Time series method is to calculate and analyze the actual data in the past few periods in time order to determine the predicted value of product sales revenue in the forecast period. Due to different calculation procedures, this method can be divided into historical period (quarterly) average method, rolling (or weighted) average method and radix plus average trend method.
Causality (correlation) analysis is to predict the development trend of things in the planning period by using the causality developed inside things and focusing on the role of external factors that affect the development and change of things. This method is generally suitable for enterprises with soaring sales.
Cost-volume-profit analysis is based on dividing costs into variable costs and fixed costs. According to the internal relationship among sales costs, sales volume and profits, assuming that both of them are known, it infers another factor to seek the best scheme. Using this method, we can not only predict the sales volume and sales revenue of the breakeven point, but also predict the sales volume and sales revenue needed to achieve the profit target.
Extended data:
After the prediction target is determined, in order to meet the requirements of the prediction work, it is necessary to collect data related to the prediction target, and the adequacy and reliability of the collected data have an important impact on the accuracy of the prediction results. Therefore, the collected data must be analyzed and the following conditions must be met:
1, data pertinence: that is, the collected data must meet the requirements of the expected target.
2. Authenticity of data: that is, the collected data must be obtained from reality and verified.
3. Integrity of data: The integrity of data directly affects the progress of sales forecast. Therefore, various methods must be taken to ensure data integrity.
4. Comparability of data: For the same data, different sources and statistical caliber may be quite different. Therefore, when collecting data, it is necessary to analyze the obtained data, such as eliminating some untrue data caused by random events and adjusting incomparable data through analysis. In order to avoid the error of prediction results caused by the data itself.
Baidu Encyclopedia-Sales Forecast