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Forecasting Models

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Forecasting Models
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Forecasting involves the use of various estimating methods to determine the possible future outcomes. Organizations use the forecasting models in production as well as other operations management to implement optimal strategies and make informed decisions. Considering the forecasting models discussed in chapter 6, they have various strengths and weaknesses. One major strength of these forecasting models is that an organization can get better perspectives on future outcomes by relying on the data previously collected. Secondly, all the forecasts give sufficient information to make future decisions. They provide valuable information that an organization can use to make future decisions about the organization (Hall, 2018). One of the major weaknesses is that the past data may be inaccurate or incomplete and in situations, it may not be possible to make judgments based on this faulty data. Secondly, the amount of data given affects all the forecast. If there isn’t enough data to complete one forecast, then you can’t really present other forecasts because they share data.
The primary condition where regression is an applicable and useful forecasting tool is when you are trying to see the relationship between two variables. For instance, a manager who thinks that expanding into new premises will grow customer traffic and sales can support this belief using a regression model and the correlation between company revenues and facility size.

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Regression analysis helps in identifying the relationships and helps in predicting that which variables are related to each other as a dependent variable may be dependent on an independent variable. The graph plotted during the method also helps in analyzing the relationship between two variables, given some past data and two or more than two variables.
Reference
Hall, S. (2018). Advantages of Regression Analysis and Forecasting. Retrieved from https://smallbusiness.chron.com/advantages-regression-analysis-forecasting-61800.html

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