Methods/techniques of demand forecasting in economics with examples (5 Methods)

Demand forecasting uses predictive analysis of historical data to estimate future customer demand for products or services. This video will cover five key methods for demand forecasting.

This method relies on sufficient past sales data arranged chronologically to form a time series. It assumes past trends will continue into the future, allowing for predictions. For example, fashion companies like Forever 21 use this to predict upcoming seasonal styles.

The Delphi method seeks a group consensus through expert questionnaires. Experts provide opinions to an initiator, who then summarizes the information. This method is valuable for high-impact business projects and political issues, helping to identify opportunities and risks.

This method involves collecting forecasts from sales personnel, who are in direct contact with customers and distribution channels. Individual forecasts are combined to create an overall demand forecast, leveraging salespersons' experience for more accurate predictions.

For short-term demand forecasting (e.g., a year), this method directly interviews potential customers about their purchasing intentions. Companies like TATA Motors use this to understand end-consumer demand and make future forecasts.

Regression analysis is a statistical method to identify linear relationships between two or more variables. It helps quantify connections, such as between eating habits and weight. In demand forecasting, quantity demanded is the dependent variable, while income, price of goods, and related goods are independent variables.