Methods of Traditional Forecasting

As seen in Part 1, Forecasting is an important part of the demand planning strategy. Human beings have been cognizant of the importance of forecasting since time immemorial. We have forecasted weather patterns to understand mother nature to become an agrarian community from hunters and gatherers. While the awareness about the importance of forecasting is intuitive yet many large organizations still use archaic methods of forecasting to get the job done. This part of the series looks at the various traditional forms of forecasting methods in prevalence.

Quantitative Traditional Forecasting Techniques

Survey Method

Suitable for short term forecasts in this method surveys are conducted with customers, POS owners and experts of the markets. This method can be a good gauge of customer intention and the fashion trend and even be used for price determination. Being a method that reaches out to the primary sources for the information it is really simple to implement. If the result from this method is implemented in totality the results can be unbiased. However, it is not easy to run a survey across a representative sample and also oftentimes customers are unwilling to participate.

Collective Opinion Method

In this method the point of sales owners estimate future demand of the products in their regions and categories. While this may be the simplest method the accuracy can vary significantly. This may be the only option available in case there is no statistical model that can be applied due to the lack of historical data – for example, new product/category introduction.

Market experiment method

The basis of this method is running surveys and experiments in the market for similar samples including product features, customers and demography. Changes in demand with respect to changes in prices and product features are recorded to determine the impact on demand. While the above three most common traditional methods are used by almost all organizations BluePi recommends the use of statistical methods for greater accuracy and confidence in forecasts and planning. Please see our next blog in this series for the major Statistical methods in play.

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