged around 40,000 units. “But, we are unlikely to touch sales in excess of 20,000 units as was witnessed in the previous fiscal,” he told The Hindu .

The acreage is down by about 3 lakh hectares, compared to 26 lakh hectares normal, in the State and farmers have switched over to other crops like cotton, pulses and maize on account of shortfall in the kharif plantation during the early phase of monsoon. The State, according to figures released by the Centre, faced the worst water crunch, with a 52 per cent deficiency in the reservoir levels.

Tractors, according to Mahindra and Mahindra, are extensively used in the canal irrigation where they serve as multi-utility vehicles. Thanks to the steep drop in release of water to canal irrigated areas, the usage had come down significantly.

Mahindra and Mahindra, accordingly, forecast the tractor growth rate during the year to half to around 6 per cent from the earlier projected 12 per cent. “Tractor growth rate is expected to be around 6 per cent during the year with first quarter showing some de-growth and second quarter expected to be even,” he said. The company, however, sounded optimistic in claiming that sales are expected to pick up by November when the Rabi operations start. “The second half is expected to ensure growth of around 6 per cent,” Mr. Goenka said. The company has registered sale of 13,000 units in the period between April and August, but was unlikely to touch the last year’s figure in excess of 20,000 units.

Agriculture Department secretary V. Nagi Reddy admitted that the monsoon had not been upto the expected levels and this was sure to bring down the crop production. Though the State had witnessed normal rainfall, the deficit in water availability could be attributed to the shortage in the catchment areas in Karnataka and Maharashtra that reduced inflows into reservoirs. According to him, there was over 10 per cent drop in the total cultivated area because of the deficit rains. “Fall in production is, however, unlikely to be proportionate with the dip in the total acreage as the shortfall is likely to be made up by higher production of other crops,” Mr. Nagi Reddy said.

  • Econometric Models

Econometric models are more complex and comprehensive as this model uses mathematical and statistical tools to forecast demand. This model takes various factors which affect the demand. For example, demand for passenger transport is not only dependent upon the population of the city, geographical area, industrial units, their location etc.

It is not easy to locate one single economic indicator for determining the demand forecast of a product. Invariably, a multi-factor situation applies Econometric Models, although complex, are being increasingly used for market analysis and demand forecasts.

  • Simple Average Method

Among the quantitative techniques for demand analysis, simple Average Method is the first one that comes to one's mind. Herein, we take simple average of all past periods - simple monthly average of all consumption figures collected every month for the last twelve months or simple quarterly average of consumption figures collected for several quarters in the immediate past. Thus,

Sum of Demands of all periods =

demand forecasting.pptx