- Functional nature of demand.
- Functional nature of market demand.
3. TYPES OF FORECASTING:-
- short-run forecasting
- long-run forecasting
- FIRM LEVEL
- INDUSTRY LEVEL
- NATIONAL OR GLOBAL LEVEL.
NATURE OF GOODS:-
- Producer goods
- Consumer goods
- Consumer durable and services
DEGREE OF COMPETITION:
- Political developments.
- Changing fashions.
- Customer references.
- Changes in technology.
- Changes in price level or inflation.
FUNCTIONAL NATURE OF MARKETING DEMAND:
WHAT CONSTITUTES A SCIENTIFIC APPROACH TO FORECASTING:-
- Identify & state the objectives of forecasting clearly.
- Select appropriate method of forecasting
- Identify the variables affecting the demand for the given product or service.
- Express these variables in appropriate firms.
- Collect the relevant data represent the variables.
- Determine the most probable relationship between the dependent, independent variables, using the appropriate statistical techniques.
- Make appropriate assumptions to forecast & interpret results in terms of market share, turn over in terms of value & volume. Product groups, individual products, sizes & brands of each individual product.
- Let these be alternative forecasts to make this forecasting exercise more meaningful.
METHODS OF DEMAND FORECASTING:
- Where the product is new in the market for which no data exists previously.
- When the buyers are few and they are accessible.
- When the cost of reaching them is not significant.
- When consumers stick to their intentions.
- When they are willing to disclose what they are willing to do.
- Survey may be expensive.
- Sample size and timing of survey.
- Methods of sampling.
- In consisted buying behavior.
Sales force opinions:-
- The sales people are paid based on their results.
- Targets are set for the salesmen.
- The salary of the salesmen depends upon the targets.
- Incentives are paid to the salesmen who achieved the targets.
- Salespersons having more knowledge about the information of sources.
- Salesmen are cooperative.
- Trend line by observation.
- Least square method.
- Time series analysis.
- Moving average method.
- Exponential smoothing.
Year no. (T)
T * T
ΣT = 25
3) Time series analysis:-
4) MOVING AVERAGE METHOD:
Date and month
Daily sales (lakhs)
3-day moving average
5) EXPONENTIAL SMOOTHING:
(units in lakhs)
(units in lakhs)
Simultaneous equation method
CORRELATION AND REGRESSION METHODS:
- Results of this method would be more reliable as the expert is unbiased, has no direct commercial involvement in its primary activities.
- Independent demand forecast can be made relatively quick and cheap.
- This method constitutes a valid strategy particularly in the case of new products.
- Acceptability of the product can be judged in a limited market.
- Before its too late, the corrections can be made to product design if necessary, thus major catestrophy, in terms of failure, can be avoided.
- The customer psychology is more focused in this method and the product and services are aligned or redesigned accordingly to gain more customer acceptance.
- It reveals the quality of product to the competitors before it is launched in his wider market. The competitors may bring about a similar product or often misuse the results of the test marketing against the given company.
- It is not always easy to select a representative audience or market.
- It may also be difficult to extrapolate the feedback received from such a test market, particularly where the chosen market is not fully representative.
- Historical data for significantly long period is not available.
- Turning points in terms of policies or procedures or casual factors cannot be precisely demanded.
- Sales fluctuations are wide and significant.
- The reasons of statistical methods are more reliable at the national level rather than firm or industry level, in such cases, the management has to rely more on its judgment to access the validity of such results.