Principle and Methods of Making Sales Forecast

Sales forecasting is an important, but difficult area of management science. The reasons why businesses forecast is because they want to have a peep of what they should expect ahead, launch new product lines, withdraw others from the market and many more. Whether it’s a macro forecasting that concerns the entire market or micro forecast which covers the units of a specific product that is sold in the market, it’s important for the forecasting to be done correctly. There are several statistical techniques which can be used for forecasting and the specific method which is used depends on the product’s demand profile. Here are prominent principles and methods of sales forecasting.

Principle of Sales Forecasting

Before making sales forecasting for business, it is important to consider the sales strategies, competition and buyer behavior as this will determine whether your sales targets can achieve. Too many forecasts are simply lists or histories of what the seller has done without taking into consideration what the buyer is doing. Also, understanding your business competitors move will greatly improve your sales forecasting.

Decomposition of Sales Component

Decomposition is one of the commonly used methods of sales forecasting. It’s a method which uses time series approach and takes into account 4 variable factors or components such as cyclical component, product component, irregular component and seasonality to do a forecast of the future product values over a certain period of time. Decomposition works out each variable separately in a bid to determine the values for each of the components, and then sum up the total output into one aggregate value. Most sales forecast professionals prefer this method of sales forecasting because it takes into account many variables before aggregating them. In essence, this means better results can be achieved.

Simple Exponential-Smoothing

Unlike decomposition which uses the history of the product as input for the forecast, exponential smoothing makes use of carefully selected weighted moving averages. Simple exponential smoothing targets at getting rid of the irregular patterns which a product has over a certain period of time. This is an awesome method for forecasting a product with components that exhibit very strong irregular and cyclical patterns. Businesses which mainly deal in products whose demand peak at certain times of the month prefer using simple-exponential smoothing technique to do their sales forecast in a more accurate manner.

Census X-11 Method

This method has more resemblance to standard composition due to the fact that it uses similar variables which include: seasonality, trend, irregularity and cyclicality as the inputs for forecasting. The only difference comes on how these variables are used. Census X-11 puts more emphasis on the cyclical and seasonal components of the product whose market demand is being predicted. This method also factors into specific number of days that are available in the month which demand for the products is being forecast. The reason for using number of days is for it to provide an accurate prediction for the requirements of the product for the number of days,weeks or months under consideration.

Which is the best forecasting technique?

When thinking about the bets method for forecasting, it’s important to remember that not all forecasts are always accurate. The best sales forecast method is one that ensures efficient running of the business at a minimal cost. You shouldn’t be bogged down in methodologies and theories or trying to get 100{1c5e34432a70a21262253472a7e43bf53d6962c98f84dad9538d42bf2a3f7857} forecasts. It’s important to know how each of the above methods work and select one that deliver almost accurate sales forecast result for your business.