收益和预测是直接相关的。预测有助于确定收益以及与收益相关的关键风险的确定。风险的确定是同步进行的，这对盈利方面有积极的影响(Jiang & Cui, 2013)。因此，预测提供了对历史数据的简要分析，从而有助于预测未来的收益，也有助于确定与收益相关的关键风险，从而提高整体利润率。预测的统计方法有助于用户更容易和更精确地确定最终导致总成本最小化的因素。与预测有关的风险取决于历史数据的事实和数字。最终，用户从一个不同的数据源进行准备，这个数据源要么是从主数据源收集的，要么是从辅助数据源收集的，要么是从两个数据源都获得的，这被称为混合数据收集技术和分析(Hampton, 2011)。
Earning and forecasting are directly related to each other. Forecasting helps to determine the earning along with the determination of the key risk associated with the earning. Determination of the risk goes hand on hand which has a positive impact on the earning aspect (Jiang & Cui, 2013). Forecasting thus provides a brief analysis of the historical data and thus helps to predict the future earning also helps to determine the key risk related to the earning and thus increase the overall margin of profit. A statistical approach to the forecasting helps to provide the users to determine easily and more precisely which eventually leads to the minimization of the overall cost.The risk related to the forecasting is dependent on the facts and figure of the historical data. Eventually, the user prepares from a different source which is either collected from the primary source or the secondary sources or obtained from both the sources are referred as the mixed data collection techniques and analysis (Hampton, 2011).
The data may contain false facts and figure which might lead to the false earning report which eventually decreases the probability of success of the forecasting techniques. Therefore it is very much essential to prepare and project the historical data from defined and authentic sources which will lead to the forecasting of the facts and figure more accurate and precise. Therefore it is very evident that forecasting risk is well thought-out to be one of the important and initial steps which need to be taken care. It also helps to provide and protect the integrity of the historical data along with the principal earning report related to it and thus making the user mitigate the risk associated with the forecasting tools and techniques.Forecasting is dependent on the data and variable which are generated and prepared by the previous recording (Guerard, 2013). The forecasting techniques such as sampling, probability, data analysis, etc. help to prepare and publish the historical data into forecasted facts and figures.