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September 2, 2021

Types, Examples, and Methods of Demand Forecasting

It is impossible to predict the future that too with certainty. But, you can use different techniques, and one of them is demand forecasting. Using a forecasting model, it becomes easy to make sound business decisions. 

Demand Forecasting: Types, Methods and Examples

Types of Demand Forecasting

There are different types of demand forecasting. However, it is necessary to understand that the forecast differs depending on the various forecasting model. One of the best practices includes multiple demand forecasts. It helps in providing a clear picture of future sales. 

Besides, you can use more than one forecasting model for highlighting the difference in predictions. Such differences point to a need for better research and data inputs. Let us check out the different types of demand forecasting.

Passive demand forecasting

It is the simplest type of demand forecasting. For this model, you have to use past sales data for predicting the future. Besides, it is vital to use the data from the same season for projecting sales in the future.

Therefore, you are comparing apples to apples. Besides, it is true if your business faces seasonal fluctuations. A passive forecasting model works perfectly in case you want to build solid data. Also, it is a perfect model for companies that target stability instead of growth.

Moreover, passive demand forecasting is much easier than other different types. It is because passive demand forecasting does not require statistical methods as well as study economic trends. 

Active demand forecasting

In case your business is going through the growth phase or is a startup. Then active demand forecasting is a great choice. This model considers the market research, expansion plans, and marketing campaigns.


Moreover, the active projections often factor in externals. Some of the considerations include economic outlook, growth projections for the market sector, etc. Startups having low historical data will need to keep their assumptions depending on external data.


Short-term projections

The short-term demand forecasting considers the next three to twelve months. It is useful when it comes to managing the just-in-time supply chain. Besides, the short-term demand helps in adjusting to the projections depending on the real-time sales data.

For example, if you run a product lineup that faces frequent changes, you have to know short-term demand. When it comes to businesses, the short-term forecast is a piece of a giant puzzle. 


Demand Forecasting Methods

Different methods are there for creating demand forecasts. Listed below are some of the demand forecasting methods to know about.

Trend projection

It uses the past sales data to find out the future sales. Trend projection is the simplest as well as the straightforward demand forecasting method. Besides, it is necessary to adjust to the future estimates for the historical anomalies. For example, you saw a sudden increase in the demand last year. But, it happened after your product features on any popular TV show.

Market research

This method is based on the various data from the customer surveys. Market research takes time as well as effort for sending out surveys as well as tabulated data. Moreover, this method provides valuable insight that you cannot get from internal sales data. 

Examples of Demand Forecasting

Almost every business gets a lot of benefits from demand forecasting. Here are a few examples of demand forecasting and the benefits eCommerce companies get from it.

Passive projection

Suppose a couple sells costumes, decorations, and party favors for kids. They have been doing this business for years. The average last three years of sale is used for projecting the trends of the upcoming year. From the historical data, they understood that May and October are the best year and December and August is the worst month,

Therefore, you must know a few things about demand forecasting. If you want to use it for business, it is vital to know about demand forecasting.

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