What are demand forecasting methods?

In order to forecast demand, we must have historical data on the market and past revenue, but the time span, the scope of the market, and other details can change the results. There are six common ways to calculate a demand forecast, but even these methods can be tweaked to meet the needs of a company.

  • Passive – Passive demand forecasting is common in small businesses, because it is the simplest way to estimate future demand. In this method, only past demand performance is used to make predictions about future demand. This means it can be potentially inaccurate, but easier to calculate a result (ie. for the last 19 weeks, carrots sold at 13 cents a piece, therefore we can expect for them to sell at 13 cents this next week).

  • Active – Active demand forecasting is typically used by companies that are growing and expanding. The active method of predicting demand takes into account aggressive growth plans such as marketing or product development and also the general competitive environment of the industry.

  • Short-term – Short-term demand forecasting only predicts demand for three to 12 months in the future. This can give businesses an idea of what to expect within the next few quarters up to a year, but not longer. Seasonal demand is often calculated this way.

  • Long-term – Long-term demand forecasting is used to predict demand for more than a year in the future, often up to three or four years out. Marketing and product strategies are often based on this type of demand forecast.

  • External macro level – External demand forecasting is based upon the macroeconomics of the market and external environmental factors. These types of predictions drive internal business decisions, such as product portfolio evaluation and expansion and the development of new customer segments.

  • Internal business-level – Internal business-level demand forecasting takes into account only internal metrics such as revenue, costs of goods sold, profit margins, cash flow, etc. This does not take external data into account, so it makes forecasts based only on current business processes.