Data on demands of the market may be needed for a number of purposes to assist an organization in its long-term, medium and short-term decisions. Forecasting.

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Presentation transcript:

Data on demands of the market may be needed for a number of purposes to assist an organization in its long-term, medium and short-term decisions. Forecasting is essential for a number of planning decisions and often provides a valuable input on which future operations of the business enterprise depend.

Some of the areas where forecasts of future product demand would be useful are indicated below (1) Specification of production targets as functions of time. (2) Planning equipment and manpower usage, as well as additional procurement. (3) Budget allocation depending on the level of production and sales.

4) Determination of the best inventory policy. 5) Decisions on expansion and major changes in production processes and methods 6) Future trends of product development, diversification, scrapping, etc. 7) Design of suitable pricing policy. 8) Planning the methods of distribution and sales promotion.

It is thus clear that the forecast of demand of a product serves as a vital input for a number of important decisions and it is therefore, necessary to adopt a systematic and rational methodology for generating reliable forecasts.

Forecasting generally refers to the scientific methodology that often uses past data along with some well- defined assumptions or ‘model’ to come up with a “forecast” of future demand. In that sense, forecasting is objective.

A prediction is a subjective estimate made by an individual by using his intuitive ‘hunch’ which may in fact come out true but the fact that it is subjective (A’s prediction may be different from B’s and C’s) and non-realizable as a well- documented computer programme (which would be used by anyone) deprives it of much value.

This is not to discount the role of intuition or subjectivity in practical decision making.

TIME SERIES Is a set of observations on a variable of interest that has been collected in time order.

TIME SERIES Is a set of observations on a variable of interest that has been collected in time order.

In order to identify patterns in time series data, it is often convenient to think of such data as consisting of several components. TREND, CYCLE, SEASONAL VARIATIONS AND IRREGULAR FLUCTUATIONS.

TREND refers to the upward or downward movement that characterizes a time series over time. Thus trend reflects the long run growth or decline in the time series. Trend movements can represent a variety of factors. For example, long run movements in the sales of a particular industry might be determined by changes in consumer tastes, increase in total population, and increases in per capita income.

CYCLE refers to recurring up-and-down movements around trend levels. These fluctuations can last from 2 to 10 years or even longer measured from peak to peak or trough to trough. One of the most common cyclical series data is the business cycle which is represented by fluctuation in the time series caused by recurrent periods of prosperity and recession.

SEASONAL VARIATIONS (1) are periodic patterns in a time series that complete themselves within a calendar year or less than are repeated on a regular basis. Often seasonal variations occur yearly. For example, soft drink sales and hotel room occupancies are annually higher in the summer months, while department store sales are higher in during Christmas holidays.

SEASONAL VARIATIONS (2) Seasonal variations can also last less than one year. For example daily restaurant patronage might exhibit within week seasonal variations, with daily patronage higher on Fridays and Saturdays.

IRREGULAR FLUCTUATIONS are erratic time series movements that follow no recognizable or regular pattern. Such movements represent what is “left over” in a time series after trend, cycle, and seasonal variations have been accounted for.

FORECASTING TIME HORIZONS The primary purpose of forecasting is to provide valuable information for planning the design and operation of the enterprise. Planning decisions may be classified as long term, medium term and short term.

LONG TERM DECISIONS Long term decisions include decisions like plant expansion or new product introduction which may require new technologies or a complete transformation in social or moral fabric of society.

MEDIUM TERM DECISIONS Medium term decisions involve such decisions as planning the production levels in a manufacturing plant over the next year, determination of manpower requirements or inventory policy for the firm.

SHORT TERM DECISIONS Short term decisions include daily production planning and scheduling decisions. For both medium and short term forecasting, many methods and techniques exist.