Demand Forecasting Methods

There are as many demand forecasting methods as there are companies doing demand forecasting. We think that is great, a company that is working to develop and implement an effective demand planning work process should take on an appropriate demand forecasting methodology and "tweak" it to make it effective for them. Different companies have different factors that influence demand - seasonality, interest rates, demographics, etc. There are however, four basic methods of forecasting customer demand:

- Qualitative forecasts, which are subjective and typically rely on human judgement and opinions to make a forecast. This method is appropriate when there is little or no historical data available, or when experts have market intelligence that is critical to making a forecast.

- Time series forecasting methods use historical demand to make a forecast. These are typically based on the assumption that past demand history is a good indicator of future demand. Time series forecasts are appropriate when the economic environment is stable, and the pattern of basic demand does not vary significantly from one year to the next. This is the simplest method to implement and can serve as a good starting point for a demand forecast.

- Casual forecasting methods involve assuming demand patterns correlate highly with certain factors in the economic environment, the state of the economy, interest rates, etc. For example, if product pricing is strongly correlated with demand, a company can use casual methods to determine the impact of price promotions on demand.

- Simulation forecasting methods attempt to imitate the customer choices that give rise to demand to arrive at an accurate demand forecast. Using simulation methods, a company can combine time series and casual methods, as well as specific customer input from sales and marketing.

A company may find it difficult to decide which method is most appropriate for forecasting demand. In fact, using multiple forecasting methods, and then using the combination of their forecasts as the actual forecast is usually the best method. That is why we advocate customizing a demand planning process to fit every unique client.

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