Question

• (a) In about 5 lines explain how associative methods of forecasting differ from Time series methods of forecasting. (b) Which one would you use to explain how the demand for pork might affect the demand for beef?   
• What all does Hard Rock Café’s Point of Sale (POS) system capture? At what level is the information aggregated?   
• (a) In about 5 lines, discuss the key differences between Time Series method of forecasting and Qualitative Methods of forecasting. (b) Name 3 methods of forecasting under each method.

Answer 1

1. Associative, and Times series methods use the past data to forecast. The time series method has an assumption that history will repeat itself, and there are identifiable patterns in all the behaviors in the present and the future. The method is useful in the earlier short term stages of the product. There are two types: additive and multiplicative. The additive method includes adding or subtracting the quantities, whereas the multiplicative method helps the researchers to get a percentage. On the other hand, the associative method is also a casual model. It is a method that finds other variables that can predict the primary variable for its interest. It assumes that there is a historical relationship between the dependent and the independent variables. It also states that each variable is easy to predict. The associative method can provide a better relationship between the demand of the pork and the beef demand. It is because these are two variables dependent on each other. They also have a historical relationship.

2. The Point of Sale method of forecasting captures the consumers' data as soon as they enter the café. The method records the sales of each customer. The Hard Rock Café transfers the data to the Orlando corporate office to record the financial data and predict for the future. The forecast happens daily, based on sales. However, it is also possible that the forecast might be wrong because of the changing environment.

3. The time series method of forecasting uses past data to forecast the sales or gains. The method involves numbers to forecast. On the other hand, the qualitative method of forecasting involves the researchers' judgments and opinions. The time-series data is better because it uses numbers to prove the data. Nevertheless, the qualitative method only uses judgments, which can differ from one researcher to the other.

4. The time series method of forecasting includes auto aggression, moving average, and vector auto aggression. On the other hand, the qualitative method of forecast includes Delphi Method, Executive Opinions, and Salesforce polling.

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