Unit 9: Forecasting.
Research the following topics related to Forecasting:
- Qualitative/Quantitative/Mixed Methods
- Forecasting Demand
- Forecasting accuracy
Select three of the topics listed and compose three paragraphs describing the topics, one paragraph per selected topic, based on the course material and additional research you conduct online.
Forecasting demand refers to a forecasting method that looks at the future demand of a particular product or service. Forecasting demand helps in inventory management, assessing capacity requirements, production planning, and in decision making such as when targeting a new market (Pride, 2011). Both qualitative and quantitative assessments help in forecasting demand. Forecasting demand involves estimating the future sales of a particular product or service in relation to a projected marketing plan. Forecasting demand involves analysis of three key areas in a business or organization. These areas include the sales forecast of the company, industry analysis, and an environmental analysis.
Regression models make future predictions or forecasts by using past data. Regression technique analyzes the relationship between two or more variables (dependent and independent variables) (Pride, 2011). The Delphi Method is a qualitative forecasting technique introduced by the Rand Corporation. The Delphi Method employs opinion given by experts in making forecasts and predictions. As such, this method does not rely on historical data unlike other methods in making future predictions. In using this method, experts conduct a Delphi study. The Delphi study involves the analysis of the social, political, and technological factors that may have an impact on the business. The results of the study inform the development of new programs, sales strategies, or even new products.
Forecasting accuracy helps businesses evaluate how accurate the forecasts they used were. It is necessary for businesses to assess the accuracy of the forecasting techniques they use. Forecasting accuracy can help in estimating the forecast model bias, compare different forecasting methods, and in assessing the magnitude of the forecast errors. A number of measures can help to assess the forecasting accuracy. These include mean forecast error, mean absolute deviation, forecast error, tracking signal, and others. These methods rely on the analysis of forecasts and the actual outcomes (Clements & Hendry, 2000). They also analyze information use in forecasts as well as the rationality of the particular forecasts conducted.
Clements, M. P., & Hendry, D. F. (2000). Forecasting economic time series. Cambridge [u.a.: Cambridge Univ. Press.
Pride, W. M. (2011). Marketing principles. South Melbourne, Vic: Cengage Learning.
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