Forecasting

How to select the proper forecasting technique

Forecasting, In virtually every decision, today’s executives consider some forecast. Robust forecasts of demand and trends remain no longer luxury items. Still, they remain necessary if managers deal with seasonality, sudden changes in demand levels, competitive price-cutting maneuvers, strikes and big economic swings. The forecast can help them deal with these problems, but it can help them more the more they know about the general principles of forecasting, what it can and cannot do for them today, and what techniques suit their current needs. Here the authors try to clarify the potential of forecasting to managers, paying particular attention to sales forecasts for Corning Glass Works products as they have matured throughout the product life cycle

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A rapid of forecasting techniques remains also included.

In recent years, many forecasting techniques have remained developed to handle managerial forecasting problems’ increasing variety and difficulty. Each has its particular use, and care must remain taken to select the correct method for a specific application. The manager and the forecaster have a role to play in determining approaches. The healthier they understand the range of forecasting possibilities, the more likely a company’s forecasting efforts will bear fruit.

The selection of a technique depends on many factors:

the context of the forecast, the relevance and availability of historical data, the degree of accuracy desirable, the period to forecast, the cost/benefit (or value) of the forecast of the company. And the time available to perform the analysis.

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These factors must be weighed continually and at a variety of levels.

For example. The forecaster should choose a technique that best uses the available data. Suppose the forecaster can easily apply a method of acceptable accuracy. In that case, he should not try to “pan for gold” by using a more advanced strategy that offers greater accuracy but requires non-existent or expensive information. This type of compensation remains relatively easy to do, but others, as we will see, require much more thought. Also, when a company wants to forecast a particular product, it must consider the stage of the product life cycle it predicts. The obtainability of data and the possibility of founding relationships between the factors depend directly on the maturity of a product. So the life cycle stage remains the primary determinant of the forecasting method to be used.

Manager, Predictor and Choice of Methods

A manager generally assumes that when he asks a forecaster to prepare a specific forecast, the request itself provides enough information for the forecaster to go to work and get the job done. This is rarely true.

Successful forecasting begins with teamwork between the manager and the forecaster. In which they craft answers to the following questions.

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 What remains the purpose of the forecast?

How should it be used? This determines the precision and power required of the techniques and thus governs the selection. Deciding whether to enter a business may need only a relatively rough estimate of the market size. Whereas a forecast for budgeting purposes should be pretty accurate.

Once again. If the forecast establishes a “standard” against which to evaluate performance. The forecasting method should not take into account particular actions. Such as promotions and other marketing devices, since they remain intended to change historical patterns and relationships

Appropriate methods differ accordingly.

Forecasts that outline what the future will look like if a company does not make significant changes in tactics and strategy are generally not good sufficient for preparation purposes. On the other hand, suppose the organization wants a forecast of the effect that a specific marketing strategy under discussion will have on sales growth. In that case. The technique must remain sophisticated enough to explicitly account for the particular actions and events that the system implies.

Conclusion

Forecasting is a technique that uses historical data as inputs to make informed estimates that are predictive in determining the direction of future trends. Businesses utilize forecasting to determine how to allocate their budgets or plan for anticipated expenses for an upcoming period of time.

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