While seeing into the future of your supply chain may be impossible, predicting what may happen can be estimated by looking at the past. When a company wants to know how their finances, supply chain, and marketing may perform in the future, they often examine how things went in previous years.

Historical business data can help you successfully estimate things like seasonal trends and product success. One of the processes for looking at this data in the supply chain world is called demand forecasting.

What is demand forecasting?

Demand forecasting is the practice of looking at a company’s historical data for things such as finances, marketing, and supply to understand likely future trends. Demand forecasting methods end up within one of three categories, either qualitative forecasting, time-series analysis, or casual models. Forecasting can include looking at different lengths of time, using statistical methods, or looking at external influences on your future business.

Importance of demand forecasting for ecommerce

Businesses use forecasting in many ways to help gain an advantage over the competition. From inventory and supply chain management to cash flow and spend, there are many areas where you can use demand forecasting within your planning.

The types of demand forecasting

Passive demand forecasting

Passive forecasting is the most straightforward when looking for a basic, non-nuanced prediction. In this type of forecasting, you look at historical data from your sales in the past to estimate future sales. Unfortunately, this model doesn’t take into account variables, such as retailers that will have seasonal fluctuations. Passive forecasting models often can only be accurately used for analytics with businesses that are highly steady in sales and have robust historical sales data.

Active demand forecasting

The active demand model is most commonly used for businesses that are either very new or have aggressive growth within their marketing campaigns. Because your company may not have the past sales data to have accurate demand forecasts, active forecasting often looks at other resources such as market research, economic data, and supply chain management data.