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However, demand forecasting is known to be a challenging task for businesses due to the intricacies of analysis, specifically quantitative analysis. [4] Nevertheless, understanding customer needs is an indispensable part of any industry in order for business activities to be implemented efficiently and more appropriately respond to market needs.
Economic forecasting is the process of making predictions about the economy. Forecasts can be carried out at a high level of aggregation—for example for GDP, inflation, unemployment or the fiscal deficit—or at a more disaggregated level, for specific sectors of the economy or even specific firms.
Forecasting is the process of making predictions based on past and present data. Later these can be compared with what actually happens. For example, a company might estimate their revenue in the next year, then compare it against the actual results creating a variance actual analysis. Prediction is a similar but more general term.
In macroeconomics, demand management it is the art or science of controlling aggregate demand to avoid a recession.. Demand management at the macroeconomic level involves the use of discretionary policy and is inspired by Keynesian economics, though today elements of it are part of the economic mainstream.
ARIMA univariate and multivariate models can be used in forecasting a company's future cash flows, with its equations and calculations based on the past values of certain factors contributing to cash flows. Using time-series analysis, the values of these factors can be analyzed and extrapolated to predict the future cash flows for a company.
See Demand forecasting and Production budget. Price-based forecasts seek to forecast demand as a function of marketing variables, such as price or promotion. These involve building specialized forecasts such as market response models or cross price elasticity of demand estimates to predict customer behavior at certain price points. [4]
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